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INDEX ____________________________________________________________________________ Accumulation and distribution of heavy metals in Leucaena leucocephala Lam. and Bougainvillea Albert Einstein D S Juson, Maria Kariza M Martinez, and Johnny A Ching* [doi: http://dx.doi.org/10.18006/2015.4(1).01.06 ] 01.06 Biochemical and physiological analysis of zinc tolerance in Jatropha curca Preeti Badoni, Maya Kumari, Vikas Yadav Patade, Atul Grover* and M Nasim [doi: http://dx.doi.org/10.18006/2015.4(1).07.15 ] 07.15 Diva technology: indispensable tool for the control of Johne’s disease Sujata Jayaraman, Mukta Jain, Kuldeep Dhama, S V Singh, Manali Datta, Neelam Jain, K K Chaubey, S Gupta, G K Aseri, Neeraj Khare, Parul Yadav, A K Bhatia and J S Sohal* [doi: http://dx.doi.org/10.18006/2015.4(1).16.25 ] 16.25 Detection of quantitative trait loci (qtl) associated with yield and yield component traits in sorghum [Sorghum bicolor (L.) Moench] sown early and late planting dates Zenbaba Gutema*, Teshale Assefa and Fuyou Fu [doi: http://dx.doi.org/10.18006/2015.4(1).26.36 ] 26.36 Response of soybean (Glycine max) to molybdenum and iron spray under well-watered and water deficit conditions Ayoub Heidarzade, Mohammadali Esmaeili*, Mohammadali Bahmanyar and Rahmat Abbasi [doi: http://dx.doi.org/10.18006/2015.4(1).37.46 ] 37.46 Mesquite (Prosopis juliflora DC.) has stimulatory effect on nitrate reductase activity in rice seedlings Gowsiya Shaik and Santosh Kumar Mehar* [doi: http://dx.doi.org/10.18006/2015.4(1).47.51 ] 47.51 Effect of different planting dates and defoliation on the properties of sugar beet (Beta vulgaris L.) Mohammad Nabi Ilkaee*, Zohre Babaei, Amirsaleh Baghdadi and Farid Golzardi [doi: http://dx.doi.org/10.18006/2015.4(1).52.58 ] 52.58 Wild edible mushrooms of Nagaland, India: a potential food resource Toshinungla Ao, Chitta Ranjan Deb* and Neilazonuo Khruomo [doi: http://dx.doi.org/10.18006/2015.4(1).59.65 ] 59.65 Phytoplankton community in aquaculture and non-aquaculture sites of Taal Lake, Batangas, Philippines Airill L. Mercurio*, Blesshe L. Querijero and Johnny A. Ching [doi: http://dx.doi.org/10.18006/2015.4(1).66.73 ] 66.73
Residual effects of compacted digested effluent on growth of dwarf napier grass in warm regions of Japan Hadijah Hasyim, Yasuyuki Ishii*, Ahmad Wadi, Ambo Ako Sunusi, Satoru Fukagawa and Sachiko Idota [doi: http://dx.doi.org/10.18006/2016.4(1).74.84 ] 74.84 Characterization and impact of mycorrhiza fungi isolated from weed plants on the growth and yield of mustard plant (Brassica juncea L.) Halim*, Resman and Sarawa [doi: http://dx.doi.org/10.18006/2016.4(1).85.91 ] 85.91 Development of a protocol for the application of commercial bio-stimulant manufactured from Kappaphycus alvarezii in selected vegetable crops Kosalaraman Karthikeyan and Munisamy Shanmugam* [doi: http://dx.doi.org/10.18006/2016.4(1).92.102 ] 92.102 Inhibition of quorum sensing in Chromobacterium violaceum cv026 by violacein produced by Pseudomonas aeruginosa Any Fitriani*, Dwi Putri Ayuningtyas and Kusnadi [doi: http://dx.doi.org/10.18006/2016.4(1).103.108 ] 103.108 Water quality in aquaculture and non-aquaculture sites in Taal lake, Batangas, Philippines Blesshe L Querijero* and Airill L Mercurio [doi: http://dx.doi.org/10.18006/2016.4(1).109.115 ] 109.115 Effect of aqueous extract of Amaranthus spinosus on hematological parameters of wistar albino rats Bhande Satish S* and Wasu Yogesh H [doi: http://dx.doi.org/10.18006/2016.4(1).116.120 ] 116.120
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KEYWORDS
Bio-monitoring
Bougainvillea spectabilis
Leucaena lecocephala
Heavy metals
ABSTRACT
This study was conducted to determine the degree of heavy metal contaminations in the soils around the
perimeter of an industrial park located in the city of Sta. Rosa, Laguna, Philippines that houses light-to-
medium scale manufacturing industries, through accumulation of heavy metals in two plant systems viz.
Bougainvillea spectabilis (bougainvillea) and Leucaena lecocephala (ipil-ipil). Results of study revealed
that the soil samples collected from the study site contained higher concentrations of Cu and Zn
compared to a residential site as non-polluted source, some amount of nonessential mineral like Cd and
Pb was also found from the sample collected from the study area. Findings of the study suggested that
Cu is an immobile element, was highly accumulated in the roots of B. spectabilis, while highest
concentration of Zn was accumulated in the leaves. Moreover, the leaves of L. leucocephala collected
from the study site accumulated significantly higher concentrations of both Cu and Zn as compared to
the leaves of the same plant species collected in a residential site. The non-essential metals, Cd and Pb,
exhibit no significant difference in their accumulation and distribution to different plant parts and
between the industrial and residential sites.
Albert Einstein D S Juson1, Maria Kariza M Martinez
1, and Johnny A Ching
1,2,*
1Biological Sciences Department, College of Science and Computer Studies, De La Salle University-Dasmariñas, City of Dasmariñas, Cavite, Philippines
2Graduate Studies Department, College of Science and Computer Studies, De La Salle University-Dasmariñas, City of Dasmariñas, Cavite, Philippines
Received – December 02, 2015; Revision – December 21, 2015; Accepted – January 21, 2016
Available Online – February 15, 2016
DOI: http://dx.doi.org/10.18006/2015.4(1).01.06
ACCUMULATION AND DISTRIBUTION OF HEAVY METALS IN Leucaena
leucocephala Lam. AND Bougainvillea spectabilis Willd. PLANT SYSTEMS
E-mail: [email protected] (Johnny A Ching)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
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1 Introduction
Environmental pollution by heavy metals as a result of
increasing industrial activities has become a main global
concern. One of the most predominant environmental pollution
caused by various productions from industries is heavy metals
contamination in the air and soil (Gaur & Adholeya, 2004).
Although living organisms can tolerate numerous ranges of
heavy metals, still at excessive levels several body systems of
organism could be damaged (Chronopoulos et al., 1997).
Because of this hazardous nature of heavy metals to human
health, monitoring of the environmental burden of heavy
metals is an important ecological interest (Onianwa & Ajayi,
2002; Peng et al., 2006). There are two different methods in
order to monitor or assess the extent of pollution caused by
heavy metals, i.e. direct method that measures metal
concentrations in the substrate and indirect method that studies
the presence of metal in some living organisms such as plants
(Hervada-Sala et al., 2003).
Plants can be described as solar driven pumping stations for
those that degrade pollutants or accumulate them from their
immediate environment (Cunningham et al., 1995). Use of
plants in removing toxins from the environment is known as
phytoremediation and is an important means of cleaning up
these toxins. Many plants species were used and have been
reported successful in absorbing contaminants such as lead,
cadmium, chromium, arsenic, and various radionuclides from
the soil (Wang et al., 2002; Sekara et al., 2005; Yazaki et al.,
2006; Ching et al., 2008). There are also plants that used in
bio-monitoring; these plants can be grouped into two viz. bio-
indicator plants and bio-accumulator plants. Bio-indicator are
those plants which are more sensitive to pollutants and shows
visible symptoms of contamination on the leaf and other plant
systems, these plants are generally used as pollution marker,
whereas bio-accumulator plants have built resistance against
these pollutants; they can store pollutants without any visible
damage on their morphology and physiology (Radnai, 1997).
Burhan et al. (2001) suggested that there are about 50 metals
which are of special interest with respect to the toxicological
importance to human health, plants and animals. Essential
elements such as Fe, Zn and Cu are useful to plants at low
concentration but playing a detrimental role in plant
development at higher levels. While trace metals present in the
environment are not only hazardous to ecosystems but can also
cause hazard to human health and plant growth (Shafiq &
Iqbal, 2006). Because of such problems, it was deemed
necessary to determine the accumulation of heavy metals such
as Cu, Zn, Cd, and Pb. Present study was formulated for
accessing the presence of these heavy metals in the soil
samples collected from the perimeter of an industrial park
situate in the city of Biñan, Laguna, Philippines soils. Two bio-
accumulator common plant species viz. Bougainvillea
spectabilis (bougainvillea) and Leucaena lecocephala (ipil-
ipil) were used for the study. Further, this study determined the
contamination level of the industrial area soil and the degree of
heavy metal accumulation in the roots, stem, and leaves of B.
spectabilis and in the leaves of the L. leucocephala collected
around the industrial park.
2 Materials and Methods
2.1 The Study Site
The study site is a 224-hectare industrial park located in the
city of Sta. Rosa, Laguna, Philippines. This industrial park is
an estate houses for light-to-medium scale manufacturing
industries like garments, foods and papers, plastics, ceramics,
paints, electronics, rubber, home appliances and car parts.
2.2 Collection of Soil Samples and Plant materials
Two most common plant species of study area are B.
spectabilis and L. lecocephala selected for the present study.
Plant samples i.e. roots, stems and leaves of B. spectabilis and
leaves of L. lecocephala were collected from the plant found
within 5 meters range around the perimeter of the study site.
Simultaneous to the collection of plant samples, about 0.5 kg
soil samples were also collected from the upper 2 -10 cm of the
surface soil (Ochotorena, 1994). Likewise, soil and plant
samples of the same species were collected from a residential
site in the city of Biñan, Laguna, more than 20 km away from
the study site to serve as basis of comparison from a non-
polluted source (Tsikritzis et al., 2002).
2.3 Processing of Samples and Concentration Analysis
Prior to determination of heavy metal concentration, samples
collected from the different plant parts were oven dried at
150°C, ash of the dried samples were made in the furnace at
450°C (Ochotorena, 1994). One-half gram of dry samples was
digested with 4 ml of 65% HNO3, and 1 ml of 37% HCl for 20
min. After digestion, the remaining soil and sand particles
were removed by filter paper. The digested and filtered
samples were diluted with 0.2% nitric acid. At the same time,
blank solutions of 1 ml hydrochloric acid and 4 ml nitric acid
was also prepared (Tsikritzis et al., 2002).
Soil samples were also oven-dried at 100-105°C.
Representative sample was taken by quartering technique and
was ground to pass a 60-mesh sieve. About 0.5 g of the
sample was weighed into a porcelain crucible and ignited at
450°C in furnace to destroy the organic matter. It was
decomposed twice with 10 ml of a 1:1 mixture of concentrated
HNO3 and HF in a 100 ml polypropylene beaker and was
evaporated to dryness over a water bath. The residue was
dissolved in a 20 ml of 2M HNO3 and was diluted in a 100-ml
volumetric flask (Mitra, 2003).
02 Juson et al
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Table 1 Average Concentrations of Heavy Metals (mean ± SD) in the Soils from Industrial and Residential Sites.
Heavy Metal Average Metal concentration (mg/kg)
Industrial Residential
Cu 0.847 ± 0.01a
0.793 ± 0.01b
Zn 3.464 ± 0.04a
2.869 ± 0.04b
Cd 0.690 ± 0.05a
0.688 ± 0.08a
Pb 1.390 ± 0.02a
1.334 ± 0.02a
Metal concentrations are average of three replicates; mean ± SE values followed by the different letter in same horizontal row are
significantly different
Aliquots of the plant and soil solutions were taken for the
concentration analysis of copper (Cu), zinc (Zn), cadmium
(Cd), and lead (Pb) using a graphite furnace atomic absorption
spectrophotometer (AAS). The analysis was performed at the
Chemistry Research Center of De La Salle University-
Dasmariñas in the city of Dasmariñas, Cavite, Philippines.
2.4 Data Analysis
The degree of heavy metal concentrations for each of the plant
sample collected from the study site was measured by
comparing it to the heavy metal concentrations of the same
plant species collected from the residential site. To determine
the significant difference in the heavy metal concentrations
among the collected plant species and the pattern of variations
in the heavy metals content accumulated in the different plant
parts, two-way analysis of variance (ANOVA) was employed.
Whenever there is significant difference, Tukey test was used
as post-statistical treatment. All statistical analyses were done
at 95% level of significance.
3 Results and Discussion
3.1 Concentration of heavy metals in soil sample
Soil samples collected from the industrial site were found to
contain significantly (p<0.05) higher Cu and Zn
concentrations, both considered as essential metals, than those
collected from a residential site (Table 1). Concentrations of
metals in industrial sites have an average of 0.847 mg kg-1
for
Cu and 3.464 mg kg-1
for Zn. While those collected in the
residential sites, concentrations have an average of only 0.793
mg kg-1
and 2.869 mg kg-1
for Cu and Zn, respectively.
However, for the non-essential metals, Cd and Pb, no
significant difference was established between the metal
concentrations in the soils of industrial and residential sites.
Although significantly higher concentration of Cu and Zn was
reported from the samples collected from the industrial site but
it did not exceed from the standards set by the Government of
China, i.e. 250 mg kg-1
for Cu and Zn. These concentrations
were also within the range from soils collected at polluted sites
in China (Wang et al., 2003) but slightly higher than soils
samples collected from agricultural land, pasture lands and
forests of Belguim (Aydinalp & Marinova, 2003). High
concentrations of metals in soil from the industrial site could
be attributed to the industrial activities that pollute the
environment with gases containing these heavy elements. Soil
is contaminated by material from the air and by direct
depositing of pollutants. Most of the industrial plants were
operated without taking into consideration the problem of
pollution and wastes, and consequently they have no
technological ways to manage the problem (Wang et al., 2003;
Ching et al., 2008). Areas near heavy industries, including
smelters and mining sites, are exposed to the atmospheric
deposition of heavy metals, so that such deposition may
contribute significantly to the concentrations of metals in the
soils (Wang, et al., 2003).
3.2 Accumulation of heavy metals in plant sample
Accumulation and distribution of heavy metals in the roots,
stems, and leaves of B. spectabilis collected from industrial
and residential sites are presented in Table 2. Roots were
found to have significantly higher concentrations of Cu as
compared to stems and leaves. While for the Zn, leaves were
found to accumulate the highest concentration followed by
stems and roots. However, Cd and Pb did not show any
significant variations of in the distributions to the different
plant tissues of the plant sample. Only Cu and Zn, the
essential elements, showed significantly higher concentrations
in B. spectabilis collected from industrial site as compared to
the samples collected from the residential site but there was no
visible damage or symptoms of contamination on the examined
plant parts.
Roots worked as a primarily passageway for all fluids and
nutrients spread to the plant tissues, thus it could accumulated
higher concentration of metals. Johansson et al. (2005)
reported that accumulation of Cu varied with plant species,
these researchers reported that in Pistacia terebinthus and
Cistus creticus, most of the Cu was found in the roots, while
Bosea cypria accumulated most of the Cu in the leaves, in this
manner, results of present study are in agreement with P.
terebinthus and C. creticus. Zn is a mobile element and it
primarily enters through the roots of the plant species and
spread throughout the plant system. According to Herrero et
al. (2003), plants have special Zn transporters mechanism to
absorb this metal.
Accumulation and distribution of heavy metals in Leucaena leucocephala lam. and Bougainvillea spectabilis willd. plant systems. 03
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Table 2 Accumulation and distribution of heavy metals in plant tissues samples of B. spectabilis collected around the Perimeter of an
Industrial Park and residential area
Heavy
metals
Sites Average Metal Concentration (mg/kg)
Roots Stems Leaves Total
Cu Industrial 1.256±0.02x
0.142±0.004y
0.835±0.02z
2.233a
Residential 0.423±0.01x 0.045±0.01
y 0.399±0.02
x 0.867
b
Zn Industrial 1.208±0.02x 1.544±0.01
x 2.150±0.01
y 4.902
a
Residential 0.313±0.02x 0.540±0.03
x 1.818±0.03
y 2.671
b
Pb Industrial 0.629±0.1x 0.676±0.03
x 0.677±0.05
x 1.982
a
Residential 0.656±0.08x 0.596±0.07
x 0.606±0.04
x 1.858
a
Cd Industrial 1.490±0.04x 0.964±0.006
x 1.484±0.03
x 3.938
a
Residential 1.267±0.02x 1.409±0.04
x 1.321±0.05
x 3.997
a
Metal concentrations are average of three replicates; mean ± SE values followed by the different letter a/b shows significantly different
between the study site and residential site while mean ± SE values followed by the different letter x/y/z shows significantly different
between the various plant tissues
Similarly, Cd, is also a mobile element in the soil and is taken
up by plants primarily through the roots. Cd and Pb strengthen
the effect of each other’s. Further, Cd promotes the
accumulation of Zn, but this process decelerated the number of
Cu and Pb in soil concentrations (Valizadehfard et al., 2012).
Pb is one of the elements that could also be taken by plant
through the aerial way. Since that it could pass through the air,
there was a high accumulation in the leaves of the plant.
Another factor that contributes to the high accumulation of
lead in the leaves only was the slow mobility of the metal
(Ogundiran & Osibanjo, 2008).
Heavy metal accumulation in the leaves of L. leucocephala
collected from industrial and residential sites were presented in
Table 3. Although there was no morphological symptoms of
contamination observed but the concentrations of essential
heavy metals, Cu and Zn, in the leaves of plant samples
collected from the industrial site were reported as significantly
higher (p<0.05) than those collected in the residential site.
However, in case of non-essential metals, Cd and Pb, there was
no significant difference was observed in the metal
concentrations in leaves samples collected from both sites.
These results were congruent to the findings of Rehman &
Iqbal (2009) in the study of metal transfer ratio in L.
leucocephala by using soils of industrial areas of Korangi and
Landhi, Karachi. Results of this study revealed that the
presence of high concentrations of metals in the leaves of the
plant could be attributed to other sources like aerial deposition.
Non-essential metals, like Cd and Pb, have lesser accumulation
as compared to the essential metals, i.e. Cu and Zn. This may
be possible because of slower mobility of these metals
(Yazaki, et al., 2006).
Conclusion
Soil samples collected from the industrial site were found to
have significantly higher levels of essential metals, Cu and Zn,
than those collected from the residential site. While for the
non-essential metals, Cd and Pb, no significant difference was
established between the metal concentrations in the soils of
industrial and residential sites. However, heavy metal
concentrations in the soils collected from the study site were
found to be within the range of non-polluted soil. Higher
concentrations of Cu and Zn was reported in the plant sample
collected industrial site but this higher concentration is not
making any morphological damage, so it can be conclude that
these two plant species worked as a potential bio-accumulators.
On the contrary, the non-essential elements Cd and Pb did not
show any significant variations for both plant samples
collected on both sites. Cu accumulated highest in the roots of
B. spectabilis while its leaves accumulated the highest
concentration of Zn. Heavy metals can also be distributed and
accumulated by means of aerial deposition, thus metals could
be transmitted to the leaves and stems of the plant. Cd and Pb
are evenly distributed in all the tissues of B. spectabilis having
no significant difference on their concentrations.
Table 3 Accumulation and distribution of heavy metals in leaves of L. leucocephala collected from the industrial and residential sites.
Heavy metals Average Metal Concentration (mg/kg)
Industrial site Residential site
Cu 3.418± 0.46x
1.181 ± 0.01y
Zn 3.203 ± 0.1x
1.536 ± 0.07y
Cd 0.679 ± 0.06x
0.677 ± 0.06x
Pb 1.487 ± 0.07x
1.411 ± 0.05x
Metal concentrations are average of three replicates; mean ± SE values followed by the different letter in same horizontal row are
significantly different
04 Juson et al
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The same pattern of accumulation was observed in the leaves
of L. leucocephala.
Furthermore, researches must be carrying out in order to
establish the phytoremediation capability of plants that are
common in industrial sites. Likewise, studies on the
interactions among several metal contaminants affecting the
uptake mechanisms in plants must also be carried out along
with establishing the transformation processes for metal
tolerance of different plant species.
Acknowledgements
The researchers express their deepest gratitude to the Dr. Airill
Mercurio, Ms. Chona Bandelaria and Ms. Jonnacar San
Sebastian of the Biological Sciences Department under the
College of Science and Computer Studies of De La Salle
University-Dasmariñas for their unwavering support and
intelligent inputs in all possible ways.
Conflict of interest
Authors would hereby like to declare that there is no conflict of
interests that could possibly arise.
References
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KEYWORDS
Antioxidant enzymes
Growth parameters
Lipid peroxidation
Proline content
Zinc accumulation
ABSTRACT
Jatropha curcas L., widely recognized as a viable option for production of bio diesel, has been assessed
for its ability to withstand stress induced by supra-optimal zinc concentrations. In the present study
plants were exposed to varying Zinc (Zn) concentrations (0, 500, 1000, 1500 and 2000 mg/kg), and and
different growth, physiological and biochemical parameters were studied. It was reported that up to
1500 mg/kg Zn, no significant effects on most of the growth parameters of the plants could be seen.
However at 2000 mg/kg Zn, a clear retardation of growth was visible, which was apparently reflected by
the physiological as well as biochemical parameters. These effects were more profound in the aerial
parts of the plant. Atomic Absorption Spectra (AAS) profiles suggested that Zn got mainly accumulated
in the roots after absorption from the soil. Osmotic adjustments indicated significantly increased
accumulation of proline, phenols and reducing sugars with increasing concentration of Zn as compared
to the control. Membrane damage was not observed up to 1000 mg/kg concentration. Jatropha, owing to
its tolerance to supra-optimal Zn concentrations is, thus, a suitable candidate for phytoremediation of Zn
from contaminated soils along with cultivation for biofuel production.
Preeti Badoni1, Maya Kumari
2, Vikas Yadav Patade
3, Atul Grover
1,* and M Nasim
1
1Defence Institute of Bio-Energy Research (DIBER), Goraparao, P.O. Arjunpur, Haldwani 263139. India
2Office of Director General Life Sciences, Defence Research and Development Organization, DRDO Bhawan, Rajaji Marg, New Delhi 110011. India
3Defence Institute of Bio-Energy Research (DIBER) Field Station, Panda Farm, Pithoragarh 262501. India
Received – October 01, 2015; Revision – October 21, 2015; Accepted – January 27, 2016
Available Online – February 15, 2016
DOI: http://dx.doi.org/10.18006/2015.4(1).07.15
BIOCHEMICAL AND PHYSIOLOGICAL ANALYSIS OF ZINC TOLERANCE IN
Jatropha curcas
E-mail: [email protected] (Atul Grover)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
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1 Introduction
Heavy metals (HMs), frequently referred to lead (Pb),
chromium (Cr), arsenic (As), zinc (Zn), cadmium (Cd), copper
(Cu), mercury (Hg) and nickel (Ni) occur naturally in the soils.
Beyond a certain concentration, these heavy metals are toxic.
In recent years, their concentrations in soil have become a
concern worldwide (Rascio & Navari-Izzo, 2011; Villiers et
al., 2011). Zn is a necessary cofactor for many biological
reactions, known to limit oxidative degradation of auxin and is
necessary to maintain membrane integrity (Tsonev & Lidon,
2012). Zinc concentration in soils lesser than 125 ppm is
considered optimum for the growth of plants (Hussain et al.,
2010). Plants growing in such edaphic environments display
Zn concentrations in the range 0.02-0.04 mg g-1
dry weight
(Tsonev & Lidon, 2012). Higher concentrations of Zn in soil,
however, have direct effects on the growth and yields of the
plants (Chibuike & Obiora, 2014), and thus adversely affect
the agriculture.
The general symptoms are stunting of shoot, curling and
rolling of young leaves, death of leaf tips (Rout & Das, 2003)
and chlorosis (Rout & Das, 2003). Due to Zn toxicity, the
activity of proteins present in the plasma membrane and
especially the activity of SH groups gets affected which causes
damage to membrane stability. As soon as heavy metals pass
through the plasma membrane, they can immediately interact
with all metabolic processes (Rout & Das, 2003). To avoid Zn
toxicity in plants, the excess quantities of Zn shall be cleaned
up from the soil. Among several methods available for such
clean up, phytoremediation is catching attention in recent
years, as plants survive for longer durations and have potential
to permanently fix the pollutants. Plants have many cellular
mechanisms involved in the detoxification of heavy metals and
thus tolerance to metal stress. These include the binding of
metals to cell wall and extracellular exudates, reduced uptake
or efflux pumping of metals at the plasma membrane, chelation
of metals in the cytosol by peptides such as phytochelatins,
repair of stress-damaged proteins and the compartmentation of
metals in the vacuole by tonoplast located transporters (Hall,
2002). However, this necessitates that plants being used for
phyto-remediation should be non-edible and can grow
effectively at the polluted sites (Nanda & Abraham, 2011).
In view of the above, we have assessed the potential of
jatropha, which is also being projected as a promising bio fuel
crop, to survive and thrive under condition of higher soil
concentrations of Zn. It is a small tree that has naturalized in
most parts of the world and grows in a variety of agro-climatic
areas. Many studies show the potential of J. curcas to recover
and reclaim heavy metal contaminated soil (Yadav et al.,
2009).
2 Materials & Methods
2.1 Plant material and Zn concentrations
Mature, healthy and current harvest seeds of J. curcas strain
DARL-2 were soaked overnight in 0.1% (w/v) Bavistin,
washed several times under running tap before sterilizing with
70% (v/v) ethanol and followed by three washes of sterile
water. Thereafter, seeds were allowed to germinate on moist
filter papers in Petri dishes. After germination, seedlings of
uniform size were selected and transplanted into pots
containing autoclaved mixture of sand and soil in 1:1 ratio.
ZnSO4.5H2O solution was added in the pots to obtain the Zn+2
concentrations of 0 (control), 500, 1000, 1500, 2000 mg/kg of
soils. Experiment was conducted with three replicates each,
and replication had five pots having three plants each. Both
control and treated pots were irrigated at regular interval.
The Zn concentration in soil and in different parts of the plant
(root, stem and leaf) was estimated using Atomic Absorption
Spectrometer (M Series 650294v129, Thermo Electron
Corporation, USA) fitted with an air-acetylene burner,
expressed as mg/g dry weight of the sample.
2.2 Growth parameters
Root length, shoot length, total number of leaves, fresh weight
and dry weight of root and stem were recorded for each
treatment after 4 months.
2.3 Physiological parameters
Total chlorophyll (a + b) and carotenoids were determined
from fresh leaf (100 mg FW) according to Arnon (1949). The
leaf material was ground in a pre-chilled mortar in acetone
(80% v/v). After homogenization, the mixture was filtered and
the volume was adjusted to 10 ml with cold acetone. The
absorbance of the extract was measured at 645, 663, and 470
nm using a spectrophotometer (UV-Vis Dual Beam, Labomed
inc.) and the pigments content were calculated. The
chlorophyll stability indices (CSI) were determined using the
formula:
Total chlorophyll content in stressed leaves / total chlorophyll
content in control leaves X 100
The leaf relative water content (RWC) was determined
according to Patade et al. (2011). Fresh weight (FW) of the
leaf was recorded immediately after plucking from the plant.
After 24 h of saturation with deionized water the turgid weight
(TW) was recorded. Dry weight (DW) was recorded after
drying the leaves for 48 hrs in the hot air oven at 70oC. The
RWC was calculated as:
RWC (%) = [(FW-DW)/ (TW-DW)] X100
Reducing sugar was estimated as described by Miller (1959).
About 100 mg leaf sample was homogenized in 3ml of 80%
ethanol. The homogenate was centrifuged at 6000 g for 10 min
at 48oC and the supernatant was mixed with equal volume of 3,
5-dinitro-salicylic acid (DNSA) reagent. Distilled water was
08 Badoni et al
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used for blank readings. The reactants were mixed by
vortexing and the tubes were placed in a boiling water bath for
10 min after which they were cooled on ice. The absorbance
was measured at 540 nm and the reducing sugars content (mg
g-1
FW) was calculated based on standard curve with glucose as
standard.
Leaf pieces (~1.0 cm2) after washing with distilled water were
transferred to glass culture tubes containing 20 ml distilled
water and incubated for 24 h with intermittent shaking. Electric
conductivity was recorded using EC meter (WTW, Germany).
EC1 was recorded after 24 hrs of incubation of the leaf. Tubes
were capped and then autoclaved at 121oC for 20 min. to
completely kill the tissues and release all electrolytes. EC2 was
recorded after cooling the solution to room temperature.
Membrane damage rate (MDR) was calculated using the
formula (Lutts et al., 1995):
MDR (%) = (EC1 / EC2) X 100
Proline content was determined according to Bates et al.
(1973). 200 mg of leaf was homogenized in aqueous
sulfosalicylic acid (3% w/v). The filtered homogenate was
reacted with equal volume each of acid ninhydrin and acetic
acid for 1 h at 100°C in a water bath. The reaction mixture was
extracted with toluene and the absorbance was recorded at 520
nm using toluene as a blank. Proline concentration (µg g-1
FW)
was determined from a standard curve using L-proline as a
standard.
Lipid peroxidation was determined according to the method of
Heath & Packer (1968). 100 mg of leaf was homogenized in
1.5 ml of 0.25% Thiobarbituric acid (TBA) in 10%
Trichloroacetic acid (TCA). The mixture was heated at 95oC
for 30 min. and then cooled in ice, it was then centrifuged at
10000 g for 10 min. Absorbance of the supernatant was read at
532 nm and 600 nm, keeping 0.25% TBA in 10% TCA as
blank. MDA content was calculated according to its extinction
coefficient of 155 mM-1
cm-1
.
Total phenolic content was estimated according to Folin-
Cioalteu method as described by Ainsworth & Gillespie
(2007). The leaf tissue was ground to a fine powder using
liquid nitrogen. 2 ml of 95% (v/v) ice cold methanol was then
added to the ground tissue and incubated for 48 h at room
temperature in dark. It was then centrifuged at 13000 g for 5
min. Supernatant (100 µl) was taken and mixed with 200 µl of
10% (v/v) F-C reagent to which, 800 µl of 700 mM Na2CO3
was added and again incubated at room temperature for 2 h.
Absorbance was recorded at 765 nm. Total phenolic content
was calculated based on standard curve with gallic acid as
standard and expressed as mM µM-1
gallic acid equivalent.
2.4 Antioxidant enzyme assays
CAT activity was measured in a reaction mixture (1.0 ml)
containing 50 mM phosphate buffer (pH 7.0) and 15 mM H2O2
as described by Maehly & Chance (1959). The reaction was
initiated by adding 50 µl enzyme extract and the activity was
determined by monitoring decrease in absorbance at 240 nm (E
= 39.4mM-1
cm-1
) for 2 min. at intervals of 15 sec, as a result of
H2O2 decomposition. The slope of the rate assay (ΔA) was
used to determine the enzyme activity, which was expressed as
µmol.mg protein-1
min-1
.
APX activity was determined according to Nakano & Asada
(1981). The reaction mixture (2.0 ml) contained 50 mM
phosphate buffer (pH 7.0), 0.5 mM ascorbate, 0.1 mM H2O2
and 0.1 mM EDTA. The reaction was started by adding 100 µl
of crude enzyme. The H2O2 dependent oxidation of ascorbate
was followed by a decrease in the absorbance at 290 nm (E =
2.8 Mm-1
cm-1
). APX activity was measured in terms of
µmol.mg protein-1
min-1
.
GPX activity was determined according to Kar & Feierabend
(1984). The reaction mixture (1.0 ml) contained 50 mM
phosphate buffer (pH 7.0), 0.1 mM EDTA, 10 mM guiacol and
10 mM H2O2. Oxidation of guiacol was monitored by
measuring the increase in absorbance at 470 nm (E = 26.6 Mm-
1cm
-1) for 1 min at interval of 15 s after addition of 50 µl of
crude enzyme. GPX activity was measured in terms of µmol of
tetraguaicol formed mg protein-1
min-1
.
2.5 Statistical Analysis
Mean, standard error and statistical significance of mean
values for different parameters were determined. Analysis of
variance (ANOVA) for all the variables was performed using
Cropstat for Windows (7.2.2007.2 module, IRRI, Phillipines).
3 Results
3.1 Growth responses
Compared to the control, the growth parameters were not
significantly (p>0.05) affected up to 1500 mg/kg Zn (Table 1)
as seen by non-significant differences in various growth
parameters (root length, shoot length, fresh and dry weight of
the root and fresh and dry weight of the stem). However, at
2000 mg/kg Zn all the growth parameters were significantly
(p<0.05) reduced except the root length as compared to the
control (Table 1).
3.2 Zn accumulation in different plant parts
A significant amount of Zn was detected in J. curcas plants
grown at different concentrations of metal. Accumulation was
maximum in the roots, i.e., 8.93 mg/g DW followed by the
stem 3.61 mg/g DW and leaves 0.79 mg/g DW (Figure 1).
About nine folds higher Zn level was detected in the roots at
2000 mg/kg Zn as compared to the control. Similarly the level
of Zn in the stem and leaves of plants at 2000 mg/kg Zn was
11.5 folds and 1.27 folds respectively in relation to the control.
Biochemical and physiological analysis of zinc tolerance in Jatropha curcas. 09
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Table 1 Effect of different concentrations of Zn on growth parameters of J. curcas. Standard error of three treatment means (SE) and
LSD values are given in the last row.
Zn conc.
(mg/kg soil)
Root length
(cm)
Shoot length
(cm)
Total
leaves
Fresh weight
stem (g)
Dry weight
stem (g)
Fresh weight
Root (g)
Dry weight
Root (g)
0 8.233 21.767
9.000
3.625
2.493
0.270
0.056
500 8.483 22.333
8.33
3.785
2.690
0.467*
0.072*
1000 7.050 20.833
9.00
3.699
2.462
0.330*
0.063*
1500 5.267 20.733
10.67*
3.277
2.570
0.234
0.053
2000 4.583 14.600*
8.00
1.778*
1.398*
0.161*
0.024*
SE 0.778 0.293 0.24 0.128 0.093 0.013 0.001
5% LSD 2.295 0.956 0.77 0.418 0.303 0.039 0.005
The values marked with asterisk (*) are significantly different from control at P ≤ 0.05, as determined using Least Significant Difference
(LSD) test.
3.3 Zn concentration in soil before planting and after
harvesting of J. curcas
The results of soil analysis showed that the percent uptake of
Zn increased significantly (p<0.05) at different concentrations
as compared to the control (Table 2). At 2000 mg/kg Zn
concentration, the percentage uptake of Zn from soil increased
by 6.68 folds as compared to the control.
3.4 Chlorophyll and carotenoid contents
The total chlorophyll and carotenoides contents, and the
chlorophyll stability index was increased significantly (p<0.05)
at 1000 mg/kg Zn as compared to the control but at lower (500
mg/kg) and higher (≥ 1500 mg/kg) concentrations of Zn, no
difference in the total chlorophyll content and the chlorophyll
stability index were observed (Table 3).
3.5 Osmotic adjustments
In response to different concentrations of Zn, RWC of the leaf
was not significantly (p>0.05) changed as compared to the
control, but the accumulation of reducing sugars has
significantly (p<0.05) increased in relation to the control.
Significantly (p<0.05) higher content of total phenol (1.44
folds) and proline (2 folds) was observed at 2000 mg/kg Zn as
compared to the control (Figure 2a&b).
Figure 1 Accumulation of Zn in plant parts exposed to different concentrations of Zn. Different letters indicate significant differences at
p>0.05, as determined using Least Significant Difference (LSD) test. Error bars indicate SE of three treatment means.
10 Badoni et al
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Figure 2a Effects of different concentrations of Zn on RWC
measured in leaves of J. curcas. Different letters indicate
significant differences at p>0.05, as determined using Least
Significant Difference (LSD) test. Error bars indicate SE of
three treatment means.
Figure 2b Effects of different concentrations of Zn on reducing
sugar measured in leaves of J. curcas. Different letters indicate
significant differences at p>0.05, as determined using Least
Significant Difference (LSD) test. Error bars indicate SE of
three treatment means.
Figure 2c Effects of different concentrations of Zn on total
phenol measured in leaves of J. curcas. Different letters
indicate significant differences at p>0.05, as determined using
Least Significant Difference (LSD) test. Error bars indicate SE
of three treatment means.
Figure 2d Effects of different concentrations of Zn on proline
content measured in leaves of J. curcas. Different letters
indicate significant differences at p>0.05, as determined using
Least Significant Difference (LSD) test. Error bars indicate SE
of three treatment means.
3.6 Lipid peroxidation and Membrane damage rate
Higher concentrations of Zn has affected the membrane
properties which is revealed by significantly (p<0.05)
increased (1.31 folds) amount of MDA content at 2000 mg/kg
Zn as compared to the control (Figure 3a). However, the
electrical conductivity of the leaves was not significantly
(p>0.05) changed in response to higher Zn concentrations as
compared to the control (Figure 3b).
3.7 Antioxidant enzyme activities
The activities of the antioxidant enzymes (CAT, APX and
GPX) were significantly (p<0.05) increased in response to
higher concentrations of Zn as compared to the control (Figure
4a-c). In relation to the control, significantly (p ≤ 0.05) higher
CAT activity was observed in all the treatments and the highest
increase of 2.8 folds was observed at 1000 mg/kg Zn. The
APX activity was significantly (p ≤ 0.05) increased up-to 1500
mg/kg Zn (2.3 folds) but at 2000 mg/kg Zn the APX activity
was decreased in relation to the control. GPX activity was also
significantly (p ≤ 0.05) increased in all the treatments in
relation to the control and the highest increase of 3.4 folds was
observed at 2000 mg/kg Zn.
Biochemical and physiological analysis of zinc tolerance in Jatropha curcas. 11
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Table 2 Analysis of the soil sample used for growing J. curcas exposed to different concentrations of Zn.
Initial Zn conc. in soil (µg/g) Final Zn conc. in soil (µg/g) % Zn uptake by plant from soil
(Control) 12 10.33
13.89
500 55.00*
89.00*
1000 103.00*
89.70*
1500 112.00*
92.53*
2000 144.00*
92.80*
SE 0.82 1.00
LSD p≤0.05 0.58 0.71
The values marked with asterisk (*) are significantly different from control at P ≤ 0.05, as determined using Least Significant Difference
(LSD) test.
Table 3 Effect of different concentrations of Zn on pigment content in J. curcas. Standard error of three treatment means (SE) and LSD
values are given in the last row.
Zn conc. (mg/kg soil) Chl (a + b) (mg/gFW) Chlorophyll stability index (CSI) Carotenoids (mg/gFW)
0 8.40
100
415.56
500 9.16
109.06
442.47
1000 14.22*
169.33*
633.56*
1500 9. 01
107.28
483.21
2000 7.99
95.06
354.70
SE 0.49 5.99 18.39
LSD 1.61 19.55 59.97
The values marked with asterisk (*) are significantly different from control at P ≤ 0.05, as determined using Least Significant Difference
(LSD) test.
Figure 3a Effects of different concentrations of Zn on MDA
measured in leaves of J. curcas. Different letters indicate
significant differences at p>0.05, as determined using Least
Significant Difference (LSD) test. Error bars indicate SE of
three treatment means.
Figure 3b Effects of different concentrations of Zn on EC
measured in leaves of J. curcas. Different letters indicate
significant differences at p>0.05, as determined using Least
Significant Difference (LSD) test. Error bars indicate SE of
three treatment means.
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Journal of Experimental Biology and Agricultural Sciences
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Figure 4a Effects of different concentrations of Zn on CAT
activity measured in leaves of J. curcas. Different letters
indicate significant differences at p>0.05, as determined using
Least Significant Difference (LSD) test. Error bars indicate SE
of three treatment means.
Figure 4b Effects of different concentrations of Zn on APX
activity measured in leaves of J. curcas. Different letters
indicate significant differences at p>0.05, as determined using
Least Significant Difference (LSD) test. Error bars indicate SE
of three treatment means.
Figure 4c Effects of different concentrations of Zn on GPX activity measured in leaves of J. curcas. Different letters indicate significant
differences at p>0.05, as determined using Least Significant Difference (LSD) test. Error bars indicate SE of three treatment means.
Discussion
Despite being an essential micronutrient, the threshold of
toxicity due to Zn varies among plant species (Tsonev &
Lidon, 2012). J. curcas, has remarkable ability to withstand
elevated levels of Zn concentration, often accumulating excess
concentrations within the cells. It was reported that shoot
length, total number of leaves, fresh weight of stem, fresh
weight of root, dry weight of stem and dry weight of root were
not affected up to 1500 mg/kg Zn. At 2000 mg/kg Zn,
however, a significant decrease in the growth parameters was
observed, though no significant reductions occurred in the root
length. Growth inhibition is a general phenomenon associated
with most of heavy metals (Luo et al., 2010) and there are
reports which show that higher Zn concentrations results in
biomass decline and inhibition of cell elongation and division
(Tsonev & Lidon, 2012).
Zn acts as a structural and catalytic component of proteins,
enzymes and as a co-factor for normal development of pigment
biosynthesis which could be the reason behind increased
chlorophyll and carotenoid contents at 1000 mg/kg Zn as
compared to the control. Chlorophyll pigments are present in
the chloroplasts of leaves and it has been found that under
stress the amount of chloroplast increases for maintaining the
photosynthesis in plants. Increased content of photosynthetic
pigments was also observed by other workers (Jamil et al.,
Biochemical and physiological analysis of zinc tolerance in Jatropha curcas. 13
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2007; Pinhiero et al., 2008; Rahdari et al., 2012) under
different abiotic stresses.
The RWC in Jatropha plants grown at different concentrations
of Zn was not significantly affected as compared to the control,
indicating ability of Jatropha to osmotically adjust to higher
concentrations (upto 2000 mg/kg) of Zn in soil. Osmotic
adjustment was also inferred in terms of levels of accumulation
of reducing sugars, phenols and proline in leaf tissues. The
accumulation of reducing sugars could be a result of starch
degradation, and helps in adjusting water potential in the
cytosol, i.e., intracellular osmotic adjustment. In case of
accumulation of heavy metals, altered water potential would be
instrumental in adjusting to higher concentrations of
accumulated ions in the vacuole, and would protect integrity of
cellular membranes (Naghavi, 2014).
Proline too is a well documented osmolyte involved in abiotic
stress tolerance including heavy metal stress (Chandra et al.,
2012; Corcuera et al., 2012; Diaz et al., 2014; Pandey &
Gupta, 2015). Elevated levels of proline during stress
conditions could be a result of increased catabolism of the
phenolic compounds (Hamid et al., 2010). Importantly, free
proline chelates the metal ions, forming non-toxic metal-
proline complexes, thereby protecting cellular structures, and
metabolism thereof (Patel et al., 2013). Results of present
study indicated that increase in total phenolic content at higher
concentrations of Zn as compared to the control. Presumably,
the oxidative effects of metal ions and metalloids are prevented
by the antioxidant activity of phenolics that allows them to
scavenge free ions due to their redox properties, thereby
showing elevated levels of proline (Hamid et al., 2010). The
breakdown of phenolics is triggered by the enzymes and a
trailing cascading reactions, what we commonly also refer to
as participation of ‘antioxidant enzymes’, which would involve
hydrogen donors and quenchers of reactive oxygen species
(ROS). H2O2 is an important ROS that disrupts the functions of
the cell. CAT, APX and GPX are important enzymes that
regulate the levels of H2O2 (Hosseini & Poorakbar, 2013). We
have found an increased activity of CAT, APX and GPX
enzymes at different concentrations of Zn as compared to
control suggesting higher abilities of Jatropha to withstand
oxidative stress generated by Zn.
From the above discussion, it is inferred that J. curcas can
remove a significant amount of Zn from the soil and roots are
the primary sink for accumulation of the metal, causing almost
no damage to the plant growth.
Acknowledgements
Authors thank Dr. Shashi Bala Singh, Director and Dr.
Somnath Singh of Defence Institute of Physiology and Allied
Sciences (DIPAS), Delhi for allowing access to Atomic
absorption spectrometer. Preeti Badoni thanks Defence
Research and Development Organization (DRDO) for research
fellowship.
Conflict of interest
Authors would hereby like to declare that there is no conflict of
interests that could possibly arise.
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KEYWORDS
Paratuberculosis
Tuberculosis
Johne‟s disease
Secreted antigens
DIVA
Vaccine
Vaccination
ABSTRACT
Ruminant Paratuberculosis (Johne‟s disease) is categorized as List B disease by OIE. Paratuberculosis is
a disease of socio-economic and public health importance and has significant effect on in the
international trade of animals and animal products. Control of paratuberculosis is priority in many
countries and different countries have designed their own control programs tailored to their farming
practices and geographical conditions. However, the major component shared by these control programs
is “Test and Cull” policy. Due to inability of detecting paratuberculosis in early stages this policy has
globally failed to control the disease and hence there is global urgency in developing control measures.
Vaccination has shown promise in controlling this disease. However, vaccination in present form cannot
be used due to lack of DIVA (Differentiation of Infected from Vaccinated Animals) technology, because
present vaccines interfere with diagnosis of naturally infected paratuberculosis animals and animals
infected with tuberculosis. Therefore markers are needed to be identified for developing DIVA. This
paper summarizes the findings of vaccination trials conducted in different countries and highlights the
importance of vaccination in controlling paratuberculosis and also discusses strategies for developing
DIVA for paratuberculosis vaccines.
Sujata Jayaraman1,#
, Mukta Jain
1,#, Kuldeep Dhama
2, S V Singh
3, Manali Datta
4, Neelam Jain
4, K K
Chaubey3, S Gupta
3, G K Aseri
1, Neeraj Khare
1, Parul Yadav
5, A K Bhatia
6 and J S Sohal
l.*
1Amity Institute of Microbial Technology, Amity University Rajasthan, Kant Kalwar, NH-11C Delhi-Jaipur Highway, Jaipur- 303 002, India
2Division of Pathology, Indian Veterinary Research Institute, Izatnagar, Bareilly-
243122, Uttar Pradesh, India 3Animal Health Division, Central Institute for Research on Goats, Makhdoom, PO - Farah, Mathura- 281122, Uttar Pradesh, India
4Amity Institute of Biotechnology, Amity University Rajasthan, Kant Kalwar, NH-11C Delhi-Jaipur Highway, Jaipur- 303 002, India
5Amity University Science & Instrumentation Centre, Amity University Rajasthan, Kant Kalwar, NH-11C Delhi-Jaipur Highway, Jaipur- 303 002, India
6Department of Microbiology and Immunology, GLA University, Chaumuhan, Mathura, Uttar Pradesh, India
Received – November 23, 2015; Revision – December 14, 2015; Accepted – January 27, 2016
Available Online – February 15, 2016
DOI: http://dx.doi.org/10.18006/2015.4(1).16.25
DIVA TECHNOLOGY: INDISPENSABLE TOOL FOR THE CONTROL OF JOHNE‟S
DISEASE
E-mail: [email protected] (J S Sohal)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author (# Authors equally contributed to this work)
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
Journal of Experimental Biology and Agricultural Sciences
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ISSN No. 2320 – 8694
Production and Hosting by Horizon Publisher
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All the article published by Journal of Experimental
Biology and Agricultural Sciences is licensed under a
Creative Commons Attribution-NonCommercial 4.0
International License Based on a work at www.jebas.org.
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1 Introduction
Johne‟s disease (JD) or Paratuberculosis has emerged as wide-
spread, highly prevalent and economically devastating
infectious disease of domestic livestock around the world
(Singh et al., 2014). JD is characterized by persistent diarrhea
with progressive loss of weight. Chronic diarrhoea results in
protein losing enteropathy. Disease is caused by an extremely
fastidious microbe known as Mycobacterium avium subspecies
paratuberculosis (MAP). It is highly resistant to environmental
stress like temperature, drying and is able to persist for years in
farm soil (Singh et al., 2013). In India disease has been widely
reported from all the domestic ruminant species (Singh et al.,
2014). In India MAP has also been reported from wild
ruminants such as blue bulls, hog deer, bison (Singh et al.,
2010a; Singh et al., 2011a) as well as other animals like rabbit
and primates (Singh et al., 2011b; Singh et al., 2012).
Paratuberculosis is a spectral disease where it takes years for
clinical signs to appear in animals. In very early stages (silent
stage) typically there are no signs of disease and none of the
available tests can detect infected animals at this stage, this
stage progresses to sub-clinical disease, where shedding of
MAP in feces can be occasionally seen without any signs of
the disease (Tiwari et al., 2006). This stage often then
progresses to clinical infection. At this stage animal have
intermittent diarrhea and progressive weight loss without
reduction of appetite. Sporadic signs at this stage generally
give way to more severe infection. These animals will give
positive results with fecal culture tests, because of host
shedding massive numbers of organism. Animals in this stage
are also positive on serological assays. Clinical signs continue
for months, which may usually results in death.
Paratuberculosis is increasingly being recognized as significant
problem affecting animal health, farming and the food industry
due to the high prevalence of the disease across the world.
Paratuberculosis can cause significant economic loss in
affected herds, as a result of reduced milk yield, poor milk
quality, poor feed conversion, increased susceptibility to
disease in general, reduced reproductive efficiency, premature
culling and reduced slaughter values. It is estimated that 68.0%
of US dairy herds are infected with JD, costing between $200
million to $1.5 billion per year to dairy industry (Sohal et al.,
2015). A study from India by Vinodhkumar et al. (2013)
estimated loss of Rs 1,840 (US$ 38.33) per infected
sheep/year. Another study from India in a Holstein Frisian
(H/F) dairy farm estimated loss of Rs 1,63,800.0 (US$ 2465)
in 180 days due to JD (Rawat et al., 2014). Besides costly to
animal husbandry, MAP is gaining interest as a zoonotic and
food-borne pathogen. Evidences suggest the involvement of
MAP in human diseases like Crohn‟s disease and type I
diabetes (Sohal et al., 2015). MAP is not killed by
pasteurization and milk has been considered as main source of
infection transmission to humans. MAP has frequently been
isolated from pasteurized milk and milk products (Shankar et
al., 2010). Rising concern of the MAP zoonosis has generated
lot of awareness among veterinarians and medicos seeking to
control this disease in animals. Therefore paratuberculosis
needs immediate attention for control in animals. This paper
discusses the role of vaccination and DIVA (Differentiation of
Vaccinated & Infected Animals) technology in efforts to
control Johne‟s disease.
2 Vaccination as tool of Paratuberculosis Control
Due to predominant subclinical nature of disease and
prolonged course of infection, early diagnosis is not possible
therefore control of paratuberculosis is problematic task. The
most widely practiced control strategy for paratuberculosis is
test and cull policy. However, due to lack of tools to detect
disease in early stages; test and cull policy is not sufficient in
preventing spread of MAP (Bastida & Juste, 2011). Despite
test and cull policies in place disease burden has continued to
increase (Singh et al., 2014). Positivity (number of positive
animals vs number of tested animals) of ruminant species in
India for paratuberculosis (cattle, goat, sheep and buffalo)
increased from 11.6% to 23.3% over the period of 28 years
(1985-2013) (Singh et al., 2014). Therefore alternate strategies
are required if control of paratuberculosis is to be achieved.
Vaccination programs in past have been successfully deployed.
As a result, there is increased interest in use of vaccination
against paratuberculosis. Vaccination is a cost-effective
strategy for paratuberculosis containment (Singh et al., 2007;
Juste & Perez, 2011; Bush et al., 2008; Dhand et al., 2013).
Vaccination reduces morbidity & mortality due to JD, reduces
shedding of MAP in feces, improves clinical signs (reduces
diarrhea & increases body weight), cures intestinal lesions and
enhances flock immunity to JD (Singh et al., 2007; Singh et
al., 2010b; Singh et al., 2013). Studies have confirmed that
vaccination not only reduces the prevalence of JD but also has
economic benefits to farmers (Groenendaal et al., 2015).
Vaccination also provides revival against MAP infection i.e.
therapeutic effects observed in already infected animals (Singh
et al., 2010b).
Benefits of vaccination have been summarized in Table 1.
Therefore vaccination is being considered an economically
attractive tool for controlling Johne‟s disease (Sohal et al.,
2015). Examples are there from countries like Iceland and
Australia where compulsory vaccination programs brought
about sufficient reductions in prevalence of paratuberculosis
(Sohal et al., 2015). Another indirect benefit of
paratuberculosis vaccination is that there is some degree of
cross protection for tuberculosis (de Val et al., 2012). Both
killed and live attenuated vaccines have the same efficiency in
controlling paratuberculosis (Singh et al., 2007) however,
killed vaccines have longer shelf life and are safer.
17 Jayaraman et al
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Table 1 Beneficial effects of vaccination against MAP
S.
No.
Name/ kind of vaccine Country Species Major Observation Reference
1. Laboratory Scale
(Live)
USA Cattle Vaccination reduces fecal
shedding of MAP
Larsen et al., 1974
2. Fromm (Killed) USA Cattle Hurley & Ewing 1983
3. Laboratory Scale
(Live)
Denmark Cattle Jorgensen, 1983
4. Laboratory Scale
(Live)
France Cattle Argente, 1992
5. Phylaxia (Killed) Hungary Cattle Kormendy, 1994
6. Neoparasec (Live) Germany Cattle Klawonn et al., 2002
7. Lio–Johne (Live) Spain Sheep Aduriz, 1993
8. Laboratory Scale
(Live)
Greece Sheep Dimareli–Malli et al., 2013
9. Live Vaccine New Zealand Sheep Gwodz et al., 2000
10. Killed vaccine - Goat Kalis et al.,
2001
11. Weybridge (Live) UK Cattle Vaccination improves
production
Wilesmith, 1982
12. Lelystad (Killed) Netherlands Cattle Kalis et al., 1992
13. Lio–Johne (Live) Spain Sheep Aduriz, 1993
14. Gudair (Killed) Australia Sheep Windsor et al., 2003
15. Neoparasec (Live) New Zealand Sheep Gwozdz et al., 2000
16. Laboratory Scale
(Killed)
Netherlands Cattle Histological improvement
after vaccination
van Schaik et al., 1996
17. Silirum (Killed) Spain Cattle Garcia–Pariente et al., 2005
18. Laboratory Scale
(Killed)
Iceland Sheep Sigurdsson, 1960
19. Lio–Johne (Live) Spain Sheep Aduriz, 1993
20. Mycopar (Killed) USA Sheep Thonney & Smith, 2005
21. Laboratory Scale
(Live)
Norway Goat Saxegaard & Fodstad, 1985
22. Laboratory Scale
(Killed)
USA Goat Kathaperumal et al., 2009
23. Laboratory Scale
(Killed)
India Goat Histological improvements,
reduction fecal shedding,
improves production and
therapeutic effects
Singh et al., 2007; Singh et
al., 2010b
24. Gudair (killed) Australia, New
Zealand and
Spain
Goat and
Sheep
Histological improvement,
reduction fecal shedding,
improves production
Griffin et al., 2009;
Reddacliff et al., 2006;
Eppleston et al., 2004; Corpa
et al., 2000
25. Killed Vaccine Iceland Sheep Reduction in mortality,
improves clinical signs and
reduction in fecal shedding of
MAP
Sigurdsson & Gunnarson,
1983
26. Live Vaccine Cyprus Sheep Reduction in mortality,
improves clinical signs and
reduction in fecal shedding of
MAP
Crowther et al., 1976
DIVA Technology: Indispensable Tool for the Control of Johne‟s disease. 18
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3 Issues of Paratuberculosis Vaccination
Vaccination efforts against paratuberculosis have succeeded
numerous times (Table 1); however, there are several issues in
implementing vaccination programs. First, vaccination against
paratuberculosis may interfere with routine diagnosis of
paratuberculosis. ELISA is the most widely used test for
diagnosing paratuberculosis because of low cost, rapid
turnaround time and high sensitivity. Other tests are costly,
time consuming, have poor sensitivity and requires
sophisticated facilities so are of limited utility when
incorporated into paratuberculosis control programs. However,
presently available ELISAs cannot discriminate vaccinated
individuals from naturally infected individuals. ELISA results
can be a problematic in certifying herds for disease
(paratuberculosis) free status where a compulsory vaccination
has either lowered the prevalence or eradicated the disease
from herd due to the fact that these tests can‟t discriminate
between pathogen and vaccine-induced immunological
responses. Since positive ELISA diagnostic test results for
MAP are often sufficient in triggering herd cull responses,
false positive results can be economically disastrous for cattle
farms. Secondly, vaccination against paratuberculosis will
interfere with diagnosis with tuberculosis and there are
evidences on this (Juste & Perez, 2011).
MAP and M. bovis share antigenic structures; therefore
immune responses generated by vaccination against these two
can interfere with diagnosis of paratuberculosis as well as
tuberculosis. Hence, implementing vaccination against MAP
will not only affect the diagnosis of paratuberculosis but will
also affect the tuberculosis control programs. Considering
these issues most of the countries are hesitant to vaccinate
against MAP. This problem is not just restricted to
paratuberculosis, there are number of animal diseases where
vaccines are available but cannot be used. One example is
FMD; vaccines are available and are quite effective in
controlling clinical disease but are not used in disease free
countries, as it interferes with diagnostic test results. Positive
immunological test results could ruin the disease free status
even of vaccinated healthy livestock populations, which, in
turn, can lead to serious economic losses in a region‟s
agronomy (Meeusen et al., 2007).
4 DIVA Technology
The primary goal of vaccination is to help in elimination of
disease. However, vaccinations elicit immune responses
similar to those found infected animals, thereby rendering
traditional diagnostic screening protocols useless as a means of
determining true herd disease status. Therefore it is essential to
differentiate immune responses due to vaccination compared to
natural infection. The term Differentiation of Infected from
Vaccinated Animals (DIVA) was coined in 1999 by Jan T. van
Oirschot (van Oirschot, 1999). It is now generally used in
place of older term „marker vaccines‟. The DIVA principle has
now also been extended to include killed whole organism
vaccines (Pasick, 2004). The general DIVA principle is that
antibody response produced by vaccination can be
differentiated from the antibody response elicited by natural
infection.
DIVA tests work by detection of immune response against
specific antigens which are present in the infectious agent but
in the absence of vaccine. Successful DIVA technologies has
been developed for animal vaccines like bovine rhinotracheitis
(IBR), pseudorabies, classical swine fever (CSF) etc (Meeusen
et al., 2007). Strategies for developing DIVA based vaccines
for other diseases like bovine tuberculosis (Vordermeier et al.,
2001), avian influenza (Rahn et al., 2015), PPR (Liu et al.,
2014) and bluetongue virus (Calvo-Pinilla et al., 2014) are also
under development. Though there has been great demand to
develop DIVA strategies for paratuberculosis, so far no
progress has been made and to our knowledge there is no
laboratory working on it. Till date, vaccination is the only
practical method for controlling paratuberculosis.
Since popular commercially available paratuberculosis
vaccines are whole cell killed preparations, simple strategies
can be designed to develop DIVA technology to differentiate
infected and vaccinated animals. Killed whole cell vaccines
will generate immune response only against cellular antigens
i.e. vaccinated animals will only have antibodies against
cellular antigens. However, in naturally infected animals will
have antibodies against both cellular and secreted (culture
filtrate antigens) antigens. Immune response against secreted
antigens can be selectively used to differentiate vaccinated and
naturally infected animals (Fig. 1). Therefore secreted antigens
of MAP can serve as markers of differentiation between
vaccinated and naturally infected animals and can be used to
develop DIVA. There have been reports that secreted antigens
are released early during the infection process and elicit
antibody responses (Ahmad, 2010), hence these can be used as
markers for early sero-diagnosis of paratuberculosis in early or
subclinical stages (Facciuolo et al., 2013). Presently available
commercial ELISAs contain a crude antigen mixture termed
PPA, which is prepared by thorough physical disruption of
mycobacterial bacilli followed by removal of cell debris.
The low sensitivity of available conventional ELISA tests can
be attributed to the lack of secreted antigens. Hence, a simple
ELISA based test can be developed using secreted antigens to
diagnose paratuberculosis as well as the same secreted antigens
based ELISA can be used to differentiate vaccinated and
infected animals if used in conjunction with conventional
ELISA protocols (Table 2). If MAP specific secreted antigens
are incorporated in this system then same ELISA regimen can
be used for diagnosis, DIVA marker detection and for
differentiating paratuberculosis & tuberculosis infection. Table
3 summarizes the MAP secreted proteins that can be used to
develop DIVA for killed whole cell vaccines and for
differentiating paratuberculosis and tuberculosis.
19 Jayaraman et al
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Figure 1 Scheme of the immune response that can be used to differentiate vaccinated and naturally infected animals.
Table 2 Scheme of the differentiation of healthy, infected and vaccinated animals
Concluding Remarks
Paratuberculosis is a devastating disease, negatively affecting
the livestock agronomy throughout the world, its presence
triggers trade restrictions and raises serious public health
concerns. Therefore control of paratuberculosis is of the utmost
urgency. Most extensively accepted “Test and Cull” policy is
very costly to farmers and governments; moreover it is not
particularly effective in stemming the physical spread of MAP
from one region to the next. Through the scientific, technical
and farming experiences it is becoming clear that vaccination
is the only practical solution for controlling this disease.
However, in the absence of DIVA technology, vaccination
programs cannot be implemented at national scale, as
vaccinations often elicit immune responses indistinguishable
from those generated by pathogens (using standard test
regimens).
DIVA Technology: Indispensable Tool for the Control of Johne‟s disease. 20
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Table 2 List of secreted MAP proteins that can be used to develop DIVA (in killed whole cell vaccine system) and for differentiating
paratuberculosis and tuberculosis.
S. No. Secreted Protein Function Remark
1. MAP 2609 - Tested for antigenicity by Willemsem et al. (2006)
2. MAP 2942c - Tested for antigenicity by Willemsem et al. (2006)
3. MAP 0210c - Tested for antigenicity by Willemsem et al. (2006); Mon
et al. (2012)
4. MAP 0209 - Tested for antigenicity by Mon et al. (2012)
5. MAP 0187c - Tested for antigenicity by Mon et al. (2012)
6. MAP 1272 Putative invasin, NlpC/P60 superfamily Tested for antigenicity by Mon et al. (2012)
7. MAP 1569/ ModD - Tested for antigenicity by Souza et al. (2011)
8. MAP 0471 - Tested for antigenicity by Facciuolo et al. (2013)
9. MAP 1981c - Tested for antigenicity by Facciuolo et al. (2013)
10. MAP 0196c - Tested for antigenicity by Facciuolo et al. (2013); Mon et
al. (2012)
11. MAP 1693c Peptidyl-prolyl cis–trans isomerase Tested for antigenicity by Mon et al. (2012); Roupie et
al. (2012)
12. MAP 0853 - Tested for antigenicity by Bannantine et al. (2008)
13. MAP 4308c - Tested for immunogenicity by Roupie et al. (2008)
14. CobT Phosphoribosyl transferase Tested for immunogenicity by Byun et al. (2012)
15. MAP 2168c - Tested for antigenicity by Cho et al. (2007)
16. MAP 1022c - Cho et al. (2006)
17. Antigen 85C Mycolyl transferase Tested for antigenicity by Shin et al. (2005)
18. PepA (N-terminal) Serine proteinase Tested for antigenicity by Cho et al. (2007)
19. PepA (C-terminal Serine proteinase Tested for antigenicity by Cho et al. (2007)
20. MAP 3273c - Gurung et al. (2014)
21. AhpC Alkyl hydroperoxide reductase C Tested for antigenicity by Olsen et al. (2001)
22. AhpD Alkyl hydroperoxide reductase D Tested for antigenicity by Olsen et al. (2001)
23. MAP 3680c - Tested for immunogenicity by Carlos et al. (2015)
24. Superoxide dismutase
(Sod)
- Tested for antigenicity by Shin et al. (2005)
25. MAP 0586c Possible transglycosylase SLT domain Tested for immunogenicity by Roupie et al. (2008)
26. MAP 2677c Glyoxylase Tested for antigenicity by Roupie et al. (2012)
27. MAP 3199 - Tested for antigenicity by Leroy et al. (2007)
28. MAP 1272c Putative invasin, NlpC/P60 superfamily Tested for antigenicity by Mon et al. (2012)
29. MAP 2942c - Tested for antigenicity by Gumber et al. (2009)
30. GreA Transcription elongation factor GreA Tested for antigenicity by Mon et al. (2012)
31. MAP 0593c - Tested for antigenicity by Gumber et al. (2009)
32. MAP 2411 - Tested for antigenicity by Kawaji et al. (2012)
33. MAP2168c - Tested for antigenicity by Cho et al. (2007)
34. Ppa Inorganic pyrophosphatase Tested for antigenicity by Gumber et al. (2009)
35. ClpP ATP-dependent Clp protease proteolytic
subunit
Tested for antigenicity by Gumber et al. (2009)
36. Ag85A - Tested for antigenicity by Rosseels et al. (2006)
37. Ag85B - Tested for antigenicity by Rosseels et al. (2006)
21 Jayaraman et al
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Journal of Experimental Biology and Agricultural Sciences
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This, in turn, greatly impairs determination of livestock herd
infectious disease status- critical for the entire livestock
agronomy. Since killed vaccines have good protective efficacy
against paratuberculosis, the strategy proposed in the paper can
be used to develop DIVA ELISA using the above
comprehensive list of antigens. A careful selection and
screening of secretory antigens is performed, we can develop
an ELISA based test that can be used as routine diagnostic
tool, as a DIVA tool and one that will be able to differentiate
paratuberculosis and tuberculosis. We suggest that the
development and validation of such a test be carried out on
global scale, with many laboratories working in conjunction
with one another, so that an effective strategy can be developed
for combating the worldwide spread of Johne‟s disease and
animal tuberculosis.
Conflict of interest
Authors would hereby like to declare that there is no conflict of
interests that could possibly arise.
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KEYWORDS
QTL
DArT
Yield and yield components
Planting dates
Sorghum
ABSTRACT
Genetic improvement for grain yield is one of the challenges in plant breeding programs. QTL analysis
is often used to dissect complex trait like grain yield for a better genetic manipulation. The purpose of
this study was to map QTLs associated with yield and yield component traits of sorghum grown under
early and late planting dates. A total of 528 recombinant inbred lines (RILs) and their two parents were
sown early and late planting times in an augmented rectangular lattice block design with two
replications to generate field phenotypic data. A total of 379 markers consisting of DArT, SSR and
morphological markers were used to genotype the RILs and the parents. Results revealed the presence of
overall twelve QTL across traits and planting dates. More QTLs were detected for grain yield as
compared to each of the other traits and most QTL associated with grain yield were consistent across
planting dates while QTL associated with yield component traits were not. Stable QTLs detected in this
study might provide valuable information in breeding sorghum for enhanced grain yield in diverse
growing environment.
Zenbaba Gutema1,*
, Teshale Assefa2 and Fuyou Fu
3
1Department of Biology, Northern Virginia Community College, Annandale Campus, 8333 Little River Turnpike, Annandale, VA 22003
2Department of Agriculture, Iowa State University, 2104 Agronomy Hall, Ames, Iowa, USA
3Department of Agronomy, Purdue University, 915 W. State Street, West Lafayette, USA
Received – October 25, 2015; Revision – November 08, 2015; Accepted – January 27, 2016
Available Online – February 15, 2016
DOI: http://dx.doi.org/10.18006/2015.4(1).26.36
DETECTION OF QUANTITATIVE TRAIT LOCI (qtl) ASSOCIATED WITH YIELD
AND YIELD COMPONENT TRAITS IN SORGHUM [Sorghum bicolor (L.) Moench]
SOWN EARLY AND LATE PLANTING DATES
E-mail: [email protected] (Zenbaba Gutema)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
Journal of Experimental Biology and Agricultural Sciences
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1 Introduction
Grain yield genetic improvement is one of the most important
objectives of many plant breeding programs around the world.
However, grain yield genetic manipulation has remained to be
a continued challenge in crop breeding. Sorghum [Sorghum
bicolor (L.) Moench] is the fifth most important cereal crop in
the world (FAO, 2012). It is the staple food for millions of
people in Africa and Asia. It is also one of the major feed crops
in the developed countries. Sorghum is extensively grown in
arid and semi-arid tropical and subtropical regions of the world
(Doggett, 1988). Sorghum cultivation has also been expanded
to the wet, cool temperate regions of the world particularly in
North America. Despite its economic importance, however,
sorghum has not been characterized very well genetically.
The multiplicative and interactive nature among yield
components in the formation of sorghum grain yield makes the
genetic manipulation of this important trait more complex
(Francis et al.,1983; Heinrich et al.,1985; Saeed et al., 1986).
Quantitative trait loci (QTL) analysis approach is useful in
dissecting such a complex trait for a better genetic
manipulation. QTLs linked with robust molecular markers
could be used to increase the efficiency of selection and
genetic gain in grain yield improvement.
QTL analysis has been used to detect genomic regions and
QTL associated with grain yield and its component for some
other crop species (Lu et al., 1997; Lu et al., 2006; Liu et al.,
2008; Xue et al., 2010). In sorghum, QTL associated with yield
and yield component traits have been reported recently
(Shehzad & Okuno, 2015). Further, a number of QTLs have
been also reported recently under certain contrasting conditions
such as photoperiod (Zou et al., 2012) and drought adaptation
(Phuong et al., 2013; Borrell et al., 2014) but till now, planting
dates have not been considered in QTL analysis. Although in
general late planting is considered normal, farmers desire early
planting because of its several advantages including full
utilization of late spring and early summer rainfalls. Early
planting may also help in completing plant life cycle before
cold spell during the growing season (Yu & Tuinstra, 2001).
Most of the current sorghum cultivars are developed under late
planting, however, early planting needs to be considered as
well.
In the present study, large numbers of molecular and field data
were generated on grain yield and its component traits like
plant population, kernel number and kernel weight by using
RIL population sown early and late planting dates. The data
were subjected to QTL analyses utilizing relatively dense
genetic map constructed from mix of molecular and
morphological markers. Several QTL were detected
segregating in this large population for each of the traits.
However, only few QTL were found to be stable across
planting dates. These stable QTL were listed and characterized
for further studies targeting sorghum breeding for better grain
yield.
2 Materials and Methods
2.1 Genetic materials and experimental design
Sorghum recombinant inbredlines (RILs) lines were derived
from a cross between SRN-39 (an African caudatum) and Shan
Qui Red (SQR), (a Chinese germplasm line). The two parents
differ for a number of characteristics including yield and yield
components. About 1000 random F2 plants of this cross were
selfed and advanced up to the F5 generation by the single seed
descent method. Selfed seeds from each inbred line were used
to grow F5:6 progeny rows which were selfed and bulked (Cisse
& Ejeta 2003). Subsequent generations were maintained
through repeated cycles of selfing and bulking to F5:9 seeds
from which a total of 528 RI lines were sampled for the
purpose of this study. Seeds of these parents were maintained
in the on-going sorghum breeding nurseries.
The RILs and the parents were grown in an augmented lattice
design with 24 sub-blocks within two replications. The parents
were repeated in each sub-block thus each replication
constituted 576 total entries each with a two-row plot. Rows of
six meter length, spaced 75 cm apart were drill-seeded at the
rate of approximately 10 seeds per 30 cm at a depth of 2.5 cm
by a John Deer Max Emerge planter modified for small
research plots. The seedlings were hand-thinned to a spacing of
6 plants per 30 cm. The nurseries were planted during the 2005
and 2006 crop seasons at Purdue University Agronomy Center
for Research and Education (ACRE) in West Lafayette,
Indiana. The nurseries were planted early and late planting
dates each year. The first planting dates were at least three
weeks earlier than the late (normal) planting and they were
chosen to enhance performance differences among the RILs
under cool and wet soil conditions. Relatively large data were
generated for QTL analysis on sorghum grain yield and yield
components. Three yield components: plant population size,
kernel number, and kernel weight were assessed.
Weather conditions were measured at hourly intervals via a
weather station close to the test plots. Weather data during the
early and late planting dates of the experiments are
summarized in Table 1. The weather conditions were
contrasting between early and late planting dates especially
during the early growing period (times during seedling growth)
of the nursery. The average rainfall was lower in 2005 than in
2006.
27 Gutema et al
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Table 1 Climatic condition of study site at Purdue University Agronomy Center for Research and Education, West Lafayette, Indiana in
2005 and 2006 crop seasons.
Planting time Planting Date Temperature (0C) Rainfall (mm)
Soil Air
Min Max Min Max Average
Early May 4, 2005 11.9 20.0 9.3 20.8 54.1
Late May 23, 2005 19.2 28.1 18.0 26.0 61.5
Early April 27, 2006 9.6 26.0 6.3 26.9 89.4
Late May 30, 2006 19.7 28.3 18.3 27.3 86.0
Data courtesy of Purdue University Weather Station.
2.2 Phenotypic data measurements and analyses
The middle five meters of the two rows in each of the RILs
entries were used for yield and yield component traits
measurements in this study. Plants per plot (3.75 m2) were
counted at maturity to determine plant population size.
Panicles of counted plants were harvested manually at the end
of the growing season for each plot, threshed and weighed for
grain yield (kg/plot) for QTL analyses but converted to t/ha for
analyses of variance (ANOVA), which was used to examine
significant differences among the RILs for these traits. One
hundred counted seed weights were measured and kernel
number per plant was estimated from data on kernel weight,
grain yield and number of plants per plot. Values were
averaged per replication for each of the traits for QTL
analyses.
The ANOVA was carried out using GLM procedure in SAS V.
9.1 (SAS Institute, Cary, NC) using the following general
model: Y = µ + G + L R + ε, (Knoll & Ejeta, 2008) where
Y is the dependent variable, μ is the experiment mean, G is a
genotypic effect, R is a replicate, L is a lattice block (nested in
rep), and ε is the error. Broad sense heritability was estimated
following method of Cisse & Ejeta (2003).
2.3 Genomic DNA isolation
Leaf tissue for genomic DNA isolation was harvested from
field grown seedlings at three weeks after planting.
Approximately one gram sections were cut from the uppermost
second and third leaves and bulked. Harvested leaf tissue was
kept on ice during harvest and lyophilized upon returning to
the laboratory. The lyophilized samples were kept at -80oC
until grinding to a fine powder with a UDY Cyclone Mill. A
CTAB based DNA extraction method according to Saghai-
Maroof et al. (1984) was used with only minor modifications.
2.4 Genotyping
The 528 RILs and the two lines were genotyped with three
types of markers vise-a-vise morphological markers scored in
the field or laboratory, SSR markers scored in our laboratory
and Diversity Array Technology (DArT™) markers scored at
DArT Plc., Yarralumla, Australia. A total of 359 DArT™
markers that were polymorphic between the parents, 15 SSR
markers and five morphological markers (seedling color, plant
color, seed color, presence/absence of a pigmented testa layer
and pericarp color) were used to construct a dense sorghum
genetic linkage map using the maximum likelihood method of
Join tMap 4 (Van Oijen, 2006).
2.5 QTL analysis
Single-trait analyses were undertaken for each environment
data using composite interval mapping (CIM) (Zeng, 1994)
with QTL Cartographer version 1.17ji (Basten et al., 2005).
The CIM was undertaken with conditional settings of 10 cM
(default) control intervals, five control markers set by QTL
Cartographer stepwise regression and forward/background
(FB) stepwise regression to account for the genetic background
variation. The five most significant (default) markers were
utilized and the default threshold level of 2.5 LOD in QTL
Cartographer 1.17ji (Basten et al., 2005) was used to declare a
QTL.
3 Results
3.1 Linkage map construction
A genetic linkage map consisting 11 linkage groups was
constructed in which chromosome A was found to be broken
into two linkage groups according to Bhattramakki et al.
(2000). We used SSR markers from this published map to
anchor the relatively new DArT markers. The map spans 1175
cM with an average marker distance of 3.14 cM with no major
gap.
3.2 Parental lines phenotypic analysis
The parental lines displayed significant divergence for all the
traits except for grain yield (Table 2). The SQR parent had
more plants per plot as compared to SRN-39 under early cold
planting. On the other hand, SRN-39 had better field
establishment under late planting as expected for this Africa
originated cultivar adapted to higher temperatures. However, it
did not exceed the SQR even under improved temperatures,
suggesting the importance of SQR for field establishment
under any planting condition. Contrary to plant population,
SRN-39 had more kernels as compared to SQR under both
early and late plantings.
Detection of quantitative trait loci (qtl) associated with yield and yield component traits in sorghum [sorghum bicolor (l.) moench] sown early. . . 28
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Table 2 Summarized mean performance of parental lines in field experiments planted early and late during 2005 and 2006 crop seasons
at the Agronomy Center for Research and Education testing site of Purdue University, West Lafayette, Indiana.
Planting time Parental line Traita
Plant population
(count)
Kernel number Kernel weight
(gm)
Grain yield (t/ha)
Early SRN-39 24.08±10.3 2699.49±120 3.71±0.3 4.31±0.8
SQR 44.37±4.2 1584.00±70 2.84±0.4 5.21±0.4
Late SRN-39 32.23±6.2 1622.64±60 3.75±0.2 5.11±0.3
SQR 43.05±3.2 1521.01±45 2.86±0.3 4.46±0.2
Overall mean SRN-39 28.16±8.2 2161.07±90 3.73±0.3 4.71±0.7
SQR 43.71±4.0 1552.51±65 2.85±0.4 4.84±0.3 a/Traits measured in augmented rectangular lattice block design with the parents repeated in each of 24 lattice blocks replicated twice in
four field experiments conducted over two years.
SRN-39’salso had heavier kernels than SQR under both
planting dates. The result of higher kernel number by SRN-39
under early planting as compared to SQR when it planted
under late normal planting was probably in response to sparse
plant population under cold early planting that killed some of
its seedlings. Kernel weight was not significantly different in
the planting dates for this parent. SQR yielded more grain than
SRN-39 under early planting but not under late planting.
Overall, SQR had higher yield than SRN-39 despite of SRN-
39’s outperformance both in kernel number and kernel weight.
The results might be a reflection of higher impact of plant
population size on the development of grain yield in sorghum
as compared to kernel number or kernel weight.
3.3 Phenotypic analysis and broad-sense heritability
Results in Table 3 showed wide variations and transgressive
segregations for all traits among the RILs at both early and late
planting dates. Phenotypic mean values for grain yield and
other traits in this RIL population appeared to be more or less
normally distributed (Figure 1). Mean agronomic performances
were lower than each parent except for plant population trait
where the RILs mean performance was higher than the ‘low’
parent SRN-39. The results indicated the extreme sensitivity of
the African origin SRN-39 parent to cold weather and\or the
efficiency of cold tolerance genes from Chinese highland SQR
parent.
The RILs had better performance under late (normal) plantings
for plant population size as well as grain yield traits as
expected. However, for kernel number, on average, RILs had
better performance under early plantings like the parents. For
kernel weight, similar performance was observed across
planting times although lower kernel weight was measured for
2006 late planted nursery. In general, mean agronomic
performances of the RILs were better during 2005 crop season
as compared to 2006. The air and soil temperatures during
2005 plantings improved quickly resulting into higher
performance across planting dates during this season. In
contrary, continued colder weather in 2006 crop season
plantings killed seedlings of several entries particularly in early
planted nursery and resulted into erratic field establishment
which in turn resulted into lower agronomic performances for
most traits. The highest overall mean agronomic performance
was noted for 2005 late planted nursery, while the lowest was
noted for 2006 early planted nursery, reflecting two possible
extreme growing conditions for sorghum in our study. Overall,
high standard deviations were recorded for all the traits except
for kernel weight.
Table 3 Mean agronomic performance, range and heritability values of yield and yield component traits of sorghum measured in 528
RILs planted early and late cropping season.
Year Planting time Traita
Plant population (count) Kernel number Kernel weight (gm) Grain yield (t/ha)
2005 Early 40.7±13.1 1257.5±47 3.0±0.4 3.7±1.1
Late 43.9±10.6 1210.9±45 3.1±0.5 4.1±1.3
2006 Early 17.6±9.8 2171.7±1120 3.0±0.4 2.7±1.4
Late 36.0±7.8 1297.2±40 2.8±0.4 3.4±1.1
Mean±Stdevb
34.6±15.0 1484±789.2 2.3±0.4 3.5±1.3
Range 1.0 – 78.0 39.7- 9102.1 1.3 – 4.7 0.004 - 7.7
Heritability (H2) 0.64 0.68 0.93 0.77
aTraits measured in augmented rectangular lattice block design with 24 lattice blocks replicated twice in four field experiments
conducted over two years. bStdev = Standard deviation.
29 Gutema et al
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Broad-sense heritability values were in general high and the
high values illustrate the utility of this large RILs population in
our study in determining greater genetic influence on the
expression of traits as compared to the environment. The
highest heritability value was calculated for kernel weight
(0.93), followed by grain yield (0.77). Kernel number (0.68)
and plant population (0.64) had relatively low heritability
indicating more environmental influence in the expression of
these two traits of present study.
The ANOVA showed that there was highly significant
variation for entries in each of the two years experiment for all
the traits (Table 4). Planting date also had a significant effect.
Furthermore, the interaction of planting date with the RI lines
was highly significant in both years showing high genotype-
by-environment interaction. The observed high phenotypic
variability of all the traits in terms of ranges and ANOVA
results indicated that the population was suitable for QTL
analyses.
Figure 1 Phenotypic value distribution for 528 RILs planted in an augmented rectangular lattice design with 24 lattice blocks replicated
twice in four field experiments conducted over two years.
Detection of quantitative trait loci (qtl) associated with yield and yield component traits in sorghum [sorghum bicolor (l.) moench] sown early. . . 30
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Journal of Experimental Biology and Agricultural Sciences
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Table 4 Analysis of variance for grain yield and yield component traits of sorghum.
Year Source dfa Plant
Populationb
Kernel
numberb
Kernel
weight
Grain
yield
2005 Planting Date 1 43.558 0.218 15.281 5.297
Rep(Planting Date) 2 0.891 0.134 0.339 0.219
Lattice block (Planting date x Rep) 92 0.388 0.027 0.029 0.058
RIL 526 2.854 0.067 0.665 0.289
Planting Date x RIL 526 0.299 0.013 0.035 0.045
Error 960 0.152 0.007 0.019 0.021
2006 Planting Date 1 1991.5 19.944 22.226 31.31
Rep (Planting Date) 2 16.856 1.671 0.028 0.725
Lattice block (Planting date x Rep) 92 0.531 0.028 0.025 0.053
RIL 526 2.307 0.091 0.547 0.399
Planting Date x RIL 526 0.824 0.028 0.035 0.090
Error 960 0.182 0.011 0.015 0.030 aDegrees of freedom.
bError variances for plant population and kernel number were not strictly homogenous in this analysis. ***, All
mean squares are significant at α = 0.0001.
3.4 Phenotypic correlation among traits
Pearson correlation coefficients were computed among traits
values (Table 5). The largest but negative sign correlation
coefficient (r=0.57) was observed between plant population
and kernel number, the negative sign of the coefficient
suggesting the opposing effect of these two traits in the
formation of final grain yield in sorghum. The second largest
but with positive sign of correlation coefficient (r=0.51) was
between plant population and grain yield, indicating positive
impact of plant population on grain yield of sorghum.
The other negative coefficient (r=0.26) was observed between
plant population and kernel weight, again indicating the
opposing effect of these two traits in the formation of sorghum
grain yield. Significant positive correlations coefficients were
also observed for both kernel number and kernel weight with
grain yield. These results were as expected as both of these
traits actually contribute to the measure of grain yield.
Interestingly, kernel number and weight also had a positive
correlation.
3.5 QTL detection
Sixteen data sets were organized and analyzed for QTL
detection. Using the default 2.5 LOD threshold to declare a
QTL in QTL Cartographer, a total of 12 QTL were detected
across traits and planting dates as summarized in Table 6.
Seven chromosomes (linkage groups) of the ten sorghum
chromosomes were mapped with one or more QTL (Figure 2).
Twenty two DArT and two SSR markers were closely linked
with QTLs of the traits (Table 7). Compared planting time
wise, in general, the number of QTL detected tended to be
higher in late (normal) planted nurseries as compared to early
planted nurseries.
3.6 Plant population
Two QTLs were detected for plant population (Table 6). These
QTL were detected in both early and late planted nurseries of
2005 crop season but no QTL detected for plant population in
our extended cold season experiments of 2006 where cold had
significant impact on seedling establishment. The phenotypic
variation explained by these QTLs ranged from two to three
percent and the additive effects for both QTL were 3.2. The
increasing alleles of the QTLs expressed under early planting
time was contributed by the Chinese cold tolerant SQR line
while the alleles for QTLs expressed under late planting
contributed by African originated SRN-39 genotype both of
these results being as expected.
3.7 Kernel number
Three QTL were detected for kernel number across planting
dates and years (Table 6). Unlike in plant population trait, two
QTLs were detected in severe cold conditions of 2006 early
planted nursery. From phenotypic data analysis, kernel number
trait performance was best in this nursery and the result might
suggest the importance of good phenotypic performance in the
detection of more QTL. The phenotypic variations explained
by the QTLs were four percent and were the same for all the
QTL. The additive effects were103 and 227 for alleles
contributed by the parent SRN-39 and 159 for alleles
contributed by the parent SQR.
3.8 Kernel weight
Like in plant population, only two QTLs were detected with
the default 2.5 LOD threshold used for other traits but with
slight modification of this threshold to 2.4, four more QTLs
were detected for kernel weight (data not shown).
31 Gutema et al
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Journal of Experimental Biology and Agricultural Sciences
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Table 5 Pearson correlation coefficients (R) among yield and yield component traits values from data on 528 RI lines replicated twice in
four field experiments conducted over two years.
Traits Plant population Grain yield Kernel weight Kernel number
Plant population 1.00
Grain yield 0.51*** 1.00
Kernel weight -0.26*** 0.10*** 1.00
Kernel number -0.57*** 0.15*** 0.10*** 1.00
***, Significant at α = 0.0001.
Table 6 Number of QTL detected with data collected early and late (normal) planted nurseries for grain yield and yield component traits
of sorghum as analyzed through composite interval mapping (CIM).
Year Planting Date Number of QTL detected
Total
Plant population Kernel number Kernel weight Grain yield
2005 Early 1 - - 2 3
Late 1 1 - 1 3
2006 Early - 2 - - 2
Late - - 2 2 4
Total 2 3 2 5 12
Despite similar phenotypic performance of kernel weight trait
across most of our environments, QTLs detected for kernel
weight were limited to 2006 late planted nursery. Both parents
contributed to the increasing alleles.
3.9 Grain yield
A total of five QTLs were detected for grain yield although
from the partially overlapping position three QTLs seemed to
be the same. No QTL detected for grain yield in 2006 cold
early planted nursery in a manner this environment affected
QTL detection for plant population. From phenotypic data
analysis, plant population has significant impact on grain yield
which might have again reflected on the detection of QTL for
grain yield in this environment. Three QTLs were detected in
three of four environments indicating the most consistence of
grain yield QTL in this study. Two of the QTL were found on
two different chromosomes (C and E) but three QTLs were all
found on the same chromosome (F). A LOD score as high as
4.5 were noted for one of these QTL showing high evidence
for grain yield QTLs in our analysis. The phenotypic variations
explained by the QTL ranged from two to five. Unlike yield
component traits where both parents contributed the increasing
alleles, all the increasing alleles were contributed by SRN-39
for grain yield.
4. Discussion
4.1 Phenotypic traits analysis
Traits from seedling to crop maturity can impact grain yield of
sorghum (Heinrich et al., 1985; Saeed et al., 1986). Present
study shows that plant population (density) is the most
important trait among yield component traits of sorghum to
increase grain yield per unit area. The far reaching importance
of plant population sizes in grain yield per unit area was
recognized for maize long ago (Tokatlidis & Koutroubas
2004). In sorghum, the importance of plant population size
might be overlooked because sorghum plants try to
compensate grain yield loss due to sparse population by
tillering (Stickler & Pauli, 1961). Observation on parental lines
demonstrated this assertion. We observed that SRN-39
responded to sparse population by tillering and producing more
and heavier kernels, but surprisingly it did not produce higher
grain yield than SQR. Clearly, SQR produced more plant
population per unit area than SRN-39, which resulted into
higher grain yield. The results indicated the importance of
plant population for increasing grain yield in sorghum,
especially under cold early planting. Furthermore, our RILs
correlation analyses show that plant population is positively
and highly correlated with grain yield, suggesting that an
increase in plant population per unit area would results into an
increase in grain yield as well. On the other hand, it was
observed that plant population is negatively correlated with
other yield components such as kernel number and kernel
weight. This result suggested the counter effect of increased
plant population on grain yield through these two yield
component traits. As the number of plants per plot increases,
smaller panicles (thus fewer kernel number/panicle) with
smaller kernel size (thus lesser kernel weight) are produced
because of plant to plant competition. Therefore, optimum
plant population (density) should be established by empirical
field data to maximize grain yield for a given cultivar under a
given production condition (Francis et al., 1983).
Detection of quantitative trait loci (qtl) associated with yield and yield component traits in sorghum [sorghum bicolor (l.) moench] sown early. . . 32
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Journal of Experimental Biology and Agricultural Sciences
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Figure 2 Genetic linkage map showing significant QTL associated with grain yield and yield component traits of 528 RIL and their
parents grown early and late planting dates.QTL named as q=QTL, followed by abbreviation name of the trait: YE=grain yield,
KN=kernel number, KW=kernel weight and PP=plant population, and linkage group number (LG) and then serial number of the QTL
per linkage group.
Table 7 List of QTL mapped for plant population, kernel number, kernel weight and grain yield analyzed using CIM.
Trait QTLa Flanking marker
b Position
c Additive effect R
2d (%) LOD score Source
e
Plant population qPP-LG02 DM164-DM233 130 3.24 3 3.0 SQR
qPP-LG11 DM290-DM37 99 3.16 2 2.7 SRN-39
Kernel number qKN-LG03 DM320-DM143 50 159 4 3.3 SQR
qKN-LG05 DM275-Txp145 46 227 4 3.5 SRN-39
qKN-LG07 DM271-DM1 13 103 4 3.4 SRN-39
Kernel weight qKN-LG06 DM276-DM130 22 0.10 3 3.3 SRN-39
qKN-LG08 DM11-DM71 50 0.08 3 2.7 SQR
Grain yield qYE-LG07 DM28-DM61 50 0.23 4 3.4 SRN-39
qYE-LG08 DM278-DM138 45 0.22 5 3.6 SRN-39
qYE-LG11-1 DM157-DM57 30 0.32 5 4.5 SRN-39
qYE-LG11-2 Txp258-DM145 15 0.16 4 3.5 SRN-39
qYE-LG11-3 DM157-DM57 22 0.14 2 2.6 SRN-39 aQTL named as q=QTL, followed by abbreviation name of the trait: YE=grain yield, KN=kernel number, KW=kernel weight and
PP=plant population, linkage group number (LG) and serial number of the QTL per linkage group. bLeft and right flanking markers;
DM=DArT marker. cShows absolute positions of test locations from left telomere in centiMorgans.
dVariation explained by the QTL.
eShows source parents for the increasing allele.
DM3260.0DM210.3Txp21117.7DM31626.4DM2339.1DM14254.4DM29955.2DM15561.3DM7961.6DM24164.3DM13965.5DM28768.6DM17468.9DM23472.6DM22774.3DM33380.6DM988.9DM28599.7DM35100.3DM340101.5DM72109.8DM95109.9DM99111.1DM102112.4DM334114.2DM38118.0DM267118.2DM212120.4DM352122.2DM203127.3DM193128.3DM164128.9DM195129.6DM233132.7DM69133.8DM122134.2DM260136.3DM259138.6DM129144.5DM208DM288DM209
153.0
DM322155.1DM243164.3DM18166.2Txp8169.5DM183174.5DM292DM256
174.7
DM261174.9
qPP-LG02
LG2
DM1730.0DM1095.1DM1818.0DM20713.9DM8522.4Txp21722.8DM6523.4DM19923.6DM137DM156DM41
23.7
DM8823.9DM16224.2DM635.3DM31038.5DM32839.1DM32042.0DM3642.2DM24643.7DM14357.2DM2057.3DM26958.3DM5877.8DM11978.1DM29185.3DM21593.1DM251DM258
100.8
qKN-LG03
LG3
Sedlcolor0.0
DM26310.3DM16512.7Plancolor19.2DM3220.5DM5221.5DM23623.9
DM18436.0
DM27541.0
DM32758.8Txp14561.7DM20266.8DM33571.9DM16874.9DM8180.0DM8980.4DM21984.4
DM34198.1DM29599.5DM15101.9
DM313110.6DM3113.3
DM192122.6
DM350131.7
DM346140.4DM330142.5
DM282152.5qKN-LG05
LG5
DM2380.0DM2714.0DM305DM226DM249
5.4
DM122.0
Txp15928.9
DM28034.3Txp31236.1
DM2844.7
DM18752.1
DM6163.5DM35964.4DM28466.6DM18867.6DM13571.2
DM23780.8
DM14894.1DM30100.2DM230103.1DM323106.1DM166108.5DM298108.9DM302115.2
DM347125.0
qKN-LG07qYE-LG07
LG7
DM460.0DM2551.8DM1348.0Txp25812.2DM15716.2DM14528.8DM5029.2DM21829.5DM5731.6DM11339.2DM12139.5DM11840.3DM35642.0DM248DM178
42.1
DM27042.2DM22345.9DM4248.1DM24756.2DM30162.2DM167DM128
81.9
DM1988.9DM34389.3DM10889.6DM25791.8DM26595.6DM29097.4DM1297.7DM3798.9DM5100.4DM228106.5DM49110.2
qPP-LG11
qYE-LG11-1
qYE-LG11-2
qYE-LG11-3
LG11
DM2440.0DM339DM26
8.2
DM448.4DM16DM252
8.7
DM14010.2DM17912.9Txp28524.7DM325DM25
33.9
Txp6943.3DM27846.6DM1148.5DM13849.7DM7152.8DM13255.9DM34259.3
DM20474.1
DM23279.9
DM32990.0DM34892.4DM21196.9
DM221106.8
DM22112.8
DM355124.6DM303130.6DM114133.5DM262134.7
qKW-LG08
qYE-LG08
LG8
DM2810.0DM30412.5DM27614.1DM283DM151
14.4
DM19114.5DM19418.1DM4018.3DM34418.6DM13027.7DM731.7DM17232.6DM14132.8DM9333.3DM31838.5DM30854.3DM27458.2DM27363.4DM6867.9DM16082.3DM28985.4DM22994.1DM896.3DM32196.6DM19097.2DM8097.3DM8497.5DM9297.8DM12398.0Txp43104.6DM222106.1DM136111.3
qKW-LG06
LG6
33 Gutema et al
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It was also observed that kernel number and kernel weight had
highly significant positive correlation within themselves and
with grain yield suggesting both of these traits could be equally
important in breeding high-yielding sorghum cultivars. These
two interdependent traits could be manipulated simultaneously
or separately in selection of sorghum with high grain yield.
However, kernel number was found to be influenced by
planting time, while kernel weight was not. Our data showed
that more kernels produced under early planting as compared
to late planting. This result might be due to better opportunity
of longer growing season under early plantings or smaller plant
population size. When cold weather killed seedlings of several
RI entries during early planting, we observed that the
remaining seedlings use the opportunity of having more space
to grow more profusely producing larger panicle and more
kernels as we observed for SRN-39 parent also. The results
indicated the importance of planting time for maximum kernel
number. Contrary to kernel number, kernel weight seemed to
be lightly affected by planting time. Based on Saeed et al.
(1986), kernel weight might be affected more by moisture
availability in the soil during critical period of grain filling
rather than planting time. In present study, although less
rainfall was received in the first year of our experiments as
compared to the second year, there was no moisture stress that
could affect grain fill or kernel weight at any time.
In addition to yield increase per unit area, yield stability across
diverse growing environments is also an important
consideration for plant breeders. In present study, both plant
population and kernel number traits seemed to be unstable
across environments. On contrary, grain yield and kernel
weight seemed to be more stable. Based on its stability and
high heritability, kernel weight might be one of the most
important traits to attain stable grain yield in sorghum under
diverse growing environments.
More stable grain yield could be obtained by late planting
because optimum plant population can be established under
late planting. However, in our study we found that late planted
nurseries exhibited rapid growth rate, which could promote
lodging during late seedling growth because of higher
temperature. This again demonstrated the importance of
optimal time of planting to attain optimum plant populations
under early planting cold conditions. This can be realized with
the development of sorghum cultivars with cold tolerance
genes suited to early planting (Knoll & Ejeta, 2008).
Although the extended growing time of present early planting
did not seem to translate to higher overall mean grain yield,
there were several individual entries that had higher grain yield
under early planting, consistent with Knoll & Ejeta (2008)
observations for sorghum hybrids. The observation of extreme
values (both minimum and maximum) under early cold
planting was a recurring result for most of the traits measured
in our study including panicle size and plant height (data not
shown). This indicates both the challenges and the
opportunities for sorghum genetic improvement under cold
early planting.
4.2 QTL Analysis
Considering the quantitative nature of the traits in this study,
divergence in the parents for most of the traits and
performance of the RILs, surprisingly few QTL were detected
in this study for each trait. However, in QTL analysis, several
factors such as data quality, phenotypic performance, marker
density, population size and growing environment can
contribute to the power of QTL detection.
Considering data quality, obviously good quality data such as
limited number of missing plot would be necessary to detect
more QTL. In our study, missing plots were not more than
three in our over 4600 plots and in general our data can be
regarded as of a high quality. Other than limited number of
missing plots, field agronomic performance by the genotype is
also important to detect QTLs. The detections of more QTLs
with our better performing nurseries might justify this
assertion. However, from phenotypic data analysis, it was
surprising that QTLs were detected rather in the least
performing environment for kernel weight trait. It might be
suggested that other data structures were also important in
detection of more QTLs rather than mere phenotypic
performance scored for kernel number. In addition,
environment can affect the number of QTLs being detected. In
some extreme cases, QTL may not even detect as for most
traits in 2006 cold early planted nursery. Besides phenotypic
data, genotypic (marker) data are an important issue in the
power of QTL detection (Darvasi et al., 1993; Doerge et al.,
1997; Doerge, 2002). In this study, relatively large and dense
genetic map constructed from various markers was used. Our
study confirms the utility of DArT marker system for sorghum
as demonstrated in other most recent publications (Mace et al.,
2008; Mace et al., 2009; Mace & Jordan, 2011). Besides
marker size, population size could affect the number of QTL
detected (Beavis, 1994). In sorghum, Rami et al. (1998)
detected no QTL with their limited population size. In our
study, relatively large population size was utilized and to our
knowledge, we deployed the largest (N=528) RI lines
population ever used to analyze QTL in sorghum.
From the above discussions, the few number of QTL detected
in present analyses might be the actual number of QTL
segregating in this population. The relatively high heritability
values calculated for each trait and large LOD score
particularly for grain yield trait in our study might give certain
confidence in the number of QTLs detected. In our study, apart
from our interest in the exploration of the number of QTLs
expressed under contrasting environments, identification of
QTLs associated with sorghum grain yield and its component
traits deemed useful in breeding sorghum for higher grain
yield.
As described in phenotypic data analyses, plant population is
crucial in attaining high grain yield in sorghum and therefore,
identification of robust QTLs associated with this trait is of
particularly interest as previously addressed by Knoll & Ejeta
(2008). However, due to the fact that plant population develops
Detection of quantitative trait loci (qtl) associated with yield and yield component traits in sorghum [sorghum bicolor (l.) moench] sown early. . . 34
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early in the season when environmental conditions are less
conducive for sorghum plant, QTLs associated with plant
population size accessed through stand count at maturity are
environmentally sensitive and may not be detected at all as in
our 2006 experiments. Kernel number per panicle is also
basically set during early growth as it is related to plant
population (density). However, there is flexibility for sorghum
plant to realize this trait more as a function of time in the
growing season. This makes QTL associated with kernel
number trait important for sorghum breeding aimed at higher
grain yield. Regarding kernel weight, QTLs detected were few
and limited to single environment in our study. However, when
we decreased the QTL detection threshold LOD just slightly
from the default 2.5 to 2.4, four more QTL were detected (data
not shown) and these QTLs were consistent across planting
dates (environments). These results might substantiate our
findings in phenotypic data analysis and suggest the
importance of kernel weight QTL in breeding sorghum for
yield stability across diverse growing environments. In
phenotypic data analysis, we observed the environment to have
little impact on kernel weight as evidenced by small mean
standard deviation and high heritability for this trait.
Consistent with the most quantitative nature of grain yield trait,
the highest number of QTLs was detected for grain yield in our
study despite little divergence in the parents for this trait.
Rather many loci could contribute to the overall grain yield
making breeding for grain yield a challenging task but from
our finding, it is likely that one major QTL significantly
contributed the greatest portion of grain yield as in oligogenic
traits. Surprisingly our results showed that QTLs for grain
yield were more stable across planting dates as in kernel
weight. The results were consistent with the observations
reported by Stuber et al. (1992) in corn. In our study, it might
be speculated that the effect of environment on grain yield was
buffered through physiological functions of the yield
components since grain yield is rather the result of complex
interaction of the individual components (Saeed et al., 1986).
In conclusion, our findings indicated that although grain yield
trait is complex, one major QTL that significantly contribute to
grain yield could be identified and utilized in breeding
sorghum for higher grain yield. In addition, the robust SSR
markers detected flanking grain yield and its component in our
study could be used in breeding sorghum to improve grain
yield under different planting conditions if validated with
further research.
Acknowledgments
The financial support for this study was provided by the
International Sorghum and Millets Research Network
(INTSORMIL) of USAID.
Conflict of Interest
The authors declare that there is no conflict of interests that
could possibly arise.
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KEYWORDS
Micronutrient
Soybean
Water deficit stress
Yield parameters
ABSTRACT
Effects of foliar application of molybdenum and iron either individually or in combination on the yield
properties of soybean crop were investigated under water deficit condition at research farm of Sari
Agricultural Sciences and Natural Resources University, Sari, Iran during the cropping season of 2014.
This experiment was laid out in factorial arrangement based on completely randomized block design
with three replications. The two irrigation regimes were used (Irrigation after 65 and 130 mm
evaporation from Class A pan) as primary factors while spray application of micronutrient (water as
control Fe, Mo and Fe + Mo) were considered as the secondary factors. Result of study revealed that
drought stress and micronutrient sprays have effect on all studied parameters such as pod number, seed
number, yield and weight of 1000 seeds. Also, the interactions were statistically significant among
studied parameters. According to the results drought stress severely impressed the number of pods, total
seed numbers, seed yield, seed protein and seed oil. Furthermore, using of micronutrients spray
particularly Fe+Mo on soybean crop is environmentally acceptable strategy and reduced the damages
caused by water deficit condition.
Ayoub Heidarzade1, Mohammadali Esmaeili
1,*, Mohammadali Bahmanyar
2 and Rahmat Abbasi
1
1Department of Agronomy, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
2Department of Soil Sciences, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
Received – December 16, 2015; Revision – December 29, 2015; Accepted – January 31, 2016
Available Online – February 20, 2016
DOI: http://dx.doi.org/10.18006/2015.4(1).37.46
RESPONSE OF SOYBEAN (Glycine max) TO MOLYBDENUM AND IRON SPRAY
UNDER WELL-WATERED AND WATER DEFICIT CONDITIONS
E-mail: [email protected] (Mohammadali Esmaeili)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
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1 Introduction
Soybean (Glycine max) is a common legume plant and
cultivated for more than 3000 years in Southeastern Asia
(Dwevedi & Kayastha, 2011). Soybean stands first in the world
as edible oil and occupies important place in the economy.
Climatic and edaphic factors severely affect its production;
according to Turner (1991) performance of this crop is highly
affected by the availability of trace elements such as
Molybdenum and Iron. It has been also well reported that
deficiency of micronutrients such as Fe, Mn and Zn affect the
soybean production (Khudsar et al., 2008; Caliskan et al.,
2008).
Furthermore, various researcher reported that the application of
essential micronutrients such as Zinc, Iron and Magnesium
improve the yield and yield components of crops (Davis, 1983;
Fox & Guerinot, 1998; Ekhtiari et al., 2013). Normally
fertilization carried out in soil but in this condition very less
amount of nutrient reached to the plant system and remaining
amount waste through leaching in soil, it also cause land and
water pollution. Foliar fertilization is better option to avoid
leaching and in this quick translocation of nutrients carried out
in different parts of the plant system (Neumann. 1982).
According to Ghasemian et al, (2010) micronutrient spray can
enhance resistance against the environmental stress.
Geographical region Iran is characterized by arid climatic
conditions with high pH and mean temperature, here plants
mostly affected by different abiotic stresses.
In this condition drought stress is the main limiting abiotic
factor for crop production and decline the efficient use of dry
and semi dry lands. Furthermore, these water stress conditions
also severely affect the absorption of micronutrients by plants.
Water deficient conditions affect the water potential and turgor
pressure of the cells and this can disturbs the normal plant
physiological mechanisms (Hsiao, 1973). These changes
induced various effects on growth and yield parameters of the
crops (Reisdorph & Koster, 1999). Many studies showed
inhibitory effects of drought stress on different plant
properties, such as grain yield in maize (Ebrahimian &
Bybordi, 2011); growth and productivity in sunflower, fresh
and dry weights in shoot and flowers of marigold (Tagetes
erecta L.) and Asian red sage (Asrar & Elhindi, 2011; Liu et
al., 2011) and yield reduction due to limited growth in bread
wheat (Abbas et al., 2009). In soybean, biological nitrogen
fixation carried out by bacterium Bradyrhizobium sps., it was
reported that drought condition adversely affect the biological
nitrogen fixation in this crop.
Low soil fertility and limited availability of macro and micro
nutrients are the most important constraints under drought
conditions. Diagnosis and development of new strategies are
required which can help in inducing drought tolerance or
reduced the determinable effect of drought on crop, these
techniques will also help in the full utilization of the available
resources and convert semi-arid land to arable regions (Bruce
et al., 2002). Role of trace elements in crops production under
drought stress conditions have been less studied by researchers.
The aim of the present study was to investigate the response of
soybean in term of yield, yield components, seed oil and
protein yield to foliar spray of micronutrient (Fe and Mo)
under drought condition.
2 Materials and Methods
2.1 Study area and Experimental setup
In order to investigate the effects of micronutrient spray on
yield parameters of soybean under drought stress condition,
present study was conducted at research farm of Sari
Agricultural Sciences and Natural Resources University during
the cropping season of 2014. Each experimental plot had 5
meters long and 3 meters (3m×5m) wide and 6 ridges spaced
50 cm apart. Soil samples were collected and its
physicochemical properties were analyzed in soil science
laboratory, Department of soil science, Sari Agricultural
sciences and natural Resources University. All the
physicochemical properties were analyzed by the method
described by Blakemore et al. (1987).
Table 1 Physicochemical and mechanical properties of the
experimental area soil.
Depth 0-30cm
Texture Clay silt
EC dS/m 1.4
pH 7.5
T.N.V% 19.3
O.C% 3.48
Pppm 12.3
Kppm 367.3
N (%) 0.251
Uniform healthy soybean seeds (033 cultivar) were purchased
from Iran's Oilseed Research and Development Company
Deputy of Sari, Iran. Selected seeds were used for hand sowing
in the month of June, 2014 after removing the trashes and
impurities. The experiment was laid out in factorial
arrangement based on completely randomized block design
with three blocks. Two irrigation regimes were used viz
irrigation after 65 mm (as normal irrigation) and 130 mm (as
water deficit) evaporation from Class A pan along with the
simultaneous application of spray fertilization of the selected
micronutrient either singly or in combination (water as control,
Fe, Mo and Fe + Mo). For this purpose FeSO4 and
(NH4)6Mo7O24 (Merck, Darmstadt, Germany) were used as
Fe (400 ppm) and Mo (4 ppm) spray treatment, respectively.
38 Heidarzade et al
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The foliar spray of the selected micronutrient was carried out
for three times viz. at the start of stem elongation, flower buds
formation and pod set stage (according to the drought stress
treatment). Urea and ammonium phosphate were applied as
nitrogen and phosphate sources at 150 kg/ha-1
and 100 kg ha-1
,
respectively.
The plots were irrigated by tape irrigation method and the
applied water amounts were controlled by water meters and the
following equation:
d = FC− θ D/100
Where, FC%= field capacity ; θ%=soil moisture content; Dcm =
soil depth; dcm = irrigation water depth. Soil moisture content
was determined by oven drying method (ASTM D2216-10,
2010).
During foliar application, the plots were surrounded by
polyethylene to avoid the drift of solutions. Soybean was
manually harvested completely from each plot (15 m2) at full
physiological maturity of pods (80-90% dry weight). Total
grain yields after drying in oven (65°C for 72h) were adjusted
to 12% moisture content. Harvest index (HI) by dividing the
total grain yield on total biomass was calculated:
HI = (GY/BM) × 100%
Where, GY= grain yield and BM= biomass
2.2 Estimation of total protein content of soybean seeds
Estimation of total protein content was based on the total
nitrogen contents. Nitrogen content of soybean seeds was
measured by Total Kjeldahl Nitrogen (TKN) method as
mentioned by Isaac & Johnson (1976) (Kjeltec Auto1030
Analyzer, Foss Tecator AB, Hoganas, Sweden). For nitrogen
determination the pure seeds were dried (Fan Azma Gostar,
24060, Iran) for 72 h in oven. Total reduced nitrogen was
determined by using a micro Kjeldahl procedure with sulfuric
acid, digestion catalyst and conversion of organic nitrogen to
ammonium form according to the Total Kjeldahl Nitrogen
(TKN) method. Nitrogen content is then multiplied by a factor
to arrive at protein content. The average nitrogen (N) content
of proteins that found by the above method led to use of the
calculation N × convert factor (5.71) (King-Brink & Sebranek,
1993).
2.3 Estimation of Total seed oil content
Total oil content of soybean seeds was determined by using the
soxhlet device; the pure seeds of each treatment were dried and
weighted before insert into the device. The chloroform was
used as solvent, it is a popular solvent seed oil extraction,
particularly for lipids of intermediate polarity and when mixed
with methanol it becomes a general extraction solvent. So the
dried and powdered seed samples were inserted into the
soxhlet device and the extraction was completed by
evaporating the solvent.
2.4 Statistical analysis
Analysis of variance was performed for studied traits by using
the general linear model (PROC GLM) procedure in Statistical
Analysis System (SAS) and the mean comparisons were
evaluated based on Least Significant Differences (LSD).
3 Results and Discussion
Drought stress and micronutrient sprays were significantly
affected all studied soybean parameters. Also, the interactions
were statistically significant among studied traits with the
exception of seed number/pod (table 2).
3.1 Pod number/ plant
Number of pods per plant is an important growth characteristic
in soybean and could be helpful in determining the final plant
performance during the growing period (Ohashi & Nakayama,
2009). During the growth stage, plants were highly affected by
water availability and micronutrient application which directly
become visible at pods initiation and forming (table 3). Water
deficits plots produced a lower number of pods/plant.
Table 2 ANOVA for soybean parameters in response to different micronutrient spray under two irrigation regimes.
Oil yield
(kg ha-1
)
Protein yield
(kg ha-1
)
Seed yield
(kg ha-1
)
1000 grain
weight (g)
Seed number/
plant
Pod number/
plant
d.f S.O.V
** ** ** ns ** ** 2 Block
** ** ** * ** ** 1 W.S. (A)
** ** ** ns ** ** 3 M.S. (B)
** ** * ** ** ns 3 AB
795.33 5391.83 27099.61 0.16 33.78 2.46 14 Error
23 Total
5.49 5.57 5.28 0. 39 5.27 3.34 CV
Whereas W.S. – Water stress condition; MS- Micronutrient Spray, **;* and ns indicated significant difference at 0.01 and 0.05
probability level and non significant respectively
Response of soybean (Glycine max) to Molybdenum and Iron spray under well-watered and water deficit conditions. 39
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Table 3 Means of main effects of drought stress and micronutrient spray on pod numbers.
Treatments Pod number/ plant
Water status Normal 54.57a
Stress 39.12b
Micronutrient spray Control 40.86c
Fe 42.36c
Mo 50.35b
Fe + Mo 53.81a
Data with the same letters are not significantly different according to LSD (0.05) probability levels.
This could be explained by a reduction in flower production
and by an increase in flower abortion (Ekhtiari et al., 2013).
According to the results drought stress severely impressed the
number of pods so that the plants which were exposed to water
limitation showed highly reduction in term of pod numbers
compared to normal condition (more than 28% reduction).
Throughout the different spray of microelements the maximum
positive effects on pod numbers was reported from Fe + Mo
spray treatment (with 53.81 pods/plant) (table 3).
Translocation of assimilates from the source leaf to the pods in
soybean plant depends on many factors, such as deficiency in
water supply and photosynthetic rate (Chen et al., 1993;
Ohashi et al., 2000; Nobuyasu et al., 2003). According to
Ohashi et al. (2009) drought stress reduced the plant dry
weight by decrease pod dry matter accumulation, also they
found that, stress conditions reduced the rate of photosynthesis
significantly, but these conditions induced greater partitioning
of assimilates from the leaf compared to the well water
condition. However, these assimilates did not move to the
reproductive parts and accumulated in the vegetative
structures, mostly in the stem. Findings of present study are in
agreement with the Ekhtiari et al. (2013) who suggested that
water deficit showed highly inhibition in soybean seed yield.
Furthermore, Ohashi et al.(2009) reported different responses
of pod thickness and dry matter to drought stress during the
grain filling stage in soybean plants. Kaiser et al. (2005)
suggested the significant effect of micronutrient such as Mo
especially on soybean production. Low soil fertility and limited
availability of macro and micro nutrients are the most
important constraints under drought conditions. Various
studies suggested the reduction in soybean production due to
deficiency of micronutrients especially Fe, Mo and Zn (Kaiser
et al., 2005; Khudsar et al., 2008; Caliskan et al., 2008).
3.2 Seed /plant
The average number of seeds for each plant is relatively
constant in normal condition and almost controlled by genetic
factors, but it can be rapidly change under adverse
environmental conditions (Ohyam et al., 1992). The
importance of seed number in final performance of legumes
especially in soybean production was investigated by many
authors (Kobraee et al., 2011; Yasari & Vahedi, 2012; Yadavi
et al., 2014; Abdel-Latif & Haggan, 2014) all of them
suggested a positive correlation between seed numbers per
plant and the final seed performance. However, the average
number of seeds was significantly affected by irrigation and
micronutrient levels (table 2). According to the results obtained
from mean comparison (fig. 1), the number of seeds per plant
in each micronutrient spray treatment was reduced under water
deficit (Irrigation after 130 mm evaporation from pan class A)
condition as compared to control. Minimum reduction due to
drought stress among above parameter was related to Fe+Mo
treatment (7% reduction in compare control), in other words,
there was no significant difference with the control.
Figure 1 Response of soybean seed numbers to micronutrient spray under different water status
40 Heidarzade et al
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Water deficiency reduces water potential and turgor pressure in
plant which lead to difficulty in performing normal
physiological function especially during the reproductive
period (Lisar et al., 2012). Also, in present study highest seed
numbers per plant was obtained when Fe+Mo spray was
applied under normal irrigation (more than 173 seeds in each
plant) and the lowest was belong to water spray treatment in
drought stress condition (less down 65 seeds/plant) (fig. 1).
The role of molybdenum in plant growth and seed setting has
been well documented before (Arnon & Stout, 1939;
Anderson, 1942; Davies, 1945; Mitchell, 1945; Fido et al.,
1977; Chatterjee & Nautiyal, 2001; Kaiser et al., 2005). Result
of study suggested that by using some good strategies such as
foliar application of essential micronutrient especially Mo+Fe
help in normal functioning of specific plant enzymes to
participate in reduction and oxidative reactions, it could
reduced the damage caused by drought stress in plants
particularly in soybean.
Figure 2 Impact of micronutrient spray under different water
status on the weight of 1000 soybean seed.
Figure 3 Response of soybean seed yield to micronutrient
spray under different water status.
3.3 Effect of foliar spray on 1000 grain weight
Weight of 1000 Grain is an important yield contributing factor,
which plays an important role in showing the potential of a
crop variety. The average weight of 1000 grain was in ranges
of 101.6-103.2g and statistically analysis revealed that water
limitation significantly affected this parameter, in contrast the
micronutrient sprays didn’t (table 2). However, the interactions
had significant effects on this parameter (fig. 2). According to
the mean comparison the highest 1000 grain weights was
obtained in control treatment (water spray with stress) with
103g but it was not significantly different from the Fe+Mo
spray treatment (102.3g). Since the high genetically
dependence of grain weight to the variety, this factor affected
in lower range by drought stress and foliar application of
micronutrients compared with other yield properties. It seems
that, micronutrient treatments could increase the soybean seed
weight under water deficit condition and conversely, under
normal irrigation it didn't work. Drought stress occurring
during the critical growth stages of soybean (flowering to early
pod expansion period) ultimately decreases individual seed
weight but spray of micronutrients may rectify this effect
(Royo et al., 2000).
3.4 Seed yield
Seed yield is a final performance which resulted by integrated
effects of many complex morphological and physiological
processes occurring throughout the growth and development of
a crop. Due to water deficiency seed yield in soybean was
reduced if water limitation occurs during the critical growth
stage of growth especially at the time of pod set stage. Mean
comparisons of seed yield which influenced by drought stress
and micronutrient spray are considered in figure 3, it showed
higher reduction in seed yield through the stress condition (fig.
3). The highest positive effect on final seed yield (with 4885
kg h-1) was related to Fe+Mo treatment in normal irrigation
which was significantly higher than other treatments (figure 3).
The deleterious effects of micronutrient deficiency on seed
yields and quality have been reported clearly before (Cakmak,
2002; Welch & Graham, 2004; Kaiser et al., 2005; Malakouti,
2007). Among various abiotic stresses, drought is one of the
major environmental constraints limiting crop productivity
worldwide (Masoumi et al., 2010; Khamssi et al., 2011;
Batlang et al., 2013). About 25 % of the world’s agricultural
land is affected by drought stress (Jajarmi, 2009).
Various researchers reported the inhibitory effect of the
drought stress on the rate of photosynthesis and growth,
particularly seed yield of soybean plants severely affected (De
Souza et al., 1997; Griffin & Luo, 1999; Earl, 2002). In the
present study the seed yield was limited by water shortage but
the micronutrient sprays could partially mitigate these adverse
effects (fig. 3), for instance; spray of Fe+Mo could
compensated the yield loss due to drought stress and
accordingly no significantly difference was observed between
mentioned treatment under drought stress and control (water
spray) under normal irrigation (figure 3). Drought stress
decreases soybean yield by decline in yield components,
although there is a differential responses in yield components
to changes in environmental conditions.
Response of soybean (Glycine max) to Molybdenum and Iron spray under well-watered and water deficit conditions. 41
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According to Whan et al (1991) partitioning and translocation
of assimilates is dependent to water availability in soil
(Schnyder, 1993; Wardlow & Wilenbrink, 1994; Mohapatra et
al., 2003; ), thus Soybean yield and its components were
markedly reduced in non-irrigated plants compared with
irrigated plants (Andriani et al., 1991; Frederick et al., 2001;
Kerbauy, 2004 ). According to water deficit at early of
flowering and pod set increased flower and pod failure
(Osborne et al., 2002). Environmental condition during the
reproductive phase has a major impact on final yield (Levitt,
1980).
3.5 Protein yield
Soybeans had been cultivated widely due to exceptional
protein content (contains all 8 essential amino acids), due to
the presence of high protein content it is consider as vegetarian
meat (Dwevedi & Kayastha, 2011). Drought stress negatively
affected many physiological processes such as photosynthesis;
transpiration; accumulation and assimilates allocation (Ohashi
et al., 2006). Water status and micronutrient spray indicated
high significant effects on protein yield, also the interaction
was significant too (table 2). As drought stress by restriction in
micro and macro nutrients uptakes cause the huge yield lose in
crops(Ohashi et al., 2006) as well as application of some trace
elements such Molybdenum can play a great role in uptake the
above nutrients (Kaiser et al., 2005). The results from mean
comparison (figure 4) showed substantial different between
treatments.
Figure 4 Effect of micronutrient spray under water deficient
condition on the yield of soybean seed protein.
Although, there were a huge different between the lowest and
highest amount of protein yield, and obtained from water
spray through the water stress and Fe+Mo spray under normal
irrigation treatment respectively. Also there were no significant
difference in protein yield between Fe+Mo in drought stress
and normal irrigation. On the other hand reduction in total
protein content has been offset by foliar application of Fe+Mo
combination. Various studies have been proven the role of
molybdenum in biological nitrogen fixation and plant nitrogen
metabolism (Mendel & Haensch, 2002; Williams & Frausto da
Silva, 2002). Furthermore, molybdenum increased the
nitrogenase activity and fix higher nitrogen by forming larger
root nodules (Parker & Harris, 1977; Adams, 1997; Vieira et
al., 1998). All this ultimately leads to increase nitrogen uptake
and transformation to vital metabolites such as proteins (Kaiser
et al., 2005).
Figure 5 Impact of micronutrient spray under different water
status on soybean seed yield (The bar demonstrated the oil
percentages)
3.7 Oil yield
Like protein, content of seed oil is also a major parameter
which determining the nutritional value of soybean, seeds of
soybean contains about 20% oil (Dwevedi & Kayastha, 2011).
In present study the mean comparison of seed oil yield and
percentage (fig. 5) indicated that drought conditions have
negative impact on the oil yield but the oil percentage
increased. Meanwhile unlike to other studied parameters (seed
yield and protein content) seed oil percentage reduced (fig. 5).
Chung et al. (2003) suggested that soybean seed protein
content is negatively correlated with the amount of seed oil
percentage. Further, it has been demonstrated that water
availability will affect seed oil yield and quality (Ku et al.,
2013). Nevertheless the highest positive effect on seed oil yield
in both water status treatments was related to Fe+Mo spray
application which had dramatically difference by the other
micronutrients spray. Dornbos & Mullen (1992) performed a
differential irrigation experiment on soybean cultivars and
reported a 4.4% increase in protein content and 2.6% decrease
in oil content under severe drought stress. Similar type of
findings was obtained by Vollmann et al. (2000) when they
evaluated the response of soybean cultivars to drought
condition. Result of this study confirmed a negative correlation
between seed protein and seed oil contents as well as the effect
of drought on seed protein and seed oil contents. They
suggested that, variations in contents of seed protein and oil
were attributed largely to the differential rainfall during the
seed filling stage.
42 Heidarzade et al
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Conclusions
Findings of the present study well demonstrated the positive
effects of micronutrients spray particularly Fe+Mo treatment
on various growth parameters of soybean plant. Further, it was
well reported that seed protein and seed oil were strongly
affected by water stress conditions. Seed oil percentage
response conversely to drought stress as compare to other
parameters but this act couldn’t alter the final performance of
oil yield. Also high reduction in pod numbers during the
reproductive stage due to its sensitivity to water limitation was
the main cause of the final yield loses. Overall, when plants
like soybean are not supplied with an optimum amount of Fe
and Mo due to environmental limitation, growth inhibition and
physiological changes will be appear more quickly, depending
on the strength and duration of the imposed stress.
Conflict of Interest
Authors would hereby like to declare that there is no conflict of
interests that could possibly arise.
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KEYWORDS
Prosopis juliflora
Aqueous leaf extract
Rice
Nitrate reductase
ABSTRACT
Prosopis juliflora is an invasive and allelopathic plant widespread in most parts of the world. P. juliflora
is known to influence the growth of plants growing in its vicinity by the release of the allelochemicals
during the decomposition of its litter. The negative effect is manifested by inhibition of the various
physiological processes of the target plants. In the present study the effect of aqueous leaf extract of P.
juliflora on the nitrogen metabolism of rice seedlings was assessed through the means of estimation of
nitrate reductase (NR) activity of rice seedlings. For the study, aqueous leaf extract of dry mature leaves
was prepared. From this, three concentrations viz., 1%, 10%, and 25% of the leaf extract were prepared
by diluting with distilled water, while distilled water served as control. Rice seeds were incubated in
different concentrations of extract for 10 days. Germination data was recorded and used for calculating
the germination indices. After 10 days of exposure to the extract, seedlings were harvested and
measurements for root and shoot length, fresh weights of root, shoot, and seed was taken and nitrate
reductase activity of the seedlings was assayed. Germination and phenotypic results showed no negative
affect by the extract. The activity of NR significantly increased with increase in the concentration of the
extract. Our study revealed that the activity of NR was promoted by the extract addition.
Gowsiya Shaik1 and Santosh Kumar Mehar
1, 2,*
1Department of Botany, Sri Venkateswara University, Tirupati, AP, India
2Dept. of Botany, J.N.V. University, Jodhpur, India
Received – October 19, 2015; Revision – November 08, 2015; Accepted – January 31, 2016
Available Online – February 20, 2016
DOI: http://dx.doi.org/10.18006/2015.4(1).47.51
MESQUITE (Prosopis juliflora DC.) HAS STIMULATORY EFFECT ON NITRATE
REDUCTASE ACTIVITY IN RICE SEEDLINGS
E-mail: [email protected] (Santosh Kumar Mehar)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
Journal of Experimental Biology and Agricultural Sciences
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ISSN No. 2320 – 8694
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1 Introduction
The word Allelopathy was coined by Plant Physiologist
Mollisch (1937). The word Allelopathy (allelon + pathos) is
derived from the Greek allelon, „of each other‟, and pathos, „to
suffer‟; hence it means: the injurious effect of one upon
another. The term thus relates the scientific knowledge which
concerns the production of biomolecules by one plant, mostly
secondary metabolites, that can induce suffering in, or give
benefit to, another plant. It therefore involves the biochemical
interaction among plants. A plant influencing other plants
growing in its vicinity, by the release of chemicals in the
rhizosphere or through the litter, is known as allelopathic. The
formal definition for the allelopathy is “any direct or indirect
harmful or beneficial effect by one plant (including
microorganisms) on the other, through production of chemical
compounds that escape into the environment” (Mollisch, 1937;
Rizvi & Rizvi, 1992). There are hundreds of plants which were
reported to be allelopathic in nature (Mollisch, 1937; Sen &
Chawan, 1970; Rizvi & Rizvi, 1992; Thoyabet et al., 2009;
Weston & Duke, 2003). The chemicals that are released from
the allelopathic plant are known as allelochemicals.
Allelochemicals in majority are secondary metabolites,
released into the environment as exudates, volatiles and/or
residues of plant tissue decomposition (Weston & Duke,
2003). These allelochemicals when released into the
environment have been shown to possess a broad activity
spectrum on biological systems in surroundings (Corcuera et
al., 1993; Wink et al., 1998). The effects of allelochemicals‟
action has been detected and reported at different levels of
plant viz., molecular, structural, biochemical, physiological
and ecological levels (Gniazdowska & Bogatek, 2005).
Prosopis juliflora is reported to influence the growth of other
plants (Rizvi & Rizvi, 1992; Thoyabet et al., 2009). Phenolic
compounds present in this plant have biological toxicity
towards many plants and can cause disturbances in various
processes by interfering with the enzymology of the target
plants. Our previous works on germination and seedling
growth of rice by the P. juliflora extracts has showed no
negative influence at lower concentrations, instead the effects
were stimulatory (Mehar, 2011; Shaik & Mehar, 2014; Shaik
& Mehar, 2015). In the present investigation, the effect of P.
juliflora on the nitrogen metabolism of rice plants was
analyzed by assessment of variation in the activity of NR when
the rice seedlings are exposed to P. juliflora litter extract.
2 Materials and methods
2.1 General methodology
Karnool Sona variety of rice was used as the test plant in the
study. Collection of P. juliflora leaf material and processing is
detailed in our earlier studies (Shaik & Mehar, 2014; Shaik &
Mehar, 2015). 2D-DM (2 day dry mature) leaves‟ extract of P.
juliflora was used as source of allelopathic material at three
concentrations viz., 1%, 10% and 25%, while distilled water
served as control.
2.2 Setup of the experiment
Seeds were surface sterilized using 0.1% HgCl2 for 60 seconds
and kept for incubation in the different petriplates containing
10ml of the above treatments (during the initial wetting of the
filter papers). In each petriplate, 10 seeds were placed and the
triplicates of the each treatment were maintained. The
incubation period was 10 days at the room temperature of 28o
C ±2.
2.3 Data Collection
Germination data collected throughout the incubation period
was used for calculating germination indices i.e. total
germination (GT), speed of germination(S), speed of
accumulated germination (AS), co-efficient of the rate of
germination (CRG) as per Chiapusio et al. (1997). After 10
days of exposure to allelopathic extract, Root length (RL) and
Shoot length (SL) were measured.
2.4 Nitrate reductase assay
Rice seeds germinated in extracts were used for nitrate
reductase assay according to the method of Hageman &
Hucklesby (1971) and Evans & Nason (1953) after 10 days of
exposure to allelopathic extract.
2.5 Statistical analysis
All the germination indices‟ values for all the treatments were
compared with control using Mann-Whitney U-Test. RL and
SL were compared to control using paired t-test. Activity of
nitrate reductase was compared with control using t-test.
Mann-Whitney U-Test and T-test were performed using SPSS.
3 Results
3.1 Germination
Result of study indicated that leaf extract did not show any
inhibitory effect on the germination of rice seeds. The Gt, S,
AS and CRG were 100% in 1% and 10% extracts but at higher
concentration i.e. 25% some reduction was reported in the Gt,
S, AS and CRG and it was 83.3%, 66.7%, 66.7% and 71.1%
respectively. All the germination indices were comparable to
control at all the concentration (Table 1, values are as
percentage of control).
Growth of the plant was not significantly reduced by any of the
extract concentrations. SL (Figure 1a) and RL (Figure 1b) were
not affected by the exposure to extract. In comparison with
control, the change in the root and shoot lengths of the seedling
were statistically not significant.
48 Shaik and Mehar
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Table 1 Germination indices values of different treatments (values are the percentage of the control).
Treatments Gt S AS CRG
1% 100NS
100 NS
100 NS
100 NS
10% 100 NS
100 NS
100 NS
100 NS
25% 83.33333 NS
66.66667 NS
66.66667 NS
71.11111 NS
Gt=Total germination, S=Speed of Germination, AS=Speed of accumulated Germination, CRG=Co-efficient of the rate of Germination,
NS=Not Significant
3.2 Nitrate Reductase activity
In the present investigation, NR activity was maximum at 25%
followed by the 10% and 1%. It was significantly (p≤0.001)
promoted in comparison to control. There was linear
relationship between the concentration of the extract and the
NR activity of rice seedlings (R2 =0.966 (y=0.013x+0.039;
Figure 2.). This indicates the extracts have stimulatory affect
on the activity of the NR enzyme.
Discussion and Conclusions
Seed germination assays are the preliminary screening to check
the effect of allelopathic extracts. In the present study,
germination indices clearly indicated that the there is no
inhibition of the germination when exposed to the allelopathic
extracts of the P. juliflora. Even the higher concentration, 25%
was not inhibitory. Results of present study are in contrast to
the reports of Siddique et al. (2009).
A B
Figure 1 Boxplots for shoot length (A) and root length (B), the treatments labeled A, B and C represent 1%, 10% and 25% of P. juliflora
extract
Figure 2 NR activity of Rice seedlings
Mesquite (Prosopis juliflora DC.) has stimulatory effect on nitrate reductase activity in rice seedlings. 49
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Journal of Experimental Biology and Agricultural Sciences
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Although there are reports of the negative effect of P. juliflora
extracts on the germination (Noor et al., 1995; Nakano et al.,
2001), it also needs to be considered that the effect is
dependent on the concentration and type of the material being
used. It was reported that, seed characteristics such as seed size
and seed coat permeability can influence the uptake and effects
of allelochemicals in seeds and interference of the
allelochemicals varies accordingly (Marianne et al., 2000).
Seed germination assays (Barnes & Putnam, 1987; Pérez,
1990; Chase et al., 1991) showed that species with small seeds
were more sensitive, and hence were inhibited more than larger
seeded species when exposed to similar concentration of the
allelochemicals. Seedling parameters also had no significant
reduction. In this manner findings of present study are
contradictory to the findings of Thoyabet et al. (2009) and
Sen& Chawan (1970). Thoyabet et al. (2009) has reported the
reduced root length by the extracts of leaves of P. juliflora.
Similarly, Sen& Chawan (1970) reported the inhibition in
germination and early seedling growth. As in the case of
germination, effect on the seedling parameters is also
dependent on the type of donor plant, test plant and the
concentration of the extracts being used.
Along with the suppressing effects on the germination and
seedling parameters the allelochemicals are reported to
suppress the activity of the respiratory and photosynthetic
enzymes, and therefore, there is perceived scope for the
inactivation of the NR by the allelochemicals.
Nitrogen and sulphur are very important nutrients for plant
growth (Fazili et al., 2010) and play important role in amino
acid biosynthesis, and regulate the protein synthesis (Harris et
al., 2000). According to Fazli et al., (2005), the increased
amount of nitrogen and sulphur nutrition affected lipid
accumulation, acetyl-CoA concentration and acetyl-CoA
carboxylase activity. Nitrate reductase is a key enzyme in the
nitrogen metabolism. Nitrate is assimilated through a pathway
involving nitrate uptake steps and by two reductive steps
catalyzed by the enzymes NR and nitrite reductase (NiR). But,
here we have found no inhibitory effect on the NR activity;
instead with increase in the concentration of the extracts, the
NR activity has been promoted.
Based on the above results, here we conclude that extract had
no negative effect on the germination of rice seeds, and its
seedling growth. Besides, the activity of nitrate reductase was
promoted by the extract addition which further suggests that
the addition of litter has stimulatory effect on the nitrogen
metabolism in rice and its overall growth.
Conflict of interest
Authors would hereby like to declare that there is no conflict of
interests that could possibly arise.
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Mesquite (Prosopis juliflora DC.) has stimulatory effect on nitrate reductase activity in rice seedlings. 51
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KEYWORDS
Defoliation stage
Sugar Percentage of Root
Root Yield
White Sugar Yield
ABSTRACT
The experiment was conducted in spring 2014 to evaluate the effect of defoliation on the quantitative
and qualitative characteristics of sugar beet in Motahari research station located in the Kamal Shahr
region in Karaj, Iran. The study was conducted in split plot factorial with completely randomized block
design with four replications. The main factors included two planting dates viz 23 April, 2014 (suitable
planting time) and 18 May, 2014 (Late planting) and the sub-factors included five levels of defoliation
including stage of early cotyledon growth to two true leaves (2 leaves), the stage of plant deployment
(about 12 leaves), mid-growth (about 32 leaves) and late season of growth (about 54 leaves) and another
sub-factors included five levels of defoliation intensity of leaves included 25%, 50%, 75% and 100% of
defoliation and non-defoliation stage (control) as randomized and factorial were considered. Result of
study revealed that different planting dates have significant effect on the sugar percentage of root. In
addition, the treatment of defoliation stage could have a significant effect on root yield and white sugar
yield (p>0.01).The treatment of defoliation intensity had a significant effect on all three traits (p>0.01).
In general, increase in the defoliation intensity negatively affects the root yield and significantly reduced
the white sugar yield (compared to control). Among the various stages of defoliation, middle stages of
the defoliation have least effect on the evaluated traits which indicated more sensitivity of this treatment
during the growing season of plant.
Mohammad Nabi Ilkaee1,*
, Zohre Babaei1, Amirsaleh Baghdadi
1 and Farid Golzardi
2
1 Department of Agronomy, Karaj Branch, Islamic Azad University, Karaj, Iran 2 Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran.
Received – December 31, 2015; Revision – January 14, 2016; Accepted – January 30, 2016
Available Online – February 20, 2016
DOI: http://dx.doi.org/10.18006/2015.4(1).52.58
EFFECT OF DIFFERENT PLANTING DATES AND DEFOLIATION ON THE
PROPERTIES OF SUGAR BEET (Beta vulgaris L.)
E-mail: [email protected] (Mohammad Nabi Ilkaee)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
Journal of Experimental Biology and Agricultural Sciences
http://www.jebas.org
ISSN No. 2320 – 8694
Production and Hosting by Horizon Publisher
(http://publisher.jebas.org/index.html).
All rights reserved.
All the article published by Journal of Experimental
Biology and Agricultural Sciences is licensed under a
Creative Commons Attribution-NonCommercial 4.0
International License Based on a work at www.jebas.org.
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Journal of Experimental Biology and Agricultural Sciences
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1 Introduction
There are several biotic and abiotic factors which able to
damage the leaves of sugar beet plants and subsequently
reduce the yield. Among these, some of the already noted
factors are cold and frost, drought, hail, wind, pests and
diseases which can effectively reducing the leaf area (Jadidi et
al., 2010). Sugar beet production under semi-arid conditions of
growth has been mainly decreased due to the limited access to
water (Morillo-Velarde & Ober, 2006). Water shortage may be
a significant limiting factor and can reduce the quality of sugar
beet root in the future due to climate changes (Jones et al.,
2003). In the Middle East, low rainfall during the months of
July and August, when water demand is maximum,
supplemental irrigation is necessary to avoid lowering the
quality of sugar beet root. Furhter, sugar beet is a drought
tolerant species (François & Maas, 1994) and part of the plant
foliage (defoliation) limited the water demand and respond to
the environmental stress (Vesk & Westoby, 2003).
Since the leaves of plants are the main area of receiving
sunlight and photosynthetic. Therefore, any reduction in the
surface of leaves or their low efficiency can be considered as
main factors in reducing the ability of plant to assimilate
carbon dioxide and on the other hand decrease the
translocation of assimilates into the storage or vegetative
organs and subsequently impairs the plant yield. For this
reason, the estimation of yield loss caused by defoliation has
an important role in farm management (Muro et al., 2001;
Ashley et al., 2002;Abdi et al., 2007). Data obtained from the
simulated hail damages as defoliation in the United States,
Canada, England, India and Spain suggest that damages
resulted from hail on the quantity and quality of sugar beet
depend on the severity of the damage in stage and period of
development (Alimoradi, 2001). Every year pests, diseases and
hail caused considerable damage to sugar beet farms in the
country. Further, there are no scientific patterns to estimate the
damages caused by hail and other factors reducing leaf area in
sugar beet farms. Though some effort has been carried out for
the estimation of these damages but these are often not
accurate. That’s why this study was conducted to eastimate the
damages caused by hail factors. With this effect of leaf area
reduction via defoliation on qualitative and quantitative yield
of sugar beet was also determined. The effects of time and
intensity of defoliation on root yield and other quantitative and
qualitative characteristics of root were also studied. In
Montana, Morris (1950) found that complete defoliation in late
June or early July in sugar beet reduced yield to a quarter of
the normal conditions and 50% defoliation can reduce yield to
one sixth of normal conditions (Morris, 1950). Under similar
condtions, Afanasiev et al. (1960) reported that more than 75%
defoliation caused reduction in root yield to less than 6% and
the yield of the plant to less than 20%.
According to the results of the research, complete defoliation
caused 80% reduction in weight of the leaves between 23% to
27% decline in the yield of root. In fact, when sugar beet is
confronted with semi-arid conditions, high temperature, light
and salinity stress is not easily separable and more complex
situation is created (Munns, 2002; Chaves et al., 2002).
According to the reports of Jones et al. (1955) in the UK on
sugar beet, 50%, 75% and 100% defoliation at 4 or 8- leaf
stages decreased the root yield to 5%, 10% and 27% ,
respectively. The results of artificial defoliation at 120 and 144
days after planting in India showed that defoliation treatments
of 25%, 50%, or 75% did not reduce the root yield of sugar
beet, but 100% defoliation at 120 days after planting
significantly decreased the root yield (Singh et al., 1980).
Defoliation to 100% in late June or early July or middle of
September or the middle of October decreased the average root
yield in the 3-year period to 23, 27, 20 and 10%, respectively
(Stallknecht & Gilbertson, 2000).
2 Materials and Methods
The experiment was conducted in Motahari research station
located in Kamalshahr of Karaj during 2014. The station is
located at Latitude 35° 15' N and longitude 50°51' E with an
altitude of about 1300 meters above sea level. This area with
180-150 dry days is considered of the hot and dry
Mediterranean climate zones. Split plot factorial experiments
were carried out in a randomized complete block design with
four replications. Treatments of planting dates as main plots
were placed on two levels, including 23 April, (appropriate
time of planting) and 18 May, (at late planting ). Treatments of
defoliation as sub plots were the early growth of cotyledon to
two true leaves (2 leaves), establishment stage (about 12
leaves), middle of growth (about 32 leaves) and the end of the
growing season (about 54 leaves) along with five levels of
defoliation intensity factors including the removal of 25, 50, 75
and 100 percent of leaves and non-defoliation (control) as
factorial and random. Row to spacing was 50 cm and the
length of the rows was 8 m and each sub-plots had four lines
and the final harvest took place taking into consideration
marginal effects. The amount and time of use from nutrient
elements were imposed based on soil test results. During the
growing season, pests and weeds were controlled at critical
times. Irrigations time was also determined based on the
amount of evaporation between 80 and 90 ml from class A
pan. Plant density on the farm was considered about 100
thousand plants per hectare.
Defoliation per plot was treated on the green leaves with at
least 75 per cent healthy leaves. Defoliation was imposed using
scissors and its intensity was based on experimental treatments
on each leaf, independently. During the growing season, the
process of light absorption was performed using a radiometer
in intervals of 20 days, since the beginning of the treatment.
The total numbers of leaves were counted every 15 days to
determine the time of treatment in the control plot. The final
harvest was simultaneously carried out in all the plots in late
October or early November, 2014. In the running time of each
treatment, dry weights of leaf, petiole, stem and storage root as
well as leaf area were determined at a level of about 1 square
53 Ilkaee et al
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meter after 4 weeks and at harvest time; and the trend of
changes was examined in different treatments. Also root yield,
sugar content of root and white sugar yield were measured at
the end of the growing season. Sugar content of roots was
measured by polarimetry (Kunz et al., 2002). Also, according
to the results, the reduction in sugar yield caused by leaf
damage was determined in each growth stage. Data obtained
from this study was analyzed using SPSS software and
ANOVA analysis method and LSD test was used for mean
comparison (P<0.05).
3 Results and Discussion
3.1 Root yield
According to the results of variance analysis, the root yield of
sugar beet was not affected by different planting dates. The
main effects of defoliation treatments, defoliation intensity and
interaction between planting date and the defoliation was
reported on the root yield and these were significantly
different(P<0.01) to each other (Table 1). Among these,
lowest root yield was obtained in the middle stage of growth
with an average of 48.10 tons per hectare which showed
significant differences compared with other treatments. The
highest root yield (57.40 tons per hectare) was also achieved in
the early stages of growth (Figure 1). This factor can be
attributed to the fact that at the beginning of growth, the pace
of growth in many plants is directly associated with the amount
of light received by their leaf area (Monteith, 1977; Gallagher
& Biscoe, 1978). In fact, when the plant encounters in the early
stages with a treatment of defoliation has more time for the
next leaf production and capture more light, resulting in
increased yield so that plant is almost associated with higher
levels of leaves until the middle stages of growth. Compare the
average interaction between planting date and defoliation
showed that the highest ratio of root yield was observed in the
treatment of early planting date and the initial defoliation stage
(64.72 tons per hectare) and the lowest root yield was in the
treatment of late planting date and in the middle of the
defoliation stage (42.27 tons per hectare) (Figure 3). It is also
remarkable that the ratio of root yield was reduced by
increasing the intensity of defoliation. So that the highest root
yield (61.89 tons per hectare) was obtained in control and the
lowest rate (51.05 tons per hectare) was in treatment of 100%
defoliation (Figure 2); it could be due to reduced ability to
absorb light by plant with increasing the intensity of
defoliation. Result of the present study are in agreement with
the findings of Morris (1950,) also found that with increasing
the intensity of defoliation, the root yield will be greatly
reduced. Further, Afanasiev et al. (1960) reported that
complete defoliation led to a reduction of 23 to 27 percent of
yield in sugar beet. Similar types of results was obtained by
Singh et al. (1980), they suggested that complete defoliation at
120 days after planting can severely reduce root yield; but
unlike the results of this study, Singh and colleagues did not
observe any reduction in root yield in the treatments of 25%,
50% and 75% defoliation. Jones et al. (1955) in their research
on sugar beet in the United Kingdom reported that 50%, 75%
and 100% defoliation in the 4 and 8-leaf stages decreased root
yield, respectively, to 5%, 10% and 27%.
3.2 Sugar content of root
According to the results of Table 1, plants that were planted at
late planting date had higher sugar content, so that the ratio of
these traits showed significant differences compared to the
early planting which the ratio in late May planting was 15.16%
while in early planting it was 14.03% (Figure 4). This can be
attributed to the fact that, unlike the earlier planted plants,
plants that were planted later have spent most of their energy
for storage of sugar in the root. In fact, early planting has
probably led to more opportunities for more suitable vegetative
growth. According to present research, there is a negative
correlation between root weight and sugar content in sugar beet
was reported by various researchers (Abdollahian Noghabi,
1992; Ashraf Mansouri, 2000; Ebrahimian, 1993; Habibi,
1993; Beigy, 2007; ). Also in the studies of Bazrafshan et al.
(2008) highest percentage of sugar in late planting date (25th
June) was 14.98% and 17.72% on 20th May (Sarmast-Garusi,
2011).
Table 1 Analysis of variance for treatments of planting date, defoliation stage and intensity of defoliation on physiological traits in sugar
beet.
Source of variations (S.O.V.) Degree of Freedom (d.f.) Root yield Sugar content of root White sugar yield
Replication 3 439.01 1.85 4.50
Planting dates(Pd) 1 4058.45 ns
51.05* 15.13
ns
Error Pd 3 697.07 3.03 16.62
Defoliation(D) 3 788.96 **
1.47 ns
13.21 **
Defoliation intensity(Di) 4 714.76 **
2.31**
14.84**
Pd×D 3 198.56 * 0.44
ns 2.29
ns
Pd×Di 4 49.53 ns
0.91 ns
0.31 ns
D×Di 12 96.21 ns
1.02 ns
1.23 ns
Pd×D×Di 12 65.75 ns
1.00 ns
0.96 ns
Error 114 66.61 0.6 1.15
C.V. (%) 14.92 5.31 16.79
n.s: not significant. *, **: Statistically significant at P < 0.05, 0.01, respectively.
Effect of different planting dates and defoliation on the properties of sugar beet (Beta vulgaris L.) 54
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Figure 1 The effect of defoliation stages on root yield of sugar
beet
Figure 2 The effect of the intensity of defoliation treatment on
root yield of sugar beet
In this regard, have stated that on April planting, the sugar
content of root was more compared to late planting date due to
the production of larger roots (Chaves et al., 2002). The
intensity of defoliation had a significant effect (P<0.01) on
sugar content in roots (Table 1). The most sugar content
(15.04%) was related to the control and the lowest percentage
(14.35%) was observed in treatments of 100% defoliation
(Figure 5). According to the table of mean comparisons, there
was a significant difference among treatments of control and
defoliation. This means that defoliation, reduced sugar content
in sugar beet root, but the intensity of defoliation had no
significant effect on reducing the traits. The results of these
experiments were in agreement with the reports of Kamandi et
al. (2008). Also in accordance with the results of Sarmast-
Garusi (2011) in the maximum reduction of sugar content was
found in complete defoliation treatment. In this study, sugar
content was not affected by the mean defoliation stage. These
results indicate that plant leaves for their development use the
large amount of sugar stored without recycling opportunities.
3.3 White sugar yield
According to the results, it can be stated that unlike planting
date which had no significant effect on the yield of white
sugar, some factors, such as intensity and stages of defoliation
caused significant difference (P<0.01) on this trait (Table 1).
Among the intensity of defoliation treatments, the highest yield
of white sugar (6.57 tons per hectare) was belonged to 25%
defoliation and the lowest rate (5.88 tons per hectare) was
obtained in 100% defoliation (Figure 7); but generally
complete defoliation treatments caused a significant decrease
in yield of white sugar compared to the control. In fact, there
was an inverse relationship between high intensity of
defoliation and white sugar yield that can be attributed due to
less absorption of light by leaves.
Figure 3 The effect of interaction between treatments of planting
date and defoliation stage on root yield of sugar beet
Figure 4- The effect of planting date on the sugar content in sugar
beet root
55 Ilkaee et al
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Figure 5- The effect of the intensity of defoliation on the sugar
content in sugar beet root
Figure 6- The effect of defoliation stages on the yield of white
sugar in sugar beet
Figure 7- The effect of the intensity of defoliation on the yield of white sugar in sugar beet.
According to Stallknecht & Gilbertson (2000) 100%
defoliation leads substantially to decrease in the amount of
sugar yield. Further, according to the results of Kamandi et al.
(2008), white sugar yield was declined with increasing of
defoliation compared with the control (non- defoliation). In
this study, it was observed that the least amount of white sugar
yield was achieved in the middle stage of growth, which this
decrease can be expected due to the lowest of produced root
yield. The greatest amount of white sugar yield was belonged
to the early stage treatments with 6.79 tons per hectare and the
lowest rate was observed in the middle stage treatments with
5.55 tons per hectare (Figure 6). According to the results of
Muro et al. (1998) in defoliation treatments in the middle of
growth had the greatest impact on reducing of root yield and
consequently the yield of white sugar.
Acknowledgements
The authors would like to thank respectable authorities on
Motahari research station in Kamalshahr of Karaj, as well as
Department of Agronomy, Faculty of Agriculture, Islamic
Azad University of Karaj, Iran that helped me out in carrying
out this study.
Conflict of interest
Authors would hereby like to declare that there is no conflict of
interests that could possibly arise.
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Effect of different planting dates and defoliation on the properties of sugar beet (Beta vulgaris L.) 58
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KEYWORDS
Food security
Natural resource
Socio-economic value
Underutilized
WEM
ABSTRACT
Wild edible mushrooms (WEM) are known for its medicinal and nutritional value across the globe.
WEM have become one of the most prized after food especially in the developed countries where people
are mostly health conscious. The present study throws light on the diverse flora of WEMs of Nagaland
and how it can be income generator for the tribal people with proper research in this aspect. Till now,
the knowledge of distinguishing between edible and non-edible varieties is only confined to people who
go for mushroom hunting. As such the indigenous knowledge remains with only those few people
involved. The current data can pave the way for future research work and also make people aware of the
many varieties of WEMs available in the state. A total of 33 WEMs were collected and identified during
the peak mushroom season of the state i.e. from end May to September of every study year.
Toshinungla Ao, Chitta Ranjan Deb*
and Neilazonuo Khruomo
Department of Botany, Nagaland University, Lumami 798 627, Nagaland, India
Received – November 27, 2015; Revision – December 24, 2015; Accepted – January 31, 2016
Available Online – February 20, 2016
DOI: http://dx.doi.org/10.18006/2015.4(1).59.65
WILD EDIBLE MUSHROOMS OF NAGALAND, INDIA: A POTENTIAL FOOD
RESOURCE
E-mail: [email protected] (Chitta Ranjan Deb)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
Journal of Experimental Biology and Agricultural Sciences
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ISSN No. 2320 – 8694
Production and Hosting by Horizon Publisher
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Creative Commons Attribution-NonCommercial 4.0
International License Based on a work at www.jebas.org.
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1 Introduction
Wild edible fungi have been collected and consumed by people
for thousands of years. Wild edible fungi are important sources
of nutrition and medicines. Around 2000 species of
mushrooms are considered safe for human consumption and
about 650 of these possess medicinal properties (Rai et al.,
2005). Mushrooms have a long association with humankind
and provide profound biological and economical impact. Since
time immemorial, wild mushrooms have been consumed by
man (Das, 2010). Edible mushrooms have high content of
proteins, vitamins, minerals, fibers, trace elements and low/no
calories and cholesterol (Murugkar & Subbulakshmi, 2005).
Mushrooms have been used in folk medicine for thousands of
years and are considered to be Neutralceuticals while others
can produce potent Neutriceuticals (Ribeiro et al., 2005). Due
to its traditional usage, Trametes versicolor has been
considered among the 25 major medicinal macrofungi
worldwide (Boa, 2004) and polysaccharo-peptides purified
from this species, show experimental immune-modulatory and
anti-cancer effects (Cheng & Leung, 2008). Besides,
mushrooms are known to be rich sources of various bioactive
substances like anti-bacterial, anti-fungal, anti-viral, anti-
parasitic, anti-oxidant, anti-inflammatory, anti-proliferative,
anti-cancer, anti-tumour, cytotoxic, anti-HIV, hypo-
cholesterolemic, anti-diabetic, anti-coagulant, hepato-
protective compounds, among others (Wasser & Weis, 1999;
Ajith & Janardhanan, 2007).
Mushrooms are a boon for progress in developing countries
like India with rich biodiversity especially in the field of food,
medicine and unemployment (Wani et al., 2010). World
production of mushroom exceeds 3 million tons worth a
market value of U.S $ 10 billion. Netherlands, Poland, Ireland
and Belgium are major exporting countries of fresh
mushrooms in the world. China is the largest exporter of
preserved mushrooms and Netherlands and Spain are the other
major countries (Harsh & Joshi, 2008). Germany, U.S.A and
France are considered to be major importing countries of
prepared and preserved mushrooms. Till 2008 India ranked 6th
as an exporter of mushrooms. India has a great potential to be
an important producer of mushroom in the future and currently
ranks 54th in the world in producing mushrooms. Edible
mushrooms are valuable sources of nutrients and bioactive
compounds in addition to its rich flavors and culinary features.
Recently mushrooms have become increasingly popular as
functional foods for its potential beneficial effects on human
health (Guillamon et al., 2010). Modern pharmacological
research confirms large parts of traditional knowledge
regarding the medicinal effects of mushrooms due to their
antifungal, antibacterial, antioxidant and antiviral properties
(Wani et al., 2010). Wild edible mushrooms are not well
documented in many countries, poorly studied and
underutilized though they are rich source of non wood forest
product. There is no systematic survey and study on mushroom
harvest, its market and income generation potential (Tibuhwa,
2013). The FAO of the UN has emphasized the adoption of
mushrooms as an ideal food for developing countries and its
contribution to global food security.
Wild edible mushrooms are used as food and medicine by the
indigenous tribes of Similipal Biosphere Reserve (SBR) of
Odisha, India. More than ten ethnic groups of SBR were found
to be mycophilic and have extensive traditional mycological
knowledge (Sachan et al. 2013). The mushrooms identified in
the SBR are native to many parts of India which were reported
by some authors in the North-Eastern hills of India (Verma et
al., 1995; Singh et al., 2007; Tanti et al., 2011); North Western
Himalayas (Atri et al., 1997) and Kanyakumari district
(Davidson et al., 2012). The northeast region of India is known
for its rich biodiversity. The high humidity during monsoon
period provides ideal agro-climatic conditions for the growth
of mushrooms. The people of Nagaland are highly known for
coveting wild edible mushrooms. Mushrooms are highly prized
delicacy of the state. Very few works has been done on wild
edible mushrooms in Nagaland (Kumar et al., 2013). In most
of these reports the mushroom resources are ill presented. The
purpose of the present study was to bring to light the rich
diversity of WEMs of Nagaland and its potential as a valuable
food resource.
2 Materials and Methods
Survey Area
Nagaland is located in the North Eastern region of India with
total geographic area of 16,579 sq Km. Nagaland shares
borders with Myanmar in the East, Assam in the West,
Arunachal Pradesh and a part of Assam in the North and
Manipur in the South. It lies between 93o15ˊ to 95
o15ˊ E and
25o10ˊ to 27
o4ˊ N. According to the meteorological data of the
state the average annual rainfall ranges between 2000-2500
mm while, temperature during summer ranges from 16-31oC
and drops as low as 4oC during winter. During the present
study regular surveys and collection were carried out in various
districts and market areas of Nagaland from October 2013–
May 2015 during the peak mushroom season of the state.
Forest areas and market places of Mokokchung, Zunheboto,
Kohima, Tuensang, Phek and Wokha were surveyed during
this period. Local markets were surveyed to know about the
wild varieties sold during the season and regular mushroom
collectors were interviewed to gain more knowledge about the
hunting areas.
Wild edible mushrooms were collected in silver foil/collection
boxes and brought to the laboratory for identification.
Mushrooms with leathery texture were preserved in 4% (v/v)
formaldehyde solution and mushrooms with soft texture were
preserved in 2% (v/v) formaldehyde solution and maintained
as herbarium specimens.
60 Toshinungla et al
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Table 1 List of Wild Edible Mushrooms (WEM) found in Nagaland, India.
Name of Species (Family) Habitat Season of collection Accession No
Auricularia auricula-judae (Bull.) Quél (Auriculariaceae) On dead stumps and branches of sub-tropical and temperate trees especially Alnus species. End May-November NUBOT-TA-AA-01
A. polytricha (Mont.) Sacc (Auriculariaceae) In clusters on rotten or dead and decaying stumps and twigs September-November NUBOT-TA-AP-02
Cantharellus cibarius (Fr.) (Cantharellaceae) Found under Lithocarpus in sub-tropical forests End June-October NUBOT-TA-CC-03
Lactarius piperatus (L.) Pers. (Russulaceae) Under sub-tropical semi-evergreen forests June-October NUBOT-TA-LP-04
Lactarius volemus (Fr.) (Russulaceae) Under sub-tropical semi-evergreen forests including pine June-October NUBOT-TA-LV-05
Lentinula edodes (Berk.) Pegler (Omphalotaceae) On trunks of Oak trees June-July NUBOT-TA-LE-06
Hericium cirrhatum (Pers.) Nikol (Hericiaceae) On trunks of semi-evergreen and temperate trees June-July NUBOT-TA-HC-07
Dacryopinax spathularia (Schwein) G. W. Martin (Dacrymycetaceae) On dead and decaying logs in large groups June-July NUBOT-TA-DS-08
Schizophyllum commune Fr. (Schizophyllaceae) On branches of dead wood and cut timber April-August NUBOT-TA-SC-09
Strobilomyces strobilaceus (Scop.) Berk (Boletaceae) Grows in association with semi-evergreen and coniferous trees June-September NUBOT-TA-SS-12
Amanita strobiliformis (Paulet ex Vittad.) (Amanitaceae) Under sub-tropical semi evergreen forest trees June-August NUBOT-TA-AS-19
Boletus edulis Bull. (Boletaceae) Under coniferous and semi-evergreen forest types August-September NUBOT-TA-BE-22
Tricholoma imbricatum (Fr.) P. Kumm. (Tricholomataceae) In coniferous woods, especially with pine July-August NUBOT-TA-TI-27
Pleurotus pulmonarius (Fr.) Quél. (Pleurotaceae) In clusters on cut timber and fallen logs June-September NUBOT-TA-PP-28
Clavaria fragilis Holmsk. (Clavariaceae) Grows in clusters on ground amongst leaf litters and in fields August-November NUBOT-TA-CF-35
Tremella fuciformis Berk. (Tremellaceae) On dead or fallen branches of broadleaved trees September-November NUBOT-TA-TF-37
Lentinus squarrosulus Mont. Singer (Polyporaceae) On dead stumps of trees like Oak June-August NUBOT-TA-LS-40
Hygrocybe conica (Schaeff.) P. Kumm (Hygrophoraceae) In grass in fields after burning the area June-July NUBOT-TA-HC-41
Russula heterophylla (Fr.) Fr. (Russulaceae) Under Lithocarpus and Castanopsis in sub-tropical forests October-January NUBOT-TA-RH-44
Suillus luteus (L.) Roussel (Suillaceae) Under coniferous especially pine September-November NUBOT-TA-SL-46
Xerocomellus chrysenteron (Bull.) Šutara (Boletaceae) Under sub-tropical semi-evergreen forests including pine July-November NUBOT-TA-XC-48
Suillus pictus (Peck) A.H. Sm. & Thiers (Suillaceae) Under sub-tropical semi-evergreen forests June-November NUBOT-TA-SP-49
Laccaria tortilis (Bolton) Cooke (Hydnangiaceae) On bare soil in damp woods August-November NUBOT-TA-LT-51
Melanoleuca grammopodia (Bull.) M. (Tricholomataceae) Found to grow on leaf mulch or composted soil in fields June-October NUBOT-TA-MG-61
Aleuria aurantia (Pers.) Fuckel (Pyronemataceae) Found to grow in groups on soil amongst grasses or on bare soil or at roadside August-November NUBOT-TA-AA-62
Macrolepiota albuminosa (Berk.) Pegler (Agaricaceae) Grows on termite mounds in grassy fields May-August NUBOT-TA-MA-63
Termitomyces heimii Natarajan (Lyophyllaceae) Found to grow on termite mounds and clayey soil May-August NUBOT-TA-TH-64
Lentinus sp. (Polyporaceae) Grows on tree trunks and dead barks of Oaks End May-June NUBOT-TA-L-69
Termitomyces eurhizus (Berk.) R. Heim (Lyophyllaceae) Grows in groups on ground in termite mount soil July-August NUBOT-TA-TE-71
Lycoperdon perlatum Pers. (Agaricaceae) Grows in fields, roadsides, in woods and amongst fallen leaf litter End April-September NUBOT-TA-LP-72
Laetiporus sulphureus (Bull.) Murr. (Polyporaceae) Grows on dead stumps as well as living tree trunk of hardwoods and oaks July-September NUBOT-TA-LS-73
Coprinus comatus (O.F. Müll.) Pers. (Agaricaceae) Grows amongst grasses in sub-tropical forests May-October NUBOT-TA-CC-74
Pleurotus citrinopileatus Singer (Pleurotaceae) Grows on trunks of hardwood June-August NUBOT-TA-PC-75
Wild edible mushrooms of nagaland, india: a potential food resource. 61
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Figure 1 Some of the wild edible mushrooms of Nagaland; a. Auricularia polytricha, b. Aleuria aurantia, c. Auricularia judae, d.
Cantharellus cibarius, e. Coprinus comatus, f. Dacryopinax spathularia, g. Laetiporus sulphureus, h. Lactarius volemus, i. Laccaria
tortilis, j. Lactarius piperatus, k. Lentinula edodes, l. Lycoperdon perlatum, m. Macrolepiota albuminosa, n. Pleurotus citrinopileatus, o.
Pleurotus pulmonarius, p. Schizophyllum commune, q. Termitomyces eurrhizus, r. Termitomyces heimi, s. Tremella fuciformis, t.
Tricholoma imbricatum.
A part of the collected materials were dried at 40-72oC using
blowing hot air and kept for future references, characterization
and documentation. The habitat, odor, morphology, spore print
and adaptation to the environment studied prior to the
preservation of the collected macro fungi. Identification of the
collected mushrooms was done by standard microscopic
methods (Roy & De, 1996) and by studying the macroscopic
and microscopic characters (David, 1986; Das, 2009; Philips,
2006). The mushroom specimens were deposited in the
herbarium of Department of Botany, Nagaland University,
Lumami, India with the accession numbers as mentioned in
Table 1.
62 Toshinungla et al
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3 Results
A total of 33 Wild Edible Mushroom (WEM) species
belonging to Auriculariaceae, Cantharellaceae, Russulaceae,
Polyporaceae, Hericiaceae, Dacrymycetaceae,
Schizophyllaceae, Boletaceae, Amanitaceae,
Tricholomataceae, Pleurotaceae, Clavariaceae, Tremellaceae,
Hygrophoraceae, Suillaceae, Hydnangiaceae, Pyronemataceae,
Agaricaceae and Lyophyllaceae were collected and identified
as per various literatures (Table 1). Besides edible mushrooms,
9 species are used for medicinal purpose to cure different
diseases (Table 2). Figure 1 shows some of the common wild
edible mushrooms of Nagaland. Market surveys revealed that
WEM are highly coveted food resource in Nagaland. The local
people prepare soups, chutney, salads and various side dishes
from mushrooms. During the season, there is high demand of
edible varieties of WEMs and these are sold ranging from 50-
250 INR per packet at local markets. The prize varies
depending on popularity, taste and demand. Some popular
varieties available at local markets during the season are
Schizophyllum commune, Lentinus edodes, L. squarrosulus,
Termitomyces heimi, T. eurhizus, Auricularia auricula-judae,
Lactarius volemus, and Pleurotus pulmonarius. S. commune
and L. edodes are sold in dried form throughout the year till
stocks last with the local people.
Discussions
Nagaland is one of the North Eastern states of India which is
agro-climatically very rich and supports the growth of many
wild mushrooms. Unfortunately till date there is no systematic
survey of wild edible mushrooms in the state. Indigenous
knowledge possessed by the local people about WEMs will
provide significant opportunities to develop micro-enterprises
and entrepreneurship. This can be a means of achieving
sustainability. Mushroom hunting is not gender oriented in the
state i.e. both men and women are equally involved. Folk
taxonomy through traditional knowledge and experience is
usually used to identify edible mushrooms from poisonous
ones. Naming of the species is done in local dialect to keep
memory and transfer the knowledge from one generation to the
next. The study promotes awareness to harvest and exploit this
underutilized local resource, which will provide nutritious food
and employment opportunities especially to the disadvantaged
groups (i.e. unemployed and old people) (Kumar et al., 2013;
Sachan et al. 2013; Tanti et al., 2011; Tibuhwa, 2013).
The exploitation of WEM would contribute significantly in
boosting the economy and at the same time, food security is
checked. Mushrooms are a source of income generator
especially for rural areas. The cultivation of WEM hardly
causes any effect on the environment in fact they act as
ecological indicators. As such the study calls for awareness
and cooperation from forest conservers to allow mushroom
gatherers to freely collect this non wood forest resource which
is highly underutilized. The present work also highlights the
ethno-medicinal potential of the state. The uses (nutritional and
medicinal values, neutriceuticals and neutraceutical
compounds) of WEM is likely to be lost if these are not
properly documented and screened. Further studies need to be
carried out in order to assess the ethno-medicinal potential of
WEMs for discovery of novel compounds for their
pharmaceutical applications.
The present work may lead to the creation of a database for
WEM of the state as no such work has been carried out in
depth. The first phase of this study enumerates the wild edible
mushrooms of Nagaland. Works on nutritional analysis,
molecular profiling of wild edible mushrooms is in progress.
During recent times, cultivated mushrooms have gained much
attention because of the many health benefits of mushrooms
but unfortunately in remote regions of the world like Nagaland
no such markets are available for the local people to enjoy the
highly popular cultivated mushrooms. In such circumstances,
the wild edible mushrooms which are available in the state
should be brought to light so that the people can reap the
benefits of consuming edible mushrooms like the rest of the
world. Moreover, with proper research and infrastructure
facilities, WEM can be commercialized which can play a key
role in the socio-economic upliftment of the people.
Table 2 Medicinal uses of WEM as described by other researchers.
Name of the species Medicinal uses
Auricularia auricula-judae Anti-tumor, anticoagulant, hypocholesterolemic
Auricularia polytricha Anti-coagulant, hypocholesterolemic
Pleurotus pulmonarius Anti-HIV, hyperglycemic
Cantharellus cibarius Anti-microbial
Schizophyllum commune Anti-cancer (drug- Schizophyllan)
Lentinula edodes Anti-tumor, anti-HIV, natural antidote
Lactarius piperatus Anti-tumor, anti-bacterial, anti-oxidant
Lycoperdon perlatum Antimicrobial and Antifungal (lycoperdic acid)
Lentinus squarrosulus Used as neutraceutical
Sources: Chang & Miles, 2004; Das, 2010; Patel et al., 2012; Sachan et al., 2013; Sharma & Atri, 2014.
Wild edible mushrooms of nagaland, india: a potential food resource. 63
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Acknowledgement
The authors are thankful to the University Grants Commission,
Govt. of India, New Delhi for financial help through the UGC-
SAP (DRS-III) program to the Department of Botany. The
infrastructure and facility used from the Institutional Biotech
Hub, Department of Botany, Nagaland University are duly
acknowledged.
Conflict of Interest
Authors would hereby declare that there is no conflict of
interests.
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KEYWORDS
Phytoplankton
Taal Lake
Aquaculture
Importance value
ABSTRACT
This study was aimed to assess the phytoplankton communities between the aquaculture and non-
aquaculture sites of the Taal Lake in Batangas, Philippines for a sampling period of 10 months from
August 2013 to May 2014. Total of 39 phytoplankton genera under Division Chlorophyta, Cyanophyta,
Chrysophyta and Pyrrophyta were reported from the study site. Among these, 36 genera were observed
from the aquaculture sites while only 30 genera from the non-aquaculture sites. Results of the density
revealed that availability of phytoplankton was significantly higher in the aquaculture than the non-
aquaculture sampling stations for all major phytoplankton divisions. Highest monthly density was also
recorded during the summer months of March to May 2014 and lowest in the month of January 2014
due to sulphur upwelling. The most dominant phytoplankton based on importance value for both
sampling sites was Microcystis followed by Merismopedia in aquaculture sites and Oscillatoria in non-
aquaculture sites, all under division Cyanophyta, indicating the organic pollution and eutrophication of
Taal Lake.
Airill L. Mercurio1,*
, Blesshe L. Querijero2 and Johnny A. Ching
1
1Biological Sciences Department, College of Science and Computer Studies, De La Salle University-Dasmariñas, City of Dasmariñas 4115, Cavite, Philippines.
2Animal Biology Division, Institute of Biological Sciences, College of Arts and Sciences, University of the Philippines, Los Baños 4031, Laguna, Philippines.
Received – November 25, 2015; Revision – December 20, 2015; Accepted – January 21, 2016
Available Online – February 20, 2016
DOI: http://dx.doi.org/10.18006/2016.4(1).66.73
PHYTOPLANKTON COMMUNITY IN AQUACULTURE AND NON-
AQUACULTURE SITES OF TAAL LAKE, BATANGAS, PHILIPPINES
E-mail: [email protected] (Airill L. Mercurio)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
Journal of Experimental Biology and Agricultural Sciences
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ISSN No. 2320 – 8694
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All rights reserved.
All the article published by Journal of Experimental
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Creative Commons Attribution-NonCommercial 4.0
International License Based on a work at www.jebas.org.
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1 Introduction
Taal Lake covers an area of 268 km2, lies 60 km south of
Manila, in the province of Batangas. The lake provides
multiple services to various users, including fisheries, of which
aquaculture has flourished rapidly over the years. The lake is
also used for recreation, tourism, navigation, and as water
source for the nearby cities and agricultural fields (Mutia,
2001). Aquaculture had been the major source of livelihood of
the fisher folk living in the lakeshore since 1970 (Gibertas,
2008). Fish cage operators rely on the water of Taal Lake for
intensive fish production (Vista et al., 2006).
In aquaculture, phytoplankton contributes to primary
productivity that helps in maintaining fisheries (Brraich &
Saini, 2015). Phytoplankton serve as food of zooplanktons
which are usually being fed to fish larvae reared in fish
hatcheries (Moncheva & Parr, 2010; Diwowo, 2013).
Phytoplanktons also play an important role in material
circulation and energy flow in aquatic ecosystem. Its presence
often controls the growth, reproduction capacity, and
population characteristics of other organisms (Ariyadej et al.,
2008). It is also an important biological indicator of the water
quality (Edward & Ugwumba, 2010; Brraich & Saini, 2015).
The current study compared the phytoplankton community in
two separate areas in Taal Lake, the fish cage farming sites and
non-aquaculture sites during a 10-month sampling period from
August 2013 to May 2014 as indicator of possible effect of
aquaculture activities on lake productivity.
2 Materials and Methods
2.1 Phytoplankton Collection and Measurement
Phytoplankton samples for quantitative and qualitative
analyses were collected from three sampling stations for the
aquaculture sites and one sampling station for the non-
aquaculture sites. Each sampling station has three sub-
sampling stations; total of 12 sub-sampling stations for the
study site. The aquaculture sampling stations, located in the
municipalities of Talisay and Laurel, and the non-aquaculture
station in the municipality of Tanauan were identified using
GPS Garmin E-trex® Global Positioning device (Fig. 1).
One liter lake water was collected and 10 ml of it was taken in
a test tube for centrifugation (Hermile®) for 5 min at 4,000 rpm
to concentrate its algal component. The supernatant was
decanted and 1 ml precipitate was placed in a vial preserved
with one drop of Lugol’s iodine. The isolated phytoplanktons
were identified and photographed using photomicroscope
(Nikon®) at 400x. Phytoplankton frequency, abundance and
density were determined for the identification of dominant
species based on importance value.
Figure 1 Sampling stations for aquaculture and non-aquaculture sites in Talisay and Laurel, Batangas, Philippines (Map created by the
author using Q-GIS).
67 Mercurio et al
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The phytoplankton was counted using Haemocytometer
method (Martinez et al., 1975). Final population of
phytoplankton was calculated by using following formula:
The importance value of the phytoplankton species was
determined by adding the relative values of the frequency,
density and abundance. The phytoplankton species which has
the highest importance value was considered as the most
dominant. The frequency, abundance and density, and their
relative values are calculated by the standard formulas given
by Umaly, 1988.
Where, RF is relative frequency, RA is relative abundance and
RD is relative density.
2.2 Quantitative Analysis of isolated Phytoplankton
Quantitative analysis of the importance value of phytoplankton
was done using the summation of the relative values of the
frequency, density and abundance of the different species of
plankton collected from the lake. Mann-Whitney U test at 95%
level of confidence was used to determine the significant
difference of phytoplankton density between the aquaculture
and non-aquaculture sites of Taal Lake.
3 RESULTS AND DISCUSSION
3.1 Phytoplankton Communities
A total of 39 genera of phytoplankton belonging to four major
divisions namely, Chlorophyta, Chrysophyta, Cyanophyta and
Pyrrophyta were observed in the aquaculture and non-
aquaculture sites in Taal Lake. The detail of isolated genera
has been provided in Table 1. Among the total isolated genera,
36 were isolated from aquaculture sites while only 30 genera
from the non-aquaculture sites.
Results presented in table 2 revealed that the density of
phytoplankton is significantly higher in the aquaculture than
the non-aquaculture sampling stations for all major
phytoplankton divisions.
Both organic and inorganic matter from commercial
aquaculture operations have been implicated in phytoplankton
production (Bunting, 2013).
Figure 1 Representative phytoplankton in aquaculture and non-aquaculture sites in Taal Lake, Batangas, Philippines.
Phytoplankton community in aquaculture and non-aquaculture sites of Taal Lake, Batangas, Philippines. 68
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Table 1 Collected phytoplankton in aquaculture and non-aquaculture sites of Taal Lake
No. Genus Aqu. sites Non-aqu. sites No. Genus Aqu. sites Non-aqu. sites
Division- Chlorophyta Division- Chrysophyta
1 Actinastrum X 1 Coconeis
2 Ankistrodesmus 2 Coscinodiscus
3 Asterionella 3 Cyclotella
4 Chlorella X 4 Cymbella X
5 Chlorococcum X 5 Diatoma
6 Chodatella 6 Fragilaria
7 Closterium 7 Gomphonema X
8 Coelastrum 8 Melosira
9 Cosmarium 9 Navicula X
10 Crucigenia X 10 Nitzschia
11 Eudorina 11 Synedra X
12 Kirchneriella 12 Tabellaria
13 Oocystis Division - Cyanophyta
14 Scenedismus 1 Anabaena
15 Schroederia X 2 Chroococcus
16 Selenastrum 3 Merismopedia
17 Staurastrum 4 Microcystis
18 Tetraedron 5 Oscillatoria
19 Treubaria Division - Pyrrophyta
20 Westella X 1 Glenodinium X
2 Peridinium X
In aquaculture, usually only a fraction of the fish feed is being metabolized. Feeds that were not taken by the fishes tend to settle at the
bottom and decomposed which results to the growth of phytoplankton and bacteria (Glibert et al., 2002).
Table 2 Density of phytoplankton (per ml of water) by division in aquaculture and non-aquaculture sites of Taal Lake.
Division Aquaculture Non-aquaculture
Chlorophyta 12,189a 6,668
b
Chrysophyta 7,304a 2,748
b
Cyanophyta 193,711a 107,800
b
Pyrrophyta 200a 0.0
b
Different letters as superscript in the same row indicate significant difference (p<0.05) between the average total counts of phytoplankton
communities in aquaculture and non-aquaculture sites of Taal Lake.
3.1.1 Division Chlorophyta
Of the 39 genera of phytoplankton, 20 genera were observed
under Division Chlorophyta. The Chlorophyta or the green
algae appear bright grass green because their chlorophyll is not
concealed by large amounts of accessory pigments. They
exhibit a surprising level of nutritional variation. Among
these, Coelastrum has highest density at both sites, with mean
value of 2,608 cells per ml in aquaculture and 2,307 cells per
ml in non-aquaculture sites. Unlike other green algae,
Coelastrum exhibit asexual reproduction by autocolony
formation. Coelastrum cells are connected to one another by
blunt processes to form hollow coenobia that will give rise to
autocolonies without the involvement of flagellate zoospores
(Graham & Wilcox, 2000). Actinastrum, Crucigenia, and
Westella were observed only in non-aquaculture sites because
these are rare species and prefer low level of nutrients.
Chlorella, Chlorococcum and Schroederia were observed only
in aquaculture sites indicating preference for high level of
nutrients. Schroderia has the lowest density of 175 cells per ml
in aquaculture sites. Ankistrodesmus has the lowest density of
200 cells per ml in non-aquaculture sites.
3.1.2 Division Chrysophyta
Under Division Chrysophyta, total 12 genera namely Coconeis,
Coscinodiscus, Cyclotella, Cymbella, Diatoma, Fragilaria,
Gomphonema, Melosira, Navicula, Nitzschia, Synedra and
Tabellaria were observed. In the aquaculture sites, the
phytoplankton with the highest average total count was the
genus Melosira with mean value of 4,528 cells per ml while
genus Cymbella has the lowest value of 100 cells per ml.
69 Mercurio et al
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Similarly, the highest number of phytoplankton that was
observed in the non-aquaculture sites are Melosira with a value
of 1,288 cells per ml, but the lowest number of phytoplankton
are the Coscinodiscus with an a density 100 cells per ml.
Among the 12 genera, four of them were not observed in the
non-aquaculture sites which include Cymbella, Gomphonema,
Navicula and Synedra. Melosira has the highest density
among the phytoplankton under this Division because
Melosira takes advantage of the high nutrient levels promoting
its growth and benefits from low levels of competition and
grazing by having resting stage in the sediments (Horne &
Goldman, 1994).
3.1.3 Division Cyanophyta
Among the four major divisions, Cyanophyta has the highest
phytoplankton density. Five genera i.e. Anaebena,
Chroococcus, Merismopedia, Microcystis and Oscillatoria
were observed under Division Cyanophyta. Microcystis has the
highest total count of 10,666 and 8,579 cells per ml in both the
aquaculture and non-aquaculture sites, respectively. Among
the studied population, the lowest number of phytoplankton
was Anaebaena with an average density of 900 cells per ml in
the aquaculture sites and Chroococcus with only 1,570 cells
per ml in the non-aquaculture cites. Microcsytis is the most
dominant species that was observed in both aquaculture and
non-aquaculture. Microcystis become dominant since they
produce secondary chemicals called microcystins which causes
blooms in freshwater that protects them from zooplanktons and
grazers (Carmichael et al., 1988; Krebs, 2009). Cyanobacteria
or blue green algae are “nuisance algae” which becomes
abundant when nutrients are plentiful. Cyanobacteria can even
tolerate low oxygen conditions and concentrations of H2S.
They prefer alkaline conditions and pH may rise up to 9
(Vincent, 2009).
The energy required for the vertical movement of the blue
green algae is small, especially for those species that use
carbohydrate ballast such as the Microcystis to balance more
permanent gas vacuoles and to regulate their position in the
water column. The ballast is used up overnight and the algae
float to the surface in the morning to resume the cycle (Horne
& Goldman, 1994).
3.1.4 Division Pyrrophyta
Only two genera of dinoflagellates were observed under
Division Pyrrophyta, namely Glenodinium and Peridinium.
These were present only in the aquaculture sites and observed
during the month of May. Both of them have an average count
of 100 cells per ml. Dinoflagellates grow best in summer
because they can actively swim to favorable light and
nutrients. Their requirements are complex and require high
organic substrates. Their population may decline due to
zooplankton grazing. The active swimming of large
phytoplankters such as dinoflagellates requires also large
amounts of energy unlike small phytoplankton (Horne &
Goldman, 1994).
3.2 Monthly Density of Phytoplankton
The monthly density of the observed phytoplankton in both
aquaculture and non-aquaculture sites during the 10-month
sampling period is shown in Fig. 2. Results showed that the
phytoplankton density is at its peak during summer i.e. March
to May. Results are in agreement with the findings of Horne &
Goldman (1994) those have reported that phytoplankton grows
best in summer due to higher light intensity. Light is a
fundamental aspect of phytoplankton ecology since they are
the primary producers in aquatic areas. They convert light
energy into biomass through photosynthesis (Graham &
Wilcox, 2000). On the other hand, the phytoplankton density
is lowest on the month of January and this may be attributed to
the sulphur upwelling that transpired last January 16, 2014
(BFAR, 2014). Sulfur upwelling in Taal Lake usually occurs
from November to February when the northeast wind disturbs
the sediments in the lake, resulting in the upwelling of
hydrogen sulfide which is a poisonous gas (BFAR, 2014). This
affected the density of the phytoplankton.
Figure 2a Monthly density of observed phytoplankton (over-all).
Phytoplankton community in aquaculture and non-aquaculture sites of Taal Lake, Batangas, Philippines. 70
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Figure 2b Monthly density of observed phytoplankton (division wise)
3.3 Importance Value of Phytoplankton
The dominant phytoplankton species in both aquaculture and
non-aquaculture sites of Taal Lake were identified by
determining their importance value (Table 3). This was carried
out by adding the relative frequency, relative abundance and
relative density per genus (Umaly,1988).
Table 3 Dominant Phytoplankton Species based on Importance Value.
Dominant species Relative frequency Relative abundance Relative density Importance Value
Aquaculture sites
Microcystis 22.273 22.271 22.271 66.815
Merismopedia 16.722 16.720 16.720 50.162
Melosira 9.454 9.454 9.454 28.362
Oscillatoria 6.348 6.348 6.348 19.044
Coelastrum 5.445 5.445 5.445 16.335
Non-aquaculture sites
Microcystis 19.340 18.831 19.340 57.511
Oscillatoria 14.090 13.720 14.090 41.900
Anaebena 10.709 10.427 10.709 31.845
Merismopedia 10.089 9.832 10.089 30.010
Westella 7.214 7.025 7.214 21.453
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Microcystis has highest importance value for both aquaculture
and non-aquaculture sites which indicates that it is the most
dominant species. Merismopedia rank as the second dominant
species in aquaculture sites, while Oscillatoria in non-
aquaculture sites. Other identified dominant species in
aquaculture sites include Melosira, Oscillatoria, and
Coelastrum, while Anabaena, Merismopedia, and Westella for
the non-aquaculture sites. These findings were in agreement
with the study of Xing et al. (2013), wherein one of the
dominant phytoplankton observed in Baiyangdian Lake during
spring was Microcystis, which is an indicator of
eutrophication. Ansari et al. (2008) also reported that
Microcystis and Oscillatoria dominate Unkal Lake in
Kartanaka, India. Occurrence of bloom of Microcystis and
Oscillatoria indicates organic pollution and eutrophication of
Unkal Lake. Further, highest importance value belonging to
division Cyanophyta indicates organic pollution and
eutrophication of Taal Lake.
Conclusions
Phytoplanktons serve as an indicator of water quality and
trophic condition of a lake. The phytoplankton community in
aquaculture and non-aquaculture sites of Taal Lake, Batangas,
Philippines was assessed. During the sampling period, a total
of 39 genera of phytoplankton under divisions Chlorophyta,
Chrysophyta, Cyanophyta and Pyrrophyta was observed in the
study site. Statistically, phytoplankton density in aquaculture
sites is significantly higher than non-aquaculture sites. The
monthly density of phytoplankton was observed to be highest
during the summer months of March to May 2014 and lowest
in the month of January 2014 due to sulphur upwelling.
Dominant phytoplanktons were also determined based on
importance value. In both aquaculture and non-aquaculture
sites, Microcystis ranks first thereby is the most dominant
species, followed by Merismopedia in aquaculture sites and
Oscillatoria in non-aquaculture sites. All the three
phytoplankton with the highest importance value belong to
division Cyanophyta indicating organic pollution and
eutrophication of Taal Lake. Thus, regular environmental
monitoring of the lake is hereby recommended.
Acknowledgements
The authors acknowledge the University Research Office
(URO) of De La Salle University-Dasmariñas (DLSUD) for
providing financial support, Dir. Esmeralda Paz-Manalang of
Regional Fisheries Office, Ms. Nenita S. Kawit of the Inland
Fisheries Research Station, Mr. Aljon S. Andrade of BFAR
RFO IV-A in Tanauan, Batangas, and Mr. Victor H. Mercado,
PASu TPVL, the TLAAI and LGU’s of Talisay and Laurel,
Batangas.
Conflict of interest
Authors would hereby like to declare that there is no conflict of
interests that could possibly arise.
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73 Mercurio et al
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Journal of Experimental Biology and Agricultural Sciences
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KEYWORDS
Digested effluent
Dwarf Napier grass
Aftereffect
Compaction effect
Plant production
ABSTRACT
In regional intensive livestock farming, animal waste has a significant dispersal problem. One of the
solutions is to process animal wastes to digested effluent of manure (DEM) by the operation of biogas
plants. The objectives of the present study were to determine the residual effects of DEM in field
application at three levels in the previous two years and the effect of compacted DEM amended with
solid manure in a pot trial on production in a dwarf variety of late-heading type Napier grass
(Pennisetum purpureum Schumach). Plant growth attributes (plant height, tiller number, mean tiller
weight and plant dry weight) in the year examined tended to increase with DEM application rate the
previous two years, while the difference between the previous year’s treatments was less than 25%, the
aftereffect of manure application on normal Napier grass was more than 4 times higher. Pot-cultured
growth attributes were highest for liquid DEM and chemical fertilizer, followed by a mixture of DEM
with manure under the same total nitrogen supply, and decreased significantly with a decrease in the
DEM-amended mixture application. Thus, it is concluded that DEM would have a limited residual effect
as in the chemical fertilizer plot and a smaller effect than manure application, and a mixture of DEM
amended with solid manure should facilitate supplying DEM to forage crops by compaction.
Hadijah Hasyim1, Yasuyuki Ishii
2,*, Ahmad Wadi
3, Ambo Ako Sunusi
4, Satoru Fukagawa
5 and
Sachiko Idota2
1 Interdisciplinary Graduate School of Agriculture and Engineering, University of Miyazaki, Miyazaki, Japan
2 Faculty of Agriculture, University of Miyazaki, Miyazaki, Japan
3 Polytechnic Agriculture Negeri Pangkep, Segeri Mandalle, Indonesia
4 Department of Animal Sciences, Hasanuddin University, Makassar, Sulawesi Selatan, Indonesia
5 Nagasaki Agricultural and Forestry Technical Development Center, Shimabara, Nagasaki, Japan
Received – January 08, 2016; Revision – January 27, 2016; Accepted – February 15, 2016
Available Online – February 20, 2016
DOI: http://dx.doi.org/10.18006/2016.4(1).74.84
RESIDUAL EFFECTS OF COMPACTED DIGESTED EFFLUENT ON GROWTH OF
DWARF NAPIER GRASS IN WARM REGIONS OF JAPAN
E-mail: [email protected] (Yasuyuki Ishii)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
Journal of Experimental Biology and Agricultural Sciences
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ISSN No. 2320 – 8694
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International License Based on a work at www.jebas.org.
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1 Introduction
In integrated dairy production, large quantities of high quality
herbage are required to reduce the costs of nutrient supply for
herbivore production. Livestock wastes should be treated
promptly to produce fermented manure (Annicchiarico et al.,
2011). Adequate plant nutrient supply from organic fertilizers
is essential to increase the potential of herbage production in
eco-friendly livestock farming (Barnes et al., 1995; Whitehead,
2000). Plant growth is determined by defoliation intensity,
fertilizer input and mineral nutrient loss in the cropping
systems (McFarland et al., 1998). Biogas plants produces
methane gas to generate electricity from livestock manure and
end product is digested effluent of manure (DEM), which is
assessed as the promising organic fertilizer (Cornes, 2006;
Nest et al., 2015). High rate of herbage production is essential
by supplying high rate of fertilizer input, which can reduce the
cost of application using DEM, replacing chemical fertilizer
application (Hasyim et al., 2014).
Napier grass (Pennisetum purpureum Schumach) has a wide
genetic variation from normal to dwarf genotypes in the tropics
and subtropics (Barnes et al., 1995; Rengsirikul et al., 2011) as
well as in the warm regions of Japan (Wadi et al., 2003;
Khairani et al., 2013). Dwarf varieties of late-heading type
(dwarf) Napier grass was introduced from Thiland into
southern Kyushu, Japan in 1996 (Ishii et al., 1998; Mukhtar et
al., 2003). Dwarf Napier grass tended to have higher tiller
density and leaf percentage than normal Napier grass (Ishii et
al., 1998), can survive in winter at the coastal southern Kyushu
(Utamy et al., 2011) and is suitable to grazing of beef cows
(Ishii et al., 2005).
In previous study by same authors (Hasyim et al., 2014),
growth of dwarf Napier grass was positively associated with
DEM application via leaf area development without disturbing
the chemical environments of soils neighboring the examined
areas. However, the residual effect of DEM application on
plant growth in the field the following year in the absence of
fertilization has not been determined. Liquid DEM requires
transport from biogas plants to forage fields; however, due to
its low concentration of nutrients, compaction of DEM
amended with cattle manure and dried under plastic house
should facilitate the supply of DEM to the field.
The objective of this study was to determine the aftereffects of
DEM at three levels of field application in the previous two
years and the effect of compacted DEM amended with solid
manure in a pot trial on plant production in dwarf Napier grass
in southern Kyushu, Japan.
2 Materials and Methods
2.1 Aftereffects of DEM application to fields in the previous
two years
2.1.1 Plant culture
The experiment was conducted on Andosols at 31 m above sea
level in Kibana Agricultural Research Station, University of
Miyazaki in southern Kyushu, Japan (131.41°E, 31.83°N).
Previous two cropping years, field was fertilized by different
fertilizing treatments (2007 to 2008). Lime (200 g m-2
) and
fermented cattle manure (600 g m-2
) were basally dressed on 8
May, 2007. Dwarf Napier grass was grown by transplanting
individual rooted tillers with 2 plants m-2
(0.5 m × 1.0 m of
spacing) on 10 May, 2007, and Italian ryegrass (cv. Ace, Snow
Brand Seed Co. Ltd. Sapporo, Japan) was sown into the inter-
row spaces as an intercrop after harvesting dwarf Napier grass
in autumn on 30 October, 2007 and 27 October, 2008. The
plots (13.5 m2/plot) were set into a randomized blocked design
with 3 replications and were divided into 4 treatments, which
had 3 levels of DEM application at 5.04, 2.52, and 1.26 g Nm-2
at each application, considered high (H), medium (M), and low
(L) levels, respectively, and chemical compound fertilizer (C)
application at the same rate of N (5.04 g N m-2
time-1
) as H
level with additional 4 times and 3 times of split application
per season of dwarf Napier grass and Italian ryegrass,
respectively. In the season of 2009, no fertilizer application
was carried out to examine the after (residual)-effect of the
previous two years’ DEM application on plant growth of dwarf
Napier grass under the twice-cutting practice per season.
2.1.2 Plant measurement
Dwarf Napier grass plants were sampled 2 times at the harvest
on 18 July and 4 November, 2009, and divided into various
plant fractions such as leaf blade (LB), stem inclusive of leaf
sheath (ST), and dead part (D) to determine dry matter weight
(DMW). Some plant growth attributes, such as plant height and
tiller number were also investigated for randomly selected 3
plants (1 plant from each replication) at each fertilization level
and mean tiller weight (MTW) was calculated by plant DMW
divided by plant tiller number.
2.2 Compaction effect of DEM amended with solid manure in
the pot trial
2.2.1 Plot design and plant culture
Dwarf variety of late-heading type Napier grasses were
transplanted at one shoot per pot to 1/2000 a Wagner pot, 25-
cm of diameter and 30-cm of depth, filled with Andosols on 15
May, 2009 and grown outdoors for 4-5 months in an
experimental field of the Faculty of Agriculture, University of
Miyazaki. The plots were arranged by a completely
randomized block design with 3 replications, where cattle
manure enriched with digested effluent of manure (solid DEM)
supplied at transplanting with 3 levels, 5.04, 10.08, 20.16 g N
m-2
yr-1
for low (L), medium (M) and high (H) level,
respectively, amended with liquid DEM (DEM) and chemical
compound fertilizer (C), split-supplied 4 times at 5.04 g N m-2
application-1
(the same N supply as the H level, 20.16 g N m-2
yr-1
of solid DEM).
75 Hasyim et al
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Journal of Experimental Biology and Agricultural Sciences
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Table 1 Mineral and water concentration of solid and liquid digested effluent of manure (DEM)
Solid DEM Liquid DEM
Composition Solid DEM (mg/g FM)) Characteristics Liquid DEM
Water 79 pH 8.3
TN 20.4 EC (mS/cm) 17.7
TC 393.7 Composition (mg/L) -
Na 5.0 NH4+ 3296
Mg 5.6 K+ 1582
P 10.1 Mg2+
30
K 31.9 Ca2+
234
Ca 21.1 Na+ 299
Fe 1.1 PO4- 75
Mn 0.2 SO4- 79
Zn 0.2 NO3- 38
The mineral composition and water content of solid and liquid
DEM are listed in Table 1. The spacing of pots was 50 cm ×
100 cm and whole plots were surrounded by bordering plants
grown in soil. Watering was done every day with a plastic vase
set at the outlet of each Wagner pot to protect from runoff of
nutrients. Plants were defoliated at 25 cm above the soil
surface twice, on 27 August and 27 October, 2009.
2.2.2 Plant measurements
Changes in growth attributes, such as plant height and length,
and tiller number, were measured every week, and the dry
matter weight (DMW) of each plant fraction, LB, ST and D of
herbage and stubble parts, underground stem part (UG) and
root (R), and leaf area (LA) were determined at defoliation and
the leaf area index (LAI) was calculated. After harvest, pots
were rearranged to fill the empty spaces left by defoliation.
Plant organs from harvested plants were separated and dried at
70°C to determine DMW. Plant LA was measured with an
AAM-8 automatic area meter (Hayashi Denkoh Co. Ltd,
Tokyo, Japan). Wintering ability of this species was
determined by the percentage of overwintering plants that had
one or more regrown tillers from stubble, and the tiller number
and plant height of regrown plants the following spring on 3
June, 2010.
Figure 1 Changes in the mean air temperature (○), minimum air temperature (●), total solar radiation (SR, △) and precipitation (PRE, □)
in the growing season in 2009 (Data from Japan Meteorological Agency, 2015).
0
5
10
15
20
25
30
0
100
200
300
400
500
600
700
800T
emp
(℃
), S
R (
MJ
/m2/d
ay)
PR
E (
mm
)
2009
J
Month
F M A M J J A S O N D
Residual effects of compacted digested effluent on growth of dwarf napier grass in warm regions of Japan 76
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Journal of Experimental Biology and Agricultural Sciences
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Figure 2 Changes in plant height (A), tiller density (B), mean tiller weight (C) and plant dry matter weight (DMW, D) in dwarf Napier
grass following the previous two-years’ fertilizing treatments in 2009. Solid DEM manure: L level (5.04 gN/m2/year), M level (10.08
gN/m2/year), H level (20.16 gN/m
2/year), chemical compound fertilizer: C level (20.16 gN/m
2/year) and liquid DEM level (20.16
gN/m2/year). ns: P > 0.05.
2.3 Statistical analysis
Analysis of variance was carried out using SPSS software
(version 15.0) by one-way analysis procedures for growth and
yield attributes of dwarf Napier grass in a randomized
complete design. Mean separation was tested using the least
significance difference method at the probability of 5%.
3 Results
3.1 Climatic conditions
Climatic conditions in 2009, based on data from Miyazaki
Meteorological Observatory, were not very different from
those in a normal year, except for a higher mean temperature
from late August to late October and higher precipitation from
late July to early August and from mid- to late September
(Figure 1). The maximum daily mean air temperature and solar
radiation values occurred in late August. Since air temperature
and solar radiation decreased from late September until the end
of the year, this decrease might have severely suppressed plant
growth.
3.2 Seasonal changes in growth attributes and DMW
Seasonal changes in plant growth attributes, such as plant
height, tiller density, mean tiller weight and plant DMW were
determined two times at the time of cutting i.e. in mid-July and
early November of 2009 (Figure 2). Every growth attribute
tended to increase with the increase in the previous two years’
DEM application rate at both the first and second cuttings, but
did not differ among the treatments. Therefore, no application
rate-dependent plant growth in dwarf Napier grass was
observed in the following year of 2009.
3.3 Seasonal changes in growth attributes and DMW
Seasonal changes in plant growth characters, such as plant
height, plant length and tiller number, were monitored every
week for all fertilizer levels during the growing season in 2009
(Figure 3). For all levels of fertilization, plant height and plant
length increased linearly with time. The increase in plant
height and plant length over time was faster in late June to
mid-July, which may have been due to the higher mean air
temperature in this period. The differences in plant height and
plant length among levels of fertilization were small and not
significant from May to June, 2009 but expanded from July to
October, 2009. Tiller density reached the maximum in early
July and turned to decrease thereafter at all levels of
fertilization.
0
20
40
60
80
100
120
140
L M H C L M H C
I (18 July) II (4 Nov.)
Pla
nt
hei
ght
(cm
)
Cutting time and treatment
(A)ns
0
20
40
60
L M H C L M H C
I (18 July) II (4 Nov.)
Till
er d
ensi
ty(N
o./
m2)
Cutting time and treatment
(B)ns
ns
0
2
4
6
8
10
L M H C L M H C
I (18 July) II (4 Nov.)
Mea
n t
iller
w
eight
(g/t
iller
)
Cutting time and treatment
(C)
ns
ns
0
100
200
300
400
500
L M H C L M H C
I (18 July) II (4 Nov.)
DM
W (
g/m
2)
Cutting time and treatment
(D)
ns
ns
ns
77 Hasyim et al
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Journal of Experimental Biology and Agricultural Sciences
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Figure 3 Changes in plant height (A), plant length (B) and tiller number (C) in dwarf Napier grass under different fertilizing treatments in
2009. Low (▲), middle (■) and high (●) rate of solid DEM application, chemical compound fertilizer (○) and liquid DEM (◇)
application. Symbols with different letters denote significant difference between treatments on the same date at the 5 % level. ns: P >
0.05.
0
20
40
60
80
100
120
140P
lant
hei
ght
(cm
)
MonthMay June July Aug. Sep. Oct.
(A)
nsns
nsns
a
ab
ab
ab
b
c
c
abc
a
a
a
a
b
c
bc
b
a
a
d
c
a
a
b
d
cd
c
b
a
a
cb
b
a
a
d
c
baa
d
bc
b
aa
d
c
baa
dc
baa
b
ns
b
ab
aab
ab
ab
ab
ab
a a
ab
a
b
a
c
b
ababa
aab
c
b
b
b
a
aaa
b
a
aaa
0
20
40
60
80
100
120
140
Pla
nt
length
(cm
)
MonthMay June July Aug. Sep. Oct.
(B)
ns ns ns
ab
abab
cb
aa
bcab
bcbb
baa
aa
c
b
d d
c
baa
d
c
baa
bd
bc
baa
dbc
b
aa
d
c
b
aa
d
bc
baa
d
cb
aa
dcb
aa
a
ab
ab
ab
b
b
a
ab
abab
a
b
ab
aa
b
ab
aaa
a
aa
a
bc
b
a
c
b
ab
aba
abab
a
aa
a
0
50
100
150
200
250
Til
ler
den
sity
(N
o.
m-2
)
MonthMay June Aug.July Sep. Oct.
(C)
ns
aa
babc
c
ab
aa
abb
a
bc
ab
bcc
aa
b
bcc
aa
b
cc
aa
b
c
c
aab
b
c
c
ab
b
a
c
c
ab
b
a
c
c
b
b
a
a
a
b
b
a
a
a
c
c
b
ab
a a
ab
b
d
c
a
c
b
e
d
c
c
b
b
a
b
d
c
b
a
d
c
b
b
aa
d
c
b
b
d
c
a
b
a
d
c
b
b
a
d
c
b
b
a
d
c
b
b
a
Residual effects of compacted digested effluent on growth of dwarf napier grass in warm regions of Japan 78
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Journal of Experimental Biology and Agricultural Sciences
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Table 2 Percentage of overwintered plants (POP), tiller density and plant height of regrown plants in dwarf Napier grass as affected by
the previous years’ fertilizing treatments on 3 June, 2010
Treatment POP (%) Tiller density (No./m2) Plant height (cm)
L 100 27.0c ± 4.9✝ 47.7
c ± 3.0
M 100 43.7b ± 4.8 57.2
b ± 4.4
H 100 67.3a ± 7.1 62.7
ab ± 8.8
C 100 67.7a ± 4.3 57.5
b ± 5.5
DEM 100 69.3a ± 9.1 64.7
a ± 4.8
✝: Mean ± standard deviation (n = 6). As for treatments, refer to Figure 2. Figures with different letters denote significant difference
between treatments on the same attribute at the 5 % level.
The tiller density increased with increased level of N
fertilization, and tended to be largest in the C level from July to
August in the first-cut plants and in the DEM level in the
second-cut plants, although the difference in tiller density
between fertilization with the same N level (H, C and DEM)
was not significant (P > 0.05) in the first cutting.
Changes in MTW of the herbage part and LAI with cutting
time were compared among the 5 treatments. At both cutting
times, MTW of the herbage increased with increased N
fertilization level, and the rate of increase of MTW tended to
be larger at the first cutting than the second cutting. The
differences in MTW at the same N level (H, C and DEM) were
small and not significant at either cutting time (Figure 4A).
The LAI increased significantly with increase in N application
level in the first-cut plants, and differences in LAI at the same
N level (H, C and DEM) were not significant in the second-cut
plants (Figure 4B).
Seasonal changes in annual total dry matter yield (TDMY)
were compared among the 5 levels of fertilization at both
cutting times. The TDMY increased with increased N
application level at both cutting times, while the difference in
TDMY between the C and DEM levels was smaller than
differences compared to the other 3 levels at both cutting times
(Figure 5A).
The ratio of top to underground weight (T/(R+UG)) tended to
increase with increased N application level at both cutting
times, reaching about 2, while there was no significant
difference in T/(R+UG) among the levels examined, except for
the lowest ratio in the L level (Figure 5B).
The relationship of CGR to LAI was positive and linear among
the 5 fertilizer levels in both cutting periods, and the regression
coefficient was higher for second-cut plants than first-cut
plants (Figure 6A). The relationship of LAI to NAR was
negative and linear among the 5 fertilizer levels in the first
cutting, while the regression of LAI on NAR was not
significant (P > 0.10) in the second cutting (Figure 6B).
Therefore, annual TDMY in dwarf Napier grass was positively
and linearly related with the annual total N input among the 5
fertilizer levels (r = 0.923, P < 0.05), as shown in Figure 7.
Figure 4 Changes in mean tiller weight (A) and leaf area index (LAI, B) in dwarf Napier grass under different fertilizing treatments in
2009. Treatment: low (L), middle (M) and high (H) rate of solid DEM application, chemical compound fertilizer (C) and liquid DEM
(DEM) application. Symbols with different letters denote significant difference between treatments on the same date at the 5 % level.
0
2
4
6
8
10
12
L M H C DEM L M H C DEM
I (27 Aug.) II (27 Oct.)Mea
n t
ille
r w
eigh
t (g
tille
r-1)
Cutting time and treatment
(A)
b
a
c
b
a
a
c bcab
b
0
2
4
6
8
10
L M H C DEM L M H C DEM
I (27 Aug.) II (27 Oct.)
LA
I (m
2m
-2)
Cutting time and treatment
(B)
ab
d
c
b
aaa
a
b
a
0
2
4
6
8
10
12
L M H C DEM L M H C DEM
I (27 Aug.) II (27 Oct.)Mean
tille
r w
eig
ht
(g t
ille
r-1)
Cutting time and treatment
(A)
b
a
c
b
a
a
c bcab
b
0
2
4
6
8
10
L M H C DEM L M H C DEM
I (27 Aug.) II (27 Oct.)
LA
I (m
2m
-2)
Cutting time and treatment
(B)
ab
d
c
b
aaa
a
b
a
79 Hasyim et al
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Journal of Experimental Biology and Agricultural Sciences
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Figure 5 Changes in total dry matter yield (TDMY; A), and top to root ratio (T/(R+UG); B) in dwarf Napier grass (DL) under different
fertilizing treatments in 2009. Treatment: low (L), middle (M) and high (H) rate of solid DEM application, chemical compound fertilizer
(C) and liquid DEM (DEM) application. Symbols with different letters denote significant difference between treatments on the same date
at the 5 % level.
Overwintering ability, determined in the following spring on 3
June, 2010, is shown in Table 2. The number of overwintering
plants was 100% in all treatments; however, tiller density and
plant height of overwintered plants increased with increased
solid DEM application, becoming nonsignificantly different at
the H level of solid DEM from the C and liquid DEM levels.
4 Discussions
4.1 Aftereffects of liquid DEM and solid manure application
on plant growth in the following year
Plant growth in the following year under no additional
fertilization was evaluated by annual TDMY following liquid
DEM application, as shown in Table 3A, and results were
compared with the aftereffects of manure application on plant
growth in the following year under no fertilization for normal
Napier grass (cv. Merkeron) reported in Sunusi et al. (2006), as
shown in Table 3B. The ratio of annual TDMY in the
following year remained stable in the range 0.7-0.8 for dwarf
Napier grass for the tested liquid DEM application levels,
while it increased from 0.2 to 1.0 for normal Napier grass
depending on manure application level. Even though the total
N application level differed significantly between liquid DEM
and manure application, the residual effects of DEM on plant
growth in the following year appear to be limited since no
positive effect was observed with a higher rate of liquid DEM
application.
4.2 Characteristics of solid and liquid DEM compared with
manure and chemical fertilizer application
The present study attempted to solve the major difficulty in
transporting liquid DEM to forage fields by using solid DEM,
which was processed by amending liquid DEM with cattle
manure without disturbing the fermentation process for the
manure. As shown in Table 1, solid DEM concentrated the
mineral nutrients compared with liquid DEM and facilitated
supplying this organic fertilizer to forage crops by compaction.
The response of plant growth to the application rate of solid
DEM was almost linear, which means that the increase in
application rate of solid DEM led to a positive linear increase
in the growth of dwarf Napier grass in terms of plant height,
tiller number, LAI and TDMY, especially at the second
cutting, as shown in Figures 3-5.
0
500
1000
1500
2000
2500
3000
3500
L M H C DEM L M H C DEM L M H C DEM
27 Aug. 27 Oct. Annual total
TD
MY
(g
m-2
)
Date and treatment
H S UG R(A)
bacde
aababbcc
aab
bccdd
a
abab
bc
aab abc b
aabc bc
abab
dc
ab
a
d bc
c b b a ac
b
a a
bcd
c
b
aa
d
c
b
a a
0
1
2
3
L M H C DEM L M H C DEM L M H C DEM
27 Aug. 27 Oct. Annual total
T/(R
+UG
)
Date and treatment
(B)
a aa
a
ba a a
a
b b
aaaa
0
500
1000
1500
2000
2500
3000
3500
L M H C DEM L M H C DEM L M H C DEM
27 Aug. 27 Oct. Annual total
TD
MY
(g
m-2
)
Date and treatment
H S UG R(A)
bacde
aababbcc
aab
bccdd
a
abab
bc
aab abc b
aabc bc
abab
dc
ab
a
d bc
c b b a ac
b
a a
bcd
c
b
aa
d
c
b
a a
0
1
2
3
L M H C DEM L M H C DEM L M H C DEM
27 Aug. 27 Oct. Annual total
T/(R
+UG
)
Date and treatment
(B)
a aa
a
ba a a
a
b b
aaaa
Residual effects of compacted digested effluent on growth of dwarf napier grass in warm regions of Japan 80
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Journal of Experimental Biology and Agricultural Sciences
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Figure 6 Relationships of crop growth rate (CGR; A) and net assimilation rate (NAR; B) with leaf area index (LAI) in dwarf Napier
grass in 2009. I and II denote the first and second cutting periods, respectively. Low (▲), middle (■) and high (●) rate of solid DEM
application, chemical compound fertilizer (○) and liquid DEM (◇) application.
However, if plant growth was compared at the same N level
(the H level) with chemical (C) and liquid DEM application,
LAI and TDMY tended to be higher in the C and liquid DEM
levels than in the H level of solid DEM, as shown in Figures
4B and 5A. The N recovery rate for conventional solid manure
is around 50% in a sole maize cropping season (Idota et al.,
2013), whereas liquid DEM contains mostly inorganic forms
of N (NH4+ and NO3
-) as well as chemical fertilizer, which
should act as a fast effective fertilizer supporting the growth of
plants and leads to a higher N recovery rate than manure
application (Idota et al., 2013). Based on the annual TDMY in
dwarf Napier grass, the H level of solid DEM application
showed 73% and 69% of the yielding ability relative to liquid
DEM and C, respectively. Thus, an increase in application rate
of solid DEM from the H level may be necessary to achieve
the same dry matter yield (DMY) with liquid DEM and C
application, and estimates of the cumulative or residual effect
of solid and liquid DEM application on subsequent plant
growth in the year following application is needed, as in the
case of manure application (Sunusi et al., 2006).
4.3 Response of growth and partitioning in dwarf Napier
grasses to different levels of solid DEM application
An increase in solid DEM application rate led to a positive
increase in plant growth attributes, in terms of plant height,
tiller number, LAI and TDMY in dwarf Napier grass. In
addition, a diminishing return of DMY in response to solid
DEM application occurred from the M to H level compared
with the L to M level (Figure 5). This indicates that dry matter
productivity is most responsive to nitrogen supply up to 200 kg
N ha-1
year-1
under these experimental conditions. Several
experiments have evaluated the effect of high amounts of
manure on forage crops on farms (Kagata et al., 1999; Sunusi
et al., 1999; Idota et al., 2005; Hasyim et al., 2007).
Figure 7 Relationship between annual total dry matter yield (TDMY) of dwarf Napier grass and annual total N input among different
ferilizing treatments in 2009. Low (▲), middle (■) and high (●) rate of solid DEM application, chemical compound fertilizer (○) and
liquid DEM (◇) application
I : y = -0.0972x + 2.64r = -0.908 (P < 0.05)
II : y = -0.525x + 8.96r = -0.413 (P > 0.10)
0
2
4
6
8
10
0 2 4 6 8
NA
R (
g m
-2d
ay-1
)
LAI (m2 m-2)
I
II
(B)
I : y = 1.87x + 1.03r = 0.999 (P < 0.01)
II : y = 6.08x + 3.33r = 0.872 (P < 0.10)
0
5
10
15
20
25
30
0 2 4 6 8
CG
R (g m
-2d
ay-1
)
LAI (m2 m-2)
I
II
(A)
10
10
I : y = -0.0972x + 2.64r = -0.908 (P < 0.05)
II : y = -0.525x + 8.96r = -0.413 (P > 0.10)
0
2
4
6
8
10
0 2 4 6 8
NA
R (
g m
-2d
ay-1
)
LAI (m2 m-2)
I
II
(B)
I : y = 1.87x + 1.03r = 0.999 (P < 0.01)
II : y = 6.08x + 3.33r = 0.872 (P < 0.10)
0
5
10
15
20
25
30
0 2 4 6 8
CG
R (g m
-2d
ay-1
)
LAI (m2 m-2)
I
II
(A)
10
10
y = 128.0x + 253.8r = 0.923 (P < 0.05)
0
500
1000
1500
2000
2500
3000
3500
0 5 10 15 20 25
TD
MY
(g m
-2)
N input (g m-2 yr-1)
81 Hasyim et al
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Journal of Experimental Biology and Agricultural Sciences
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Table 3 Ratio of dry matter yield (DMY) under no fertilization in the following year (2009) to that for the previous liquid DEM
application under 4 application levels in 2008 (A), compared with the ratio to the previous manure fertilizing year under 3 application
levels in 1995 (B).
(3A) Aftereffect of liquid DEM application (3B) Aftereffect of solid manure application✝✝
Treatment DMY in
2008
(g/m2)✝
Total N
application in
2008 (g/m2)✝
Ratio of
DMY2009 to
DMY2008
Treatment DMY in
1994
(g/m2)
Total N
application in
1994 (g/m2)
Ratio of
DMY1995 to
DMY1994
L 625 5.0 0.79 Low 605 0.0 0.22
M 794 10.1 0.65 Middle 1884 55.1 0.47
H 939 20.2 0.67 High 2653 110.5 0.97
C 899 20.2 0.66 ✝: Data from Hasyim et al. (2014). ✝✝: Data from Sunusi et al. (2006).
In Napier grass and related species, under field conditions, the
critical level of nitrogen application was determined to be 600
kg ha-1
year-1
in Miyazaki for normal Napier grass (cv. Wruk
wona) and king grass (Wadi et al., 2003) and 564 kg ha-1
year-1
for king grass and Napier grass (cv. Hawaii and cv. Africa)
grown in Indonesia (Siregar, 1989). Thus, in subtropical and
tropical conditions, the ceiling nitrogen input that effectively
increased DMY in Napier grass and related species is between
600 and 800 kg ha-1
year-1
. The critical level of nitrogen input
could vary depending on environmental stress conditions such
as low temperature, low solar radiation, drought or
waterlogging of soil, limiting dry matter production (Ahmad &
Butt, 1985). In the present pot experiments, these factors could
shift the critical level of nitrogen input to a lower level.
In terms of dry matter partitioning, dwarf Napier grass tended
to transport photosynthetic assimilates to the root and
underground stem more favorably than to the aboveground
parts compared with normal Napier grass. This suggests that
the lower herbage yield of the dwarf variety compared to the
normal one could be due to a difference in top to root ratio. In
contrast, in normal Napier grass, the top to root ratio can
change to above 10 under field conditions, which may be one
of the major reasons for high dry matter productivity of normal
Napier grass (Ito & Inanaga, 1988).
4.4 Growth parameters and their relationship to DMY as
affected by manure application level
Both LAI and CGR increased with increased solid DEM
application rate, and the increase in CGR was positively
correlated with the increase in LAI. The higher regression
coefficient of CGR with LAI at the second cutting than at the
first cutting may be due to the higher NAR at the same LAI.
Therefore, the high solid DEM application rate was presumed
to be one of the primary factors that widened the variation in
the regression between LAI and CGR. However, the increase
in LAI was concurrent with the decrease in NAR, which led to
a diminished return of DMY in both types of Napier grass.
According to Ito & Inanaga (1988), the increase in CGR of
Napier grass cv. Merkeron before the end of September in
Miyazaki was roughly proportional to the increase in LAI
when the LAI was less than 12. Therefore, the level of
fertilization affected CGR through a primary effect on LAI in
dwarf Napier grass.
Conclusions
Two types of DEM processed by a biogas plant, solid and
liquid DEM, could be used as effective organic fertilizers
capable of producing DMY of 22 and 30 t ha-1
year-1
,
respectively, showing yielding ability comparable with
chemical fertilizer at 32 t ha-1
year-1
. Residual effects of liquid
DEM application were limited, and application of solid DEM
can concentrate the mineral nutrients in liquid DEM. A
mixture of DEM amended with solid manure should facilitate
supplying DEM to forage crops due to the benefits of
compaction.
Conflict of interest
Authors would hereby like to declare that there is no conflict of
interests that could possibly arise.
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Residual effects of compacted digested effluent on growth of dwarf napier grass in warm regions of Japan 84
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KEYWORDS
Mycorrhiza fungi
Grasses weed
Mustard plant
Ultisols
ABSTRACT
Present study was aim to determined the impact of mycorrhiza fungi isolated from grasses weed on the
growth and yield of mustard in Ultisols. Study was conducted in net house located in Sindang Kasih
Village, Dictrict West Ranomeeto; Regency South Konawe Province of Southeast Sulawesi in the
month of June to September 2014. Mycorrhiza fungi infection observated on plants root done in the
Laboratory of the Faculty of Forestry and Environmental Science, Halu Oleo University, Kendari,
Indonesia. Study was conducted in completely randomized block design (CRBD) with five treatments,
each treatment was replicated with 5 replications. The variables observed for results were characteristic
of mycorrhiza fungi, plant height, number of leaves, leaf area, fresh plant weight, dry plants weight,
shoot root ratio, percentage of mycorrhiza fungi infection to plant roots. Results of study revealed that
the treatments contains mycorrhiza fungi propagules @ 100 g per polybag show superiority over all the
tested treatments in improving plant growth characteristics and yield of mustard plant.
Halim1,*
, Resman2 and Sarawa
3
1Specifications Weed Science, Department of Agrotechnology, Faculty of Agriculture, Halu Oleo University, Southeast Sulawesi, Indonesia,
2Specifications Soil Science, Department of Agrotechnology, Faculty of Agriculture, Halu Oleo University, Southeast Sulawesi, Indonesia
3Specifications Agronomy, Department of Agrotechnology, Faculty of Agriculture, Halu Oleo University, Southeast Sulawesi, Indonesia
Received – October 01, 2015; Revision – November 02, 2015; Accepted – February 20, 2016
Available Online – February 20, 2016
DOI: http://dx.doi.org/10.18006/2016.4(1).85.91
CHARACTERIZATION AND IMPACT OF MYCORRHIZA FUNGI ISOLATED
FROM WEED PLANTS ON THE GROWTH AND YIELD OF MUSTARD PLANT
(Brassica juncea L.)
E-mail: [email protected] (Halim)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
Journal of Experimental Biology and Agricultural Sciences
http://www.jebas.org
ISSN No. 2320 – 8694
Production and Hosting by Horizon Publisher
(http://publisher.jebas.org/index.html).
All rights reserved.
All the article published by Journal of Experimental
Biology and Agricultural Sciences is licensed under a
Creative Commons Attribution-NonCommercial 4.0
International License Based on a work at www.jebas.org.
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1 Introduction
Mustard (Brassica juncea L.) crop is one of the most important
vegetable crops which play an important role in the improving
living standards of farmers. Haryanto (2006) reported the
nutritive value of this crop and suggested that each 100g of
green mustard leaf lettuce contains 2.3g protein, 4.0g
carbohydrates and 0.3g of fat. Furthermore, it is also a good of
sources of vitamins and 100g of mustard leaves had 1.94mg of
vitamin A, 102mg of vitamin C and 0.09mg of vitamin B.
Furthermore, Margianto (2008) suggested that these nutrient
and vitamins are essential for the human body. Annual
production of this crop from Indonesia is still below its
maximum potential. Various factors such as type of soil,
farmer practices and low fertility are responsible for the low
production of this crop in Indonesia. Statistical data of
agricultural department suggested that average production of
mustard plants in Ultisol in Southeast Sulawesi only 3.74 tons
ha-1
(BPS, 2010).
The dominant soil types in Southeast Sulawesi is Ultisols
which is characterized by pH 5.77, 1.92% organic carbon,
0.17% Nitrogen, 12.75 ppm Phosphorus and 0.22 me100g-1
Potassium (Halim & Rembon, 2013; Halim et al., 2015).
Various efforts based on principles of conservation and
ecofriendly natural sources to improve soil fertility of this
Ultisols were carried out. Use of mycorrhiza for improving soil
fertility is a common practice for many crops. Halim (2013)
reported that some kinds of grasses weeds were naturally
infected by mycorrhiza fungi. Mycorrhiza isolated from these
types of weed grasses had positive impact on the soil fertility.
Similar types of results was also reported from the another
research conducted by same authors (Halim et al., 2014). They
also reported that roots of broad-leaved weeds, grasses weed
and sedges weed are infected by mycorrhiza fungi.
2 Materials and Methods
2.1 Study area and Experimental setup
Present study was conducted from June to September 2014 in
net house, village Sindang Kasih, District West Ranomeeto,
South Konawe Regency, Southeast Sulawesi Province and
Laboratory of the Faculty of Forestry and Environmental
Science, Halu Oleo University Kendari, Indonesia. Plant were
grown in polybag (40 cm x 50cm) and study was conducted in
completely randomized block design (RCD) with five
treatments i.e. without mycorrhiza fungi propagules (M0),
mycorrhiza fungi propagules@ 25 g per polybag (M1),
mycorrhiza fungi propagules@ 50 g per polybag (M2),
mycorrhiza fungi propagules @ 75 g per polybag (M3) and
mycorrhiza fungi propagules@ 100 g per polybag (M4), each
treatment was replicated with 5 replications.
2.2 Preparation of planting media
The soil has been taken from the study area field, it cleared
from debris such as twigs, roots, leaves and small rocks.
Cleared soil sifted into a polybag with a weight of 10kg soil
and recommended dose basic NPK fertilizer along with
organic manure was added to each polybag. The mustard seed
sown for 7 days in media seedbed mixture of rice husk, soil,
sand, with the volume ratio 1: 0.5:1 was transferred to the
polybags. Mycorrhiza fungi isolated from the roots of Imperata
cylindrica that had previously been propagated on maize
(Halim, 2012) were transferred to the each polybags.
2.3 Observation of Variables
Isolated mycorrhiza fungi were characterized with the standard
identification key for mycorrhiza. Various growth parameters
such as plant height, number of leaves and leaf area were
measured on the intervals of each seven days which start from
the 7th days after planting and continue upto 28 days after
planting (DAP). The total leaf area was measured by using the
formula proposed by Sitompul & Guritno (1995):
L= p x l x k x j
Note: L= leaf area, P = length of leaf, l = plant fresh weight (g
plant-1
), k = the coefficient of leaf area (0.78), j = number of
leaves.
The fresh weight of the plants (g plant-1
) was measured after
harvest while the dry weight of the plant (g plant-1
) was
measured after harvesting drying plant in oven at a temperature
of 80 0C for 48 hours. Further, Ratio leaf area was measured
(cm2 g
-1) by the using formula proposed by Sumarsono (2010).
Ratio leaf area = L/ W
Whereas L = leaf area (cm2), W = dry weight the plant (g)
Shoot root ratio of the mustard plant was measured by using
the formula proposed by Gardner et al. (1991).
Shoot root ratio = shoot dry weight/ root dry weight
2.4 Percentage of the mycorrhiza fungi infection
The Observations were carried out using a dissecting
microscope at a magnification of 40X. Furthermore,
mycorrhiza fungi infection was calculated by using the formula
proposed by Brian & Schults (1980).
Where IP= the percentage of mycorrhiza fungi infection; r1=
the number of root infected examples and r2= the number of
root not infected examples
86 Halim et al
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Table 1 Effect of mycorrhiza fungi on the average height of mustard (cm) at the age 7-14, 14-21 and 21-28 DAP.
Treatment Average plant height
7-14DAP 14-21DAP 21-28DAP
without mycorrhiza fungi (M0) 3.17d 6.20
c 8.26
d
25 g mycorrhiza fungi (M1) 4.20d 8.70
b 10.35
c
50 g mycorrhiza fungi (M2) 5.58c 9.45
b 11.47
bc
75 g mycorrhiza fungi (M3) 7.06b 10.90
ab 12.40
ab
100 g mycorrhiza fungi (M4) 8.89a 12.60
a 13.47
a
SEM value 1.04 1.19 2.78
DRMT 0.05%
2 1.34 2.19 1.60
3 1.41 2.30 1.68
4 1.45 2.37 1.74
5 1.48 2.42 1.77
Here, DAP = day after planting, SEM = standard error mean, the numbers followed by the same superscript letters in the same column
are not significantly differ on DRMT 0.05%
2.5 Data Analysis
Data of each variable were observed were analyzed by
variance of analysis. If the F count is greater than the F table,
then continued with Duncan Range Multiple Test (DRMT) at
0.05% confidence level.
3 Result
3.1 Characterization of Mycorrhiza Fungi
Two species of mycorrhiza fungi viz Gigaspora sp. and
Glomus sp. were isolated from the selected weed species.
(Halim, 2009), among these Gigaspora sp. was identified by
the presence of a single brown color terminal spore. These
spores have globular or spherical shape with more than one
layer. A complementary tool in the form of bulbous suspensor
was also reported for this species. While the Glomus sp. are
characterized by the presence of single or bunch of ripe hyaline
white or brownish yellow. Spores are located on the terminal
gametangium located on the undifferentiated hyphae in a
sporocarp (Halim, 2012). Mostly these spores are formed on
the external hyphae near the root zone.
3.2 Effect of mycorrhizal application on the growth attributes
3.2.1 Plant Height
The effect mycorrhizal fungi on average plant height are
represented in table 1; results of study revealed that application
of mycorrhizal fungi increase the height of mustard plants.
This improvement in the plant height is continued upto the 21
DAP; after this plants are not showing much improvement in
height and no significant difference was reported between 21
and 28 DAP. Highest dose of mycorrhiza (100g) shows
superiority over the other treatments and 7 DAP is was 8.89cm
which reached 13.4cm at 28DAP.
Gigaspora sp. Glomus sp.
Figure 1 Spore form of Gigaspora sp and Glomus sp.
Characterization and impact of mycorrhiza fungi isolated from weed plants on the growth and yield of mustard plant (Brassica juncea L.) 87
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Journal of Experimental Biology and Agricultural Sciences
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Table 2 Effect of mycorrhizal fungi on the average number of mustard plant leaves at the age of 7- 28 DAP.
Treatment Average Leaves Number
7DAP 14DAP 21DAP 28DAP
without mycorrhiza fungi (M0) 3.00c 4.40
b 5.40
c 7.20
c
25 g mycorrhiza fungi (M1) 3.60bc
4.60b 5.80
bc 7.80
bc
50 g mycorrhiza fungi (M2) 3.40ab
4.60b 7.20
a 9.20
a
75 g mycorrhiza fungi (M3) 3.80ab
5.00ab
6.80ab
8.60ab
100 g mycorrhiza fungi (M4) 4.00a 5.60
a 7.20
a 9.20
a
SEM value 0.16 0.24 0.62 0.52
DRMT 0.05%
2 0.52 0.64 1.03 0.95
3 0.55 0.67 1.09 0.99
4 0.57 0.69 1.12 1.02
5 0.58 0.71 1.14 1.05
Here, DAP = day after planting, SEM = standard error mean, the numbers followed by the same superscript letters in the same column
are not significantly differ on DRMT 0.05%.
3.2.2 Number of Leaves
The effect mycorrhiza fungi to the average number of leaves of
mustard plants shown in Table 2. The trends of leaves numbers
are similar to plant height and it increased with the increasing
of day of planting and dose of mycorrhiza fungi. The highest
average number of leaves per mustard plant at age of 7 DAP
was 4.00 and it was reported in the treatment M4; this number
reached 9.20 per plant in the same treatment at the interval of
28DAP. At 28DAP, treatment M2 is also showing similar leaf
number and it is significantly not differ from the M4.
3.2.3 Total Leaf Area
Total leaf area was calculated by the method given by
Sitompul & Guritno (1995). The effect mycorrhiza fungi to the
total leaf area of mustard plants shown in Table 3. Total leaf
area also increased with the increasing the dose of mycorrhizal
application and days. Highest total leaf area was reported from
the treatment containing 100g mycorrhiza at 28DAP.
3.3 Fresh and dry weight of mustard Plant
The effect mycorrhiza fungi to the average fresh and dry
weight the plants are calculated on the harvesting of plants.
Average fresh and dry weights are represented in Table 4. The
value of fresh and dry weight increased with the increasing the
dose of mycorrhiza fungi application, lowest fresh and dry
weight was reported from the treatment without mycorrhiza
application (M0) while the highest plant was reported from the
highest dose of mycorrhiza fungi application (M4).
The treatment M4 is showing 37.35 and 51.58% higher fresh
and dry weight respectively as compared to the treatment
without mycorrhiza. Treatment M3 and M4 is not showing any
significant difference (DMRT = 0.05%).
Table 3 Effect of mycorrhiza fungi on the total leaf area of mustard plants at the age 7 - 28 DAP.
Treatment Total leaf area (cm)
7DAP 14 DAP 21 DAP 28 DAP
without mycorrhiza fungi (M0) 21.36c
77.75d 341.69
d 776.88
d
25 g mycorrhiza fungi (M1) 24.52c 128.11
c 462.99
cd 995.38
c
50 g mycorrhiza fungi (M2) 27.01bc
142.46c 582.07
bc 1266.39
b
75 g mycorrhiza fungi (M3) 32.72b 228.74
b 711.03
ab 1364.30
ab
100 g mycorrhiza fungi (M4) 42.86a 288.55
a 812.68
a 1532.68
a
SEM value 0.87 0.24 1.25 20.5
DMRT 0.05%
2 6.22 42.10 143.50 198.60
3 6.53 44.19 150.60 208.50
4 6.73 45.52 155.20 214.80
5 6.86 46.45 158.30 219.10
Here DAP = day after planting, SEM = standard error mean, the numbers followed by the same superscript letters in the same column are
not significantly differ on DRMT 0.05%.
88 Halim et al
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Table 4 Effect of the mycorrhiza application of the average fresh and dry weight (g plant -1
) of the mustard plant.
Treatment Fresh weight (g
plant -1
)
DMRT
(0.05%)
Dry weight (g
plant -1
)
DMRT 0.05%
without mycorrhiza fungi (M0) 71.39c 2 = 18.47 3.99
c 2 = 0.86
25 g mycorrhiza fungi (M1) 81.70bc
3 = 19.39 5.96b 3 = 0.90
50 g mycorrhiza fungi (M2) 96.32ab
4 = 19.97 6.41b 4 = 0.93
75 g mycorrhiza fungi (M3) 107.00a 5 = 20.38 7.62
a 5 = 0.95
100 g mycorrhiza fungi (M4) 113.95a 8.24
a
SEM value 5.39 0.43
Here DAP = day after planting, SEM = standard error mean, the numbers followed by the same superscript letters in the same column
are not significantly differ on DRMT 0.05%.
Table 5 Average shoot root ratio of the mustard plant under the influence of mycorrhiza application.
Treatment Shoot root ratio DRMT 0.05%
without mycorrhiza fungi (M0) 2.01c 2 = 0.64
25 g mycorrhiza fungi (M1) 2.58c 3 = 0.67
50 g mycorrhiza fungi (M2) 3.24b 4 = 0.69
75 g mycorrhiza fungi (M3) 3.61b 5 = 0.71
100 g mycorrhiza fungi (M4) 4.39a
SEM value 0.24
Here DAP = day after planting, SEM = standard error mean, the numbers followed by the same superscript letters in the same column are
not significantly differ on DRMT 0.05%.
3.4 Shoot Root Ratio
The effect mycorrhiza fungi to the average shoot root ratio of
the mustard plant shown in Table 5. The trends are similar to
the growth parameters and highest shoot root ratio was
obtained from the treatment containing 100g mycorrhiza
culture, and it was 52.21 percent higher than the polybag
without mycorrhiza. With the increasing dose of mycorrhiza,
shoot root ration also increased and a significant difference
was reported between all the tested doses.
3.5 Percentage of mycorrhiza colonization
The average percentage of mycorrhiza fungi colonization in
the mustard plant roots are listed in Table 10. Highest dose of
mycorrhiza (M4) shows the highest colonization (42%) and this
was followed by the treatment M3, M2 and M1 respectively.
Highest colonization provides higher nutrition to the mustard
plant and because of this plant shows superiority in all the
studied attributes.
Discussions
The results of research showed that the application of
mycorrhiza fungi significantly affected all the variables of
mustard plants. The possible reason of this was the availability
of sufficient nutrients which favor the plant growth. According
to the Simarmata & Herdiani (2004) biological fertilizers such
as mycorrhiza fungi can increase the availability of nutrients
for plants in marginal land of Indonesia, which in turn
increased crop production. Findings of present study are in the
agreement with the findings of these authors. Further,
Marschner & Dell (1994) stated that the infection of
mycorrhiza fungi change the growth and activity of plant roots
by the formation of mycelia on the external surface which
caused increase in the absorption of nutrients and water. These
higher nutrients increase the plant height, number of leaves and
plant weight. Similar type of growth with respect to plants
height, number of leaves and leaf area of plants was obtained
by Mayerni & Hervani (2008). These researchers reported that
mycorrhizal infection increases the metabolism of plant growth
which could mainly take place in vegetative phase.
Husin (1997) reported that by changing plant metabolic
activities, mycorrhiza fungi influence the production of growth
hormones such as auxin and gibberellins. Among these auxin
prevent the aging of plant roots, so in this condition roots can
function longer and absorption of nutrients will also higher.
While the giberelin performing the function of enlargement
and stimulate the cell division. The ability of mycorrhiza fungi
in absorption of phosphate is not only determined by the fungal
colonies in the roots and development in the soil, but also
determined by ability of external hyphae. In fact, the
percentage mycorrhiza fungi infections on plant roots are not
always comparable to effect on crop yields. Mycorrhiza fungi
infection and the effect decreases with increasing phosphate
available in the soil.
Characterization and impact of mycorrhiza fungi isolated from weed plants on the growth and yield of mustard plant (Brassica juncea L.) 89
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Table10 The average percentage of mycorrhiza fungi infection in the mustard plant roots.
Treatment Percentage mycorrhiza fungi colonization DRMT 0.05%
without mycorrhiza fungi (M0) 0 e 2 = 4.93
25 g mycorrhiza fungi (M1) 10 d 3 = 5.18
50 g mycorrhiza fungi (M2) 18 c 4 = 5.33
75 g mycorrhiza fungi (M3) 26 b 5 = 5.44
100 g mycorrhiza fungi (M4) 42 a
SEM vaue 21.64
Here DAP = day after planting, SEM = standard error mean, the numbers followed by the same superscript letters in the same column are
not significantly differ on DRMT 0.05%.
Further, Turk et al. (2006) also confirmed that mycorrhiza can
improve the availability of Phosphorus in soil that experienced
scarcity of Phosphorus. Phosphorus uptakes in plants affect the
physiological and morphological conditions of the plant which
led to increase the production of energy in the plant body and
fresh and dry weight of plant increases (Nuhamara, 1994).
These observations confirmed the finding of present study
where higher fresh and dry plant weight was obtained by the
application of mycorrhiza.
The shoot root ratio described the patterns of plants growth as
a resultant of plant responses to the environment. Though,
shoot root ratio determined by genetic factors but it is also
strongly influenced by environmental factors such as soil and
climate. Sutedjo & Kartasapoetra (1997) suggested that if one
factor has stronger influence than any other factor, the factor
will be closed off from each of the factors that have different
properties and real work to support the production of plant.
The roots which have greater absorption area will have a
chance to absorb more nutrients, therefore the plants associated
with mycorrhiza fungi will able to improve its capacity to
absorb nutrients and water. In addition, these plant has 2-4
times higher metabolic rate as compared to the plants that do
not colonized by mycorrhiza fungi (Sieverding, 1991).
Similarly, Rasouli-Sadaghiani et al. (2010) reported that the
higher dose of mycorrhiza fungi increased the uptake of
several nutrients. Results of this study confirmed that the
higher dose of mycorrhiza fungi in the planting hole caused
higher colonization of mycorrhiza fungi in plant roots.
Acknowledgements
The author would like to thank to the Ministry of National
Education, Republic of Indonesia for the financial assistance
through the scheme of National Priorities Research Grant
Master Plan for the Acceleration and Expansion of Indonesian
Economic Development 2011-2025 in 2014. The author also
thank to the Rector of Halu Oleo University and the Chairman
of the Research Institute of Halu Oleo University for providing
us moral support and space carry out this study.
Conflict of interest
Authors would hereby like to declare that there is no conflict of
interests that could possibly arise.
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Characterization and impact of mycorrhiza fungi isolated from weed plants on the growth and yield of mustard plant (Brassica juncea L.) 91
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KEYWORDS
Application protocol
Seaweed extract
Kappaphycus alvarezii
Vegetable crops
Yield and quality
ABSTRACT
The field study was conducted to develop a protocol for application of commercially manufactured bio-
stimulant (Brand name: AquaSap) from seaweed Kappaphycus alvarezii. Efficacy of the bio-stimulant
was tested at 5% through foliar application in selected important vegetable crops. 3 to 4 applications
were applied based on the crop cycle of the plant. Total 27 vegetable crops were studied during 2012 to
2015 and observed their response towards bio-stimulant applied in terms of general health of the plant,
growth, yield and quality of the vegetable produce. 11% to 52% of yield increases were observed with
improved quality in all 27 crops studied. Therefore seaweed bio-stimulants will have enormous
potential to organic vegetable production in future.
Kosalaraman Karthikeyan and Munisamy Shanmugam*
Research and Development Division, AquAgri Processing Private Limited, B5, SIPCOT Industrial Complex, Manamadurai - 630 606. Sivaganga District, Tamil Nadu, INDIA
Received – January 12, 2016; Revision – January 27, 2016; Accepted – February 20, 2016
Available Online – February 20, 2016
DOI: http://dx.doi.org/10.18006/2016.4(1).92.102
DEVELOPMENT OF A PROTOCOL FOR THE APPLICATION OF COMMERCIAL
BIO-STIMULANT MANUFACTURED FROM Kappaphycus alvarezii IN SELECTED
VEGETABLE CROPS
E-mail: [email protected] (Muniyasamy Shanmugam)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
Journal of Experimental Biology and Agricultural Sciences
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ISSN No. 2320 – 8694
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Creative Commons Attribution-NonCommercial 4.0
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1 Introduction
Seaweed personifies not only as an alternative to conventional
chemical fertilizers but also chronically used in agriculture,
horticulture, cookies, ice-cream and jelly mix (Sumkiman et
al., 2014). Further, it was well reported that seaweed extract
contain nutrient of major and minor element, vital amino acid,
essential vitamins and plant growth regulators which stimulate
the growth and quality yield of crops. Application of seaweed
liquid extract stimulate different aspects of plant like good
health, development of root system, absorption of mineral,
enlargement of shoot, increased rate of photosynthesis and
crop yield (Sridhar & Rengasamy, 2010). Seaweed liquid
extract have newly gained importance as foliar spray for lots of
crops including various variety of grasses, flowers, cereals,
vegetables and spices (Pramanick et al. 2013 & 2014).
Further, Zodape (2001) tried various modes of seaweed extract
application such as a foliar spray, application to soil and
soaking of seeds before sowing and reported that extract not
only enhances the germination of seeds but also increases
uptake of plant nutrients and gives resistance to frost and
fungal diseases.
The aqueous extracts of the alga Codium fragile was effective
in increasing root length and it is 18.0% longer than the control
in soybeans (Anisimov & Chaikina, 2014). Furthermore, Pise
& Sabale (2010) treated fenugreek with 50% of seaweed and
reported improvement in the concentration of carbohydrate,
proteins, free amino acids, polyphenols and nitrogen content
while comparing with control plants. Similarly, yield and
nutrient content value were found higher in banana when
treated with 5% of bio-stimulant (AQUASAP) of
Kappaphycus alvarezii (Karthikeyan & Shanmugam, 2014).
Vegetables are herbaceous plants and produce large amount of
biomass within short period (Chatterjee & Thirumdasu, 2014).
Vegetables are very essential to human health as they are rich
in dietary fibre and source of essential vitamins, minerals, trace
elements, vitamins and antioxidants.
In India, vegetable production was around 146.55 million tons
from an area of 8.5 million hectare during 2010-2011. The 4
major vegetables viz. potato (28.9%), tomato (11.3%), onion
(10.3%) and brinjal (8.1%) contribute 58.6% of total vegetable
production. Other important vegetables are cabbage (5.4%),
cauliflower (4.6%), okra (3.9%), peas (2.4%) and okra
contribute 73% of total world production (Vanitha et al.,
2013). The bio-stimulant manure from red seaweed K.
alvarezii is well-off in potash with other primary nutrients like
N, P, K and secondary nutrients like Cu, Zn, Fe, Mo, Mn, etc.,
in addition and to significant amount of plant growth
regulators (Zodape et al., 2009; Prasad et al., 2010;
Karthikeyan & Shanmugam, 2014). The present investigation
describes the dosage and application protocol of bio-stimulant
manufactured from K. alvarezii (AQUASAP is brand name of
AquAgri) on some selected 27 vegetables crops for yield and
quality improvement.
2 Materials and Methods
The trial was carried out at R&D plot of AquAgri Processing
Private Limited and in the farmers’ field in Manamadurai,
Sivagangai Dt., Tamil Nadu, India. (Latitude is 9º42´56´´N
and longitude 78º28´2´´E). The annual normal rainfall
received by the district is 850 mm. The experiment trial was
conducted in 8 plots with 6 m x 4m for each vegetable crop
studied. The healthy seeds were selected and sowed carefully
into the field and the trial crops were irrigated periodically and
chemical fertilizers were applied to crops as per the
recommendation of National Horticulture Board, India. Bio-
stimulant (Aquasap) was collected from the stock of AquAgri
Processing Private Limited and 5% solution was prepared and
used.
2.1 Application protocol of bio-stimulant Aquasap for
vegetable crops
Bio-stimulant (Brand name: AquaSap) manufactured from K.
alvarezii was applied to the crops tested in the present
investigation through foliar application. Three doses viz.
vegetative, pre-flowering and post flowering stages were given
to short-term plants whereas four doses were applied to long-
term crops. Table 2-6 shows the application protocol for 27
crops tested in this study. The physico-chemical and nutritive
value of the bio-stimulant (AquaSap) has been given in table 1.
2.1.1 Tomato (Solanum lycopersicum L.)
The trial on tomato (Co3 hybrid) was conducted in June 2012
(Table 2.) The seeds were sowed in nursery beds, then nursery
plants were collected after 25th day of sowing and their roots
were dipped at 0.7% of bio-stimulant Aquasap for 10min
before transplantation. The first spray was given on 10th day of
transplantation, second and third doses were sprayed on 25-30d
(pre-flowering stage) and on 45-50d (flowering stage)
respectively and last dose was applied at first picking stage
(Table 3).
2.1.2 Lady’s finger (Okra) (Abelmoschus esculentus
(L) Moench) and Brinjal (Solanum melongeana L.)
The experiment of lady’s finger (var. US 7902) and brinjal Co2
hybrid was also conducted in 2012 (Table 2). The okra seeds
were soaked in 1% of bio-stimulant for 10 min. and the soaked
seeds were sowed into the field directly. Treated seeds were
also sowed in nursery beds and nursery plants (35d old) were
collected, treated their roots with 0.7% of bio-stimulant for 10
min before transplantation. The application of bio-stimulant
through foliar was given at the vegetative stage (15-20d),
second spray at flowering stage (35-40d) and final spray was at
first fruits picking stage (50-55d) (Table 3).
93 Karthikeyan and Shanmugam
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Table 1 Physico-chemical properties and Nutritive status of Aquasap bio-stimulant from seaweed K. alvarezii.
Parameters Units Results Parameters Units Results
Physical properties of AquaSap Nutritive Value (Amino Acid )
Alanine g/100g 0.014
Organic Matter (%) gm/100g 0.65 Arginine g/100g 0.0003
Specific Gravity - 1.14 Aspartic acid g/100g 0.0019
Electrical Conductivity dSm-1
63.3 Cystine g/100g 0.0017
pH (1% solution) - 6.68 Glycine g/100g 0.065
Moisture content (%) gm/100g 94.82 Histidine g/100g 0.0007
Total Ash (%) gm/100g 4.53 Isoleucine g/100g 0.0022
Macro and Micro Nutrient contents AquaSap Leucine g/100g 0.0022
Lysine g/100g 0.019
Parameters Units Results Tryptophan g/100g 0.007
Nitrogen (N) gm/100g 0.007 Methionine g/100g 0.0007
Phosphorous (P) mg/kg 3.57 Phenylalanine g/100g 0.0028
Potash (K) gm/100g 1.50 Proline g/100g 0.053
Sodium (Na) gm/100g 0.26 Serine g/100g 0.0013
Calcium (Ca) gm/100g 0.03 Threonine g/100g 0.0006
Silica (Si) gm/100g 0.02 Tyrosine g/100g 0.0016
Chlorine (Cl) gm/100g 2.15 Valine g/100g 0.0026
Magnesium (Mg) mg/kg 0.04 Glutamic acid g/100g 0.0022
Iron (Fe) gm/100g 16.95 Nutritive Value (Vitamins)
Sulphur (S) gm/100g 0.03 Vitamin - A IU/100g 3363.44
Boron as (B) mg/kg 768 Vitamin – E IU/100g 0.21
Copper (Cu) mg/kg 1.1 Vitamin – C mg/100g 22.52
Zinc (Zn) mg/kg 2.15 Vitamin – B1 mg/100g 0.007
Manganese (Mn) mg/kg 5.93 Vitamin –B5 mg/100g 301.1
Cobalt (Co) mg/kg 0.92 Vitamin – B6 mg/100g 3170.2
2.1.3 Chillies (Capsicum annuum L. Var. annuum)
Hybrid chilli (US 612) was selected for present study and its
seeds were sowed directly into field. The seaweed bio-
stimulant was applied at vegetative stage (40-45d), at
flowering stage (90-100d) and last dose was given at first fruits
picking stage (125-130d). In the case of transplanted plant,
nurseries were created (40d old) and treated their roots at 0.7%
of bio-stimulant for 10min before transplantation. During
growing period, first dose of bio-stimulant was given at 20-25th
day of transplantation and second and last applications were
given at 60-65th day (i.e. flowering stage) and at 80-85
th day of
transplantation (Table 3) respectively.
2.1.4 Capsicum (Capsicum annuum L)
Trial on capsicum (var. Arka Mohini) was carried out in
January 2014 (Table 2). The bio-stimulant AquaSap was
applied at vegetative (30-35d), flowering stage (60-65d) and
fruits picking stage (90-95d). But in the case of transplants
raised from 40d old nurseries whose roots were treated with
0.7% of bio-stimulant for 10min before transplantation, first
dose was given at 20-25d (vegetative stage), 60-65d (flowering
stage) and at 80-85d (first fruits picking stage) day of
transplantation (Table 3).
2.1.5 Variety of Gourds
The experimental study on nine varieties of gourds, i.e., Ash
gourd (var. MAH-1), Pumpkin (Arka Chandan), Snake gourd
(Covai -951), Ridge gourd (US 66), Bottle gourd (WARAD
MGH-4), Bitter gourd (US 475), Cucumber (local variety),
Watermelon (Ankur Kashish) and Chow chow (Green Fruits)
(Table 2) was conducted during 2012 to 2014. The seeds were
soaked in 1% of bio-stimulant for 30 min. and the seeds were
sowed in the study field. The application of bio-stimulant was
given at vegetative stage (20-25d), flowering stage (60-65d)
and first fruits picking stage (80-85d). In the case of chow
chow, mature fruits were planted in the field, and bio-stimulant
was first applied at vegetative phase of 25-30 days of
plantation, pre-flowering phase (3rd
month) and final dose was
given at flowering phase (5th month) (Table 3). In the
cucumber, first spray was done at germination phase (10-15th
day), followed by second spray at 35-40th day (vegetative
stage) and final dose was applied at flowering initiation stage
(65-70d) (Table 4).
Development of a protocol for the application of commercial bio-stimulant manufactured from Kappaphycus alvarezii in selected vegetable crops. 94
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2.1.6 Cole crops, Root and Tuber vegetables
2.1.6.1 Potato (Solanum tuberosum L.)
The potato (var. Kufri Jyoti) trial was conducted in August
2013 (Table 2). Bio-stimulant AquaSap was applied at plant
establishment stage (20-25d) vegetative phase (50-55d), early
root development stage (80-85d) and last dosage was given at
maturity stage (100-105d) (Table 5).
2.1.6.2 Cabbage (Brassica oleracea var. capitata L)
Maharani- F1, a hybrid variety of cabbage was taken for trial
in January 2013 (Table 2). 40 days old nursery plant was
created and root treatment was given at 0.7% of bio-stimulant
for 10min before transplantation. Field application of bio-
stimulant was applied at plant establishment stage (10-15d),
second dose was sprayed at head initiation stage (35- 40d) and
last spray was sprayed at head development phase (70-75d)
(Table 5).
2.1.6.3 Cauliflower (Brassica oleracea var. botrytis)
In January 2013, cauliflower (var. Shobha F1) was taken for
trial (Table 2). The root of nursery plants (35d) raised was
treated with 0.7% of bio-stimulant for 10min and transplanted.
During crop cycle, first spray of bio-stimulant aquasap was
given at plant establishment stage (10-15d), the second dose at
curd initiation stage (25-30d) and last dose was given at curd
development stage (45-50d) (Table 5).
2.1.6.4 Beetroot (Beta vulgaris L) and Carrot (Daucus
carota L)
The studies on beetroot (Vally Queen) as well as carrot (Pusa
Kesar) were conducted in 2013 and bio-stimulant Aquasap was
applied at vegetative stage (25-30d), early root development
stage (55- 60d) and root maturity stage (80 -85d) (Table 5).
2.1.6.5 Radish (Raphanus sativus L) and Knol-Khol (Brassica
caulorapa)
Radish (Roshni) and knol-khol (Early White) trial was
undertaken in January 2013. The bio-stimulant was given at
10-15th (vegetative stage), 25-30
th (early root development
stage) and at 40 - 45th day of sowing (root maturity stage)
(Table 5).
2.1.7 Other vegetable crops
2.1.7.1 Lima Bean (Phaseolus lunatus L) and Dolichos Bean
(Lab lab purpureus var. typicus)
The experiment on Lima (Co2) and Dolichos (Ankur Goldy)
beans were conducted during 2012. The seeds were soaked in
1% of bio-stimulant for 10min then sowed into the field.
During crop period, three spray of bio-stimulant were given
viz. at vegetative phase (20-25d), flowering stage (40-45d),
pod formation stage (60-65d) and last spray was given at first
picking stage (80-85th day of sowing) (Table 6).
2.1.7.2 Soybean (Glycine max (L.) Marr.)
The experiment on soybean (JSS 355) was conducted in July,
2012. The seeds were soaked in 1% of bio-stimulant for
10min and then the seeds were carefully sowed in the field.
The crop was applied with bio-stimulant Aquasap for four
times viz. at 20-25d, 40-45d, 60-65d and at 80-85th day of
sowing (Table 6).
2.1.7.3 Moringa (Moringa oleifera L.)
The efficacy trial of AquaSap on drumstick (PKM-1) was
conducted in 2012 (Table 2). The seeds were soaked in 1% of
bio-stimulant for 10min and during crop period bio-stimulant
aquasap was applied at nurseries stage (25-30th), pre-flowering
phase (3rd
month), flowering phase (4th month), and at fruits
development stage (5th month of plantation) (Table 6).
2.1.7.4 Small Onion (Allium cepa var. aggregatum)
Trial on small onion (var. Co-ON-5) was conducted in June
2013. The seaweed bio-stimulant at 5% was sprayed as foliar
application at establishment stage (10-15d), vegetative stage
(25-30d), bulb formation stage (40-45d) and bulb development
stage (60-65d) as shown in Table 6.
2.1.7.5 Bellary Onion (Allium cepa var. cepa)
Effect of bio-stimulant AquaSap on Bellary onion (var. Prema-
178) was studied in June 2013. The application of 5% bio-
stimulant was given on 10-15th (sowing establishment stage),
35-40th (vegetative stage), 60-65
th (bulb formation stage) 75-
80th (bulb development stage) day of sowing (Table 6).
3 Results and Discussion
All vegetable crops investigated in the present study responded
well at 5% dose of bio-stimulant Aquasap (from seaweed of
K. alvarezii). Highest yield was found in moringa with
52.83% over control followed by lady’s finger, chillies,
cabbage, garden lab lab, bellary onion, small onion, ash gourd,
and snake gourd with 45.84%, 37.30%, 36.74%, 33.03%,
32.53%, 30.74%, 30.15%, and 30.02% respectively with
improved quality (Table 2). Improved yield and quality in
crops applied with seaweed liquid fertilizers have been well
documented (Khan et al., 2009). Zodape et al. (2008) had
observed that okra yielded 20.94% more over control with
application of 2.5% extract of K. alvarezii and in tomato the
increment when treated with 5% extract was 60.89% Zodape et
al., (2011). The yield of brinjal with Eucheuma seaweed
powder increased marginally higher to 41.1% (Eswaran et al.,
2005). Similar kind of result with eggplant was reported when
it treated with 2% extract of Ascophyllum nodosum (Bozorgi,
2012). Babu & Rengasamy (2012) observed that when chillies
were treated with 1% and 2% of SLF of K. alvarezii, it
95 Karthikeyan and Shanmugam
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Journal of Experimental Biology and Agricultural Sciences
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increased the crop yield to 23% and 15% respectively when
compare to control.
The high yield was also observed in ash gourds with 30.15%
over control followed by pumpkin, snake gourd, ridge gourd,
bottle gourd, bitter gourd, cucumber, watermelon and chow
chow with 28.56%, 30.02%, 11.98%, 28.03%, 26.64%,
24.19%, 25.89%, and 17.34% respectively (Table 2). Ahmed
& Shalaby (2012) recommend that liquid extract of E.
intestinelis (green alga), G. pectinutum (red alga) or
commercial seaweed liquid extract (Algreen) in addition to
manure is suitable product for better vegetative growth and
yield of cucumber plants. The seaweed extract of Ascophyllum
nodosum (3g/l) applied on watermelon plant, increased the
fresh weight, fruits diameter and peel thickness than control
plant (Abdel-Mawgoud et al., 2010).
Higher crop yields were observed in cabbage (36.74%),
cauliflower (29.61%), beetroot (28.84%), knol-khol (28.80%),
radish (26.08%), potato (23.90%) and carrot (14.21%) when
compared to control plants (Table 2). The seaweed extracts
powder Alga 600 and Seaforce-2 when applied on potato; it
increased the dry tuber weight to 14.67% when compared with
control (Sarhan, 2011). Abetz & Young (1983) observed that
the yield and size of cauliflower increased when treated with A.
nodosum extract.
The yield of treated plants in moringa, dolichos bean, bellary
onion, small onion, lima bean and soybean were 52.83%,
33.03%, 32.53%, 30.74%, 25.38% and 22.10% respectively
(Table 2). Soybean treated with extract of Kappaphycus at
15% and 12.5% showed highest grain yield of 57% and 46%
respectively compared to the control and maximum straw yield
was also found with treatment of 15% extract (Rathore et al.,
2009). Similar kind of result in onion bulb (22.0%) when
treated with Eucheuma seaweed powder (Eswaran et al., 2005)
and high yield with improved quality of onion was found when
treated with extract of A. nodosum (Dogra & Mandradia,
2012).
Table 2 Effect of bio-stimulant from seaweed K. alvarezii on yield of some vegetable crops.
Cultivar name Variety name Plantation type Date of plantation Yield increase over
control (%)
Tomato Co3 Hybrid Seeds 03.06.12 20.94
Lady’s finger US 7902 Hybrid Seeds 22.05.12 45.84
Brinjal Co2 Hybrid Seeds 03.06.12 24.53
Chillies US 612 Hybrid Seeds 01.01.14 37.30
Capsicum ARKA MOHINI Seeds 01.01.14 29.28
Ash gourd MAH-1 Hybrid Seeds 12.12.14 30.15
Pumpkin ARKA CHANDAN Seeds 12.12.14 28.56
Snake gourd COVAI 951 F1 Hybrid Seeds 20.07.12 30.02
Ridge gourd US 66 Hybrid Seeds 20.07.12 11.98
Bottle gourd WARAD MGH-4 Seeds 20.07.12 28.03
Bitter gourd US 475 Hybrid Seeds 20.07.12 26.64
Cucumber Local Seeds 25.12.13 24.19
Watermelon ANKUR KASHISH Hybrid Seeds 25.12.13 25.89
Chow-chow Green fruits Fully matured fruits 15.08.13 17.34
Potato KUFRI JYOTI Seeds 15.08.13 23.90
Cabbage MAHARANI- F1 Seeds 09.01.13 36.74
Cauliflower SHOBHA -F1 Seeds 09.01.13 29.61
Beetroot VALLY QUEEN Seeds 18.01.13 28.84
Carrot PUSA KESAR Seeds 15.08.13 14.21
Radish ROSHNI Seeds 18.01.13 26.08
Lima Bean Co2 Seeds 17.07.12 25.38
Doli Chos Bean ANKUR GOLDY Seeds 17.07.12 33.03
Soybean JSS 355 Seeds 17.07.12 22.10
Moringa PKM-1 Seeds 02.05.12 52.83
Small onion CO-ON-5 Seeds 15.06.13 30.74
Bellary onion PREMA - 178 Seeds 15.06.13 32.53
Knol-khol EARLY WHITE Seeds 18.01.13 28.80
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Figure 1 Some of the vegetable crops studied in the present investigation with their vegetable yield
97 Karthikeyan and Shanmugam
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Table 3 Dosage and application protocol of seaweed bio-stimulant used for home garden vegetable crops.
Crop name Root dip I Dose II Dose III Dose TBS
Tomato b Root of nurseries was dipped
in 0.7% of bio-stimulant for
10min before transplantation.
10th day (After
transplantation)
25-30th day
(Pre-flowering
stage)
45-50th day
(Flowering phase)
21
(1+5+5+5+5)
Lady’s finger c
(Okra)
- 15-20th day
(Germination stage)
35-40th day
(Flowering
stage)
50-55th day (First
fruits picking
stage)
16
(1+5+5+5)
Brinjal Root of nurseries was dipped
in 0.7% of bio-stimulant for
10min before transplantation.
15-20th day
(Germination stage)
35-40th day
(Flowering
stage)
50-55th day (First
fruits picking
stage)
16
(1+5+5+5)
Chillies Sowing 40-45th day
(Vegetative stage)
95-100th day
(Flowering
stage)
125-130th day
(Fruits picking
stage)
15
(5+5+5)
Transplantation: Root of
nurseries was dipped in 0.7%
of bio-stimulant for 10min
before transplantation.
20-25th day (Days
after
transplantation)
60-65th day
(Flowering
stage)
80-85th day
(First fruits
picking stage)
16
(1+5+5+5)
Capsicum
(Sweet pepper
/ Bell pepper)
Sowing 30-35th day
(Vegetative stage)
60-65th day
(Flowering
stage)
90-95th day
(Fruits picking
stage)
15
(5+5+5)
Transplantation: Root of
nurseries is dipped in 0.7% of
bio-stimulant for 10min before
transplantation.
20-25th day (Days
after
Transplantation)
60-65th day
(Flowering
stage)
80-85th day
(First fruits
picking stage)
16
(1+5+5+5)
a Recommended dosage of bio-stimulant: 5%;
b IV dose at 75-80th day (Picking phase);
c Seed treatment; Seeds were soaked for 10min
in 1% of bio-stimulant before sowing, TBS - Total bio-stimulant required Per acre (L).
3.1 Effect on plant disease control
Twenty seven vegetable crops studied in the present
investigation looked healthy and generally free from disease as
compared to their control plants. Extract of seaweed have been
reported to increase resistance of plant against pest and
diseases, increase plant growth and quality yield (Jolivet et al.,
1991; Verkleij, 1992; Pardee et al., 2004; Hong et al., 2007;
Jeyaraj et al., 2008). Similarly, Sultana et al. (2011) had
reported that number of liquid seaweed extract found to control
root rotting fungi like Rhizoctonia solani, Macrophomina
phaseolina, Fusarium species and root kot nematode
(Meloidogyne spp.) on a variety of crops. The resistance to
frost and fungal disease were reported when seaweed extract
was applied to some crops (Zodape, 2001). Ara et al. (1996)
had observed that extract of Sargassum spp. controlled the root
rot disease in sunflower plant. Seaweed fertilizer was found to
boost the resistibility adjacent to disease and in addition to
reduce the insect attack (Zahid, 1999). Dogra & Mandradia
(2012) had found that extract of A. nodosum significantly
reduced the downy mildew severity over control in onion plant
and it had also been reported that seaweed extract of
Asparagopsis taxiformis found to act against phytopathogens
(Manilal et al., 2009). Lynn (1972) had observed that seaweed
extract of A. nodosum protected Capsicum annuum and sweet
pepper from stress to frost, microbial diseases and insect attack
and increased the shelf life of fruits and better seed
germination.
3.2 Effect of seed Treatment
Seed and root treatment had improved the viability of plantlets
and grow vigorously as compared to control plants in the
present study and it is in agreement with the literatures reports.
The introductory soaking of Triticum aestivun seeds in 20%
extracts of Sargassum wightii for 24 hrs gave an 11% increase
in seed germination, a 63% enhance in number of lateral roots
and 46% increase in shoot length in comparing to control
(Kumar & Sahoo, 2011). 100% seed germination was observed
in lowest concentration of SLF in black gram (Venkataraman
Kumar et al., 1993) and SLF promote the seed germination as
well as yield of the vegetable crops (Narasimha Rao & Reshmi
Chatterjee, 2014). Treatment at 0.05% of concentrated extract
of Laminaria digitata on Plantago lanceolata, Trifolium
repens and Avena strigosa had given higher germination
percentage (Thorsen et al., 2010).
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Table 4 Dosage and application protocol of seaweed bio-stimulant used for gourds vegetable crops.
Crop name Seed treatment I Dose II Dose III Dose TBS
Ash gourd Seeds were soaked for 30min in 1% of bio-stimulant
and incubated it for 6 days for before sowing
20-25th day
(Vegetative stage)
60-65th day (Flowering
stage)
80-85th day
(Picking stage)
16
(1+5+5+5)
Pumpkin Seeds were soaked for 30min in 1% of bio-stimulant
and incubate it for 6 days for before sowing
20-25th day
(Vegetative stage)
60-65th day (Flowering
stage)
80-85th day
(Picking stage)
16
(1+5+5+5)
Snake gourd Seeds were soaked for 30min in 1% of bio-stimulant
before sowing
20-25th day
(Vegetative stage)
60-65th day (Flowering
stage)
80-85th day
(Picking stage)
16
(1+5+5+5)
Ridge gourd / Ribbed
gourd
Seeds were soaked for 30min in 1% of bio-stimulant
before sowing
20-25th day
(Vegetative stage)
60-65th day (Flowering
stage)
80-85th day
(Picking stage)
16
(1+5+5+5)
Bottle gourd Seeds were soaked for 30min in 1% of bio-stimulant
before sowing
20-25th day
(Vegetative stage)
60-65th day (Flowering
stage)
80-85th day
(Picking stage)
16
(1+5+5+5)
Bitter gourd Seeds were soaked for 30min in 1% of bio-stimulant
before sowing
20-25th day
(Vegetative stage)
60-65th day (Flowering
stage)
80-85th day
(Picking stage)
16
(1+5+5+5)
Cucumber Seeds were soaked for 30min in 1% of bio-stimulant
before sowing
10th day (Germination
phase)
35-40th day
(Vegetative stage)
65-70th day
(Flowering initiation
to first picking stage)
16
(1+5+5+5)
Watermelon Seeds were soaked for 30min in 1% of bio-stimulant
before sowing
20-25th day
(Vegetative stage)
60-65th day (Flowering
stage)
80-85th day
(Picking stage)
16
(1+5+5+5) a Recommended dosage of bio-stimulant 5%, TBS - Total bio-stimulant per acre (Lit),
Table 5 Dosage and application protocol of seaweed bio-stimulant used for cole, root and tuber vegetable crops.
Crop name I Dose II Dose III Dose TBS
Chow chow
(Chayote)
25 - 30th day (Vegetative phase) 3rd month (Pre-flowering phase) 5th month (Flowering phase) 15 (5+5+5)
Potato b 20-25th day (Plant establishment stage) 50-55th day (Vegetative phase) 80-85th day (Early root development Phase) 20 (5+5+5+5)
Cabbage c 10-15th day (Plant establishment stage) 35-40th day (Head initiation stage) 70-75th day (Head development phase) 16 (1+5+5+5)
Cauliflower c 10-15th day (Plant establishment stage) 25-30th day (Curd initiation stage) 45-50th day (Curd development phase) 16 (1+5+5+5)
Beetroot 25-30th day (Vegetative stage) 55-60th day (Early root development stage) 80-85th day (Maturity stage) 16 (1+5+5+5)
Carrot 25-30th day (Vegetative stage) 55-60th day (Early root development stage) 80-85th day (Maturity stage) 15 (5+5+5)
Radish 10-15th day (Vegetative phase) 25-30th day (Early root development stage) 40-45th day (Maturity stage) 15 (5+5+5)
Knol-khol 10-15th day (Vegetative phase) 25-30th day (Early root development stage) 40-45th day (Maturity stage) 15 (5+5+5) a Recommended dosage of bio-stimulant 5%,
b IV Dose at 100-105
th day (Root maturity stage),
c Root dip: Transplantation: Root of nurseries was dipped in 0.7% of bio-stimulant for
10min before transplantation, TBS - Total bio-stimulant per acre (Lit).
99 Karthikeyan and Shanmugam
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Journal of Experimental Biology and Agricultural Sciences
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3.3 Effect of foliar application
Seaweed extract applied as foliar application found to
significantly enhance the yield, growth and quality of crops
(Pramanick et al., 2013). Seaweed liquid extract have gained
importance to different range of crops like cereals, grasses,
vegetables, species and flowers when applied through foliar
application (Crouch & Van Staden, 1992). Seaweed extract is
important to find out the organic sources for seed and foliar
treatments for effective maintenance of vigour and viability
(Dwivedi et al., 2014). The maximum yield of tomato (Zodape
et al., 2011) and banana (Karthikeyan & Shanmugam, 2014)
had been observed when using foliar application of K. alvarezii
extract. Similar kind of result was observed by Pramanick et
al., (2013) that the foliar application of seaweed sap improved
the nutrient uptake capacity of crops.
In the present investigation, it was also observed that emerging
of first flower appeared in all treated plants at least 5-10d
earlier than control and similar kind of observation had been
recorded in the literature. Dwivedi et al., (2014) reported that
seaweed extracts not only increase the vegetative growth of the
plant but it also triggers the early flowering, fruiting in crops
and ultimately on seed yields. Seaweed extracts are
ecologically safe, non-polluting, non-toxic, and harmless to
human beings, animals and birds (Dhargalkar & Pereira, 2005).
In addition to reducing the cost of inorganic fertilizers,
application of seaweed bio-stimulants improves soil health,
enhances the yield and quality of produce in organic vegetables
production thereby increasing the domestic and international
market (Chatterjee & Thirumdasu, 2014).
Conclusions
It can be concluded from the present study that 27 vegetable
crops tested had responded well to bio-stimulant (Aquasap)
manufactured from seaweed K. alvarezii. The average yield
increased from 11.98% to 45.84% with much improved
vegetable quality. Therefore, the protocol used in this study
will be useful to the farmers to produce organic vegetables.
Acknowledgement
The authors are very grateful to Mr. Abhiram Seth, MD, Mr.
Arun Patnaik, CEO and Mr. Tanmaye Seth of AquAgri
Processing Private Limited for their constant encouragement,
guidance and allocation of budget to carry out the present
investigations. The authors also wish to thank farmers who
agreed to carry out and monitor the trials in their farm.
Conflict of interest
Authors would hereby like to declare that there is no conflict of
interests that could possibly arise.
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KEYWORDS
Anti-QS
Pseudomonas aeruginosa
Extract
Chromobacterviolaceum
CV026
Violacein
ABSTRACT
Quorum sensing (QS) regulates various activities of bacteria such as biofilm forming, virulence factors,
swarming, and pigment production. Bacterium Chromobacterium violaceum produced violacein has also
been regulated by quorum sensing system. The aim of this study was to evaluate the QS inhibition
activity buviolaceum produced by the extract of Pseudomonas aeruginosa isolated from root of
Vetiveria zizanioides. P. aeruginosa cultured on King’s B agar, then was extracted using ethyl acetate as
solvent. The extract was used to test anti-QS properties on C. violaceum CV026 at different
concentration viz 0.0 mg/mL (control), 2.5 mg/mL, 3.0 mg/mL and 3.5 mg/mL. Violacein content of
culture was measured by a spectrophotometer at a wavelength of 585 nm. The extract at 2.5, 3.0, and 3.5
mg/mL concentration had a significant effect on the reduction of violacein production by 31.6 %, 35.8
% and 70.3 %, respectively. While using an extract at the same concentration level there was no
negative effect on the number of C. violaceum CV026 cells found. The results of study suggest that
among the various tested concentrations, 3.5 mg/mL extract inhibits QS in C. violaceum CV026 via
violacein production. Thus, the extract of P. aeruginosa has a very high potential to develop anti-QS.
Any Fitriani*, Dwi Putri Ayuningtyas and Kusnadi
Department of Biology Education, Indonesia University of Education, 40154, Indonesia
Received – January 02, 2016; Revision – January 27, 2016; Accepted – February 20, 2016
Available Online – February 20, 2016
DOI: http://dx.doi.org/10.18006/2016.4(1).103.108
INHIBITION OF QUORUM SENSING IN Chromobacterium violaceum CV026 BY
VIOLACEIN PRODUCED BY Pseudomonas aeruginosa
E-mail: [email protected] (Any Fitriani)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
Journal of Experimental Biology and Agricultural Sciences
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ISSN No. 2320 – 8694
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1 Introduction
Quorum sensing (QS) is a cell to cell communication
mechanism that allows bacteria to control gene expression in
order to respond to the cell density. Cell density can stimulate
synthesis of small molecules (autoinducers) and QS regulates
many activities such as bioluminescence, biofilm formation,
virulence factor, and swarming (Defoirt et al., 2013). Anti-QS
is a phenomenon of cell-cell communication related to
molecules as intermediate. Molecules as an anti-QS agent
could replace an inducer molecule which is responsible for the
induction of protein expression to produce a vilurent agent.
These anti-QS molecules can be used as a medicine.
C. violaceum is Gram-negative bacteria found in nature and
that causes infections in human and animals. This bacterium
can cause septicemia and abscess in lungs and in the liver
(Petrilo et al., 1984). QS in C. violaceum regulates violacein
pigment production, antibiotic, hydrogen cyanide and some
enzymes. C. violaceum has many genes involved in violacein
production such as vioD, vioC, vioA genes which is arranged
in an operon system mediated by N-Acyl Homoserine Lactone
(AHL) (August et al., 2000). QS plays an important role in
determining virulence factors and it has lead scientists to find a
new target in developing treatment for disease caused by
bacterial infections (Vasari et al., 2013). Actinobacteria,
Firmicutes, Cyanobacteria, Bacteroidetes and Proteobacteria
produce anti-QS enzymes (Kalia, 2013). Noncognate AHLs as
intermadiates of AHL biosynthetic pathway, a dicyclic
peptides, produced by bacteria as anti-QS or Quorum
Quenching (QQ) molecules (Bauer & Robinson, 2002).
Medicinal plants have some endophytic bacteria which
produces secondary metabolites which work as antimicrobial
agents (Strobel, 2003). Nowadays, endophytes are a source for
novel natural products in modern medicine, industry and
agriculture (Yu et al., 2010). Most novel natural products
possesing antimicrobial activities have been isolated from
endophytes.
Endophytic microbes have been isolated from various plant
tissues such as roots, leaves and stems. Fitriani et al. (2013)
have isolated and characterized 17 isolates from the root of
Vetiveria zizanioides on Luria Bertani agar media. Among
these 5 isolates have been identified with polyketide synthase
gene by polymerase chain reaction analysis. Based on 16S
rRNA analysis, one of them is Pseudomonas aeruginosa
(Fitriani et al., 2013). P. aeruginosa is Gram-negative, aerobic
and rod shaped bacteria belonging to the family
Pseudomonadaceae. Further, Allu et al. (2014) isolated and
characterized endophytic P. aeruginosa from red fruit pepper.
Antimicrobial properties of the isolated bacterial strain were
characterized against fungal pathogen Colletotrichum. Based
on the study, biocidal properties of the P. aeruginosa were
established and it was also suggested that isolated bacterium
could grow in an artificial medium. The aim of this study was
to evaluate the QS inhibition activities in term of violaceum
production inhibition by the extract of P. aeruginosa isolated
from root of V. zizanioides.
2 Materials and Methods
2.1 Preparation of bacterial culture
C. violaceum CV026 was obtained from Research Centre
Microbial Diversity, Bogor Agricultural University, Indonesia,
while the P. aeruginosa was isolated from the root of V.
zizanioides. Isolated P. aeruginosa was maintained on the
King’s B agar (Pepton 2.0%; KH2PO4 0.15%; MgSO4 0.15%;
glycerol (85%) 1.5% (v/v) and 2.0% Bacto agar (Difco, Spark,
USA) at 37oC. The culture was rejuvenated after every two
weeks. While C. violaceum CV026 was cultured in Luria
Bertani (LB) agar and incubated at 27oC. Culture was
rejuvenated for the interval of every 4 days. Before the
treatment, culture was inoculated to LB broth and incubated at
27oC for 18-24 h in water bath and shaker.
2.2 Extraction of Endophytic P. aeruginosa
Extraction of P. aeruginosa was carried out by the method
described by Niyaz Ahamed (2012) with some modification.
Briefly, P. aeruginosa were cultured in 10 mL of King’s B
agar (Pepton 2.0%; KH2PO4 0.15%; MgSO4 0.15%); glycerol
(85.0%) 1.5% (v/v); Bacto agar 2.0% (Difco, Spark, USA)
broth with 37oC in temperature and 120 rev/min of shaking for
24 hours. The overnight culture was then inoculated into 90
mL of the same medium and condition. After their stationary
phase, cultures were moved into centrifuge tube and
centrifuged at 10000 rev/min for 10 minutes. Supernatants
were then moved into separating flask and added by ethyl
acetate (Merck, New York, USA) (1:1 v/v). Separating tube
was hand-shaken constantly for about 15 minutes and left for
20 minutes. Then the upper middle layer that formed in the
contained organic matter was taken. Extract was concentrated
by vacuum evaporator with 50oC in temperature.
2.3 Anti-QS assay against C. violaceum CV026
Analysis of the anti-QS assay of P. aeruginosa extract was
conducted as reported by Krishnan et al. (2012) with
modification. One colony of C. violaceum CV026 was
inoculated in a 50 mL LB broth medium and incubated for 18-
24 h at 27oC with 110 rev/min agitations. Four mL of culture
(OD600=1.2) mixed with 20 mL LB (10.0 g/L Triptone, 5.0 g/L
Yeast Extract, 5.0 g/L NaCl) (Difco, Spark, USA) molted agar.
N-hexanoyl-L-homoserine-lactone (C6-HSL) (Sigma, St.
Louis, USA) dissolved in DMSO 100%, was also added to
agar with 1.2 μg/mL final concentration. The agar was mixed
and poured into a Petri dish and wells were made in the center
of the solidified agar plate. Three replicates were then made. A
40 µL of P. aeruginosa extract at 0.0, 2.5, 3.0, 3.5 mg/mL
concentration was put into the well, respectively. The plates
were kept in the incubator for 18-24 h at 27 oC and checked for
inhibition of the violacein.
104 Fitriani et al
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Table 1 Culture composition for each flask related violacein quantification.
Treatment Culture composition Volume Final Concentration Total Volume
Control +
LB medium 1.998 mL - 2 mL
CVO26 (OD600 0.1) 1.1857 mL 1 x 108 CFU/mL
HSL (1 mg/mL) 2.4 µL 0.12 µL/mL
DMSO 1% 140 µL 0.07 % (v/v)
Control - LB Medium 1998 mL - 2 mL
CVO26 (OD600 0.1) 1.860 mL 1 x 108 CFU/mL
DMSO 1% 140 µL 0.07% (v/v)
Extract LB Medium 1.998 mL - 2 mL
CVO26 (OD600 0.1) 1.857 mL 1 x 108 CFU/mL
HSL (1 mg/mL) 2.4 µL 0.12 µL/mL
Extract1 140 µL 0.0; 2.5; 3.0; 3.5 mg/mL
2.4 Violacein Quantification
Violacein production was analyzed by using
spectrophotometry as described by Choo et al. (2005). Table 1
showed composition medium for each flask. One mL culture
from each flask was centrifuged at 13000 rev/min for 5 min.
The supernatant was discarded while the pellet was washed 2
times using buffer phosphat. One mL DMSO was mixed with
the pellet and vortexed vigorously for 30s until the violacein
dissolved completely. The cultures were then centrifuged at
13000 rev/min for 10 min. The absorbance of supernatant was
read using the spectrophotometer (585 nm) to measure of
violacein concentration.
2.5 Analysis of C. violaceum CV026 Cell Viability
The viability of C. violaceum CV026 cell was assessed by a
total plate count (TPC). One hundred mL of C. violacein
CV026 culture with P. aeruginosa extract was centrifuged at
13000 rev/min for 10 min to remove remaining extract in the
culture. Later on the pellets were washed 2 times in 100 mL
PO4-2
and excess of P. aeruginosa extract was discarded. The
culture was added to 100 mL Muller Hinton Broth (MHB).
One mL of diluted culture to factors of 10-1
– 10-8
and one mL
of culture from factors 10-6
– 10-8
pour into Muller Hinton
Agar (MHA). The plates were incubated at 27oC for 18-24 h.
The total of viable bacteria was then counted (Choo et al.,
2005).
2.6 Antibacterial Assay
An antimicrobial assay was analyzed against C. violacein
CV026 using the total plate count (TPC) procedure. One mL
culture was serially diluted to factors of 10-1
– 10-8
and pourn
into an MHA medium. The mixture was then left to be
solidified and incubated at 27oC for 18-24 hours. The total
viable bacterial cell was then counted. To ensure this test, a
paper disc diffusion assay was also taken. 100 µL overnight
culture of C. violaceum CV026 (OD600=0.1) was spread on
MHA. Paper discs containing extracts with current
concentrations (0.0, 2.5, 3.0, 3.5 mg/mL) were loaded onto the
plate. Plates were incubated in 27oC for 24 hours. Zone of
inhibition around the disc was then observed (Sasidharan et al.,
2011).
3 Results and Discussion
Reduction in violacein productions in C. violaceum CV026 are
concentration dependent and reduced with the increasing P.
aeruginosa extract concentration. Highest concentration of P.
aeruginosa extract (3.5mg/ml) resulting in lower production of
violacein as shown in Figure 1. P. aeruginosa extract could
have influenced the mechanism of QS in C. violaceum through
decreasing violacein production. The extract could have also
interfered autoinducer production or interferred with the
expression of the gene.
Figure 1 Decreasing violacein production by P. aeruginosa
extract
Table 2 shows the result of quantification of violacein
production in the presence of P. aeruginosa extract. Violacein
production by cultures in the presence of P. aeruginosa extract
was significantly different than the culture without P.
aeruginosa extract (control). Highest inhibition in the violacein
production was reported at the highest concentration (3.5
mg/mL).
Inhibition of Quorum sensing in Chromobacterium violaceum CV026 by Violacein produced by Pseudomonas aeruginosa. 105
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Table 2 Decreasing Total Violacein production by Pseudomonas aeruginosa Extract using Spectrophotometer.
Absorbance 585 ± SD
2.5 mg/mL 3.0 mg/mL 3.5 mg/mL
E+CV+C6-HSL 0.995 ± 0.17b 0.488 ± 0.1
c 0.132 ± 0.019
d
Control (CV+C6-HSL) 1.23 ± 0.08a
Control (CV- C6-HSL) 0.0285 ± 0.002e
Statistical analysis using Mann-Whitney U test; Different superscripts shows a significant difference (P < 0.05); E:Extract; CV:
Chromobacterium violaceum; HSL: Homo Serine Lactone
According to Kalia & Pirohit (2011) violacein production
might have reduced because of the activity of gene producing
QS signal which can either inhibit or reduce violacein
production. They also reported that structure of the signal was
disrupted and the receptor sites with antagonist signal
analogues were blocked. Heulier et al. (2006) suggested that P.
aeruginosa has N-(3-oxo-dodecanoyl)-homoserine lactone (3-
oxo-C12-HSL) and N-butanoyl-homoserine lactone (C4-HSL).
They regulate the expression of a lot of genes in accordance
with the induction of the transcription of lasI and rhlI, as
autoinducers.
Figure 2 Viable cell of C. violaceum CV026 in the presence of
P. aeruginosa extract
Table 3 shows total population of C. violaceum (log CFU/mL)
in culture with extracts and controls. Total C. violaceum
CV026 population did not show any significant difference in
media with addition 0.0, 2.5, 3.0 and 3.5 mg/ml. Results of the
study reveales that P. aeruginosa extract in media did not
influence the viable cells and that the extract did not cause cell
death.
The comparison of total bacteria also can be observed from
figure 2. The decreasing violacein was not followed by
decreasing of total viable bacteria. Meanwhile, antibacterial
assay which carried by disc diffusion method, showed a similar
result that P. aeruginosa had no inhibitory activity against C.
violaceum CV026. The result of these assays indicates that
extract of P. aeruginosa has potency as anti-QS in C.
violaceum.
GC-MS analysis had been carried and revealed that the extracts
of P. aeruginosa have potential as anti-QS compounds.
According to Pratiwi (2013) P. aeruginosa extract contains 3-
(1- phenyl - 2,3dihydro - 1H - isoindol - 2 -yl) propan-1-ol and
1H-Isoindole-1,3(2H)-dithione. Both compounds are indole
derivatives and similar type of indole derivatives had been
isolated from Escherichia coli by Li & Young (2013) and
established anti-QS activity against C. violaceum. Similarly,
Romano et al. (2014) reported the mechanism of this
compound in inhibiting quorum sensing by inhibiting the
activity of vioA gene which is one of many genes contained in
vioABCD operon that is very crucial for violacein production
in C. violaceum. Similar research showed that endophytic
fungus Penicillium isolated from the stem of the milk thistle
(Sylibum marianum) produces polyhydroxy anthraquinones as
quorum sensing inhibitor (Figueroa et al., 2014).
Table 3 Antimicrobial Assay Against C. violaceum CV026
Total viable bacteria (Log CFU/mL ± SD )
2.5 mg/mL 3.0 mg/mL 3.5 mg/mL
E+CV026+C6-HSL 8.86 ± 0.16a 8.81 ± 0.41
a 8.65 ± 0.32
a
Control (C6-HSL) 9.18 ± 0.028a
Control (-C6-HSL) 9.11 ± 0.073a
Statistical analysis by Duncan test; Different superscripts shows a significant difference (P < 0.05); E - Extract; CV: Chromobacter
violaceum; HSL: Homo Serine Lactone
106 Fitriani et al
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Overall, this study shows that P. aeruginosa isolated from the
root of V. zizanioides produces secondary metabolites which
has anti-QS properties. Furthermore, P. aeruginosa extract
could inhibit violacein production in C. violaceum culture
without killing the cell. Further research will purify the extract
to get a single compound and be analyzed as an anti-QS
compound.
Acknowledgements
The authors are grateful for the Indonesia University of
Education, Bandung, Indonesia for their financial assistance
for this research experiment.
Conflict of Interest
Authors would hereby like to declare that there is no conflict of
interests that could possibly arise.
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Yu H, Zhang L, Li L, Zheng C, Guo L, Li W, Sun P, Qin L
(2010) Recent development and future prospects of
antimicrobial metabolites produced by endophytes.
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doi:10.1016/j.micres.2009.11.009.
108 Fitriani et al
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KEYWORDS
Fish cages
Taal Lake
Physico-chemical
characteristics
Water quality
Aquaculture
ABSTRACT
Aquaculture activities are often blamed for the degradation of water quality of aquatic ecosystem.
Present study was conducted to determine the water quality of Taal Lake at two different study sites viz.
one under intense fish cage farming activities and the other without aquaculture activities. The study
aims to assess the effect of aquaculture activities on selected water quality parameters, which include
transparency, temperature, pH, nitrates, phosphates, salinity, total dissolved solids (TDS) and dissolve
oxygen (DO). The study was conducted over a ten-month period in 2013-2014. Results of the study
revealed no significant differences in water temperature, pH, salinity, transparency and DO between the
aquaculture and non-aquaculture sites of the lake, although DO and transparency were consistently
lower in the aquaculture sampling stations throughout the 10-month sampling period. DO dipped to
critical level (<4 ppm) for aquatic organisms in the months of January and February. Nitrates,
phosphates and TDS were significantly higher in the area with fish cage farming activities as compared
to the non aquaculture site. Further, the study also reports the efforts of stakeholders to sustain fish cage
farming in the lake which include participative, multi-sectoral action planning, information and
education, policy formulation, regulation and licensing.
Blesshe L Querijero1,*
and Airill L Mercurio2
1Animal Biology Division, Institute of Biological Sciences, College of Arts and Sciences, University of the Philippines, Los Baños 4031, Laguna, Philippines
2Biological Sciences Department, College of Science and Computer Studies, De La Salle University-Dasmariñas, City of Dasmariñas 4114, Cavite, Philippines
Received – January 06, 2016; Revision – January 27, 2016; Accepted – February 20, 2016
Available Online – February 20, 2016
DOI: http://dx.doi.org/10.18006/2016.4(1).109.115
WATER QUALITY IN AQUACULTURE AND NON-AQUACULTURE SITES IN
TAAL LAKE, BATANGAS, PHILIPPINES
E-mail: [email protected] (Blesshe L Querijero)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
Journal of Experimental Biology and Agricultural Sciences
http://www.jebas.org
ISSN No. 2320 – 8694
Production and Hosting by Horizon Publisher
(http://publisher.jebas.org/index.html).
All rights reserved.
All the article published by Journal of Experimental
Biology and Agricultural Sciences is licensed under a
Creative Commons Attribution-NonCommercial 4.0
International License Based on a work at www.jebas.org.
_________________________________________________________
Journal of Experimental Biology and Agricultural Sciences
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1 Introduction
Among various resource based activities in and around the
lake, including its watershed areas, aquaculture activities are
often blamed for the degradation of water quality (Pullin,
1993). Aquaculture also supports food security and livelihood.
Reducing vulnerability of aquaculture production due to water
quality deterioration by fishing is a national priority for a
sustainable fish production (Jacinto, 2011). Taal Lake has an
area of 268 km2 with an aquatic surface area of 236.9 km
2 and
a maximum depth of 198 m (Castillo & Gonzales, 1976). It is
the third largest freshwater lake in the Philippines. It provides
multiple services to various users, among these fisheries is one
of the most dominant one with floating fish cages for tilapia
Oreochromis niloticus and milkfish Chanos chanos. Intensive
aquaculture and human activities caused deterioration of the
water quality of the lake and fish kills have become more
common incidents in Taal Lake (Jacinto 2011, Macandog et
al., 2014). In 2011 these incidences of fish kills in Taal Lake
were reported during May to June and killed more than 2,000
tons of farmed fish. Over 7,000 illegally operated fish cages
were dismantled by a multi-agency task force (BFAR 2014).
The changes in the physico-chemical properties of the water of
Taal Lake were reported in several studies (Zafaralla et al.,
1992, Alcañices et al., 2001, Vista et al., 2006, Rosana et al.,
2008, Papa & Mamaril, 2011). According to Galera &
Martinez (2011), the water surface temperature, pH, total
dissolved solids, total suspended solids, color and dissolved
oxygen of Taal lake in 2009 conformed the class C water
standards (DENR AO 34, 1990); and was therefore safe for
aquaculture use, and for primary contact recreation such as
bathing, swimming and skin diving.
This study was undertaken to determine and compare the
physico-chemical characteristics of Taal Lake in aquaculture
and non-aquaculture sites and tried to find out the effects of
fish cage farming on water quality as valuable inputs for policy
decisions pertaining to aquaculture production in the lake. The
study also aimed to document the stakeholders’ efforts to
sustain aquaculture production in the lake and prevent
degradation of water quality.
2 Materials and Methods
2.1 Assessment of Water Quality
Selected physico-chemical characteristics of Taal lake water at
the aquaculture and non-aquaculture sites of the lake were
determined monthly for 10 months from August 2013 to May
2014 using standard procedures. The physical parameters
include water transparency and temperature while the chemical
parameters include pH, nitrates, phosphates, salinity, total
dissolved solids (TDS) and dissolved oxygen (DO) were
studied throughout the study period. Figure 1 shows the
sampling sites, the sampling stations for the aquaculture sites
were located in three Barangays i.e. Sampaloc, Aya and
Berinayan. Among these, Sampaloc and Aya are in the
municipality of Talisay while Berinayan in Laurel
municipality. Both municipalities are located in Batangas
province, Philippines. The non-aquaculture sampling stations
were located in Barangay Wawa, Tanauan municipality,
Batangas (Figure 1). Each Barangay had three sampling
stations to serve as triplicate sampling stations or a total of 12
sampling stations. Sampling was done once every month. A
GPS Garmin E-trex® Global Positioning Device was used to
identify and mark the sampling stations.
Figure 1 Overview of Taal Lake, Philippines and the water sampling stations
110 Blesshe and Airill
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Journal of Experimental Biology and Agricultural Sciences
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Measurement of physico-chemical parameters of water was
carried out in situ, at the surface and at 10 m depth. Water
samples for chemical analysis were collected from the surface.
In aquaculture sites, measurements of parameters were done
inside fish cages. All of the physico-chemical parameters were
taken in triplicates from each of the sampling stations.
Sampling was carried out between 9 A.M to 2 P.M.
Among physical characteristics, the water temperature was
determined using standard laboratory thermometer at the
sampling site only while the water transparency was measured
by a 3.3 kg metal plate Secchi disk. For chemical
characteristics, dissolved oxygen was measured by using DO
meter (YSI 550A®) with 10 meters length cable, similarly pH,
salinity, conductivity and total dissolved solids (TDS) were
also measured by same length holding SCT pH meter (YSI
EC300A®). The nitrates and phosphates were measured using
HACH DR/890 portable colorimeter. The nitrate and
phosphate contents of the lake water were measured using
nitrates and phosphates reagents tested in a 10 ml vials
collected from each sampling stations (Umaly, 1988).
Quantitative data on water quality parameters were compared
using Mann-Whitney U test at 95% level of confidence to
determine significant difference between aquaculture and non-
aquaculture sites.
2.2 Fish Farmers’ Practices and Stakeholders’ Efforts
Affecting Water Quality
A total of 20 key respondents were interviewed for their
current fish farming practices for exploring the effect of
farming practices on the water quality such as fish stocking
densities and feeding management. Interviewed key informants
were fish cage owners, caretakers, members of the Taal Lake
Aquaculture Alliance Incorporated (TLAAI), municipal
agricultural and fisheries officers of the selected municipalities
and from relevant Philippine government agencies such as the
Bureau of Fisheries and Aquatic Resources (BFAR-IVA) and
the Taal Volcano Protected Landscape (TVPL) of the
Department of Environment and Natural Resources,
Philippines (DENR).
3 Results and Discussion
3.1 Assessment of Water Quality
Results of the study revealed no significant differences in
water transparency, temperature, DO, pH, and salinity between
aquaculture and non-aquaculture sites throughout the 10-month
sampling period, except in nitrates, phosphates levels and in
total dissolved solids where significant differences existed
(Table 1 and Figure 2). DO and transparency were consistently
lower in the aquaculture sampling stations although not
significantly different from the non-aquaculture sampling
stations.
3.1.1 Phosphates
The levels of phosphate was reported higher than the standard
DENR (0.05 – 1.0 mg/L) recommended for Class C waters
(aquaculture purpose) for both study sites during the entire
sampling period. Average monthly phosphate levels during the
10-month sampling period were significantly higher
(2.17mg/L) in the aquaculture areas than in the non-
aquaculture areas (1.91 mg/L) (Figure 2). Higher phosphates
level was observed during the months of September to October
2013, it may be because of heavy rains during these months.
Zafaralla (1993) and Alcañices et al. (2001) observed an
increase in nutrient concentration during the entire wet season
and in this manner results of present study are in agreement
with the findings of these researchers.
Table 1 Average values of the physico-chemical parameters of the water in aquaculture and non-aquaculture sampling stations in Taal
Lake from August 2013- May 2014.
Parameter Units Standard Level for Class
C Water*
Mean (+ SD)***
Aquaculture Non-aquaculture
Phosphates mg/L 0.05 (0.1)** 2.17a +0.45 1.91
b +0.23
Nitrates mg/L 10 2.93a +0.53
2.197
b +0.61
Total Dissolved Solids (TDS) mg/L 1000 1127.37a +60.70
1066.41
b +56.90
Dissolved Oxygen (DO) (minimum) mg/L 5.0 5.67a +1.40
6.73
a +1.72
pH - 6.5-8.5 8.45a +0.47
8.25
a +0.66
Salinity ppt 0.82a +0.42
0.82
a +0.23
Transparency Meter 2.52a +1.38 3.13
a +1.71
Water Temperature °C 3 oC rise 28.35
a +1.98 28.14
a +1.96
*Class C water is described as water for fishery propagation and growth of fish and other fishery products; for recreation and industrial
supply for manufacturing processes (DENR AO 34, 1990), **Values in parenthesis are considered maximum values for lakes and
reservoirs (DENR AO 34, 1990), *** Average values with the different letters as superscript on the same row indicated significant
difference (p>0.05) among the treatments
Water quality in aquaculture and non-aquaculture sites in Taal lake, Batangas, Philippines 111
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According to Hilario & Perez (2013) intensive fishing is a
point source of dissolved inorganic nutrients principally
nitrogen and phosphorus, and that wind stress was responsible
for the slow nutrient transport in Taal lake. Further, Lucas &
Southgate (2012) reported that phosphorus occurred in water
primarily as phosphate ion and in combination with organic
matter which phytoplankton assimilated and caused their
bloom. Other point sources of phosphates and nitrates in lakes
were domestic wastes that include washing detergents and
faecal matter, and agricultural run-off with fertilizers and
liquid manure from livestock.
3.1.2 Nitrates
Nitrates levels inside fish cages ranged from 1.76 mg/L to 3.69
mg/L and were significantly higher than in non-aquaculture
site. These values are higher than previous studies in Taal lake
(Zafaralla et al., 1992; White et al., 2007; Rosana et al.,
2008). In an earlier study, Dela Vega (2001) reported that for
every 1,000 kg of feed used, an estimated 47 kg N and 9 kg P
were lost into the water. The unconsumed food from fish cage
aquaculture settled at the bottom of the lake.
Figure 2 Physico-chemical parameters (phosphates, nitrates, total dissolved solids, dissolved oxygen, water transparency, and water
temperature) in fish cage farming areas (aquaculture) and in the non- aquaculture area in Taal Lake, Philippines from August 2013 to
May 2014.
112 Blesshe and Airill
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3.1.3 Total dissolved solids (TDS)
Freshwater usually have a TDS concentration less than
1000mg/L. The TDS concentrations at both sites were above
1000 mg/L and it was significantly highest during May with
the start of the rainy season. These dissolved solids are
inorganic substances which are available in ionic form.
According to Lucas & Southgate (2012) rainfall and soil
particles that are washed into the water from run-off are also
sources of TDS.
3.1.4 Water Transparency
Although water transparency was not significant different
between these two sites, the monthly water transparency at
non-aquaculture sites were consistently higher than those from
the aquaculture sites. It was reported highest in the months of
January and February, 2014, which coincided with
phytoplankton die off starting January to March 2014. Present
study showed lower transparency value (1.15 m to 5.56 m) as
compared to the previous studies of Zafaralla et al., 1992 (7.8
m), Alcañices et al., 2001 (5m), Vista et al., 2006 (4-6m).
Findings of present study are in agreement with the findings of
Rosana et al. (2008), those have reported 3.44 m transparency
in open water areas while this value was 2.92 m in cage
farming areas. Water transparency value less than 2.0 m is
considered a eutrophic lake (US EPA 1974). Taal lake
transparency values were lower than 2.0 m for several months
during the 10-month sampling period so it can be considered as
eutrophic lake (Figure 2).
3.1.5 Dissolved Oxygen
Lowest DO level was recorded in the month of January 2014,
on the same month when water transparency value was found
to be the highest. This can be attributed to the start of
phytoplankton die-off in the lake. DO levels below 4ppm were
observed in January –February, 2014 in aquaculture site. DO
measurements were taken during the mid-morning hours yet
DO levels were below 5 mg/L. This implies that there exists
only a small margin of safety before the fish are exposed to a
critical DO level of below 4mg/L. DO level may become even
critically low in late evening or during early morning hours in
the absence of photosynthesis, and in the presence of high
standing fish biomass inside cages and it may result to fish kill.
Phytoplankton die-off occurred in January-February, 2014,
followed by fish kill on the same months. Increasing the level
of DO above 6mg/L in aquaculture sites and 8mg/L in non-
aquaculture sites in March-May 2014 may be due to decrease
in the overall fish standing stock in the lake as a result of fish
kill and the light to moderate phytoplankton density during
these months (Mercurio et al., 2016).
3.1.6 Water Temperature
Water surface temperature ranged from 26oC to 31
oC, without
significant differences between the two study sites. Similar
type of result was reported by Papa & Mamaril (2011) for Taal
lake. Lowest water temperature was reported during February
2014 while the highest was during the month of May 2014.
3.1.7 pH
The pH ranged from 7.5 to 9.14 and did not statistically differ
between the two study sites. The lake is known to be of
volcanic origin with annual water overturn and occasional acid
sulphate emission which could result to low water pH
condition. The 9.1 pH value observed in the present study were
similar to the findings of Rosana et al. (2008).
3.1.8 Salinity
Salinity in Taal lake was 0.8-0.9 ppt, uniform throughout the
entire sampling period in both study sites and it considered as
freshwater.
3.2 Fish Farmers’ Practices and Stakeholders Efforts Affecting
Water Quality
Results of the study on farming practices showed efforts of fish
farmers and stakeholders to reduce organic loading in the lake.
Fish farmers were required to attend a government sponsored
seminar on Good Aquaculture Practices (GAP) before permit
to operate a fish cage was given to prospective fish cage
farmers. Regular consultation and information campaign on
good aquaculture practices particularly on reducing feed losses
were also conducted by various stakeholders. A consultative
Unified Rules and Regulation on Fisheries (URRF) in Taal
Lake was drafted and approved on July 2014 as part of the
Taal Volcano Protected Landscape (TVPL) management plan.
URRF sets a limit to 6,000 floating cages in Taal lake,
distributed to the various municipalities and this distribution
was as follows: Talisay – 2,000 cage units; Laurel – 1,350;
Agoncillo – 1,500; San Nicolas – 1,000; Mataas na Kahoy –
120; Cuenca – 20. A cage unit measures 10m x 10m x 10m.
For the circular type, a diameter of 16 m and depth of 10 m is
allowed. URRF also mandated the use of extruded floating
feed starting March 2015 to reduce feed loss.
The recommended maximum stocking density for tilapia in
cages in Taal Lake is 50 pcs/m3 or 50,000/ cage and for
milkfish is 14 pcs/m3 or 14,000/ cage. Unfortunately, some
fish farmers opted to have higher fish stocking density than
recommended. Overfeeding increases production cost and
nutrient loading to the environment (Dela Vega & Querijero,
2005; Bunting, 2013). White (2013) emphasized the
importance of significantly reducing the production Feed
Conversion Ratio (FCR) values to minimize feed costs and
feed loss. Feed costs account for more than 60 percent of total
production costs. Feed loss and fish wastes from intensive fish
cage farming may have negatively affected the quality of water
particularly the levels of nitrates, phosphates, transparency and
Water quality in aquaculture and non-aquaculture sites in Taal lake, Batangas, Philippines 113
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Journal of Experimental Biology and Agricultural Sciences
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dissolved oxygen in the aquaculture sites as shown in the
present study.
Conclusions
Aquaculture activities like fish cage farming affect water
quality as indicated by the significantly higher levels of
nitrates, phosphates and TDS and the consistently low DO and
transparency values in aquaculture sites compared to non-
aquaculture sites. To sustain aquaculture production in Taal
lake, stakeholders need to continue their collaborative, multi-
sectoral action planning, information and education campaign,
regulation and licensing that are backed up with sound data on
water quality and feedback.
Acknowledgements:
The authors acknowledge the University Research Office
(URO) of De La Salle University-Dasmariñas (DLSUD) for
providing financial support; and the Bureau of Fisheries
Region IVA, particularly Ms. Nenita S. Kawit of the Inland
Fisheries Research Station; the local government units of
Talisay and Laurel; the PASu TVPL Office and Mr. Victor H.
Mercado, and the TLAAI for kind assistance.
Conflict of Interest
Authors would hereby like to declare that there is no conflict of
interests that could possibly arise.
References
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assessment of cage culture in Lake Taal, Philippines. In:
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from three tributary rivers of Taal lake Philippines. The
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Animals and Plants. Blackwell Publishing. John Wiley and
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Pabico JP, Salvacion AR, Marquez TL, Macandog PBM, Perez
DKB (2014) Eliciting local knowledge and community
perception on fishkill in Taal Lake through participatory
approaches. Journal of Environmental Science and
Management 17: 1-16.
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Rosana MR, Clemente JP, Casao EA, Regpala RR, Kawit NS,
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Project Report, Bureau of Fisheries and Aquatic Resources
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Water quality in aquaculture and non-aquaculture sites in Taal lake, Batangas, Philippines 115
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KEYWORDS
Hematology
Amaranthus spinosus
WBC
PCV
MCV
MCHC.
ABSTRACT
Amaranthus spinosus is known for its various remedies against many ill conditions. Present study has
been carried out to verify the toxic effects of whole plant’s aqueous extract against albino rats at
hematological levels. The aqueous extract was administered orally at 125, 250, 500 and 1000 mg/Kg
body wt./day respectively for 60 days; against distilled water administered control. Results of study did
not show any mortality in all the treatment groups throughout the study period. The significant reduction
in RBC, hemoglobin, PCV and MCHC and significant increase in WBC and MCV was observed at the
dose level 1000 mg/Kg body wt/day. After 90 days of treatment withdrawal, the hematological
parameters regained to control levels. The toxic effects found to be dose dependent as hematological
parameters were altered only at higher dose level.
Bhande Satish S* and Wasu Yogesh H
P.S.G.V.P. M’s, Shri. S. I. Patil Arts, G. B. Patel Science and S. T. K. V. S. Commerce College, Shahada, Dist. Nandurbar (425 409)
Received – January 07, 2016; Revision – January 27, 2016; Accepted – February 20, 2016
Available Online – February 20, 2016
DOI: http://dx.doi.org/10.18006/2016.4(1).116.120
EFFECT OF AQUEOUS EXTRACT OF Amaranthus spinosus ON HEMATOLOGICAL
PARAMETERS OF WISTAR ALBINO RATS
E-mail: [email protected] (Bhande Satish S)
Peer review under responsibility of Journal of Experimental Biology and
Agricultural Sciences.
* Corresponding author
Journal of Experimental Biology and Agricultural Sciences, February - 2016; Volume – 4(1)
Journal of Experimental Biology and Agricultural Sciences
http://www.jebas.org
ISSN No. 2320 – 8694
Production and Hosting by Horizon Publisher
(http://publisher.jebas.org/index.html).
All rights reserved.
All the article published by Journal of Experimental
Biology and Agricultural Sciences is licensed under a
Creative Commons Attribution-NonCommercial 4.0
International License Based on a work at www.jebas.org.
_________________________________________________________
Journal of Experimental Biology and Agricultural Sciences
http://www.jebas.org
1 Introduction
Amaranthus spinosus Linn. (Family: Amaranthaceae) is
commonly known as spiny amaranth, prickly amaranth or
thorny amaranth. It is widely distributed throughout the tropics
and warm temperate regions of Asia as a weed in cultivated as
well as fallow lands (Mishra et al, 2012). In India, it is
commonly known as ‘‘Kate Wali Chaulai (Kanatabhajii)” and
used as vegetable and cultivated throughout India. It is widely
used in folk lore medicinal system of India. The whole plant
and parts of the plant contains medicinally active constituents
such as alkaloids, flavonoids, glycosides, phenolic acids,
steroids, amino acids, terpenoids, lipids, saponins, betalains, b-
sitosterol, stigmasterol, linoleicacid, rutin, catechuic tannins
and carotenoids (Kumar et al., 2014). Extracts of A. spinosus
have been reported to show diuretic, antidiabetic, antipyretic,
anti-snake venom, antileprotic, anti-gonorrheal antioxidant,
anti-cholesterolemic, antipyretic, anti-inflammatory,
spermatogenic, antitumor, antifertility, immunomodulatory,
anti malarial, hepatoprotective activities (Kirtikar & Basu,
2001; Olumayokun et al., 2004; Hilou et al., 2006; Tatiya et
al., 2007; Sangameswaran & Jayakar, 2008; Ashok et al.,
2010; Ilango et al., 2010; Joshua et al., 2010; Girija et al.,
2011; Jhade et al., 2011; Barku et al., 2013; Bavarva &
Narasimhacharya, 2013) and also effects on hematology and
biochemical changes in the epididymis (Murugan et al., 1993;
Olufemi et al., 2003).
Although, it is noticeable that A. spinosus showed various
effects, there remains considerable concern over the safety to
develop it as a drug. Evaluation of haematological parameters
can be used to resolve the extent of toxic effect of extracts on
the blood of an animal. It can also be used to clarify blood
relating functions of a plant extract or its products (Yakubu et
al., 2005).Thus, present study has been carried out to verify the
toxic effects of aqueous extract of A. spinosus on
hematological parameters using albino rats as a model.
2 Materials & methods
2.1 Plant Material
A. spinosus as a whole plant was collected from in and around
places of Nandurbar district in Maharashtra state and identified
in Department of Botany of P.S.G.V.P. M’s, Shri. S. I. Patil
Arts, G. B. Patel Science and S. T. K. V. S. Commerce
College, Shahada, Dist. Nandurbar.
2.2 Extraction preparation
Whole plant was air dried under shaded conditions and
coarsely powdered. Hundred gram of powder was refluxed
with 600 ml of water at 100oC for 24 hours. The extract was
filtered through double layer 100 m nylon wire mesh and
concentrated at 50oC to obtain crude aqueous extract.
2.3 Experimental Animals
Normal healthy male Wistar rats (Rattus norvegicus) weighing
200-240g were used in the present investigation. The animals
were maintained as per the guidelines for care and use of
Animals for Scientific Research proposed by Indian National
Science Academy, 2000 at Department of Zoology, in group of
three animals in polypropylene rat cages under 12:12 hrs. light-
dark schedule and fed with rat pellet diet and water was
provided ad libitum.
2.4 Experimental Design
The animals were divided into four group viz. Group I, Group
II, Group III and Group IV, consisting 10 animals in each
group. The aqueous extract of A. spinosus was administered
orally at 125, 250, 500 and 1000 mg/Kg body wt./day
respectively for 60 days. Control animals were administered
with distilled water. Following completion of respective
treatment schedule, all the animals were withdrawn from the
treatment for a further period up to 90 days. Five animals from
each group were sacrificed the next day following the 60th day
of treatment and remaining five after 90 days of treatment
withdrawal.
2.5 Hematology
Blood samples were collected by cardiac puncture and used for
total red blood corpuscles [RBC], white blood corpuscles
[WBC] analysis as prescribed by Lynch et al. (1969), while
hemoglobin (Crosby et al., 1954) and red cell indices viz.,
packed cell volume (PCV), mean corpuscular volume (MCV),
mean corpuscular hemoglobin (MCH) and mean corpuscular
hemoglobin concentration (MCHC) was studied by the
methodology given by Natelson (1951).
2.6 Statistical analysis
Student’s t-test was employed for the statistical comparison.
3 Results
No animal mortality was recorded in the treatment groups
throughout the study period. Treatment with aqueous extract of
A. spinosus did not show any appreciable changes in
hematological parameter in Group I and II animals after 60
days of treatment period. There was significant reduction in
RBC, hemoglobin, PCV and MCHC in the treatment group IV.
However, significant increase (p<0.001) was observed in WBC
and MCV in the treatment Group IV. The levels of MCH did
not show alterations in all the treatment groups.
After 90 days of treatment withdrawal, the hematological
parameters regained to control levels (Table1- 4).
117 Bhande and Wasu
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Table 1 Hematology of rats treated orally with aqueous extract of A. spinosus @ 125 mg/Kg body wt./day (Values with SEM of 5
animals).
Treatment Schedule RBC
(106/mm
3)
WBC
(103/mm
3)
Hemoglobin
(g/dl)
PCV
(%)
MCV
(µ3)
MCH
(µ.µg)
MCHC
(%)
Control 8.22±0.14 10.6±0.36 15.8±0.22 38.5±0.17 46.9±0.60 19.3±0.53 41.1±0.70
Treatment 60 days 8.18±0.08 10.7±0.71 15.5±0.37 38.4±0.24 46.9±0.27 19.0±0.57 40.6±0.84
TW 90 days 8.36±0.15 10.4±0.50 15.7±0.86 38.0±0.41 46.0±1.16 18.7±1.09 40.9±1.93
All the values are the mean of five replicates, TW – Treatment withdrawal
Table 2 Hematology of rats treated orally with aqueous extract of A. spinosus @ 250 mg/Kg body wt./day (Values with SEM of 5
animals).
Treatment Schedule RBC
(106/mm
3)
WBC
(103/mm
3)
Hemoglobin
(g/dl)
PCV
(%)
MCV
(µ3)
MCH
(µ.µg)
MCHC
(%)
Control 8.22±0.14 10.6±0.36 15.8±0.22 38.5±0.17 46.8±0.60 19.3±0.53 41.1±0.70
Treatment 60 days 8.16±0.12 10.9±0.29 15.4±0.32 38.6±0.12 47.1±0.78 18.9±0.62 40.9±0.38
TW 90 days 8.20±0.15 10.8±0.50 15.6±0.86 38.8±0.41 47.4±1.16 19.2±1.09 40.8±1.93
All the values are the mean of five replicates, TW – Treatment withdrawal
Discussion and Conclusions
In the present study, toxic effects of aqueous extract of A.
spinosus in male albino rats have been investigated. The results
indicate that the extract did not lead to any deleterious effects
in the animals treated at 125 and 250 mg/Kg body wt./day. The
absence of significant changes may suggest that the extract
does not have toxic effects at these dose regimens in albino
rats. The significant decrease was observed in the PCV in 500
and 1000 mg/kg. treatment group while RBC, hemoglobin,
PCV and MCHC were decrease significantly at 1000 mg/kg.
b.w./day . It was reported that administration of 50% ethanolic
and methanolic extract of A. spinosus at 0.5 gm/kg. b.w. for 7,
14 and 21 days and 250 mg/kg for 5, 7 & 14 days respectively
showed significant decrease in RBC count (Olufemi et al.,
2003; Srivastava et al., 2011). This reduction in number of
RBC may be due to the hemolytic activity of the extract at
higher dose. Similarly, Choudhury (2012) reported the
presence of glycosides & saponin in the aqueous extract of A.
spinosus. It is earlier reported that haemolysis of red blood
cells is caused by saponin (Lawrence et al., 1997). Also,
aqueous crude extracts of A. cordifolia, P. amarus, P.
muellerianus and S. virosa administered at 2ml/100 gm. body
wt./day for 14 days, caused a significant reduction in PCV, Hb
concentration and RBC, (Adedapo et al., 2007). It is earlier
reported that the oral ingestion of medicinal compounds or
drugs can alter the normal range of haematological parameters
(Ofuya & Ebong, 1996; Ajagbonna et al., 1999).
Table 3 Hematology of rats treated orally with aqueous extract of A. spinosus @ 500 mg/Kg body wt./day (Values with SEM of 5
animals).
Treatment Schedule RBC
(106/mm
3)
WBC
(103/mm
3)
Hemoglobin
(g/dl)
PCV
(%)
MCV
(µ3)
MCH
(µ.µg)
MCHC
(%)
Control 8.22±0.14 10.6±0.36 15.8±0.22 38.5±0.17 46.8±0.60 19.3±0.53 41.1±0.70
Treatment 60 days 7.96±0.33 11.4±0.68 15.2±0.19** 37.7±0.16*** 47.2±0.34 19.2±0.72 40.8±0.50
TW 90 days 8.11±0.26 10.9±0.54 15.5±0.37 37.9±0.40* 46.7±1.33 19.5±0.44 40.9±0.70
All the values are the mean of five replicates, TW – Treatment withdrawal, ** represents significance level at p<0.01, *** represents
significance level at p<0.001.
Effect of Aqueous Extract of Amaranthus spinosus on Hematological Parameters of Wistar Albino Rats. 118
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Journal of Experimental Biology and Agricultural Sciences
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Table 4 Hematology of rats treated orally with aqueous extract of Amaranthus spinosus @ 1000 mg/Kg body wt./day (Values with SEM
of 5 animals)
Treatment Schedule RBC
(106/mm
3)
WBC
(103/mm
3)
Hemoglobin
(g/dl)
PCV
(%)
MCV
(µ3)
MCH
(µ.µg)
MCHC
(%)
Control 8.22±0.14 10.6±0.36 15.8±0.22 38.5±0.17 46.8±0.60 19.3±0.53 41.1±0.70
Treatment 60 days 6.50±0.22
***
13.7±0.88
***
13.1±0.41
***
35.6±0.62
***
54.8±2.20
*** 20.1±1.10
35.9±0.66*
**
TW 90 days 7.58±0.53* 11.4±0. 86* 15.4±0.53* 37.2±1.28* 49.2±3.71* 20.8±2.09 49.9±1. 86
All the values are the mean of five replicates, TW – Treatment withdrawal, ** represents significance level at p<0.01, *** represents
significance level at p<0.001.
Administration of aqueous extract of A. spinosus showed
significant increase in WBC and MCV at the dose level 1000
mg/Kg body wt./day. The level of MCH did not show
alterations in all the treatment groups. Similarly, the
administration of aqueous ethanolic extract of M. indica stem
bark at a dose of 5000 mg/kg body weight for 14 days induced
significant increase in WBC and the differential leukocytes
counts in the tested animals (John et al., 2012). These results
suggested that the extract may have immunological properties
at higher dose level. The immuno-stimulating activity of wild
A. spinosus water extract was investigated on spleen cells from
female mice. The isolated B lymphocytes, but not T
lymphocytes, could be stimulated by wild A. spinosus in a dose
response manner. The water extract of A. spinosus directly
stimulates proliferation of B lymphocytes in vitro (Lina et al.,
2005). It is earlier accounted that the water extract of the plant
have significant immunostimulating activity (Lagos, 1986).
Nevertheless, the effects of aqueous extract of A. spinosus at
1000 mg/Kg body wt/day are temporary because every
hematological parameter regained to control levels after 90
days of treatment withdrawal and no mortality of animals was
observed throughout the study period. The toxic effects of
aqueous extract of A. spinosus was found to be dose dependent
as hematological parameters were altered only at higher dose
level (1000 mg/Kg body wt./day), while there was no toxic
effects at lower dose level. The effective dose and toxicity may
change with the solvent used in extraction protocol. It is
suggested that the safety dose level for aqueous extract of A.
spinosus could be 500 mg/Kg body wt/day in albino rats.
Acknowledgements
Authors are very much thankful to UGC (WRO-Pune) New
Delhi, India for providing financial assistance to present work.
Conflict of Interest
Authors would hereby like to declare that there is no conflict of
interests that could possibly arise.
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