ORIGINAL RESEARCH

International Journal of Recycling of Organic Waste in Agriculture (2020)9: 367-383Doi:10.30486/IJROWA.2020.1895397.1049

Compost from the food waste for organic production of cabbage, cauliflower, and radish under sub-tropical conditions

Neha Kumari1, Anit Sharma1, Mamta Devi1, Atif Zargar1, Sunny Kumar1, Umesh Thakur1, Ajay Bhatia1, Khushboo Badhan1, Sunaina Chandel1, Arpana Devi1, Kriti Sharma1, Shweta Kumari1, Mussarat Choudhary1, Arup Giri1, 2*

Received: 11 March 2020 / Accepted: 12 October 2020 / Published online: 20 December 2020

AbstractPurpose In the current scenario, food wastage is a significant concern throughout the world. This food wastage may convert to compost, and that compost may apply in the agriculture field for the better yield of crops. In this context, a field study conducted on the effects of compost prepared from food wastage on the yield of cabbage, cauliflower, and radish.Method The experiment consisted of twelve treatments and twelve control plants of all the plants. Field soil of both control and treatment plots were analyzed by standard methods. Standard methods took different morphological and chemical parameters of all the plants. Results Results indicated that compost from food waste increased soil fertility. The application of manure was significantly (p<0.01) superior over the morphological and biochemical properties of the control group plants. The application of compost increased leaf relative water content and decreased the electrolyte leakage in all the plants. The yield of cabbage (control-0.00 t•ha-1, treatment-37.05 t•ha-1), cauliflower (control-10.16 t•ha-1, treatment-22.36 t•ha-1) and radish (control-7.30 t•ha-1, treatment-20.33 t•ha-1) were significantly higher in the treatment group than the control group. The yield increment in percentages of cabbage, cauliflower, and radish was infinite %, 220.08 %, and 278.49 %, respectively. The day in terms of time, compost, and their interaction has a significant effect on the better health of cabbage, cauliflower, and radish, and more yields achieved. Conclusion Therefore, food waste is used for making compost, which is helpful for organic cabbage, cauliflower, and radish production in a sub-tropical condition.

Keywords Cabbage, Cauliflower, Compost, Food wastage, Radish, Sub-tropics

Department of Life Science, School of Basic Sciences, Arni University, H.P., IndiaAnimal Biotechnology Laboratory, DRDO-Defence Institute of High Altitude Research (DIHAR), Chandigarh, India

1

2

Arup Giri arupsatadal@gmail.com

Introduction

Food is the fuel for our life, and it is sacred corporeal in Indian culture. But, in the current scenario, food wastage is a great concern in India. Throughout the globe, about 1.3 billion tons and 67 million tons of food are wasted in India every year as disposing as raw or cooked food during the food supply chain or at the consumption time at the domestic level (Gustavsson et al. 2011; Haq 2016). The 67 million tons of waste food stands for nearly about US$14 billion. In India,

the most probable reason for the huge amount of food wastage is the bulk purchase of food or disliking of food after cooking. 18.50 % of the population wasted between 10-20 % of the food (Srinivas and Dongre 2018). In India, being a developing country, this level of food wastage should reduce as it may have negative implications on culture, economy, and environmental conditions (White et al. 2009; Haq 2016). Dumping of food wastage affects the health of the environment like releasing of the enormous amounts of greenhouse gasses, acidification of local ecosystem, eutrophication of local water bodies, etc. (Salemdeeb and Al-Tabbaa 2015; Brancoli et al. 2017).

Therefore, to reduce environmental hazards, food wastage may convert to compost and which might be helpful for the agricultural application to increase the yield as the compost has a high carbon and nitrogen

International Journal of Recycling of Organic Waste in Agriculture (2020)9: 367-383368

ratio (Risse and Faucette 2009). Agricultural utilization of compost may enhance organic farming. This farming is ecologically and economically viable. It is affordable by both farmer and consumer (Pretty and Bharucha 2014). Directly and indirectly, this farming provides an economically developed society with the excellent health condition of the populace. Organic agriculture is helpful for the production of healthy foods with higher palatability, taste, and nutritive values. It maintains the soil health and production environment for the farmers (Narayanan 2005). Therefore, organic farming is rising as the alternate farming as the increase pattern of consciousness about conservation environment as well as higher production of health hazard free food (Ramesh et al. 2005). Sub-tropical region is characterized with higher pest and disease pressure in agriculture sector, infertile soil, and lack of organic farming (Anonymous 2011).

However, no study has ever conducted on the application of prepared compost from food wastage for organic cabbage, cauliflower, and radish farming at the sub-tropical conditions. No scientific study has ever conducted on the effects of compost prepared from food wastage on the morphology, physiology especially stress physiology of the plants. Therefore, the main objectives of this study reveal with the effect of compost on the plant morphology, effect of prepared compost on plant physiology, special emphasis on stress physiology, and the effect of made compost on the yield of cabbage, cauliflower, and radish in the sub-tropical condition.

Materials and method

Experimental site

The experiment conducted at the experimental field of Arni University, Kangra (H.P.), India (Fig. 1). The environmental condition during the trial period varied (Fig. 2).

Compost preparation from food wastage

To prepare the compost, food waste from the Girl’s and Boy’s Hostel, Arni University, India, was collected in January 2019 and poured into a previously dug hole (L × W × D = 1.52 × 1.22 × 1.22 m). Generally, transformation into nitrogen, micronutrients, water, CO2, etc. takes place during decomposing of food materials. This process then attracts different types of pests, especially rats (Zahrim et al. 2015). To attenuate the pest attack, we dried up compost thoroughly and were pulverized soil mixed with the food waste in the 1:1 (w:w) ratio. Although co-composting with a suitable bulking agent such as agricultural waste can be used (Zahrim et al. 2015), blending food waste with soil is much be a more comfortable and cheaper technique. The residue was covered and left for two months. After this, the well-deteriorated compost was removed and placed on a cement pad for further drying. The dried compost applied to treatment plots @ 10 tons ha-1 (Ali et al. 2018).

Analysis of compost and soil

Soil analyzed for pH, electrical conductivity (EC), total dissolved solids (TDS), moisture, water holding capacity (WHC), and soil organic matter (SOM) following methods were described by Singh et al. (2005) (Table 1). Total nitrogen (%) was calculated from whole organic matter, as defined by Rashidi Mand Seilsepour (Lindsay and Norvell 1978). Phosphorus and potassium level was determined by using the PUSA Soil Test and Fertilizer Recommendation (STFR) meter (WST 312P). Soil sample has been processed by the DTPA (Diethylene-triamine-penta-acetic acid) method (Singh et al. 2005) to determine the available micronutrients, and thereafter digested samples were executed by Atomic Absorption Spectroscopy (AAS) (ZEEnit 700P, Analytika Jena) to determine the available micronutrients in the soil of both plots. During the analysis of the mineral, C2H2/Air was 60 Ltr/hr, C2H2/N2O was 230 Ltr/hr, Burner height was 6 mm (Singh et al. 2005).

Sl. No. Parameters Abbreviation Unit Instrumental Methods1. pH *------------- ----------- Glass electrode method (pH meter at 25 oC)2. Electrical Conductivity EC µs/cm Conductivity meter at 25 oC 3. Total Dissolved Solids TDS mg·L-1 TDS meter at 25 oC 4. Soil Moisture SM % Walkley and Black (1934)5. Water Holding Capacity WHC % Filtration Method6. Total Organic Matter TOM % Walkley and Black (1934)

Table 1 Used analytical techniques to evaluate different physico-chemical parameters of soil (Singh et al. 2005)

*pH is a logarithm

International Journal of Recycling of Organic Waste in Agriculture (2020)9: 367-383 369

Fig. 1 Field study area map at Arni University, Kathgarh, Himachal Pradesh, India

Fig. 2 Climatic condition during the experimental period at the experimental site. T°C – Temperature degree centigrade; max – maximum; min – minimum, RH – Relative humidity

Experimental field preparation

After weeding, the soil was deeply dug by spade and manually leveled. The experiment set up in a randomized complete block design. Each plot (L × W = 3.048 × 2.1336 m) had 12 plants with 3 replications. Distances between plots were 15 cm; there was a 50 cm distance between rows and 30 cm distance between plants (Bhatti et al. 2019). Irrigation was when the soil moisture content was 45-65 % (Hanson et al. 2000).

Manually weeding was executed as needed. At 47 days after planting, observations were begun and repeated at a 15-day interval until harvest, day 107.

Physio-chemical parameters of all plants

Some physio-chemical parameters like plant height (pH), leaves number per plant (LFN), length and width of leaves (LL and LW), cabbage head and cauliflower head diameter, stem diameter (SD), total dry matter

International Journal of Recycling of Organic Waste in Agriculture (2020)9: 367-383370

(TDM), leaf relative water content (LRWC), ash content of head (ACH), ash content of leaf (ACL), ash content of root (ACR), root length (RL), and root width (RW) of radish, were selected to observe the growth and quality of plants. pH was recorded from ground level up to the growing point with the help of a meter-scale from 47th days after transplanting. The LFN of randomly selected plants counted at the 47th day after plantation of cabbage and cauliflower, and 14th day of radish. The LL and LW of leaves were measured by measuring scale. From the plantation day of cabbage, cauliflower, and radish, on 107th day, 107th day, and 74th-day harvesting were completed of cabbage, cauliflower, and radish, respectively. The average stem diameter, cabbage head width and, fruit width measured by using vernier caliper after harvesting (Nagashima and Hikosaka 2011). TDM determined by the method of Waqas et al. (2017). LRWC recorded by using LRWC (%) = (FW-DW)/(TW-DW)×100 formula (Karrou and Maranville 1995). ACL, ACR, and ACH were determined by the method of Cabrera-Bosquet et al. (2009). EL of the leaf evaluated as per the methods of Blum and Ebercon (1981). With the help of a measuring scale, the RL was measured. The average weights of all the plants weighted by the weighing machine after harvesting with proper cleaning (Nagashima and Hikosaka 2011).

Antioxidant parameter analysis

For antioxidant parameter analysis, DPPH stands for 1,1-Diphenyl-2-Picrylhydrazyl (Abe et al. 2000), FRAP abbreviation of Ferric Reducing-Antioxidant Power (Benzie and Strain 1996), and ABTS stands for 2,2’-Azino-Bis-3-Ethylbenzthiazoline-6-Sulphonic Acid (Turoli et al. 2004) performed for antioxidant parameters evaluated in cauliflower and radish.

Statistical analysis

To determine the statistical significance between the control and treatment groups, all the data set has executed by the t-test and to evaluate the significant variance among the different time interval, one-way ANOVA performed after running the Statistical Packages for Social Sciences (SPSS) 24.0 IBM version software. After that, the stepwise linear regression was performed for relating vegetable yield with the applicable compost, i.e., to investigate how to compost

influence vegetable yielding. Then, we executed our dataset through two-way ANOVA to investigate the effects of compost, the day, and their interactive effects on the entire selected vegetable yield. The level of significance determined at p≤0.05 and p≤0.01. The PCA (principal component analysis) analysis was executed on the compost parameters to identify the correlated compost properties and to rectify the most effective ones.

Results and Discussion

Changes of different physico-chemical parameters of soil from control and treatment plot

Independent t-test showed deference of physicochemical parameters between control and treatment plot soil. The following parameters like pH, electric conductivity (EC), total dissolved solids (TDS), water holding capacity (WHC), soil moisture (SM), carbonate and soil organic matter (SOM) were analyzed (Table 2). There was significantly (p<0.01) decreased pH level (9.13 ± 0.04) in the control plot soil than the pH level (8.48 ± 0.01) of treatment plot soil. Slightly acidic to neutral (pH 6.0-7.5) soil is often the best for the overall availability of nutrients plant growth and microbial processes. The application of organic manure in soil may increase or decrease its pH level in different conditions (Ahmed et al. 2019). In this study, the pH level of the soil of the treatment group was lower than the control group. These might be due to the nitrification process, leaching of basic cations such as potassium, calcium, magnesium, and nitrate in the soil of the treatment group (Ozlu and Kumar 2018). The results of soil minerals analysis were also reflecting this finding. The soil moisture level was 22.38 ± 0.27 % in treatment plot soil, whereas 17.78 ± 0.53 % was in control plot soil. There was significantly (p<0.01) increased electrical conductivity level (9.24 ± 0.23 µs/cm) in control plot soil than the treatment plot soil (33.33 ± 0.33 µs/cm). Soil EC level depends upon the total amounts of soil present in the ground. EC of soil regulates the availability of nutrients to the plants; regulates the microbial activity in the field (Shrivastava and Kumar 2015). In this study, the EC level of treatment group soil was higher than the EC level of control group soil. These indicate the presence of a higher amount of dissolved salts in the organic manures (Ozlu and Kumar 2018). Total dissolved solid was (13.00 ± 0.58 mg•L-1) in control plot soil, whereas (49.52 ± 0.30 mg•L-1) in

International Journal of Recycling of Organic Waste in Agriculture (2020)9: 367-383 371

treatment plot soil, which is significantly higher than the control plot soil. The TDS in terms of a measurement of all the organic and inorganic compounds present in the solution (Taylor et al. 2018). In this study, the TDS of treatment group soil has a higher level of TDS than the control group soil because of the addition of solids in the form of compost in treatment group soil. Water holding capacity was higher (29.54 ± 0.30 %) in treatment plot soil than the control plot soil (19.84 ± 0.10 %). Crops’ productivity highly depends upon the water holding capacity of the soil. Soil water holding capacity depends upon the soil texture and present amount of organic matter. The application of compost, therefore, increases the water holding capacity, which prevents the fast leaching minerals process (Williams et al. 2016; Yang et al. 2016). In this study, WHC of treatment soil was significantly (p<0.01) higher than the WHC of control group soils. These indicate the presence of a significantly (p<0.01) more elevated level of soil organic matter in treatment plot soil (McKee et

Group pHElectrical conductivity

Total dissolved solids

Water holding capacity

Soil moisture Soil organic matter

Control 9.13 9.24 13.00 19.84 17.78 24.64

Treatment 8.48*** 33.33*** 49.52*** 29.54*** 22.38*** 97.16***

Table 2 Changes of physico-chemical parameters of soil from control and treatment plots

*** significant at p<0.01, Student’s t-test.

al. 2018). Application of soil organic manure helps in increasing the soil organic matter. So, a significantly higher level of soil organic matter present in treatment plot soil than the control group plot soil (Das et al. 2017). Soil organic matter was (24.64 ± 0.33 %) significantly lower in control plot soil than the treatment plot soil (97.16 ± 0.28 %) (Table 2). The SOM strongly influences the crop growth and productivity by providing nutrients and modifying soil quality indices such as decreasing soil compaction, stabilizing soil structure due to increased soil aggregation, and controlling soil erosion (Ding et al. 2012). Increased levels of SOM facilitate soil microbes to render the micronutrients to plants after balancing the carbon and nitrogen (Murphy et al. 2015; Poeplau et al. 2017). In this experiment, the SOM of treatment group soil was more than the SOM of control group soil, and it might be due to the addition of more carbon source through compost in the treatment group soil which improves the plant morphology in the treatment group (Ge et al. 2016; Zhu et al. 2018).

The results of NPK and available micronutrients (Mn, Fe, Cu, and Zn) showed a significantly higher

Table 3 Available nutrients level in the soil of the control and treatment group

GroupTotal Nitrogen

(kg/ha)

Phosphorus

(kg/ha)

Potassium

(kg/ha)

Manganese

(ppm)

Iron

(ppm)

Copper

(ppm)

Zinc

(ppm)

Control 1.68±0.04 28.33±2.79 176.07±12.02 0.430±0.02 0.574±0.05 0.017±0.00 0.033±0.01

Treatment 6.54±0.04*** 314.00±14.61*** 268.60±9.97*** 0.671±0.05* 0.986±0.30* 0.069±0.01* 0.063±0.00***

* significant at p<0.05, *** significant at p<0.01, Student’s t-test.

level of all the minerals in the treatment plot’s soil of both the plants (Table 3).

All the dataset of soil parameters executed through PCA analysis to know the most effective parameters for plant growth. The obtained data is presented in the Table 4. Based on the eigenvalue, only five varifactors were obtained after satisfying the Kasier–Meyer–Olkin and Bartlett’s tests followed by varimax rotation

method where total variance was 92.35%. The first varifactor of the factor analysis has the most effective parameters (Giri et al. 2019a). In this study, the first varifactor has strong positive loadings (>0.6) of SOM, N (total nitrogen), Cu, and Zn. Therefore, it is indicting that SOM is the main factor for minerals’ release. The

International Journal of Recycling of Organic Waste in Agriculture (2020)9: 367-383372

second varifactor has higher loadings of pH, Mn, and Fe. Here pH is the main factor for minerals’ release in the soil. Third factor has higher loadings of WHC, K (potassium) followed by the higher loadings of EC and P (phosphorus) in the fourth and fifth varifactor, respectively. Overall, the results indicating that SOM,

Extraction method: Principal component analysis; Rotation method: Varimax with Kaiser normalization; EC-Electrical conductivity; TDS-Total dissolved solids; WHC-Water holding capacity; SM-Soil moisture; SOM-Soil organic matter; N-Total nitrogen; P-Phosphorus; K-Potassium; Mn-Manganese; Fe-Iron; Cu-Copper; Zn-Zinc

Table 4 Soil properties obtained through the principal component analysis (PCA) with the varimax rotation method by satisfying the Kasier–Meyer–Olkin (KMO) and Bartlett’s tests

Component 1 2 3 4 5Eigenvalues 4.29 3.17 1.69 1.63 1.23% of Variance 32.98 24.35 12.97 12.57 9.47Cumulative % 32.98 57.34 70.31 82.88 92.35Rotated Component MatrixpH 0.285 0.876 -0.075 0.234 0.039EC 0.101 0.121 0.117 0.955 0.126TDS 0.090 0.192 0.530 -0.768 0.218WHC -0.199 0.310 0.922 0.025 -0.022SM -0.628 -0.224 -0.293 -0.164 0.655SOM 0.970 0.103 -0.044 0.035 -0.028N 0.971 0.099 -0.042 0.033 -0.034P 0.235 0.109 0.048 0.081 0.952K -0.024 -0.074 0.985 -0.066 -0.049Mn -0.371 0.809 0.398 -0.206 -0.029Fe 0.303 0.851 0.103 -0.057 0.054Cu 0.784 0.229 -0.079 -0.138 0.358Zn 0.795 0.001 -0.137 0.090 0.090

pH, EC, and WHC were the most responsible factors for minerals’ release in the treatment field. Therefore, the treatment field soil has the higher mineralization. These findings have been attributed with the study of Ghosh and Devi (2019).

Morphological changes in all the plants

The average plant height of control/ plant height of treatment (PHC/PHT), leaf number of control/leaf number of treatment (LFNC/LFNT), leaf length of control/leaf length of treatment (LLC/LLT), and leaf width of control/leaf width of treatment (LWC/LWT) were recorded at different time intervals. The obtained mean values were subjected to one-way ANOVA statistical analysis. The results are presented in Table 5. Results showed that all the morphological parameters of all the plants were gradually and significantly increased mainly in the treatment plot during the different time intervals. It is only possible due to the compost application to the plants. This compost helps in the improvement of soil fertility as it provides a suitable environment for several microbes, which are indirectly avail on plant growth. Compost also supports in minerals’ uptake process by the plants from the soil

(Noor et al. 2005). Therefore, PH, LFN, LL, and LW, all these parameters influenced significantly due to the application of compost in the treatment plot of all the plants (Walker and Bernal 2004; Noor et al. 2005).

Physio-chemical changes between the control and treatment group plants after harvesting

Independent t-test showed a difference in plant growth-related parameters between both treatments as well as a control group of cabbage. pH (control-13.18 ± 1.14 cm, treatment-31.67 ± 1.48 cm), LFN (control-14.33 ± 1.12 nos, treatment-17.17 ± 0.70 nos), LL (control-8.72 ± 0.50 cm, treatment-24.36 ± 1.01 cm), LW (control-5.06 ± 0.55 cm, treatment-21.13 ± 1.52 cm), SD (control-2.22 ± 0.14 cm, treatment-6.39 ± 0.23 cm), RL (control-10.42 ± 1.29 cm, treatment-16.43 ± 3.49 cm) were significantly (p<0.01) higher in treatment groups than the control group (Table 6).

International Journal of Recycling of Organic Waste in Agriculture (2020)9: 367-383 373

Group Time Plant height (cm) Leaf number/plant Leaf length (cm) Leaf width (cm)

Control 47 Days 7.53 ± 0.43a 6.29 ± 0.38a 4.40 ± 0.36a 2.59 ± 0.60b

62 Days 7.64 ± 0.45a 7.64 ± 0.44a 5.19 ± 0.28a 3.05 ± 0.21a

Cabbage

77 Days 8.06 ± 0.52a 8.71 ± 0.65a 6.27 ± 0.34a 3.33 ± 0.22a

92 Days 9.19 ± 0.57a 9.86 ± 0.77b 7.19 ± 0.48ab 3.88 ± 0.31a

107 Days 13.18 ± 1.14b 14.33 ± 1.12c 8.72 ± 0.50b 5.06 ± 0.55a

Treatment 47 Days 14.14 ± 1.53b 9.79 ± 0.58ab 12.96 ± 1.45b 7.97 ± 1.04b

62 Days 18.29 ± 1.36c 11.93 ± 1.20bc 15.21 ± 1.34b 10.82 ± 1.32b

77 Days 22.25 ± 1.14c 12.79 ± 0.61c 16.43 ± 1.34c 15.57 ± 1.37c

92 Days 22.82 ± 1.15d 13.36 ± 0.72c 20.67 ± 1.00c 17.71 ± 1.27c

107 Days 31.67 ± 1.48e 17.17 ± 0.70d 24.36 ± 1.01d 21.13 ± 1.52d

Control 47 Day 9.96±0.38a 6.00±0.35a 6.68±0.31a 2.56±0.12a

62 Day 11.07±0.37a 6.42±0.34ab 7.11±0.23ab 2.91±0.37a

77 Day 11.78±1.19ab 6.50±0.38ab 8.18±0.42b 3.11±0.19ab

92 Day 13.24±0.70b 7.25±0.41bc 9.84±0.73c 3.23±0.42ab

Cauliflower 107 Day 13.38±0.62b 7.75±0.39c 10.13±0.53c 3.93±0.34b

Treatment 47 Day 23.42±1.37a 8.08±0.48a 19.87±1.24a 9.69±0.61a

62 Day 31.19±1.03b 9.58±0.51a 25.08±1.16b 13.16±0.55b

77 Day 40.43±1.71c 9.67±0.43a 31.01±0.97c 13.22±0.55b

92 Day 40.77±1.187c 9.67±0.58a 32.45±1.88c 13.28±0.52b

107 Day 42.06±2.50c 12.08±0.66b 33.58±1.00c 13.80±0.79b

Control 47 Day 7.19±0.32a 6.00±0.30a 5.90±0.36a 2.08±0.08a

62 Day 9.59±0.66 a 6.83±0.30a 7.28±0.42a 2.23±0.11ab

77 Day 15.79±1.79a 7.33±0.33b 7.30±1.07b 2.50±0.30c

92 Day 57.84±5.73a 8.83±0.42a 9.89±1.09a 2.77±0.20abc

Radish 107 Day 84.61±7.62a 9.50±0.23b 13.68±0.98c 3.00±0.32bc

Treatment 47 Day 20.76±0.68a 6.50±0.36a 17.74±0.64a 5.53±0.15a

62 Day 28.24±1.22ab 7.25±0.58bc 20.80±0.95c 6.25±0.24a

77 Day 40.79±2.95b 8.42±0.58c 23.70±0.88c 6.35±0.29a

92 Day 88.13±8.17c 9.92±0.61c 24.65±1.68ab 6.59±0.26a

107 Day 114.67±5.93d 10.56±0.28ab 24.78±1.71bc 9.08±1.05b

Note: Means ± Standard error; One-way ANOVA; within every group within a column followed by the same letter are notsignificantly different (p<0.05).

Table 5 One-way ANOVA analysis to determine the morphological changes of all the plants during different time intervals

In cauliflower, pH (control-13.38 ± 0.62 cm, treatment-42.06 ± 2.50 cm), LFN (control-7.75 ± 0.39 nos, treatment-12.08 ± 0.66 nos), LL (control-10.13 ± 0.53 cm, treatment-33.58 ± 1.00 cm), LW (control-3.93 ± 0.34 cm, treatment-13.80 ± 0.79 cm), SD (control- 2.60

± 0.08 cm, treatment-6.86 ± 0.38 cm), RL (control-9.74 ± 0.28 cm, treatment-19.08 ± 1.37 cm), head width (HW) (control-4.35 ± 0.26 cm, treatment-114.19 ± 8.45 cm) were significantly (p<0.01) higher in treatment groups than the control group (Table 7).

International Journal of Recycling of Organic Waste in Agriculture (2020)9: 367-383374

Table 6 Effects of treatment on changes in morphological and chemical factors in cabbage after harvest

Lea

f rel

ativ

e

wat

er c

onte

nt

4.08

± 1

.73

11.7

7 ±

4.63

*

Not

e: *

, ***

sign

ifica

nt a

t p<0

.05

and

p<0.

01, S

tude

nt’s

t-te

st

Elec

troly

te le

akag

e

73.6

0 ±

13.8

6

47.7

9 ±

15.1

2***

Ash

con

tent

in le

af

4.33

± 1

.48

6.65

± 1

.03*

Stem

dia

met

er

2.22

± 0

.14

6.39

± 0

.23*

**

Roo

t len

gth

10.4

2 ±

1.29

16.4

3 ±

3.49

*

Leaf

wid

th

5.06

± 0

.55

21.1

3 ±

1.52

***

Leaf

leng

th

8.72

± 0

.50

24.3

6 ±

1.01

***

Leaf

num

ber

14.3

3 ±

1.12

17.1

7 ±

0.70

*

Plan

t hei

ght

13.1

8 ±

1.14

31.6

7 ±

1.48

***

Gro

up

Con

trol

Trea

tmen

t

Table 7 Changes of different parameters between the control and treatment group of cauliflower after harvest

Elec

troly

te

leak

age

48.9

1 ±

13.5

4

37.2

0 ±

3.95

***

Not

e: *

, ***

sign

ifica

nt a

t p<0

.05

and

p<0.

01, S

tude

nt’s

t-te

st.

Tot

al d

ry

mat

ter

0.81

±

0.09

2.58

±

0.26

***

Lea

f rel

ativ

e

wat

er c

onte

nt

0.71

±

0.05

0.90

±

0.02

*

Ash

con

tent

in h

ead

3.36

±

0.61

3.67

±

0.51

Ash

con

tent

in le

af

3.22

±

0.67

3.58

±

0.47

Hea

d w

idth

4.35

±

0.26

114

.19

±

8.45

***

Roo

t len

gth

9.74

±

0.28

19.0

8 ±

1.37

***

Ste

m

diam

eter

2.60

±

0.08

6.86

±

0.38

***

Leaf

wid

th

3.93

±

0.34

13.8

0±

0.79

***

Leaf

leng

th

12.

08 ±

0.66

***

33.5

8±

1.00

***

Leaf

num

ber

7.75

±

0.39

10.1

3 ±

0.53

Plan

t hei

ght

13.3

8 ±

0.62

42.

06 ±

2.50

***

Gro

ups

Con

trol

Trea

tmen

t

International Journal of Recycling of Organic Waste in Agriculture (2020)9: 367-383 375

In case of radish, pH (control-84.61 ± 7.62 cm, treatment-114.67 ± 5.93 cm), LFN (control-9.50 ± 0.23 nos, treatment-10.56 ± 0.28 nos), LL (control-13.68 ± 0.98 cm, treatment-24.68 ± 1.71 cm), LW (control-3.00 ± 0.32 cm, treatment-9.08 ± 1.05 cm), RD (control- 4.21 ± 0.33 cm, treatment-12.64 ± 0.75 cm), RL (control-17.06 ± 1.66 cm, treatment-23.51 ± 1.15 cm), RW (control-4.63 ± 0.77 cm, treatment-116.17 ± 13.88 cm) were significantly (p<0.01) higher in treatment groups than the control group (Table 8).

So, this is only possible due to the manure application to the plants. This manure helps in the improvement of soil fertility as it provides a suitable environment for several microbes, which are indirectly avail on plant growth. Manure also supports in minerals’ uptake process by the plants from the soil (Noor et al. 2005). Therefore, all these morphological parameters influenced significantly due to the application of prepared compost in the treatment plot (Walker and Bernal 2004; Noor et al. 2005). The concentration of starch and carbohydrates increased due to the availability of sufficient nutrients in prepared compost that might have increased stem diameter and fruit diameter. The results of the present investigation in terms of fruit diameter and stem diameter are in collaboration with the findings of Pawar et al. (2018). In cabbage, the ACL level in control group plants was 4.33 ± 1.48 %, where the ACL level in treatment plot soil was 6.65 ± 1.03 %, which was significantly (p<0.05) higher (Table 5). In cauliflower, ash content in head (ACH) (control- 3.22 ± 0.67 %, treatment-3.58 ± 0.47 %), ACL (control-3.67 ± 0.51 %, treatment-3.36 ± 0.61 %) was significantly (p<0.01) higher in treatment groups than the control group (Table 7). In radish, ash content in root (ACR) (control-4.49 ± 0.77 %, treatment-7.18 ± 1.34 %), ACL (control-3.66 ± 0.45 %, treatment-7.11 ± 0.99 %) was made up the total amount of non-combustible substances present in the plant product. Ash content of leaf of cabbage was significantly higher than the control group. The application of compost has no effective influence on the ash content of leaves. Total ash content in plants increased due to the higher accumulation of minerals like calcium, potassium, iron, etc. (Ooi et al. 2012). As the treatment plot has a higher mineral level, so our minerals result in justifying this finding. Therefore, prepared compost has a nutritive supportive role to the plants. There was a significantly (p<0.05) increase of LRWC (11.77 ± 6.63 %) in the treatment group than the control group (4.08 ± 1.73 %) of cabbage

Table 8 Changes of different parameters between the control and treatment group of radish after harvest

Ele

ctro

lyte

leak

age

41.0

9 ±

15.9

4

32.8

3 ±

6.84

***

Not

e: *

, ***

sign

ifica

nt a

t p<0

.05

and

p<0.

01, S

tude

nt’s

t-te

st

Tot

al d

ry

mat

ter

0.46

±0.

18

2.90

±

0.25

***

Lea

f rel

ativ

e

wat

er c

onte

nt

0.68

±0.

07

0.81

±0.

03*

Ash

con

tent

in le

af

3.66

±

0.45

7.11

±0.

99*

Ash

con

tent

in ro

ot

4.49

±0.

77

7.18

±1.

34*

Roo

t wid

th

4.63

±0.

77

116.

17 ±

13.8

8*

Roo

t len

gth

17.0

6 ±1

.66

23.5

1 ±

1.15

***

Roo

t

diam

eter

4.21

±0.

33

12.

64

±0.7

5***

Leaf

wid

th

3.00

±0.3

2

9.08

±

1.05

***

Leaf

leng

th

13.6

8 ±

0.98

24.7

8±

1.71

***

Leaf

num

ber

9.50

±0.2

3

10.5

6±0.

28*

Plan

t hei

ght

84.6

1±7.

62

114.

67±

5.93

***

Gro

ups

Con

trol

Trea

tmen

t

International Journal of Recycling of Organic Waste in Agriculture (2020)9: 367-383376

(Table 6). In cauliflower, there was significantly (p<0.05) increase of LRWC (0.90 ± 0.02 %) in treatment group than the control group (0.71 ± 0.05 %) (Table 7). In case of radish, there was significantly (p<0.05) increase of LRWC (0.81 ± 0.03 %) in treatment group than the control group (0.68 ± 0.07 %) (Table 8). Leaf relative water content is the measurement of water status, which is a vital indicator of water stress and drought tolerance in many crops (Soltys-Kalina et al. 2016). Significantly high leaf relative water content found in the treatment group than the control group. So, the cabbage treatment group has a more tolerant ability against drought stress. Therefore, higher LRWC in the plants of the treatment group is responsible for the higher yield in the treated plants. In cauliflower, TDM of treatment group (2.58 ± 0.26 %) was also significantly higher (p<0.01) than the control group plant (0.81 ± 0.09 %) (Table 7). However, in radish, TDM of treatment group (2.90 ± 0.25 %) was also significantly higher (p<0.01) than the control group plant (0.46 ± 0.18 %) (Table 8). Moisture content is correlated to dry matter of any products. The highest dry matter content in organic products explained by the fact that the lower nitrogen supplies under organic management. In this condition, generally, plants increased the synthesis of non-nitrogenous molecules like tend to enhance the synthesis of nitrogen-poor molecules polyphenols, cellulose, and starch. At this time, plants immediately shut down the synthesis of nitrogen-rich compounds. This phenomenon increased the dry matter content in the plants (Fjelkner-Modig et al. 2000; Herencia et al. 2011). The significantly higher level of TDM attributed to increased plant height coupled with higher stem diameter in both cauliflower and radish plants of treatment group (Krishnamurthy and Gururaj 1992). In cabbage, EL of treatment group (47.79 ± 15.12 %) was also significantly lower (p<0.01) than the control group plants (73.60 ± 13.86 %) (Table

6). There was a significant (p<0.01) decrease in EL (37.20 ± 3.95 %) in treatment group plants than the control group cauliflower plants (48.91 ± 13.54 %) (Table 7). Meanwhile, there was a significant (p<0.01) decrease in EL (32.83 ± 6.84 %) in treatment group plants than the radish control group (41.09 ± 15.94 %) (Table 8). Electrolyte leakage is a good indicator of cell death due to stress in plants. During cell death, K+ ions released in a higher amount. So, higher electrolyte leakage level indicates the higher stress level in plants (Leopold et al. 1981; Stevanovic et al. 1997). In this study, electrolyte leakage of treatment group plants of cabbage was significantly lower than the control group. So, it is indicating that the treatment group plants have fewer stress levels, and this is the main reason for the higher production in the treatment group.

Changes in antioxidant parameters of cauliflower and radish

Independent t-test showed changes in antioxidant parameters of cauliflower. It showed a statistically significant (p<0.05) changes. The application of this statistics showed a statistically decrease in DPPH, FRAP and ABTS level in treatment plot (2.55±0.16 %), (2.30±0.59 mgTE/100cm3) and (37.40±0.49 µmole/L), respectively than the DPPH, FRAP and ABTS level of control plot (4.19±0.12 %), (2.45±0.39 mgTE/100cm3) and (51.74±0.93 µmole/L), respectively (Table 9). In case of radish, FRAP, DPPH, and ABTS level (2.15±0.44 mgTE/100cm3), (4.92±1.66 %), and (50.80±0.92 µmole/L), respectively in treatment group plants showed a significantly (p<0.05) lower level than the control group plants (2.56±0.42 mgTE/100cm3), (7.82±1.37 %), and (51.78±0.86 µmole/L), respectively (Table 9).

Table 9 Difference of DPPH, FRAP and ABTS value control, and treatment group of cauliflower and radish

Plants Parameters Unit Control Treatment

CauliflowerABTS µmole/L 51.74 ± 0.93 37.40 ± 0.49*FRAP mg TE/100 cm3 2.45 ± 0.39 2.30 ± 0.59DPPH % 4.19 ± 0.12 2.55 ± 0.16*

RadishABTS µmole/L 51.78 ± 0.86 50.80 ± 0.92*FRAP mg TE/100 cm3 2.56 ± 0.42 2.15 ± 0.44*DPPH % 7.82 ± 1.37 4.92 ± 1.66*

Means bearing * signifies the difference in a row (p<0.05). Student’s t-test.

International Journal of Recycling of Organic Waste in Agriculture (2020)9: 367-383 377

The stress level in the plants identified by three different techniques like DPPH, FRAP, and ABTS were applied. All these techniques have different reactions mechanisms. FRAP assay revels with the electron transfer mechanism, but DPPH and ABTS test revel with the electron transfer as well as H atom transfer (Prior et al. 2005; Huang et al. 2005). In this study, all the antioxidant parameters showed a significantly lower level in cauliflower and radish of the treatment group. The higher level of ABTS, DPPH, and FRAP levels indicate a higher stress level in the living system (Jaganathan and Kumaravel 2016; Giri et al. 2019b). Therefore, plants of treatment group were in less stress level. This finding was also corroborative of the results of higher leaf relative water content and lower electrolyte leakage activity of treatment group plants (Table 6, 7, 8).

Effects of day, treatment, and their interaction on cabbage, cauliflower, and radish morphology

All the morphological parameters of the treatment group and the control group increased day by day. From this data set, it could not be concluded that the

growth of all the parameters might be due to the time interval or might be due to the compost treatment. This problem overcomes by; the morphological data set was executed through the two-way ANOVA test to determine the possible effect of the time interval, compost treatment, and their interaction effect responsible for the plant growth. Therefore, two-way ANOVA executed to visualize the relationship of day, compost treatment, and their interaction with plant height, leaf number, leaf length, and leaf width of the plant (Table 10 and Fig. 3, 4, 5). The results showed that the day of the experiment has significant effects on all the morphological characters at p<0.01. Compost treatment showed a significant impact on plant height, leaf number, leaf length, and leaf width at p<0.01 on the plant (Table 10 and Fig. 3, 4, 5). The interaction between the day of the experiment and treatment of the compost showed a significant effect on plant height, leaf number, leaf length, and leaf width at p<0.01 on both of the plants (Table 10 and Fig. 3, 4, 5). Higher loadings of SOM caused the higher mineralization and this might be increased after the effects of time. This result is in accordance with the previous report (Ali et al. 2018).

Table 10 Two-way ANOVA analysis for effects of the day, treatment, and their interaction on all the plant’s morphology

df-Degrees of freedom; F-F ratio; ***Significant at p<0.01

Pants SourcePlant height Leaf number Leaf length Leaf width

df F ratio df F ratio df F ratio df F ratio

Cabbage

Day (D) 4 175.581*** 4 52.178*** 4 216.918*** 4 209.128***

Treatment (T) 1 56.744*** 1 30.328*** 1 46.225*** 1 52.181***

D × T 4 10.131*** 4 3.986*** 4 14.475*** 4 4.305***

Cauliflower

Day (D) 4 799.622*** 4 146.918*** 4 1047.33*** 4 957.002***

Treatment (T) 1 25.518*** 1 15.217*** 1 28.07*** 1 9.141***

D × T 4 13.241*** 4 2.965*** 4 10.00*** 4 3.729***

Radish

Day (D) 4 3.984*** 4 30.677*** 4 405.062*** 4 284.043***

Treatment (T) 1 8.179*** 1 11.392*** 1 14.827*** 1 8.114***

D × T 4 0.077*** 4 0.823*** 4 1.871*** 4 4.340***

International Journal of Recycling of Organic Waste in Agriculture (2020)9: 367-383378

Fig. 3(A-D) Graphical representation of changes among the morphological parameters of cabbage

Fig. 4(A-D) Graphical representation of changes among the morphological parameters of cauliflower

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The yield of cabbage, cauliflower, and radish

As per the calculation, the total yield in the control group of cabbage was 0.0 t·ha-1, whereas, in the treatment group, it was 37.05 t·ha-1. Whereas the yield of cauliflower in the control group was 10.16 t·ha-1, and in the treatment group, it was 22.36 t·ha-1. In the case of radish, total yield in the control group was 7.30 t·ha-1, whereas, in the treatment group, it was 20.33 t·ha-1. The yield increment in percentages of cabbage, cauliflower, and radish was infinite %, 220.08 %, and 278.49 %, respectively. As the soil physicochemical properties showed that the application of the prepared compost improved the soil properties. The improved soil properties with higher organic matter supported the growth of cabbage. So, this is the main reason for the enhanced plant physio-chemical characteristics as well as cabbage yield, also (Fig. 6). Prepared compost helps in constructing the leaves of cabbage to form the cabbage head as it contains a higher level of zinc, copper, iron, manganese, etc. Among all of these, zinc and copper play a notable role in the development of cabbage head. As we found that the control plot has very less amount of zinc and copper and PCA analysis showed that minerals have the higher impact, therefore, it might be due to the deficiency of these minerals, the cabbage head was not formed in the control plot (Singh and Singh 2017).

Moreover, the application of compost increases soil fertility, which helps in the higher yield. Sometimes, the use of manure helps in the induction of hormonal activity in the plants and aids in nutrient uptake from the soil (Ali et al. 2018; Pankaj et al. 2018; Singh 2018).

Meanwhile, a higher level of NPK promotes plant growth, increases root development. Micronutrients help in maintaining the normal plant physiology with supporting leaf growth, shoot growth, ensured photosynthetic growth, etc. (Jamre et al. 2010; Lashkari et al. 2007; Singh 2003). Therefore, in our result, all these factors simultaneously increased the yield of cabbage, cauliflower and radish (Fig. 7). So, ultimately, the prepared compost has beneficial properties for the higher agricultural yield in this region.

Conclusion

Food wastage is a great concern throughout the globe. The conversion of food wastage to compost may reduce pollution and may be applicable for the higher yield of vegetables, crops, etc. The results of this present investigation revealed the effect of compost prepared from the food wastage as a convincing approach for the higher yield in this sub-tropical region of India. The yield increment in

Fig. 5(A-D) Graphical representation of changes among the morphological parameters of radish

International Journal of Recycling of Organic Waste in Agriculture (2020)9: 367-383380

Fig. 6 Comparative view of Cabbage after harvesting (Control group and Treatment group)

Control Group

Treatment Group

Fig. 7 Comparative view of Cauliflower and Radish during harvesting (Control group of Cauliflower and Radish in Left Column; Treatment group of Cauliflower and Radish in Right Column)

International Journal of Recycling of Organic Waste in Agriculture (2020)9: 367-383 381

percentages of cabbage, cauliflower, and radish was infinite %, 220.08 %, and 278.49 %, respectively. Therefore, the bio-conversion of food wastage should be encouraged in this low productive region due to poor soil fertility. The study also found that the application of bio-converted food wastage increased the agriculture yield after reducing the stress in plants, increase the availability of minerals in the soil for the plants’ uptake, as well as improving the soil health at this sub-tropical region of India.

Acknowledgments The authors are thankful to Vice-Chancellor

of Arni University, Himachal Pradesh, India, for financial support

and sanctioning the field for this study. We are also thankful

to Dr. Rajesh Kumar (HOD of Life Science Department, Arni

University) and Mrs. Indu Kumari (Research Associate, Life

Science Department, Arni University) for their continuous support

during the entire lab work at Arni University. We are grateful to

all the students of M.Sc. Zoology (4th and 2nd Semester, 2019) for

their constant support during the fieldwork. Corresponding author

is highly thankful to Dr. Avilekh (Program Coordinator, Dept. of

Science and Technology, Government of India, New Delhi) and

Dr. Geeta (Research Associate, DRDO-Defence Institute of High

Altitude Research, Chandigarh, India) for their statistical data

analysis input during the data analysis. Authors are grateful to

Dr. Somen Acharya (Scientist, DRDO-Defence Institute of High

Altitude Research, Chandigarh, India) for his kind help during the

minerals’ analysis by AAS.

Funding

This study was financially supported by Arni University, Himachal Pradesh, India, during the students’ Post Graduate dissertation work. University has no role during experimental work and designing of this study.

Compliance with ethical standards Conflict of interest The authors declare that there are no

conflicts of interest associated with this study.

Open Access This article is distributed under the terms of

the Creative Commons Attribution 4.0 International License

(http://creativecommons.org/licenses/by/4.0/), which permits

unrestricted use, distribution, and reproduction in any medium,

provided you give appropriate credit to the original author(s) and

the source, provide a link to the Creative Commons license, and

indicate if changes were made.

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