microalgae and biofuels: optimizing the culture …significant contribution to satisfy the primary...
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UNIVERSITÀ DEGLI STUDI DI TRIESTE
XXVI CICLO DEL DOTTORATO DI RICERCA IN BIOLOGIA AMBIENTALE
MICROALGAE AND BIOFUELS: OPTIMIZING THE CULTURE CONDITIONS OF SELECTED STRAINS TO
ENHANCE LIPID PRODUCTION. A PHYSIOLOGICAL AND BIOCHEMICAL APPROACH
Settore scientifico-disciplinare BIO 04 - FISIOLOGIA VEGETALE
DOTTORANDA
FRANCESCA BOLZAN
COORDINATORE
CHIAR.MO PROF. ALBERTO PALLAVICINI
SUPERVISORE DI TESI
DOTT.SSA ANNALISA FALACE
ANNO ACCADEMICO 2012 / 2013
Riassunto
La necessità di fonti d’energia che combinino sostenibilità ambientale, biodegradabilità,
bassa tossicità, rinnovabilità e una minore dipendenza dai derivati del petrolio, appare ai
giorni nostri piu urgente che mai. Basti pensare a come l’abuso dei combustibili fossili
abbia largamente contribuito all’eccesso di anidride carbonica nell’atmosfera, e quindi ai
cambiamenti climatici globali. Una di queste fonti d’energia è il biodiesel, un carburante
piu pulito del corrispettivo derivato del petrolio. Attualmente, le ricerche applicative
sull’utilizzo delle microalghe per la produzione di biocarburante sono avanzate ormai
ovunque nel mondo e si concretizzano attraverso la realizzazione di grandi vasche con
canali di scorrimento o di bioreattori all’aperto o al chiuso (in condizioni controllate),
sempre al fine di incrementare la biomassa. Inoltre, le microalghe hanno la capacità di
crescere rapidamente, sintetizzare ed accumulare grandi quantità (fino al 50% del peso
secco) di lipidi. Il successo e la sostenibilità economica del biodiesel, ovviamente
dipendono dalla selezione di appropriati ceppi algali.
E’ noto che la composizione biochimica delle microalghe può essere modulata
modificando le condizioni di coltura, quindi ai fini della produzione di biocarburanti su
larga scala, l’ottimizzazione dei parametri che favorisca l’incremento in biomassa e
l’accumulo di lipidi sembra essere la scelta vincente. Questo lavoro valuta l'impatto di tali
modulazioni, al fine di determinare se potenzialmente possano rendere le microalghe una
valida fonte di biodiesel a livello industriale.
To my Grandparents Elio and Angela and to Lila I don't know about heaven, but I do believe in angels
Acknowledgements
I would very much like to thank Dr. Marco Gray Grizon for being there when I really
needed.
An especial acknowledgment is for Dr Annalisa Falace to helping me to find my way.
A special thanks to Christian ‘the HPV-man’ Kranjec for his ‘British’ suggestions.
Contents
CONTENTS
Chapter 1 1
General Introduction - Biofuels and microalgae: a critical approach
Chapter 2 25
Microalgae for oil: strain selection
Chapter 3 41
Lipid extraction from microalgae: comparison of methods
Chapter 4 57
Optimizing the culture conditions for the lipid production in three selected algal strains
Chapter 5 93
General conclusions and future perspectives
Chapter 1
1
1
General introduction
Biofuels and microalgae: a critical approach
Chapter 1
3
BIOFUELS AND MICROALGAE: A CRITICAL APPROACH
Abstract Microalgae are increasingly seen as a potential alternative to traditional feedstocks for
biodiesel, which are limited and may have economic, social and environmental impacts.
However, processing microalgae for biofuels is remarkably different and poses significant
challenges in ensuring that they are competitive when compared with other feedstocks.
This article describes and critically analyses the main aspects and methods that can be
used for the downstream processing of microalgae for biodiesel production. A brief
analysis is made of the current and potential biodiesel production processes from
microalgae, focusing on their main advantages and problems.
Introduction The world has been confronted in recent decades with an energy crisis, associated with
irreversible depletion of traditional sources of fossil fuels; their use as major form of
energy is indeed unsustainable, also causing accumulation of greenhouse gases in the
atmosphere that bring about global warming. The increasing industrialization and
motorization of the world has led to a steep rise for the demand of petroleum-based fuels.
Today fossil fuels take up to 80% of the primary energy consumed in the world, of which
58% alone is consumed by the transport sector (Escobar et al., 2009). For this reason, it is
possible to conclude that fossil fuels are responsible for the emission of a significant
amount of pollutants in the atmosphere, including greenhouse gases. Furthermore,
petroleum diesel combustion is also a major source of other air contaminants including
NOx, SOx, COs, particulate matter and volatile organic compounds, which are adversely
affecting the environment and causing air pollution. Also, the sources of these fossil fuels
are becoming exhausted. With the urgent need to reduce carbon emissions, and the
dwindling reserves of crude oil, liquid fuels derived from plant material (also termed
biofuels) appear to be an attractive alternative source of energy.
Among many energy alternatives, biofuels, hydrogen, natural gas and syngas (synthesis
gas) may likely emerge as the four strategically important sustainable fuel sources in the
foreseeable future. Within these four, biofuels are the most environment-friendly energy
source. Biofuels are a favorable choice of fuel consumption due to their renewability,
biodegradability and acceptable quality of exhaust gases. They are non-toxic, free of
sulfur and carcinogenic compounds, and they contain oxygen in its molecule, making it a
Chapter 1
4
cleaner burning fuel than petrol and Diesel. Biodiesel production is expected to offer new
opportunities to diversify income and fuel supply sources, to promote employment in
rural areas, to develop long term replacement of fossil fuel and to reduce greenhouse gas
(GHG) emissions, boosting the decarbonisation of transportation fuels and increasing the
security of energy supply. Moreover, the key advantage of the utilisation of renewable
sources for the production of biofuels (Demirbas, 2008) is that the bioresources are
geographically more evenly distributed than fossil fuels; in this way the produced
bioenergy provides independence and security of energy supply.
Classification of Biofuels
Usually biofuels are classified according to their source and type. They can be solid, such
as fuelwood, charcoal, and wood pellets; or liquid, such as ethanol, biodiesel and
pyrolysis oils; or gaseous, such as biogas (methane).
Nigam and Singh (2011) have classified biofuels as primary and secondary type. The
primary biofuels are used in an unprocessed form (directly combusted) principally for
heating, cooking or electricity production such as fuelwood, wood chips and pellets, and
are those in which the organic matter is used essentially in its natural and non-modified
chemical form.
The secondary biofuels are modified primary fuels, which have been processed and
produced in a solid (e.g. charcoal), liquid (e.g. ethanol, biodiesel and bio-oil) or gaseous
form (e.g. biogas and hydrogen), which can be used for a wide range of applications,
including transport and various industrial processes. Secondary biofuels are further
divided into first, second and third generation biofuels on the basis of raw material and
technology used for their production (Fig. 1).
Chapter 1
5
Figure 1: Classification of Biofuels (Nigam and Singh, 2011).
The first-generation liquid biofuels are produced from sugars, grains or seeds. Bio-
ethanol made by fermenting sugar extracted from crop plants, and biodiesel produced
from straight vegetable oils of oleaginous plants (by transesterification processes or
cracking), are most well-known first-generation biofuels. Although biofuel processes
have a great potential to provide a carbon-neutral route to fuel production, first-generation
production systems have considerable economic and environmental limitations. The most
common concern is that as production capacities increase, so does their competition with
agriculture for arable land used for food production, and the utilization of only a small
fraction of total plant biomass reduces the land usage efficiency. The increased pressure
on arable land currently used for food production can lead to severe food shortages, in
particular for the developing world where already more than 800 million people suffer
from hunger and malnutrition (FAO, 2007). In addition, the intensive use of land with
high fertilizer and pesticide applications and water use can cause significant
environmental problems.
Chapter 1
6
Besides, Shenk et al. (2008) estimated that even if current oil-producing crops (Fig. 2)
would be grown on all arable land, these would be able to cover less than half of our
energy demand today, so biofuel production cannot contribute in any major way to global
fuel requirements. These limitations favor the search of non-edible biomass for the
production of biofuels.
Figure 2: Examples of first-generation biofuel crops. (a) Corn, (b) Wheat, (c) Oil-seed rape and (d) Tropical oil palm.
To become a more viable alternative fuel and to survive in the market, biodiesel must
compete economically with diesel. The end cost of biodiesel mainly depends on the price
of the feedstocks, that accounts for 60–75% of the total cost of biodiesel fuel (Canakci
and Sanli, 2008). In order to not compete with edible vegetable oils, the low-cost and
profitable biodiesel should be produced from low-cost feedstocks such as non-edible oils,
used frying oils, animal fats, soap-stocks, and greases. However, the available amounts of
waste oils and animal fats are not enough to match the today demands for biodiesel.
The advent of second-generation biofuels (Fig. 3) is intended to produce fuels from
lignocellulosic biomass, the whole plant matter of dedicated energy crops or agricultural
Chapter 1
7
residues, forest harvesting residues or wood processing waste, rather than from food
crops.
The major components of lignocellulosic feedstocks are cellulose and hemicellulose,
which can be converted into sugars through a series of thermochemical and biological
processes, and eventually fermented into bioethanol. In general, lignocellulosic resources
are short-rotation forestry crops (poplar, willow and eucalyptus), perennial grasses
(miscanthus, switch grass and reed canary grass) and residues from the wood industry,
forestry and from agriculture (Carriquiry et al., 2011). Biofuels produced from
lignocellulosic material generate low net GHG emissions, hence reducing environmental
impacts (Cherubini and Strømman, 2011).
Cellulose may be converted into ethanol along biological pathways using modified yeasts,
while biodiesel from ligno-cellulosic biomass is mostly obtained by gasification and
consecutive Fischer-Tropsch synthesis (de Vries et al., 2014).
It appears evident from literature that production of second-generation biofuels requires
most sophisticated processing production equipment, more investment per unit of
production and larger-scale facilities to confine and curtail capital cost scale economies.
At present, the production of such fuels is not cost-effective because there are a number
of technical barriers that need to be overcome before their potential can be realized (de
Vries et al., 2014).
Furthermore, the technology for conversion in the most part has not reached the scales for
commercial use, which has so far inhibited any significant exploitation (Brennan and
Owende, 2010).
Figure 3: Examples of second-generation biofuel feedstocks.
Chapter 1
8
Second-generation biofuels derived from non-food crops feedstock may also be
disadvantageous when replacing crops used for human consumption, or if its feedstocks
are cultivated in forest and other critical habitats with associated biological diversity.
Additionally, biodiesel needs to have lower environmental impacts and ensure the same
level of performance of existing fuels.
Therefore, on the basis of current scientific knowledge and technology projections, third-
generation biofuels specifically derived from microalgae are considered to be a viable
alternative energy resource that is devoid of the major drawbacks associated with first-
and second-generation biofuels. As seen before, conditions for a technically and
economically viable biofuel resource are that it should be competitive or, at least, cost
less than petroleum fuels; it should require low to no additional land use; it should enable
air quality improvement (e.g. CO2 sequestration) and it should require minimal water use.
Judicious exploitation of microalgae could meet these conditions and therefore make a
significant contribution to satisfy the primary energy demand, while simultaneously
providing environmental benefits (Wang et al., 2008; Khosla, 2009). Recent research
initiatives have proven that microalgal biomass appear to be one of the promising sources
of renewable biodiesel capable of meeting the global energy demand, and that it will also
not compromise production of food, fodder and other products derived from crops.
Furthermore, oil production from microalgae is clearly superior to that of palm, rapeseed,
soybean or Jatropha, and they are capable of synthesizing more oil per acre than any
terrestrial plant (Table 1).
Chapter 1
9
Table 1
Comparison of some sources of biodiesel
Crop Oil Yield (L/ha) Land area
needed (M ha)a
Percent of
existing US
cropping areaa
Corn 172 1540 846
Soybean 446 594 326
Canola 1190 223 122
Jatropha 1892 140 77
Coconut 2689 99 54
Oil palm 5950 45 24
Microalgaeb 136900 2 1,1
Microalgaec 58700 4,5 2,5
a For meeting 50% of all transport fuel needs of the US;
b 70% oil (by wt) in biomass;
c 30% oil (by wt) in
biomass. (Adapted from Chisty, 2007).
Biodiesel from microalgae
Microalgae are prokaryotic or eukaryotic photosynthetic microorganisms that can grow
rapidly and live in harsh conditions due to their unicellular or simple multicellular
structure. Using only sunlight and abundant and freely available raw materials (e.g. CO2
and nutrients from wastewater), algae can synthesize and accumulate large quantities of
neutral lipids and carbohydrates, along with other valuable co-products (e.g. astaxanthin,
Ω-3 fatty acids etc.).
Microalgae have high potential in biodiesel production compared to other oil crops.
Potentially, instead of microalgae, oil-producing heterotrophic microorganisms grown on
a natural organic carbon source such as sugar, can be used to make biodiesel; however,
heterotrophic production is not as efficient as using photosynthetic microalgae. This is
because the renewable organic carbon sources required for growing heterotrophic
microorganisms are produced ultimately by photosynthesis, usually in crop plants (Chisti,
2007).
Microalgae have the ability to grow rapidly (biomass doubling times during exponential
growth are commonly as short as 3.5h), and they synthesize and accumulate large
Chapter 1
10
amounts of neutral lipids, molecules that can be easily transesterified into biodiesel,
stored in cytosolic lipid bodies ( Hu et al., 2008). The fatty acid profile of the microalgal
cell is also relevant, because the heating power of the resulting biodiesel hinges upon that
composition (Amaro et al., 2011). Some species of diatoms and green algae have been
considered to be ideal sources of neutral lipids suitable for biodiesel production
(McGinnis et al., 1997; Illman et al., 2000). The critical starting point for this process is
identification of suitable algal strains that possess high constituent amounts of total lipids
in general, and neutral lipids in particular, and are capable of rapid accumulation of large
quantities of these molecules under various culture conditions. It was seen that under
optimal growth conditions, algae synthesize fatty acids principally for esterification into
glycerol-based membrane lipids, which constitute about 5–20% of dry cell weight
(DCW). Fatty acids include medium-chain (C10–C14), long-chain (C16–C18) and very-
long-chain (PC20) species and fatty acid derivatives. Under unfavorable environmental or
stress conditions for growth, many algae alter their lipid biosynthetic pathways towards
the formation and accumulation of neutral lipids (20–50% DCW), mainly in the form of
triacylglycerols (TAGs) (Singh et al., 2011). This was due to the shift in lipid metabolism
from membrane lipid synthesis to the storage of neutral lipids. De novo biosynthesis and
conversion of certain existing membrane polar lipids into TAGs may contribute to the
overall increase in TAGs. As a result, TAGs may account for as much as 80% of the total
lipid content in the cell (Suen et al., 1987; Tonon et al., 2002; Tornabene et al., 1983).
The utilization of microalgae for biofuels production can also serve other purposes. For
example they could remove CO2 from industrial flue gases by bio-fixation and reduce the
GHG emissions of a process while producing biodiesel. (Chisti, 2007; Wang et al., 2008;
Hossain and Salleh, 2008).
After oil extraction, the resulting algal biomass can be processed into ethanol, methane,
biohydrogen (Hossain and Salleh, 2008), livestock feed, used as organic fertilizer due to
its high N:P ratio, or simply burned for energy cogeneration (electricity and heat).
Furthermore, microalgae can be grown in areas unsuitable for agricultural purposes
independently of the seasonal weather changes, thus not competing for arable land use,
and can use wastewaters as the culture medium. Depending on the microalgae species,
other compounds may also be extracted, with valuable applications in different industrial
sectors, including a large range of fine chemicals and bulk products, such as fats,
polyunsaturated fatty acids (PUFAs), oil, natural dyes, sugars, pigments, antioxidants,
high-value bioactive compounds, and other fine chemicals and biomass (Li et al., 2008).
Chapter 1
11
For these reasons, microalgae can potentially revolutionize a large number of
biotechnology areas, including biofuels, cosmetics, pharmaceuticals, nutrition and food
additives, aquaculture, and pollution prevention.
Figure 4 shows a strategy for the production of algal biodiesel. At each stage, there are
many factors to be considered and optimized, including energy and material inputs (e.g.
nutrients, and energy for mixing during growth), and appropriate treatment of waste
products, such as spent media and residual biomass.
Figure 4: Algal biofuel pipeline, showing the major stages in the process, together with the inputs and
outputs that must be taken into consideration by life-cycle (Scott et al., 2010).
Choice of algal strain
A successful and economically viable algae-based oil industry depends on the selection of
appropriate algal strains. Bioprospection of strains is important to select the best strains
that can produce higher amounts of desired metabolic products (Araujo et al., 2011).
A multicriteria-based strategy ought thus to be considered when selecting a specific wild
microalgal strain, including a balance of growing rate, lipid quantity and quality, weak
response to environmental disturbances (e.g. temperature, nutrient input and light),
nutrient preference and rate of carbon, nitrogen and phosphorus uptake, which is
especially relevant when upgrade of brackish waters and agricultural effluents is sought
(Chisti, 2007; Li et al., 2008; Li et al., 2008a).
Chapter 1
12
Microalgal biomass production
Microalgae cultivation can be done in open culture systems and in highly controlled,
closed culture systems called photobioreactors (PBRs). Open systems can be divided into
natural waters (lakes, lagoons, ponds) and artificial ponds or containers, erected in very
different ways. Algae are grown in suspension with additional fertilizers. Gas exchange is
achieved via natural contact with the surrounding atmosphere and exposure to solar light.
Regarding the technical complexity, open systems such as the widespread raceway ponds
may vary considerably, but they are still much simpler than more recent closed systems
for the cultivation of microalgae.
Raceway ponds (Fig. 5) are the most commonly used artificial system, and they are made
of a closed loop recirculation channel that is typically about 0.3 m deep. Microalgae,
water and nutrients circulate around a race track. A paddlewheel is used to mix,
circulating the algal biomass and preventing sedimentation. The flow is guided around
bends by baffles placed in the flow channel.
Figure 5: Arial view and schematic view of a raceway pond (personal elaboration).
Open pond production does not necessarily compete for land with existing agricultural
crops, since they can be implemented in areas with marginal crop production potential
(Chisti, 2008). They also have lower energy input requirement, and regular maintenance
and cleaning are easier to perform; therefore, it may have the potential to return large net
energy production (Rodolfi et al., 2008).
The main disadvantage of open systems is that by being open to the atmosphere, they are
susceptible to weather conditions, not allowing control of water temperature, evaporation
Chapter 1
13
and lighting, and are also more susceptible to contaminations from other microalgae or
bacteria (Carvalho et al., 2006; Schenk et al., 2008).
However, raceways are perceived to be simpler and less expensive than photobioreactors,
because they cost less to build and operate. Although raceways are low-cost, they have a
low biomass productivity compared with photobioreactors (Chisti, 2007; Karthikeyan,
2012).
The use of natural conditions for commercial algae production has the advantage of using
sunlight as a free natural resource. However, for outdoor algae production systems, light
is generally the limiting factor (Pulz and Scheinbenbogan, 1998). In fact, primary
productivity can be limited by available sunlight due to diurnal cycles and the seasonal
variations, thereby restricting the viability of commercial production to areas with high
solar radiation. Some raceways were also designed with artificial light, but this design is
not practical and economically feasible for commercial production.
Bioreactors are closed systems of various shapes and sizes, in which a biological
conversion is achieved. Thus, a photobioreactor is a reactor in which phototrophs
(microbial, algal or plant cells) are grown or used to carry out a photo-biological reaction.
For continuous operation, correct amount of water, nutrients, air and carbon dioxide must
be provided. As algae grow, excess culture overflow and is harvested (Karthikeyan,
2012).
Most photobioreactors are designed as tubular reactors (Fig. 6), flat-panel reactors or
bubble column reactors.
Figure 6: Tubular photo-bioreactor (personal elaboration)
A tubular PBR consists of an array of straight transparent tubes that are usually made of
plastic or glass. This tubular array, or the solar collector, is where the sunlight is captured.
Chapter 1
14
Tube diameter is limited because light does not penetrate too deeply in the dense culture
broth that is necessary for ensuring a high biomass productivity for the PBR. Biomass
sedimentation in tubes is prevented by maintaining a highly turbulent flow generated by a
mechanical pump. Photobioreactors permit essentially single-species culture of
microalgae for prolonged durations, as the closed configuration makes the control of the
potential contamination easier (Chisti, 2007; Brennan and Owende, 2009).
In existing commercial applications, artificial light and sometimes heat are used. The
morphology of the PBR, its orientation and in particular the depth of the substrate are key
considerations, in order to allow sufficient light to penetrate the reactor. Poor design can
restrict light access and reduce areal productivity.
The PBRs have the advantages of high productivity, low contamination, efficient CO2
capture, continuous operation, and controlled growth conditions. The major drawbacks
are the high capital and operating costs. There are many design and operational
challenges which need to be resolved before commercial production of microalgae using
PBRs can be considered. Fouling and cleaning of both external and internal walls of the
PBR is a big trouble. Over time accumulation of dirt (external) or algae (internal) will
prevent light absorption. Mixing to ensure optimum photosynthetic efficiency is also a
major challenge. In order to maintain turbulent flow, energy needs to be supplied,
generally for pumping, or for sparging with gases (Bruton et al., 2009). Any parasitic
energy load needs to be minimized in order to keep a positive energy balance on the
overall process. Intermediate systems have also been designed, such as open ponds under
greenhouses allow a more controlled environment. In the same way, designers of
photobioreactors have reduced costs by using simple materials, such as transparent pipes,
using natural solar light and gravity feeding of the growth medium.
The large scale demand for microalgae may result in fertilizer shortages. At
concentrations below 0.2 µmol P/l, availability of phosphates in the culture medium will
be a growth-limiting factor. Equally nitrates availability will be a problem for growth
when concentrations are below 2 µmol N/l (Bruton et al., 2009). For diatoms, in addition
to N and P, silicate is essential. Silicon washed out from land to sea by freshwater run-off,
will be available in sufficient amounts under normal conditions. Silicon will be a limiting
factor for growth of diatoms in concentrations lower than 2 µmol Si/l. Carbon is a key
requirement, as the composition of microalgae is about 45% carbon. This is generally
supplied as CO2. For each kilogram of microalgae, at least 1.65 kg of CO2 are required
based on a mass balance (Berg-Nilsen, 2006).
Chapter 1
15
When natural constituents of algae cells are used, biomass generation by cultivation is
quite a straightforward process: light, nutrients and time are needed. If an increase of a
particular chemical compound is required, for instance lipids, specific growth conditions
should be applied. High oil content in algae is not a naturally occurring condition. This
may occur when algae are growing in particular stress condition (e.g. artificial nitrogen
starvation, high light irradiance, temperature, salinity, CO2 concentration etc). Excess
carbon is then stored in intracellular lipids. On the other hand, changing operating
conditions in large ponds is quite difficult (Bruton et al., 2009).
The main advantages and limitations of open ponds and PBR systems are summarized in
Table 2
Table 2
Advantages and disadvantages of open and closed algal cultivation plants (modified from
Grobbelaar, 2009).
Parameter Open ponds
(raceway ponds)
Closed systems
(PBR systems)
Contamination risk High Low
Water losses High Low
CO2 losses High Almost none
Reproducibility of production Variable but consistent
over time
Possible within
certain tolerances
Process control Complicated Less complicated
Standardisation Difficult Possible
Weather dependence High Less because protected
Maintenance Easy Difficult
Construction costs Low High
Biomass concentrations Low High
Closed photobioreactors have received major research attention in recent years. The noted
proliferation of pilot-scale production using PBRs compared to open raceway ponds
could be attributed to more rigorous process control and potentially higher biomass
production rates, hence, potentially higher production of biofuel and co-products
(Brennan and Owende, 2009).
Chapter 1
16
Lipid productivity
Microalgae have the ability to synthesize lipids that can be used for the production of
biodiesel. In nature, microalgal accumulation of lipids increases under certain conditions,
thus, when selecting and improving algae for high biodiesel production, it is important to
keep in mind the factors that lead to a natural accumulation of lipids in algae. Microalgae
are known to grow more abundantly in nutrient-rich (eutrophic) waters, leading
frequently to algal blooms. Once the algal population reaches its limits (either due to
nutrient depletion or high cell densities that limit light penetration) a large number of the
algal cells die. While many microalgae strains naturally have high lipid content (ca. 20–
50% dry weight), it is possible to increase the concentration by optimizing the growth
determining factors. The optimization of strain-specific cultivation conditions is of
confronting complexity, with many interrelated factors that can each be limiting. These
include temperature (Cho et al., 2007), mixing, fluid dynamics and hydrodynamic stress
(Barbosa et al., 2003), gas bubble size and distribution (Barbosa et al., 2004; Poulsen and
Iversen, 1999), gas exchange, mass transfer, light cycle and intensity (Grobbelaar et al.,
1996; Kim et al., 2006), water quality, pH, salinity (Abu-Rezq et al., 1999), mineral and
carbon regulation/bioavailability, cell fragility, cell density and growth inhibition (Schenk
et al., 2008).
However, increasing lipid accumulation will not result in increased lipid productivity, as
biomass productivity and lipid accumulation are not necessarily correlated. Lipid
accumulation refers to increased concentration of lipids within the microalgae cells
without consideration of the overall biomass production. Lipid productivity takes into
account both the lipid concentration within cells and the biomass produced by these cells
and is therefore a more useful indicator of the potential costs of liquid biofuel production
(Brennan and Owende, 2009).
An important feature of microalgae is the flexibility in controlling the composition of the
cultivated biomass using techniques such as stress levels and light control to achieve the
desired levels of lipids, proteins (e.g. from Spirulina), pigments (e.g. astaxanthin),
nutraceuticals (e.g. β-Carotene) and other products of interest. Thus, microalgal biomass
cultivated for its lipid content for conversion into biodiesel offers several choices for
obtaining additional commercially significant compounds. These include ethanol (low
conversion rates) and biogas. It is also possible to produce protein-rich feed for both
animal and human consumption (Bruton et al., 2009).
Chapter 1
17
Algal harvesting
Algal harvesting consists of biomass recovery from the culture medium, a procedure that
may contribute to 20–30% of the total biomass production cost (Molina Grima et al.,
2003). In order to remove large quantities of water and process large algal biomass
volumes, a suitable harvesting method may involve one or more steps, and be achieved in
several physical, chemical, or biological ways, in order to perform the desired solid-liquid
separation. Experience has demonstrated that albeit a universal harvesting method does
not exist, this is still an active area for research, being possible to develop an appropriate
and economical harvesting system for any algal species. Most common harvesting
methods include sedimentation, centrifugation, filtration, ultra-filtration, sometimes with
an additional flocculation step or with a combination of flocculation-flotation.
However, Sim et al. (1988) have observed that centrifugation gives good recovery and
thickened slurry, but it is energy intensive and the capital investment is high. Chemical
flocculation is more economical, but the use of toxic flocculants hinders the incorporation
of the final products/residuals into animal feed. Continuous filtration is more energy
efficient, economical and chemical-free, but algae size and morphology may be a
problem.
Richmond (2004) suggested one main criterion for selecting a proper harvesting
procedure, which is the desired product quality.
Normally harvesting of microalgae can be a single- or two-step process, which can
involve also dewatering of the biomass. The selection of harvesting process for a
particular strain depends on size (which can make it difficult to carry out) and properties
of the algal strain (Oilgae, 2010).
After harvesting and dewatering, the microalgae biomass still has about 80–85% water
(on a mass basis) (Cooney et al., 2009). Thus, an additional drying step may be required
to drive off the remaining water and leave the biomass at a minimum of 99% (w/w)
suspended solids.
Chapter 1
18
Extraction of lipids from microalgae
Extraction of microalgal lipids is an important process for the production of biodiesel.
Lipid extraction is performed by chemical methods in the form of solvent extractions,
physical methods or a combination of the two. Extraction methods used should be fast,
effective and non-damaging to lipids extracted, and easily scaled up (Rawat et al., 2010).
The solvent extraction was still the main extraction procedure used by many researchers
due to its simplicity and relatively inexpensive, requiring almost no investment for
equipment. The choice of solvent for lipid extraction, as with harvesting, will depend on
the type of the microalgae grown. Other preferred characteristics of the solvents are that
they should be inexpensive, volatile, non toxic, non polar and poor extractors of other
cellular components (Surendhiran and Vijay, 2012).
Although studies seem to indicate the feasibility of the new production processes, at least
from a laboratory and pilot project point of view, work on the implementation on the
industrial level is still lacking. Aspects that need to be further studied include: better
processes to purify biodiesel in order to meet the regulations, better ways to incorporate
biomass processing steps with the new biodiesel production processes, and a full
economic analysis of the new processes.
Biodiesel production
Biodiesel is typically a mixture of fatty acid alkyl esters, obtained from oils or fats,
which, when from plant or animal origin, are composed by 90–98% triglycerides, and
smaller amounts of mono- and diglycerides and free fatty acids, besides residual amounts
of phospholipids, phosphatides, carotenes, tocopherols, sulphur compounds and water
(Amaro et al., 2011). The transesterificationreaction needed to obtain biodiesel converts
triglycerides into fatty acid alkyl esters in the presence of an alcohol, such as methanol or
ethanol, and a catalyst, such as an alkali or acid, with glycerol as a byproduct (Vasudevan
and Briggs, 2008).
For user acceptance, microalgal biodiesel needs to comply with existing standards, such
as ASTM Biodiesel Standard D 6751 (United States) or Standard EN 14214 (European
Union). Microalgal oil contains a high degree of polyunsaturated fatty acids (with four or
more double bonds) when compared to vegetable oils, which makes it susceptible to
oxidation in storage and therefore reduces its acceptability for use in biodiesel. However,
Chapter 1
19
the extent of unsaturation of microalgal oil and its content of fatty acids with more than
four double bonds can be reduced easily by partial catalytic hydrogenation of the oil, the
same technology that is commonly used in making margarine from vegetable oils (Chisti,
2007). Nevertheless, microalgal biodiesel has similar physical and chemical properties to
petroleum diesel, first-generation biodiesel from oil crops and compares favourably with
the international standard EN14214 (Brennan and Owende, 2010).
Aim and outline of this work
This work addresses the issues related to the critical points that characterize the
exploitation of photoautotrophic microalgae in the production of biofuels, in particular of
biodiesel.
Chapter 2 underlines the key characteristics that must be taken into account when
choosing microalgal strains to be employed on industrial scale.
One of the major critical points in the strain screening process is that currently known
methods for the estimation of microalgal lipid are laborious and time-consuming. The
purpose of Chapter 3 is to compare the efficiency of several popular lipid extraction
methods. In this chapter it is also investigated the effect of ultra-sonication pre-treatment
on these extraction procedures.
Finally, Chapter 4 stresses the impact of culture conditions on biomass production and
lipid productivity. The parameters investigated in this chapter are culture mixing and
monochromatic lights.
Chapter 1
20
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Chapter 2
25
2
Microalgae for oil: strain selection
Chapter 2
27
MICROALGAE FOR OIL: STRAIN SELECTION
Abstract
Climate change mitigation, economic growth and stability, and the ongoing depletion of
oil reserves are all major drivers for the development of economically rational, renewable
energy technology platforms. Microalgae have re-emerged as a popular feedstock for the
production of biofuels and other more valuable products. Microalgae have the ability to
grow rapidly, synthesize and accumulate large amounts (approximately 20–50% of dry
weight) of lipids. A successful and economically viable algae-based oil industry depends
on the selection of appropriate algal strains. High lipid productivity is a key desirable
characteristic of a species for biodiesel production. The importance of lipid productivity
as a selection parameter over lipid content and growth rate individually is demonstrated.
Introduction
Biofuels are currently receiving much attention due to their potential as a sustainable and
environmentally friendly alternative to petrodiesel. Biodiesel, as derived from microalgae
lipids, has become a focal area of contemporary, global biotechnological research as it
holds the potential to provide a scalable, low-carbon, renewable feedstock without
adversely affecting the supply of food and other crop related products. Due to their simple
cellular structure, microalgae have higher rates of biomass and oil production than
conventional crops (Becker, 1994). Some species of algae produce large quantities of
vegetable oil as a storage product, regularly achieving 50% to 60% dry weight as lipid
(Sheehan et al., 1998).
Furthermore, since atmospheric CO2 accumulation has a serious effect on the global
environment, the control of total CO2 emission into the atmosphere is considered to be an
important issue related to the biosphere. Marine microalgae are expected to play an
important role in resolving this problem because they have a high capability for
photosynthesis and grow well in the sea, which solubilises a high amount of CO2, and
which accounts for 70% of the surface area of the earth.
The advantages of microalgae over higher plants as a source of transportation biofuels are
numerous: (1) oil yield per area of microalgae cultures could greatly exceed the yield of
the best oilseed crops (see Table 1); (2) microalgae grow in an aquatic medium, but need
less water than terrestrial crops; (3) microalgae can be cultivated in seawater or brackish
water on non-arable land, and do not compete for resources with conventional agriculture;
Chapter 2
28
(4) microalgae biomass production may be combined with direct bio-fixation of waste
CO2 (1 kg of dry algal biomass requiring about 1.8 kg of CO2); (5) fertilizers for
microalgae cultivation (especially nitrogen and phosphorus) can be obtained from
wastewaters; (6) algae cultivation does not need herbicides or pesticides; (7) the residual
algal biomass after oil extraction may be used as feed or fertilizer, or fermented to
produce ethanol or methane (Rodolfi et al., 2008).
Table 1: Comparison between different biodiesel sources. Modified from Chisti, 2007.
a 70% oil (by wt) in biomass. b 30% oil (by wt) in biomass.
The first step in developing an algal process is to choose the algal species. Pulz and Gross
(2004) observed that: “successful algal biotechnology mainly depends on choosing the
right alga with relevant properties for specific culture conditions and products”. Rigorous
selection is challenging owing to the large number of microalgal species available, the
limited characterization of these algae and their varying sets of characteristics.
Microalgae come in a variety of strains, each having different proportions of lipid,
protein, and carbohydrates contents. As shown in Table 2, under normal conditions some
microalgae have high lipids content such as Nannochloropsis sp., and others have high
protein contents like Chlorella vulgaris, while others have high carbohydrates content
like Porphyridium cruentum.
Chapter 2
29
Table 2: Chemical composition of various microalgae (adapted from Razeghifard, 2013).
n.a. not available a Values are for two types
of reactors used
From over a thousand collected, screened, and characterized microalgae, selection of the
most suitable strain for biodiesel production needs certain parameters evaluation. These
parameters include oil content, growth rate and productivity, strain adaptability, and
withstanding to different weather conditions such as temperature, salinity, pH, and high
CO2 sinking capacity and provide valuable co-products (Brennan and Owende, 2010).
Oleaginous algae can be found among diverse taxonomic groups, and the oil content may
vary noticeably among individual species or strains within and between taxa. Thus, right
strain selection is critical.
Chapter 2
30
Table 3: Oil content in some microalgae (adapted from Satyanarayana et al., 2011)
As shown in Table 3, few differences are apparent among various species, and even
within the same genus. The oil content is maximum in Botryococcus braunii, but the
associated productivity is poor. However, under adverse environmental conditions, it has
been shown to produce large quantities (up to 80% DCW) of very-long-chain (C23–C40)
hydrocarbons, similar to those found in petroleum, and thus Botryococcus has been
explored over the decades as a feedstock for biofuels and biomaterials (Metzger and
Largeau, 2005).
Rodolfi et al. (2008) tested thirty microalgal strains for their lipid production by
evaluating biomass productivity and lipid content. They found that these two parameters
were usually inversely related, a fact that has its rationale in the high metabolic cost of
Chapter 2
31
lipid biosynthesis; therefore, the best strain is the one that showed the best combination
among the two (see table 4).
Table 4: Biomass productivity, lipid content and lipid productivity of microalgal strains (adapted from Rodolfi et al., 2008).
Analyzing the two tables, it appears that the most common microalgae (i.e. Chlorella,
Dunaliella, Isochrysis, Nannochloris, Nannochloropsis, Neochloris, Nitzschia,
Phaeodactylum and Porphyridium spp.) possess oil levels between 20 and 50% (DW),
and exhibit reasonable productivities; Chlorella appears indeed a particularly good option
for biodiesel. Furthermore, of the thousand strains examined, green algae represent the
largest taxonomic group from which oleaginous candidates have been identified.
Probably, this fact is because many green algae are ubiquitous in diverse natural habitats
and, generally, grow faster than species from other taxonomic groups under laboratory
Chapter 2
32
conditions (Hu et al., 2008). On the other hand, marine microalgae are more appropriate
for large-scale production because their lipid productivities are consistently higher;
furthermore, in open culturing systems, high salinity prevents extensive contamination
and circumvents the need for fresh water. In this case, selection of fast-growing,
productive strains, optimised for the local climatic conditions is of fundamental
importance to the success of any algal mass culture, and particularly for low-value
products such as biodiesel. Fast growth encourages high biomass productivity. High
biomass density increases yield per harvest volume and decreases cost. High growth rate
also reduces contamination risk owing to out-competition of slower growers in
planktonic, continuous culture systems. A high content of the desired product increases
the process yield coefficient and reduces the cost of extraction and purification per unit
produced (Borowitzka, 1992).Growth rate and oil content (in % DW) have been the two
most studied parameters in the search for the success of large-scale cultivation of
microalgae for biofuels production (Griffiths and Harrison, 2012). However, fast growth
only rarely correlates with high lipid productivity. Lower growth rates and/or small cell
size contribute to lower the biomass productivity, even when the lipid content is high
(Rodolfi et al., 2008). Therefore, biomass yields may be considered as an adequate
criterion for biodiesel production only when associated with lipid productivity (Griffiths
and Harrison, 2012).On the other hand, generally, higher oil strains grow slower than low
oil strains. This is due to slow reproduction rate as a result of storing energy as oil and not
as carbohydrates (Vasudevan and Briggs, 2008). In addition, it should be taken into
consideration that some microalgae contain high levels of unsaturated fatty acids, which
reduce the oxidative stability of the biodiesel produced (Santos et al., 2009).
Culture conditions
The interest in microalgae for oil production is due to the high lipid content of some
species, and to the synthesis mainly of non-polar triacylglycerols (TAGs), which are the
best substrate to produce biodiesel.
Synthesis and accumulation of large amounts of TAGs accompanied by considerable
alterations in lipid and fatty acid composition occur in the cell when oleaginous algae are
placed under stress conditions imposed by chemical or physical environmental stimuli,
either acting individually or in combination. The major chemical stimuli are nutrient
Chapter 2
33
starvation, salinity and growth-medium pH. The major physical stimuli are temperature
and light. In addition to chemical and physical factors, growth phase and/or aging of the
culture also affect TAGs content and fatty acid composition.
Under optimal conditions of growth, algae synthesize fatty acids principally in form of
glycerol-based membrane lipids, which constitute about 5–20% of their dry cell weight.
Under unfavourable environmental or stress conditions instead, many algae alter their
lipid biosynthetic pathways towards the formation and accumulation of neutral lipids (20–
50% DCW), mainly in the form of TAGs (Huang et al., 2010). Several species of
microalgae can be induced to overproduce specific lipids and fatty acids through relative
simple manipulations of the physical and chemical properties of their culture medium. By
manipulating fatty acid content, microalgae represent a significant source of unusual and
valuable lipids and fatty acids for numerous industrial applications (Behrens and Kyle,
1996).
The effects of different cultivation factors on algal growth have been examined by
various authors.
Liu et al. (2008) showed that high iron concentration could induce considerable lipid
accumulation in marine strain Chlorella vulgaris. This suggests that some metabolic
pathways related to the lipid accumulation in C. vulgaris are probably modified by high
level of iron concentration in the initial medium. A significant increase in lipid
productivity as the result of accumulation of TAGs with saturated and monounsaturated
fatty acids was obtained under N-deprivation in nine strains (Breuer et al., 2012).
Achieving high lipid content without a significant decrease in the growth requires
different levels of N-stress in different species. While high N-stress is needed in some
species such as Neochloris oleoabundans and Scenedesmus dimorphus to increase the
lipid productivity, a low level of N-stress was more effective for Chlorella vulgaris and
Chlorococcum oleofaciens (Adams et al. 2013). Scenedesmus obliquus and Chlorella
zofingiensis were found to be the most promising strains for TAG production since they
accumulated TAGs as much as 35% of their dry weight with a productivity of 250–320
mg L-1
day-1
(Breuer et al. 2012).
Based upon the algal species/strains examined, it appears, with a few exceptions, that low
light induces the formation of polar lipids, in particular membrane polar lipids associated
with the chloroplast, whereas high light intensity decreases total polar lipid content with a
concomitant increase in the amount of neutral storage lipids, mainly TAGs (Brown et al.,
1996; Khotimchenko and Yakovleva, 2005; Napolitano, 1994). The fatty acid profile of
Chapter 2
34
the microalgal cell is also relevant, because the heating power of the resulting biodiesel
hinges upon that composition; most of the mentioned moieties are saturated and
unsaturated fatty acids containing 12–22 carbon atoms, often of the x3 and x6 types.
Thomas et al. (1984) analyzed the fatty acid compositions of seven fresh water microalgal
species; all of them could synthesize C14:0, C16:0, C18:1, C18:2 and C18:3 fatty acids –
whereas the relative contents of other fatty acid residues were species-specific, e.g. C16:4
and C18:4 in Ankistrodesmus sp., C18:4 and C22:6 in Isochrysis sp., C16:2, C16:3 and
C20:5 in Nannochloris sp., and C16:2, C16:3 and C20:5 in Nitzschia sp. Note that
different nutritional and processing factors, cultivation conditions and growth phases will
likely affect the fatty acid composition of microalgae: e.g. nitrogen deficiency and salt
stress induced accumulation of C18:1 in all species, and of C20:5 to a lesser extent in B.
braunii. (Amaro et al., 2011).
Microalgal molecular biology and genetic engineering
There are currently intensive global research efforts aimed at increasing and modifying
the accumulation of lipids, alcohols, hydrocarbons, polysaccharides, and other energy
storage compounds in photosynthetic organisms, yeasts, and bacteria through genetic
engineering. Many improvements have been realized, including increased lipid and
carbohydrate production, improved H2 yields, and the diversion of central metabolic
intermediates into fungible biofuels.
Furthermore, significant advances in microalgal genomics have been achieved during the
last decade. Expressed sequence tag (EST) databases have been established; nuclear,
mitochondrial, and
chloroplast genomes from several microalgae have been sequenced; and several more are
being sequenced. However, genetic engineering of algae to improve fuel feedstock
production phenotypes is still in its infancy. Most advances in the genetic engineering of
carbon storage pathways in algae have been achieved in Chlamydomonas reinhardtii but
molecular and genetic methods have been developed for other algal model species (Li et
al., 2010; Wang et al., 2009). Genome sequence information is currently available for
several eukaryotic algae, including the red microalga Cyanidioshyzon merolae, two
marine diatoms Thalassiosira pseudonana and Phaeodactylum tricornutum, several green
microalgae and some marine picoeukaryotes of the class Prasinophyceae.
Chapter 2
35
Understanding microalgal lipid metabolism is of great interest for the ultimate production
of diesel fuel surrogates. Both the quantity and the quality of diesel precursors from a
specific strain are closely linked to how lipid metabolism is controlled. Lipid biosynthesis
and catabolism, as well as pathways that modify the length and saturation of fatty acids,
have not been as thoroughly investigated for algae as they have for terrestrial plants
(Khozin-Goldberg and Cohen, 2011). However, many of the genes involved in lipid
metabolism in terrestrial plants have homologues in the sequenced microalgal genomes.
Therefore, it is probable that at least some of the transgenic strategies that have been used
to modify the lipid content in higher plants will also be effective with microalgae
(Radakovits et al., 2010). Furthermore, it is also reasonable to attempt to increase the
quality of the lipids in the process of engineering microalgae for an increased lipid
production, with regard to suitability as a diesel fuel feedstock. There are several acyl-
ACP thioesterases from a variety of organisms that are specific for certain fatty acid chain
lengths, and transgenic overexpression of thioesterases can be used to change fatty acid
chain length.
In addition, Acyl-CoA-dyacylglycerol acyltransferases (DGATs) have been demonstrated
to play an important role in the accumulation of TAG compounds in higher plants. It has
been identified as one of the key enzymes of the Kennedy pathway. In recent years it has
been suggested numerous times that the genetic engineering of a key factor of the lipid
production pathways, like the DGAT genes, could be a promising approach to increase
the cellular lipid content in microalgae, e.g. for more efficient biofuels production (Chisti,
2008; Courchesne et al., 2009; Work et al., 2011; Yu et al., 2011).
On this basis, genetic engineering can improve all aspects of algal production and
processing for enhanced biodiesel capabilities, but many ethical barriers need to be
overcome. For this reason, it will be necessary to evaluate the consequences from an
environmental point of view before proceeding to an industrial exploitation of enhanced
algae.
Chapter 2
36
Conclusions
Recent soaring oil prices, diminishing world oil reserves, and the environmental
deterioration associated with fossil fuel consumption have generated interest in using
algae as an alternative and renewable feedstock for fuel production. However, before this
concept can become a commercial reality, many fundamental biological questions
relating to the right strain selection, biosynthesis and regulation of fatty acids and TAG in
algae need to be answered. Clearly, physiological and genetic manipulations of growth
and lipid metabolism must be readily implementable, and critical engineering
breakthroughs related to algal mass culture and downstream processing are necessary to
produce low-cost biodiesel.
Chapter 2
37
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Chapter 3
41
3 Lipid extraction from microalgae: comparison of
methods
Chapter 3
43
LIPID EXTRACTION FROM MICROALGAE: COMPARISON OF METHODS
Abstract
Identification of novel microalgal strains with high lipid productivity is one of the most
important research topics in renewable biofuel research. However, the major critical point
in the strain screening process is that currently known methods (i.e. gas chromatography,
gravimetric method and staining with lipophilic fluorescent dye) for the estimation of
microalgal lipid are laborious and time-consuming. A colorimetric sulfo-phospho-vanillin
(SPV) method was developed for high-throughput quantitative analysis of total lipids. It
requires smaller amounts of sample compared to gravimetric methods for accurate
quantification and can also provide data on precise lipid composition. Also, this method is
applicable to a wide range of microalgae, from freshwater to marine species. Cell
disruption can increase the efficiency of total lipids extraction from microalgae, enabling
further conversion into biodiesel. The results showed that the sonication-assisted method
was efficient for lipid extraction in all samples, suggesting a favourable potential for
biodiesel production.
Introduction
Due to the limited stocks of fossil fuels and the increasing emission of greenhouse gas
(GHG) carbon dioxide into the atmosphere from the combustion of fossil fuels, research
has begun to focus on alternative biomass-derived fuels. One promising source of
biomass for alternative fuel production is represented by microalgae. This
microorganisms have the ability to grow rapidly, and synthesize and accumulate large
amounts of neutral lipids (mainly in the form of triacylglycerols, TAGs), which are stored
in cytosolic lipid bodies (Day et al.,1999; Chisti, 2007; Hu et al., 2008; Chisti, 2008). It
was seen that their high photosynthetic rates, often ascribed to their simplistic unicellular
structures, enable microalgae to rapidly accumulate lipids in their biomass (up to 77% of
dry cell mass), therefore they are predicted to produce about 10 times more biodiesel per
area unit of land than a typical terrestrial oleaginous crop (Chisti, 2007; Sheehan et al.,
1998; Rosenberg et al., 2008; Shenk et al., 2008). However, the selection and successful
outdoor large-scale cultivation of a robust microalgal strain, which has optimum neutral
lipid content, possesses a high growth rate, and is immune towards invasion by local
microbes, remain a major upstream challenge (Sheehan et al., 1998). Furthermore, the
Chapter 3
44
development of an effective and energetically efficient lipid extraction process from the
microalgal cells is critical for a successful upscaling of the downstream processes.
Lipids, defined as any biological molecule containing fatty acids, can generally be
classified into neutral and polar, based on the polarity of the molecular head group. The
former class comprises acylglycerols and free fatty acids, while the latter is categorized
into phospholipids and glycolipids. Neutral lipids are used primarily in the microalgal
cells as energy storage, while polar lipids are common membrane components.
Acylglycerol consists of fatty acids ester-bonded to a glycerol backbone and is
categorized according to its number of fatty acids (i.e. monoacylglycerols, diacylglycerols
and triacylglycerols).
A fundamental characteristic for biodiesel production is the suitability of lipids in terms
of the type and amount produced by an algal species, e.g. chain length, degree of
saturation and proportion of total lipid made up by triglycerides. These parameters
influence the quality of biodiesel produced. The majority of lipid-producing algal species
have a similar lipid profile, generally equivalent to vegetable oil from land plants suitable
for biodiesel production (Xu et al. 2006). The starting point for this process is
identification of suitable algal strains that possess high constituent amounts of total lipids
in general, and neutral lipids in particular, and are capable of rapid accumulation of large
quantities of neutral lipids under various culture conditions.
The composition and fatty acid profile of lipids extracted from a particular species is
further affected by the microalgal life cycle, as well as the cultivation conditions, such as
medium composition, temperature, illumination intensity and/or quality and ratio of
light/dark cycle (Guzman et al., 2010; Ota et al., 2009; Ramadan et al., 2008). For
example, Dunstan et al. (1993) observed that microalgal cells harvested during the
stationary phase have a lower polar lipid content if compared to cells of the same species
harvested during the logarithmic phase. On the other hand, when comparing lipids
obtained from logarithmic and stationary growth phase, stationary-phased lipids, despite
having an abundance of polar lipids at 51-57 wt%, contain higher levels of TAGs (20-41
wt% of total lipid) and appear more attractive for biodiesel processing than logarithmic-
phased lipids.
Numerous methods are used to assay microalgal lipid content, but there is little consensus
on the best methods for total lipid or fatty acid determination. Most studies have used
solvent extraction to remove lipids from the cells, typically based on the Folch (1957) or
Bligh and Dyer (1959) methods. However, Griffiths et al. (2010) recognised that these
Chapter 3
45
methods often extract lipids incompletely, particularly free fatty acids, and can extract
significant quantities of non-nutritive, non-saponifiable material such as pigments.
Moreover, quantification of neutral lipids requires the separation of the crude extracts and
quantification of the lipid fractions by thin-layer chromatography (TLC), high
performance liquid chromatography (HPLC) or gas chromatography (GC). The procedure
used for lipid analysis must ensure complete extraction and at the same time avoid
decomposition and/or oxidation of the lipid constituents. A major drawback of the
conventional method is that it is time-consuming and labour-intensive, making it difficult
to screen large numbers of algae.
Spectrofluorometric analysis of lipids is a high-throughput quantitative approach
originally developed by Greenspan et al. (1985). This method utilizes the fluorescent dye
Nile red, but environmental factors and other components (proteins and pigments) can
interfere with the assay and the fluorescence intensity may vary between samples
(Kimura et al., 2004; Mishra et al., 2014). Furthermore, broad-spectrum lipid
quantification assay is not possible using lipophilic dyes, since correlation between
fluorescence intensity and actual lipid content can vary among different strains. This
primarily is due to the fact that the strains with greater cell wall thickness have lower
staining efficiency (Mishra et al., 2014).
A methodology for the rapid, simple and colorimetric quantification of lipids from algal
cultures is the sulfo-phospho-vanillin assay (SPVA) developed by Chabrol et al., (1937)
and modified by Knight et al. (1972). In this assay, TAGs are hydrolysed by sulfuric acid
producing fatty acids, whose double bonds or hydroxyl groups react with the sulfuric acid
to form an alkenyl cation (which is the chromogen). The alkenyl cation then reacts with
the vanillin reagent (an aromatic hydrocarbon)
to form a chromophore with maximum
absorbance at 530 nm (Johnson et al., 1977).
The SPV method possesses many advantages:
for instance, it requires a small amount of
sample and requires less time and less labor
when a large number of samples is analyzed.
The colouring developed during the reaction
can be read and compared very easily (Fig. 1)
(Han et al., 2011; Mishra et al., 2014).
Figure 1: SPV method: coloration developed during the reaction.
Chapter 3
46
Due to the thick cell wall of several microalgae (in particular green algae) that blocks the
release of intra-lipids (Chen et al., 2009), it is necessary to use different methods apart
from the traditional mechanical press to get high yields in lipid extraction. An efficient
extraction requires that the solvent penetrates completely into the biomass and has a
connection corresponding to the polarity of the target compound, thus physical contact
between the material and the lipid solvent is related to the successful extraction. One way
to facilitate contact between the solvent and lipids is through cell rupture (Cooney et al.,
2009; Samarasinghe et al., 2012) using mechanical or non-mechanical techniques,
improving the extraction rate. Ultrasonication, microwave, bead mill and autoclave pre-
treatment are commonly used methods to promote vegetable cell disruption, and have
been tested in pure cultures of microalgal cells (Halim et al., 2012; Lee et al., 2010).
Sonication has the advantage of being able to disrupt the cells at relatively low
temperatures when compared to microwave and autoclave, and could be an effective
treatment for breaking up the rigid cell envelopes of microalgae. Intense sonication of
liquids generates sound waves that propagate into the liquid media, resulting in
alternating high-pressure and low-pressure cycles. During the low-pressure cycle, high-
intensity small vacuum bubbles are created in the liquid. When the bubbles attain a
certain size, they collapse violently during a high-pressure cycle. This is called cavitation.
During the implosion very high pressures and high speed liquid jets are produced locally.
The resulting shear forces break the cell structure mechanically and improve material
transfer (Jeon et al., 2013). This effect supports the extraction of lipids from algae.
The aim of this paper is to compare some well-known lipid extraction methods and to
verify any improvement of their efficiency employing an ultrasonication pretreatment.
Material and Methods
Dunaliella tertiolecta Butcher (Fig. 2) used in the
experiments was from a single batch, incubated in 3-liter
Erlenmeyer flasks containing autoclaved f/2 medium
(Guillard & Ryther, 1962; Guillard, 1975). Culture was
grown at 22±1°C under 40 µmol photons m-2
sec-1
(Sylvania
Aquastar, 36W, 10.000K and Osram Lumilux De Luxe 12-
950, 36W, 5.400K, 98Ra) on 14:10 h L:D cycles. Figure 2: Dunaliella tertiolecta batch culture.
Chapter 3
47
Growth rate
For the estimation of cellular density and growth rate, a standard curve of absorbance
versus cell number was established. The culture (0.1 ml) was harvested and the cell
density was immediately determined using the Bürker counting chamber at the inverted
microscope. These cell densities were plotted against the corresponding turbidity values,
obtained spectrophotometrically (Jenway 7315 UV/VIS Spectrophotometer, Staffordshire,
UK) at a wavelength of 680 nm. The equation of the line of the standard curve was then
used to convert absorbance of samples into cell number (R2
= 0.999).
For all experiments, the culture was harvested towards the beginning of the stationary
phase and the optical density measured was 0.7, i.e. linear equivalent to a 4.5×106 cells
ml−1
.
Analytical Reagents
All organic solvents (chloroform, methanol and diethyl ether were analytical grade from
Sigma-Aldrich (USA). As a lipid standard, a solution of triolein (1,2,3-Tri(cis-9-
octadecenoyl)glycerol) (Sigma-Aldrich) was used. MilliQ water from a Millipore system
was used for all analyses.
Lipid analysis
Gravimetric method
For Soxhlet extraction, 500 ml sample were centrifuged
at 3000×g for 10 min, then the water was removed and
the pellet was placed in a freeze dryer. 1 g of dried algal
material was transferred in a cellulose thimble and
placed in the extraction chamber. The Soxhlet
apparatus (Fig. 3), fitted with a condenser, was
mounted on a distillation flask containing diethyl ether.
The sample was thus extracted under reflux during 4 h.
Thereafter, the cellulose cartridge was cooled to room
temperature in a desiccator and its content was then
milled before being transferred again in the thimble. Figure 3: A Soxhlet apparatus.
Chapter 3
48
The described procedure was thus repeated during 2 h to achieve a total extraction time of
8 h (4 h + 2 h + 2 h). The content of the distillation flask was then concentrated to dryness
with a vacuum rotary evaporator and the flask was then cooled to room temperature in a
desiccators and weighed.
Spectrophotometric method
Cellular lipid content was quantified using a spectrophotometric method adapted from
Holland and Gabbott (1971). A 15 ml sample was centrifuged at 700×g for 10 min and
the pellet was resuspended in 250 μl of chloroform. Samples were then vortexed for 1
min, 500 μl of methanol were added, and the samples were mixed again for one min.
Following a 10 min incubation at 4°C, 250 μl of chloroform and 250 μl of autoclaved
MilliQ water were added and mixed for one min. Samples were centrifuged for 5 min at
800×g and the upper phase was pipetted off. The lower phase was dried at 100°C for 15
min and then resuspended in 500 μl of chloroform. A 50 μl aliquot was then dried for 10
min at 100°C, 500 μl of sulphuric acid were added and the samples were covered and
heated at 200°C for 15 min. After cooling, 1 ml of autoclaved MilliQ water was added to
each sample and absorbance was determined at 375 nm.
Sulfo-phospho-vanillin method
Lipid content (unsaturated, total) was measured with the sulfo-phospho-vanillin method
(Knight et al., 1972; Izard and Limberger, 2003). Concentrated sulfuric acid (2 ml
H2SO4) was added to a blank in a tube containing 100 µl of 80% methanol, to tubes with
triolein standard (100 µl), and to tubes with 100 µl of sample. Each tube was incubated
for 30 min at 100°C, and then cooled down to room temperature in a water-iced bath.
After the addition of 5 ml of PV solution (i.e. phosphoric acid and vanillin) the tubes were
incubated at room temperature for 15 min (Fig. 2). Absorbances were read at the
spectrophotometer at 530 nm.
Ultrasound-assisted lipid extraction
Another series of tests were run, this time submitting the biomass to ultra-sonication
before using the extraction procedures previously described. The biomass was centrifuged
at 3000×g for 20 min, the supernatant was removed and the appropriate solvent
(according to the method used) was added to the pellet. Following that, the sample was
mixed on a vortex and submitted to an ultrasonic ice/water bath for 20 min at a power and
Chapter 3
49
frequency of 50W and 30 kHz, respectively. After ultra-sonication, the standard
extraction procedures were employed.
Statistical analysis
Each analysis was repeated in triplicates. One-way analysis of variance was used for
statistical analysis of the data. Significance level of 5% was assumed for each analysis.
The error bars presented on the figures correspond to the standard deviations.
Results and Discussion
The paper presented a rigorous comparison among the most common alternative methods
for lipid quantification in microalgae. A sustainable lipid extraction technology for
microalgal biodiesel production should be effective, highly lipid-specific, cost and
energy-efficient, non-reactive with lipids, safe, and robust enough for application on
various microalgal species. Extraction of lipids from microalgae is basically a mass
transfer operation, which depends on the nature of the solute, the solvent and its
selectivity, and the level of convection in the medium (Araujo et al., 2013).
METHODS Chloroform-
methanol Gravimetric SPV
Fatty acid extracted (% dw) 8.57 ± 0.98 6.10 ± 1.35 14.32 ± 0.12
Figure 3: Lipid extraction efficiency according to method
0
2
4
6
8
10
12
14
16
Chloroform-methanol Gravimetric SPV
Fa
tty a
cid
co
nte
nt
ex
tra
cte
d (
% d
w)
Chapter 3
50
In Figure 4 it is shown that the method that presented the highest lipid yield was the
SPVA, with percentages of 14.32 ± 0.12%, followed by chloroform-methanol (8.57 ±
0.98%) and gravimetric (6.10 ± 1.35) methods. The results confirmed SPVA was a
simple, accurate and reliable method, capable of determining total fatty acid content more
efficiently than the other traditional extraction methods.
The commonly used gravimetric method significantly underestimated fatty acid content,
employed an organic toxic solvent and required dried or partially dried feedstock.
Moreover, the removal of water from the biomass (prior to the extraction step) and the
recovery of the solvents from the lipid solution (after the extraction step) both utilized
energy-intensive evaporation that needs to be avoided. Soxhlet extraction, in fact, which
takes about 2-3 days and requires large amounts of biomass, probably suffered from lipid
degradation resulting from the use of elevated temperature throughout the process.
Guckert et al. (1988) noted that the crude lipids recovered using a Soxhlet system
contained less PUFAs than those obtained by batch extractions, and ascribed this
observation to potential thermal degradation, due to the harshness of the Soxhlet method.
This method involves washing of solid mass with a solvent that has high solubility and
selectivity for the solute. The mechanism behind Soxhlet extraction is mainly diffusion,
and the procedure does not involve application of any shear stress to the biomass. The
results show that relying simply on diffusion of lipids through the cell membrane is a
slow process and results in low yield of oil.
Extraction using chloroform-methanol is fast and quantitative. Chloroform, however, is
highly toxic and its usage is undesirable because chlorinated solvents are hazardous and
also not eco-friendly; hence other non-polar solvents should be investigated. However, if
compared with the traditional gravimetric quantification, the chloroform-methanol
extraction reduces the risk of lipid oxidation by avoiding the solvent evaporation step.
The critical point was the repeatability and the reproducibility of the method (sd ± 0.98,
see Fig. 4).
The high accuracy of SPV method for the determination of a trace amount of lipids within
aqueous solution proved highly superior to the previously conventional methods for
microalgal lipid quantifications. The extraction methods have presented high repeatability
and high reproducibility and the standard error was low (sd ± 0.12). Furthermore, acid-
thermal treatment degrades extra products (non-lipid contaminants) that could affect the
measurement.
Chapter 3
51
The key step in extraction and recovery of lipids from microalgae was cell disruption. In
Figure 5 are shown the results from the comparison between a normal extraction method
and its related sonication-assisted protocol. In the presence of pretreatment, total lipid
extraction was enhanced in efficiency in all tested methods, particularly in the case of the
chloroform-methanol method, which showed a 19% increase in extracted lipids. This
demonstrated a more effective penetration of the solvent mixture compared to the other
procedures.
METHODS Chloroform-
methanol Gravimetric SPV
Fatty acid extracted (% dw) STANDARD 8.57 ± 0.98 6.10 ± 1.35 14.32 ± 0.12
Fatty acid extracted (% dw) SONICATION ASSISTED 10.22 ± 1.01 6.52 ± 1.20 15.31 ± 0.16
Figure 5: Comparison between standard extraction methods (black bars) and sonication assisted methods (white bars).
For the gravimetric method, the contribution of ultra-sonication pre-treatment was much
less significant, probably due to the fact that cell walls were already ruptured by milling
in the standard procedure.
On the other hand, the extracting power of the solvents used in the SPVA was already
higher than other methods, and the use of sonication further increased the total amount of
extracted lipids, albeit in a lesser extent (+7%).
For both colorimetric quantifications, the robust structure of the microalgal cell wall can
limit cell rupture rate when using normal mechanical methods (Chen et al., 2009), thus
0
2
4
6
8
10
12
14
16
18
Chloroform-methanol Gravimetric SPV
Fa
tty a
cid
co
nte
nt
ex
tra
cte
d (
% d
w)
Standard Sonication assisted
Chapter 3
52
slowing down the dissolution of lipids and rendering the extraction more difficult. In this
process, when cavitation bubbles suddenly burst, the pressure destroys the adjacent tissue;
this way, the cell walls are damaged by the repeated bursting of cavitation bubbles (Adam
et al., 2012). Thus the increase in lipid extraction yield after this pretreatment is attributed
to the increase in surface area caused by the rupture of microalgal cells into smaller
fragments. Previous studies have shown better lipid yields by using pretreatment
methods. Ranjan et al. (2010) demonstrated through micrographs that the use of the Bligh
and Dyer method (1959) without ultrasound application showed some distorted clusters
of biomass corresponding to disrupted cells. The application of ultrasound increased the
number of disrupted cells. Similar results were obtained in the work carried out by
Prabakaran and Ravindran (2011), and Araujo et al. (2013) with Chlorella, where the
highest efficiency was obtained with sonication method among five cell disruption
methods tested, including microwaving. By the way, Lee et al. (2010) suggest that lipid
extraction efficiency from microalgae depends on the microalgae species and
pretreatment methods involved.
Conclusions
Despite the routine use of lab-scale extraction to determine microalgal lipid content, the
variables affecting lipid extraction from microalgae are not well understood, making
scale-up for commercial production of microalgal biodiesel difficult. The downstream
technologies needed for industrial-scale production of microalgal biodiesel are still in the
early stages of development. Lipid extraction from microalgal biomass has not received
sufficient attention and represents one of the many bottlenecks hindering economic
industrial-scale production of microalgal biodiesel.
Furthermore, it has to be investigated if the extra gain in lipids obtained with
ultrasonication pre-treatment is worth the expenses to implement this technology.
The challenge for future research on microalgal biodiesel will be the development of an
effective, inexpensive and energetically-efficient enough lipid extraction process, to
make possible an industrial scale exploitation.
Chapter 3
53
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Chapter 4
57
4 Optimizing the culture conditions for the lipid production
in three selected algal strains
Chapter 4
59
OPTIMIZING THE CULTURE CONDITIONS FOR THE LIPID PRODUCTION IN THREE SELECTED ALGAL STRAINS
Abstract For a large scale biofuel production, it is fundamental to optimize productivity of
microalgae by obtaining a better understanding of the parameters influencing growth,
biomass and lipids accumulation. It is known that the biochemical composition of
microalgae can be modulated changing the culture conditions. This work assesses the
impact of such manipulations, and determine if they could potentially render microalgae a
viable source of biodiesel if put into practice at an industrial level.
First of all, culture conditions were modified by adding an air-bubbling mixing. The
results demonstrated that mixing induced an enhanced growth rate for all strains treated
and a high lipid production, especially for I. galbana.
Subsequently, we investigated the effects of blue and red light (with and without PAR)
on the growth and lipid content using LEDs (light-emitting diodes) in batch cultures.
A very high lipid production was obtained under blue light with PAR for I. galbana
(+73%), but the maximum lipid content per cell was in D. tertiolecta. However, from an
industrial point of view, it can be concluded that a high yield in biomass or an high initial
lipid content not always translates into an advantageous biodiesel productivity.
Introduction Microalgae are becoming increasingly more important for aquaculture and many
industrial applications. With this increase in application potential, culture system design
is becoming more critical in order to optimize the overall productivity/economics of the
process.
In order to exploit these organisms for large scale biofuel production, it is fundamental to
optimize productivity by reaching a better understanding of the parameters influencing
growth, biomass and lipids accumulation.
The biochemical composition of microalgae can be modulated changing the culture
conditions. Several environmental factors are responsible for the growth and biomass
composition of microalgae, such as light supply (Sheehan et al., 1998), media
composition, especially carbon and nitrogen sources (Li et al., 2008), and the growth
conditions such as pH, temperature and CO2 supply (Ugwu et al., 2007). However, the
most important optimization parameters for photoautotrophic microalgal production are
nutrient levels, light and temperature (Hu et al., 1998; Fuentes et al., 1999; Fernandez et
al., 2000). Light is the most dynamic and complex of these three parameters, and has
been widely accepted as the driving factor acting on overall biochemical composition in
Chapter 4
60
algal cultures (Trabelsi et al. 2008). Furthermore, it is essential for autotrophic organisms
to obtain chemical energy, stored in reduced carbon compounds (Dubinsky et al. 1995).
The light-trapping mechanism has been resolved in great detail. The molecular interaction
of the pigment molecules with light and the subsequent electron transfer processes have
been spectrally and kinetically resolved. Photosynthesis performed by plants and
phototrophic microorganisms is a vital process for life cycles in the biosphere. The
potential energy present in sunlight becomes trapped and is utilized as energy source for
carbon dioxide reduction.
In microalgal culture, photons of light are the major energy sources for growth of cells.
Since the photons of light can be absorbed by the microalgal cells, the properties of light
source, such as wavelength and intensity, are definitely critical for the growth of
photoautotrophic microalgae. The colour of the incident light ideally should match with
the pigment absorption band which corresponds with the lowest excited state. In the case
of chlorophyll, absorption bands are present in the blue as well as in the red spectral
regions.
While carbon dioxide is available abundantly in the atmosphere as well as from
anthropogenic sources, the availability of light is very important for microalgal growth.
Since photoautotrophic microalgae depend on light sources to obtain energy and convert
it into chemical energy such as adenosine triphosphate (ATP) and nicotinamide adenine
dinucleotide phosphate (NADP), it is worthwhile to study the effect of different light
spectra on the algal growth (Kim et al., 2013). Generally, microalgae use light of
wavelengths from 400 to 700 nm for photosynthesis. The wavelengths absorbed by
microalgae differ depending on the species. For instance, green microalgae absorb light
energy for photosynthesis through chlorophylls (as major pigments) in the range of 450–
475 nm and 630–675 nm, and through carotenoids (as accessory pigments) absorbing
light energy of 400–550 nm (Richmond, 2003).
Light intensity and wavelength play very critical roles in the photosynthetic process,
which are consequently reflected in the growth or productivity of organisms.
Microalgae need a highly efficient and optimum light source for rapid biomass yield and
high biochemical compound production, since the light provides the energy necessary to
support cellular metabolisms. Excess light may damage protein D1 in photosystem II
(PSII) causing photoinhibition, and may also lead to the formation of harmful reactive
oxygen species (ROS) and consequently to oxidative stress that can reduce the growth
rate of the microalgae. In fact, if light intensity further increases beyond an inhibitory
Chapter 4
61
threshold, the rate of photosynthesis starts to decrease with light intensity due to the
deactivation of key proteins in the photosynthetic units (Camacho Rubio et al., 2003).
Photoinhibition and its repairing is energetically very demanding and may strongly
influence the biomass productivity. The capacity for an effective and prompt acclimation
is therefore an important parameter to be considered in the characterization of an algal
species for biomass production (Simionato et al., 2011).
When the algae grow and multiply, they become so dense that they block light from
reaching deeper into the medium. As a result, light only penetrates the top few
centimetres of the water in most algal cultivation systems, as predicted by the Lambert-
Beer law. Under this artificially static or unrepresentative environmental conditions, the
algae near the irradiation source are exposed to high photon flux density, which enhances
growth rate. On the contrary, cells in the deepest layers receive less light as a result of
mutual shading and will therefore show a lower growth rate (Lucker et al., 2014).
In dense cultures, light availability can only be modified in a limited way through
manipulation of the light path, the incident irradiance, or the amount of mixing. Air
bubbling is the most usual procedure to agitate microalgal cultures, providing convenient
mixing of the organisms and renewal of nutrients around the surface of the cells
(Hadianto et al., 2013; Marshall and Huang, 2010). However, high degree of mixing in
the photobioreactor, and subsequently a high fluid velocity, are known to present a
limitation on the growth of algae cells sensitive to hydrodynamic stress, by damaging
their shear-sensitive cell structures (Barbosa et al. 2004; Sastre et al., 2007). Obviously,
while a better fluid mixing is beneficial to the growth of algae, it is also desirable to
minimize the energy consumption to drive the flow and mixing.
Several studies reported that the growth of microalgae is different depending on
wavelength. Red light (600–700 nm) and blue light (400–500 nm) stimulate the growth of
microalgae and have been considered as important light wavelengths for photosynthesis.
According to these reports, this manipulation of the light field produces changes on
growth rates and metabolic contents which affect the industrial value of the microalgae.
Light quality also has a substantial impact on cellular metabolism (Singh et al., 2009).
The short-term and long-term adaptations associated with balances in photosystem
stoichiometry have been investigated in relation to the spectral composition of light
(Allen, 2003). For example, red light was shown to be most effective for the production
of hydrocarbons by Botryococcus braunii as a renewable energy source (Baba et al.,
2012).
Chapter 4
62
Opposite results were found by Markou (2014) on Arthrospira platensis grown under
several monochromatic lights. In his studies, the highest carbohydrate and lipid contents
were obtained in blue light, while the highest biomass productivity was obtained with
pink and red LEDs. However, studies with a more physiological focus demonstrate that
the effects of blue light in particular are variable among the different algal groups
(Mercado et al., 2004).
The red emission spectrum fits perfectly with the photon energy needed to reach the first
excited state of chlorophylls a and b, the pigments present in the light-harvesting
complexes (LHC) of algae. Kim et al. (2014) found that fatty acid methyl esters (FAMEs)
yields in cells cultured under blue and red light were much greater than those cultivated
under white light, suggesting that metabolic changes associated with lipid accumulation
are directly or indirectly related to light quality.
The aim of this work is to determine the response of microalgae to different culture
conditions with respect to biomass productivity and intracellular lipid content, intended
for use in biodiesel production. Additionally, the establishment of relationships between
biochemical parameters and the physiological state of the culture was also sought, with
the final goal of identifying parameters that rapidly give indications about the current
status of the culture.
To optimize microalgal production costs for a reactor, the understanding of internal
dynamics of a culture is a necessary element in the design and operation processes.
Materials and methods
Strain selection and initial culture experimental setup resulted from a previous classified
project (data not shown).
Microalgae culture medium
Dunaliella tertiolecta Butcher used in the experiments was from a single batch, incubated
in 3-liter Erlenmeyer flasks containing autoclaved f/2 medium (Guillard & Ryther, 1962;
Guillard, 1975). Phaeodactylum tricornutum Bohlin (PLY 100, Plymouth Culture
Collection of Marine Macroalgae, Plymouth, UK) and Isochrysis galbana Parke (SCCAP
K1355; Scandinavian Culture Collection for Algae and Protozoa, Copenhagen, Denmark)
Chapter 4
63
were grown in L1 medium, silicon enriched for the diatom (Guillard & Hargraves, 1993),
at 32 and 30 psu respectively.
Microalgae were grown at 22±1°C under 40 µmol photons m-2
sec-1
(Sylvania Aquastar,
36W, 10.000K and Osram Lumilux De Luxe 12-950, 36W, 5.400K, 98Ra) on 24:0 h L:D
cycles.
Light sources development for microalgae culture systems
LED (Light Emitting Diode) is an emerging and economical technology compared to
ordinary fluorescent lamps in microalgae growth because of its longer life time, lower
heat dissipation, smaller mass and volume, single wavelength, and high efficiency of
electricity conversion, which contributes to more stable test conditions. Furthermore,
because of its low power consumption, it makes for an efficient energy source for
cultivating microalgae for biofuel production (Okumura et al., 2014).
According to Posten (2009) light intensity must be sufficiently high to penetrate through
the culture, and LED lights have the ability to distribute light uniformly in the culture
system. Moreover, if compared to the conventional tubular lamps and light bulbs, LEDs
are considered the optimal light sources for cultivating the algae and studying the effect
of light wavelength (Wang et al., 2007).
In addition, LEDs have a narrow light emission range, usually 20-30 nm wide, which can
be matched with photosynthetic needs. For instance, the emission wavelengths of blue
LED and red LED are around 450–470 nm and 645–665 nm respectively (See Fig. 2).
Figure 1. Emission spectra of LEDs. www.zeiss-campus.magnet.fsu.edu
Chapter 4
64
Experimental design
After pre-cultivating microalgae under continuous
illumination with fluorescent light, an air-bubbling system
was added. Sterile, filtered air was insuflated directly into
the flasks at a flow rate of 100 ml min-1
(see Fig. 2). No air-
bubbling was added to the control flasks.. For every
microalgal strain a growth curve was plotted.
For monochromatic treatment, microalgae were transferred
under continuous blue (470 nm) and red (660nm) lights for
five days, with an irradiance of 60 photons m-2
sec-1
,
provided by LED lamps fixed into the flasks (see Fig. 3). In
the second part of the experiment on light quality, white
light was turned off and the cultures were transferred to
darkness and irradiated under continuous red and blue
monochromatic LEDs for other five days (with the same
irradiance specified above). In these experiments, the
cultures were air-bubbled and all flasks were shielded to
prevent light contamination.
For all analyses, microalgae were harvested at the
beginning of the stationary phase.
Biomass production
Microalgae growth was monitored by counting the cell
number. Cell concentrations were determined via direct
cell count on a Burker haemocytometer (Precicolor, Germany) at the inverted microscope
(LEICA, DMIL), and the optical density (OD) was recorded at a wavelength of 680 nm
using an UV/VIS spectrophotometer (Jenway 7315 UV/VIS Spectrophotometer,
Staffordshire, UK). The relationship between cell concentration and the optical density
was established from the calibration curves (R2=0.998) by a regression equation.
Photosynthetic parameters measurement
Recording of the fluorescence emitted from chlorophyll (Chl) molecules located in
chloroplasts of photosynthesising organisms is a widely used non-destructive tool in
photosynthesis research. This technique has allowed an increased understanding of
Figure 2.Air-bubbling setup.
Figure 3. Monochromatic light setup.
Chapter 4
65
photochemical and non-photochemical processes occurring in thylakoid membranes of
chloroplasts (Roháček, 2002).
In vivo-induced chlorophyll fluorescence was determined with a pulse amplitude
modulated (PAM) fluorometer (Fluorescence Monitoring System FMS1, Hansatech,
UK.). The method of quenching analysis is based on the measurement of the fluorescence
parameters in response to saturating light in dark- or light-adapted specimens. As shown
in Figure 4, after several minutes in darkness, F0 was measured. in the dark-adapted state
(DAS), which is, in view of electron transport processes, the photochemically inactive
state of a thylakoid membrane, generally all PSII reaction centres and electron carriers of
the PSII acceptor side are re-oxidised (Roháček, 2002). Then, a saturating flash was
applied to obtain the maximal fluorescence level (Fm). Thus, the maximal quantum yield
of fluorescence (Fv/Fm) was obtained. The variable fluorescence Fv is the difference
between the maximal fluorescence from a fully reduced PSII reaction centre (Fm) and the
intrinsic fluorescence (Fo) from the antenna of the fully oxidized PSII.
Fv/Fm provides information about the underlying processes which have altered efficiency
and is given by the equation:
m
m
m
v
F
FF
F
F 0−=
Dark-adapted value of Fv/Fm reflects the potential quantum efficiency of PSII and is used
as a sensitive indicator of photosynthetic performance, with optimal values of around 0.83
measured for most plant species (Roháček & Barták, 1999; Roháček, 2002). However, a
lower value of the Fv/Fm parameter may be caused by an increase of F0 due to the initially
blocked or damaged reaction centres.
Chapter 4
66
Figure 4. Sequence of a typical fluorescence trace. A measuring light is switched on and the zero fluorescence level is measured (F0). Application of a saturating flash of light (↑L1) allows measurement of the maximum fluorescence level (Fm). A light to drive photosynthesis (actinic light - ↑L2) is then applied. After a period of time, another saturating light flash (↑L1) allows the maximum fluorescence in the light (Fm’) to be measured. The level of fluorescence immediately before the saturating flash is termed Fs. Turning off the actinic light, typically in the presence of far‐‐‐‐red light (L3), allows the zero level fluorescence ‘in the light’ to be estimated.
An increase of F0 is caused by a partially reversible decrease in the quantum yield of PSII
photochemistry, whereas a higher increase in F0 probably originates from an irreversible
disconnection of the small light harvesting complex of PSII (Lazár, 1999).
During the light period, the photosynthetic apparatus passes gradually from DAS to the
light-adapted state (LAS). The LAS is characterised by a continuous synthesis of ATP,
NADPH, and concurrent fixation of CO2 (Walker 1987). When electron transport
processes and coupled, biochemical reactions in the carbon reduction cycle are
equilibrated, and the steady-state (Fs) is reached. Application of a pulse of saturating
radiation at this state enables to determine maximum chlorophyll fluorescence in LAS
(Fm').
At the steady-state of electron transport, the actinic light was turned off and the far-red
light was applied to ensure rapid and complete oxidation of all primary electron
acceptors. (Schreiber, 2004).
The most useful parameter that measures the efficiency of the PSII photochemistry in
LAS is ΦPSII (Genty et al., 1989), calculated as:
Chapter 4
67
m
SmPSII
F
FF
'
' −=Φ
This parameter measures the proportion of light absorbed by chlorophyll associated with
PSII that is used in photochemistry. As such, it can give a measure of the rate of linear
electron transport and, therefore an indication of overall photosynthesis (Demming-
Adams et al, 1996).
Another fluorescence parameter widely used is ‘photochemical quenching’ or qP. This is
calculated as:
)''(
)'(
0FF
FsFq
m
mP
−
−=
This parameter represents the proportion of light energy trapped by open PSII reaction
centres and used for electron transport (Juneau and Popovic, 1999). A change in qP is due
to closure of reaction centres, resulting from a saturation of photosynthesis by light.
qNP is the non-photochemical quenching and reflects light energy dissipation not related
to photochemistry and represents all the non-radiative processes of de-excitation (Bilger
et al., 1995).
This parameter varies depending on changes in the trans-thylakoid pH-gradient, state
transitions, photoinhibitory processes (inactivation of PSII reaction centres, zeaxanthin
formation), etc. (Bilger and Bjorkman 1990) and is calculated as:
)'(
)'(
0FF
FFq
m
mm
PN−
−=
NPQ (with 0 ≤ NPQ ≤ ∞), another non-photochemical quenching parameter, is linearly
related to heat dissipation. Any variation in NPQ measures a change in the efficiency of
heat dissipation, relative to the dark adapted state. Under most conditions, the major
contributor to NPQ is termed ‘high energy state quenching’ and is thought to be essential
in protecting the leaf from light-induced damage. This process requires the presence of a
low pH in the lumen of the thylakoid and involves the light-induced formation of the
carotenoid zeaxanthin (Demmig Adams et al., 1996; Demmig Adams and Adams,
1996a).
Chapter 4
68
Lipid extraction
Lipid content (unsaturated, total) was measured with the sulfo-phospho-vanillin assay
(Knight et al., 1972; Izard and Limberger, 2003). Concentrated sulfuric acid (2 ml
H2SO4) was added to a blank in a tube containing 100 µl of 80% methanol, to tubes with
triolein standard (100 µl), and to tubes with 100 µl of sample. Each tube was incubated
for 30 min at 100°C, and then cooled down to room temperature in a water-iced bath.
After the addition of 5 ml of PV solution (i.e. phosphoric acid and vanillin) the tubes were
incubated at room temperature for 15 min. Absorbances were read on a
spectrophotometer at 530 nm.
Cholophyll and carotenoid extraction
Microalgae for chlorophyll determinations were sampled simultaneously with those used
for photosynthesis measurements. Chl a, b and total carotenoids were extracted in N,N-
dimethylformamide (DMF) following the methodology described by Wellburn (1994).
Samples (3 ml) were centrifuged at 3000×g for 20 min and then incubated in 2 ml DMF
for 24 h at 4°C in darkness. The absorbance was finally measured at 750, 664, 647 and
480 nm.
Statistics
All the analyses were run in triplicate. Statistical significances of means were tested with
a model one-way ANOVA followed by a multirange test (Fisher’s protected least
significance difference). A P-level of 0.05 was used to evaluate the significance. PAM
measurements for each treatment were repeated at least five times and mean values and
standard deviations were calculated.
Results and discussion
Air bubbling supply
The growth curve of culture time versus cell density during the first part of the
experiment, over a period of two weeks, is shown in Fig. 4, while the biomass increase in
the stationary phase is reported in Fig. 5.
Algae growth was described to follow five different phases (Moazami et al., 2012). They
are: lag or acclimation phase, log or exponential growth phase, declining growth phase,
Chapter 4
69
stationary phase and death (lysis) phase. From Fig. 5 it can be observed that the lag phase
occurred between day 0 and 2, the exponential phase from day 2-3 to day 8-10, stationary
phase from day 12 onwards, depending on the species.
During the first 2 days of the experiment, the strains cultured under static and dynamic
conditions grew in a similar manner, doubling about 1.5 times per day. Then the algal
cells of all microalgal strains underwent a rapid increase in cell density (Fig. 4, full
squares).
Continuous air supply stimulated the growth of I. galbana and D. tertiolecta more
effectively than that of the diatom, but in the stationary phase the Haptophycea reached a
higher cell density (18.00×104 cell ml
-1) than the other species, although its biomass
increase was only about 9.5% (See Fig. 6).
In contrast, the bubbling system resulted more effective for D. tertiolecta biomass
productivity (+ 51%) than the other strains, despite the lower OD (i.e. if compared to the
other treated strains)
Figure 5. Dynamics of the cell densities of tested strains in 24:0 light:dark cycle (▲) and 24:0 light:dark cycle plus air-bubbling system (■).
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1
0 2 4 6 8 10 12 14 16 18
Cel
lula
r co
nce
ntr
atio
n (
opti
cal d
ensi
ty)
Culture time (days)
P. tricornutum P. tricornutum + bubbl. D. tertiolecta
D. tertiolecta + bubbl. I galbana I. galbana + bubbl.
Chapter 4
70
From the graph, significant differences emerged between dynamic and static conditions
during the transition from day 3 to 10. The result of culture mixing on the specific growth
rate of I. galbana was a faster and higher log phase than that of the other strains,
suggesting that it was growing more rapidly, while for air-bubbled D. tertiolecta the
stationary phase started before that of its control. The growth curve for control and treated
P. tricornutum were similar, no significant differences were observed between lag and
stationary phases. However, under continuous mixing conditions, a good productivity was
recorded (+ 24%).
% Increase Standard deviation
P. tricornutum 23,68 ±1,52
I. galbana 9,49 ±1,00
D. tertiolecta 51,06 ±2,75
Figure 6: Biomass % increases for air-bubbled strains. Zero line represents the static cultures (controls).
Chlorophyll fluorescence parameter Fv/Fm, the potential maximum quantum efficiency,
can directly reflect the photosynthesis activity of PSII. It was observed that the
photosynthetic activity of PSII corresponded to the growth of algal cells (data not shown).
For the algal cells with the addition of air-bubbling treatment, the photosynthesis of PSII
remained highly active all the time, corresponding to a sustained increase in cell density.
0
10
20
30
40
50
60
P. tricornutum I. galbana D. tertiolecta
Bio
mas
s in
crea
se
(per
cen
tage
val
ues
)
Chapter 4
71
In natural environment, even when the outdoor incident radiation level is constant, the
irradiance within a culture varies as a function of position: cells closer to the light source
shade those further away; hence, productivity varies with position and time (Molina-
Grima et al., 1999). Obviously, cells nearest to the light source experience a higher
irradiance than cells elsewhere in the vessel. Mixing results in movement of algae through
the culture, as such, they are exposed to an intermittent, not saturating light regime.
Merchuk and Wu 2003 reported that periodical change in illumination can promote
growth, while Yoshimoto et al., 2005, postulated that flashing light effect enhances the
efficiency of photosynthesis in dense culture. This phenomenon is called the ‘flashing-
light effect’. Following the capture of photons, the photosynthetic units (PSUs) of algae
cells need few milliseconds to convert light energy into NADPH and ATP. During this
time, any photon reaching ‘excited’ PSUs is wasted. As a result, cells exposed to flashing
light waste less light energy than cells exposed to continuous light (Grobbelaar, 1991,
1994; Janssen et al., 2003; Luo and Al-Dahhan, 2004, Béchet et al., 2013).
Moreover, Grobbelaar (1994) confirmed that mixing can facilitate the exchange rates of
nutrients and metabolites between the cells and their growth medium, and these, together
with the increased light/dark frequencies, would increase productivity and photosynthetic
efficiency. For example, he observed that in the diatom Phaeodactylum tricornutum
nitrate uptake was enhanced about 21% in dynamic culture. He reported that similar
results were obtained in Spirulina sp. and Skeletonema costatum previously, so he
speculated that increased productivities in turbulent systems could be attributed to
‘flashing light’ stimulation.
Therefore, the increment in biomass production, especially evident in D. tertiolecta and
P. tricornutum, could be attributed to an enhanced availability of light and nutrients
favoured by mixing, two factors not directly intertwined but working synergistically.
In Figure 7a and 7b are shown the pigment contents of the analysed strains.
It is remarkable that the photosynthetic pigments content in D. tertiolecta was about 30
times greater than that of the other two microalgae. In any case, both for the diatom and
the Chlorophycea, the effect of air-bubbling resulted in a slight reduction in the
chlorophylls and the carotenoids, which was more evident in the case of D. tertiolecta.
Chapter 4
72
Pigment content Chl a Chl b CAR
D. tertiolecta Control 25,70±0,071 10,18±0,021 10,57±0,043
D. tertiolecta Bubbled 18,04±0,0118 8,10±0,036 8,22±0,061
Figure 7a: Average pigment contents in D. tertiolecta. Values are expressed in nanograms per cell.
0
5
10
15
20
25
30
35
40
45
50
D. tertiolecta Control D. tertiolecta Bubbled
ng/
cell Car
Chl b
Chl a
Chapter 4
73
Pigment content Chl a Chl b CAR
P. tricornutum Control 0,85±0,065 0,05±0,002 0,440,003
P. tricornutum Bubbled 0,780,017 0,020,003 0,400,015
I. galbana Control 0,930,032 0,050,004 0,630,001
I. galbana Bubbled 1,080,02 0,110,007 0,710,004
Figure 7b: Average pigment contents in P. tricornutum and I. Galbana. Values are expressed in nanograms per cell.
The pigment content of algae cells can vary significantly during cultivation. This change
is caused by light acclimation: at low light intensity, cells tend to increase their pigment
content to maximize the amount of light captured. At high light intensity, cells tend to
lower their pigment content to minimize the risks of light-inhibition (Geider et al., 1997).
In this case, mixing prevented cells from self-shading, thus increasing the irradiance into
the culture and consequently inducing the reduction in chlorophyll content per cell.
0,0
0,2
0,4
0,6
0,8
1,0
1,2
1,4
1,6
1,8
2,0
P. tricornutum Control
P. tricornutum Bubbled
I. galbana Control
I. galbana Bubbled
ng/
cell
Car
Chl b
Chl a
Chapter 4
74
On this basis, in I. galbana, the enhanced pigment content could be due to the sub-
optimum light regime. Saoudi-Helis et al. (1994), in fact, reported that this species is able
to adapt to a wide range of photon flux densities.
Control Bubbling
P. tricornutum 0,031±0,0021 0,057±0,0010
I. galbana 0,029±0,0018 0,078±0,0011
D. tertiolecta 0,024±0,0008 0,054±0,0021
Figure 8: Total lipid yields for air-bubbled and control strains (stationary phase). Values are expressed as milligrams of triolein per millilitre of culture.
In Figure 8 are reported the results about lipid content expressed in milligrams of triolein
per volume unit of culture. As shown, mixing induced a very high lipid production (more
than two-fold) for all strains, but the most interesting data regarded I. galbana, in which
the lipid content increased by 170%. Dunstan et al. (2004) reported that if the light energy
harnessed by cells exceeds that needed for cell division and maintenance, it can be used to
synthesize storage lipids. In our experiment, the air-bubbling system induced a high light
availability that would justify the increased lipid content recorded.
From a practical perspective, considering the results, I. galbana would be the best choice
for exploitation in photobioreactors, provided it is well mixed, because it demonstrated to
0
0,01
0,02
0,03
0,04
0,05
0,06
0,07
0,08
0,09
P. tricornutum I. galbana D. tertiolecta
mg
Tri
olei
n/m
l
Control
Bubbling
Chapter 4
75
be capable of multiplying faster than the other examined strains, and also of yielding
more total lipids per volume unit of culture.
ng Triolein/cells Standard deviation
P. tricornutum 0,048 ±0,0072
I. galbana 0,069 ±0,0043
D. tertiolecta 0,399 ±0,0092
Figure 9: Average lipid contents in air-bubbled strains (stationary phase). Values are expressed as nanograms of triolein per cell.
However, the results presented in Fig. 9 are also noteworthy, because they show that D.
tertiolecta had the highest lipid content per cell, which was as much as five times greater
than that of I. galbana. This points out the fact that, unlike D. tertiolecta, I. galbana
features a high division rate but only a moderate lipid accumulation. For this reason, a
way to further optimize algal culturing should be sought, especially in the case of D.
tertiolecta, in order to promote a faster growth rate.
Monochromatic light supply
The effects of different light wavelengths, provided by LEDs, on growth and lipid
production of different microalgae have been investigated. Because of the results obtained
0,00
0,05
0,10
0,15
0,20
0,25
0,30
0,35
0,40
0,45
P. tricornutum I. galbana D. tertiolecta
ng
Tri
olei
n/c
ells
Chapter 4
76
in the previous phase of the work, the air-bubbling system was kept active in order to get
the best possible results in this phase of the experiment.
Considering light as the most important energy source for photoautotrophic algae, many
studies have focused on the effect of light intensity. However, much of the experiments
conducted on the effect of monochromatic light exposure on microalgae photosynthesis,
have been run over a very short photoperiod (i.e. between 30 seconds and 1 day). In the
first part of the experiment, well-mixed oleaginous strains were separately irradiated by
continuous red and blue monochromatic lights for five days, all under white light. In the
second stage, PAR was turned off and the cultures were irradiated under continuous
monochromatic light for five days.
The biomass increase for the three algal strains under blue and red light exposures are
shown in Fig.10. Under such conditions, results obtained showed that red light regime
had significant effects on the growth of D. tertiolecta and P. tricornutum, with an
increase in biomass of more than 60 and 40% respectively. Matthijs et al. (1996)
explained that microalgae are good at absorbing red light through their green pigments,
the chlorophylls. Red light-emitting diodes are very attractive for photosynthesis. The
high biomass increase in D. tertiolecta could depend from the red emission spectrum
which fits perfectly with the photon energy needed to reach the first excited state of
chlorophylls a and b, the pigments present in the light-harvesting-antenna complexes
(LHC) of green algae.
Figure 10: Biomass % variations forlight regimes with a 24:0 light:dark cycle. Zero line re
On the other hand, for I. galbana
wavelength when compared to th
This can be explained by the observations made by previous researchers
that pure red light could cause cell damage (Figueroa
it should be noted that the specific light wavel
type of alga, and so on
conditions.
Cultivation under blue light stimulated an increase in cell density for all strains, especially
for D. tertiolecta (+ 31%). This might be due
LED can penetrate deep through the culture
resulting in an increased cell density.
P. tricornutum
BLUE+PAR
RED+PAR
-20
-10
0
10
20
30
40
50
60
70
80
OD
(p
erce
nta
ge %
)
ations for air-bubbled strains under different monochromatic (plus PAR) a 24:0 light:dark cycle. Zero line represents the controls (PAR only).
I. galbana biomass diminished by almost 10%
when compared to the control.
This can be explained by the observations made by previous researchers
that pure red light could cause cell damage (Figueroa et al., 1995; Das
it should be noted that the specific light wavelength absorbance capacity depends on the
its cellular composition, growth medium and physiological
Cultivation under blue light stimulated an increase in cell density for all strains, especially
). This might be due to the fact that short waveleng
LED can penetrate deep through the culture, thus allowing the cell to double faster
increased cell density.
P. tricornutum I. galbana
5,43 3,75
48,91 -8,65
Chapter 4
77
bubbled strains under different monochromatic (plus PAR) s (PAR only).
biomass diminished by almost 10% under the same
This can be explained by the observations made by previous researchers, who reported
., 1995; Das et al., 2011). Also,
ength absorbance capacity depends on the
its cellular composition, growth medium and physiological
Cultivation under blue light stimulated an increase in cell density for all strains, especially
to the fact that short wavelengths of the blue
thus allowing the cell to double faster,
D. tertiolecta
31,65
68,35
Figure 11:. Biomass % variations for airPAR) light regimes with a 24:0 light:dark cycle. Zero line represents the controls (PAR only).
Without white light (Fig. 11), microalgae exhibited a particular trend. Blue light
stimulated an increase in biomass for
decline in the cell count for the other strains.
Blue light, which photons contain high energy,
With these photons, electrons are elevated toward the second excited st
However, this second excited state is just as effective for charge separation as the first
excited one; in fact, the second excited state needs to relax to the first state before charge
separation can occur. The excess energy present in
Blue light does not seem to be very well fit for photosynthesis at first glance and for this
reason, may be considered redundant
Pulse amplitude modulated (PAM) f
non-invasive and rapid techniques to measure the variability of chlorophyll fluorescence
and photosynthetic performance in terrestrial plants, macro
The fluorescence parameter F
photosynthetic activity, in order to know how
different light regimes.
P. tricornutum
BLUE 16,87
RED 3,99
-25
-20
-15
-10
-5
0
5
10
15
20O
D (
per
cen
tage
%)
. Biomass % variations for air-bubbled strains under different monochromatic (without PAR) light regimes with a 24:0 light:dark cycle. Zero line represents the controls (PAR only).
Without white light (Fig. 11), microalgae exhibited a particular trend. Blue light
stimulated an increase in biomass for P. tricornutum only, while inducing a significant
ll count for the other strains.
Blue light, which photons contain high energy, can be absorbed by chlorophyll as well.
With these photons, electrons are elevated toward the second excited state of chlorophyll.
However, this second excited state is just as effective for charge separation as the first
excited one; in fact, the second excited state needs to relax to the first state before charge
separation can occur. The excess energy present in the blue photons is wasted as heat.
Blue light does not seem to be very well fit for photosynthesis at first glance and for this
reason, may be considered redundant (Matthijs et al., 1996).
Pulse amplitude modulated (PAM) fluorometry has become one of the
invasive and rapid techniques to measure the variability of chlorophyll fluorescence
and photosynthetic performance in terrestrial plants, macro- and microalgae.
The fluorescence parameter Fv/Fm was monitored (data not shown) to evaluate
photosynthetic activity, in order to know how the photosynthetic apparatus responded to
P. tricornutum I. galbana D. tertiolecta
-21,11 -12,77
-20,56 17,02
Chapter 4
78
der different monochromatic (without PAR) light regimes with a 24:0 light:dark cycle. Zero line represents the controls (PAR only).
Without white light (Fig. 11), microalgae exhibited a particular trend. Blue light
only, while inducing a significant
can be absorbed by chlorophyll as well.
ate of chlorophyll.
However, this second excited state is just as effective for charge separation as the first
excited one; in fact, the second excited state needs to relax to the first state before charge
the blue photons is wasted as heat.
Blue light does not seem to be very well fit for photosynthesis at first glance and for this
most common,
invasive and rapid techniques to measure the variability of chlorophyll fluorescence
and microalgae.
was monitored (data not shown) to evaluate
photosynthetic apparatus responded to
D. tertiolecta
12,77
17,02
During the stationary phase, the maximum quantum efficiency decreased from 0.8 to 0.5
in all strains, mainly for the second treatment (without
microalgae had been exposed to stress.
A further evidence of physiological stress was shown by the significant increase in the
NPQ values recorded in blue light for all strains in both treatments. This parameter
monitors the apparent rate constant for non
antennae. Probably, this dissipation of thermal energy significantly increased as a
consequence of a reduction in photosynthetic efficiency (Fig.
The capacity of heat di
pigments and the magnitude of the trans
and b). Xantophylls in the antenna complex are able to dissipate exce
energy quickly as heat to protect the light harvesting complexes from increased light
energy (Baker, 2008). The capacity of this mechanism is higher when the proton gradient
or the cellular concentration of these pigments is greater (Janssen
.
Figure 12: NPQ % variations in airregimes. Zero line represents the controls (PAR only).
P. tricornutum
BLUE + PAR
RED + PAR
0
10
20
30
40
50
60
70
NP
Q (
per
cen
tage
%)
During the stationary phase, the maximum quantum efficiency decreased from 0.8 to 0.5
in all strains, mainly for the second treatment (without PAR), indicating that the
microalgae had been exposed to stress.
A further evidence of physiological stress was shown by the significant increase in the
NPQ values recorded in blue light for all strains in both treatments. This parameter
arent rate constant for non-radiative decay (heat loss) from PSII and its
antennae. Probably, this dissipation of thermal energy significantly increased as a
consequence of a reduction in photosynthetic efficiency (Fig. 12 and 13).
The capacity of heat dissipation is determined by the concentration of xantophyll
pigments and the magnitude of the trans-thylakoid proton gradient (Niyogi
and b). Xantophylls in the antenna complex are able to dissipate exce
to protect the light harvesting complexes from increased light
energy (Baker, 2008). The capacity of this mechanism is higher when the proton gradient
or the cellular concentration of these pigments is greater (Janssen et al., 2000)
% variations in air-bubbled strains under different monochromatic (plus PAR) light regimes. Zero line represents the controls (PAR only).
P. tricornutum I. galbana D. tertiolecta
55,23 61,53
1,31 4,14
Chapter 4
79
During the stationary phase, the maximum quantum efficiency decreased from 0.8 to 0.5
PAR), indicating that the
A further evidence of physiological stress was shown by the significant increase in the
NPQ values recorded in blue light for all strains in both treatments. This parameter
radiative decay (heat loss) from PSII and its
antennae. Probably, this dissipation of thermal energy significantly increased as a
12 and 13).
ssipation is determined by the concentration of xantophyll
thylakoid proton gradient (Niyogi et al., 1997 a
and b). Xantophylls in the antenna complex are able to dissipate exceeding excitation
to protect the light harvesting complexes from increased light
energy (Baker, 2008). The capacity of this mechanism is higher when the proton gradient
., 2000)
bubbled strains under different monochromatic (plus PAR) light
D. tertiolecta
48,85
1,25
Figure 13: NPQ % variations in airlight regimes. Zero line represents the controls (PAR only).
In this case, blue light stimulated a strong increase of carotenoids for all strains treated
(Fig 14), especially in I. galbana
the second part (without PAR, see Fig. 15).
Very slight increases were observed
P. tricornutum
BLUE 37,45
RED 2,12
0
10
20
30
40
50
60
NP
Q (
per
cen
tage
%)
Figure 13: NPQ % variations in air-bubbled strains under different monochromatic (without PAR) ro line represents the controls (PAR only).
In this case, blue light stimulated a strong increase of carotenoids for all strains treated
I. galbana in the first part of the experiment and in D
t PAR, see Fig. 15).
were observed under red light for all strains in both treatments.
P. tricornutum I. galbana D. tertiolecta
30,23 48,85
3,45 4,25
Chapter 4
80
bubbled strains under different monochromatic (without PAR)
In this case, blue light stimulated a strong increase of carotenoids for all strains treated
D. tertiolecta in
red light for all strains in both treatments.
D. tertiolecta
48,85
Figure 14: Carotenoids % increases in airPAR) light regimes. Zero line represents the contr
Figure 15. Carotenoids % increases in airPAR) light regimes. Zero line represents the controls (PAR only).
BLUE + PAR
RED + PAR
0,00
10,00
20,00
30,00
40,00
50,00
60,00
70,00
CA
R (
per
cen
tage
%)
P. tricornutum
BLUE 14,00
RED
0,00
5,00
10,00
15,00
20,00
25,00
30,00
35,00
40,00
CA
R (
per
cen
tage
%)
Carotenoids % increases in air-bubbled strains under different monochromatic (plus PAR) light regimes. Zero line represents the controls (PAR only).
Carotenoids % increases in air-bubbled strains under different monochromatic (without PAR) light regimes. Zero line represents the controls (PAR only).
P. tricornutum I. galbana D. tertiolecta
38,21 57,37 42,72
3,00 22,30 10,46
P. tricornutum I. galbana D. tertiolecta
14,00 18,29 36,33
7,65 11,08 10,16
Chapter 4
81
bubbled strains under different monochromatic (plus
bubbled strains under different monochromatic (without
D. tertiolecta
42,72
10,46
D. tertiolecta
36,33
10,16
Chapter 4
82
The rise in the CAR concentration related to the NPQ increment could indicate that the
energy level of excitation of the antennae was regulated so to prevent an excessive
reduction of the electron transport chain, and thus any further damage to the
photosynthetic apparatus (Bilger & Björkman, 1991; Masojídek et al., 1999).
In this way, the CAR increase is related to their antioxidant activity, as confirmed by
other authors (Schubert et al., 2006; Janknegt et al., 2008).
Total lipid content under all tested light regimes is shown in Fig. 16. From the graph it
can be noted that blue light, used in conjunction with PAR, induced an increment in the
lipid content for all strains treated, especially in the case of I. galbana. On the other hand,
the increases in lipid yield observed for P. tricornutum and D. tertiolecta under red light
and PAR were due to enhanced biomass (see Fig. 10) rather than to a higher accumulation
within the cells.
When exposed to monochromatic lights alone, the microalgae performed differently:
generally speaking, the lipid yields reached by the cultures were in most cases inferior
than those obtained under monochromatic radiations plus PAR (Fig. 16).
Chapter 4
83
mg Triolein/ml
P. tricornutum Control 0,101±0,0012
BLUE + PAR 0,134±0,0021
RED + PAR 0,129±0,0014
BLUE 0,126±0,0022
RED 0,092±0,0011
I. galbana Control 0,138±0,0013
BLUE + PAR 0,179±0,0021
RED + PAR 0,1478±0,0013
BLUE 0,085±0,0014
RED 0,085±0,0016
D. tertiolecta Control 0,080±0,0024
BLUE + PAR 0,108±0,0014
RED + PAR 0,132±0,0023
BLUE 0,070±0,0012
RED 0,088±0,0024
Figure 16. Total lipid yields under all tested light regimes. Values are expressed as milligrams of triolein per volume unit of culture.
0
0,02
0,04
0,06
0,08
0,1
0,12
0,14
0,16
0,18
0,2
mg
Tri
ole
in/m
l
Control
BLUE +
PARRED +
PARBLUE
RED
P. tricornutum I. galbana D. tertiolecta
BLUE + PAR
P. tricornutum 26,04
I. galbana 73,43
D. tertiolecta 0,68
Figure 17: Lipid content % variations (per cell) under all tested light regimes. Zero line represents the controls.
As shown in Fig. 17, cellular content of lipids was significantly higher in
PAR for I galbana and P. tricornutum
found that I. galbana exhibited maximum lipid content when grown under intermittent
blue light, while Atta et al. (2013) explained that this increased lipid c
to the fact that a large amount of light energy (ATP and NADH) in the form of high li
intensity or short wavelengths is required for the production of triacylglycer
avoid any photochemical damage in microalgal
I. galbana accumulated more
After the calculation of the average lipid content per cell of
confirmed what already seen in Fig. 8, that is that this was the sp
highest intracellular lipid content. On top of that,
lipid content per cell under pure red light;
induced a decrement in the other two strains, more pron
-60,00
-40,00
-20,00
0,00
20,00
40,00
60,00
80,00
P. tricornutumPe
rce
nta
ge
( %
)
BLUE + PAR RED + PAR BLUE
-14,72 -40,71
50,56 -15,91
-4,12 4,49
variations (per cell) under all tested light regimes. Zero line represents
, cellular content of lipids was significantly higher in
P. tricornutum than the Chlorophycea. Yoshioka
exhibited maximum lipid content when grown under intermittent
. (2013) explained that this increased lipid content could be due
to the fact that a large amount of light energy (ATP and NADH) in the form of high li
s is required for the production of triacylglycer
oid any photochemical damage in microalgal cells. Under red light plus PAR, only
more intracellular lipids than its control.
After the calculation of the average lipid content per cell of D. tertiolecta
confirmed what already seen in Fig. 8, that is that this was the species that featured the
highest intracellular lipid content. On top of that, D. tertiolecta exhibited an even higher
lipid content per cell under pure red light; conversely, monochromatic lights alone
induced a decrement in the other two strains, more pronounced in the case of
P. tricornutum I. galbana D. tertiolecta
Chapter 4
84
RED
-51,36
-16,29
29,10
variations (per cell) under all tested light regimes. Zero line represents
, cellular content of lipids was significantly higher in blue light plus
. Yoshioka et al., (2012)
exhibited maximum lipid content when grown under intermittent
ontent could be due
to the fact that a large amount of light energy (ATP and NADH) in the form of high light
s is required for the production of triacylglycerols in order to
Under red light plus PAR, only
D. tertiolecta, it was
ecies that featured the
exhibited an even higher
, monochromatic lights alone
ounced in the case of
BLUE + PAR
RED + PAR
BLUE
RED
Chapter 4
85
P. tricornutum. Unsurprisingly, the Chlorophycea showed the best response to red light,
probably because of its major chlorophyll content (data not shown) which enabled a more
effective capture of the excess energy, channeling it into the lipid synthesis.
Moreover, Rismani et al. (2011) identified transcripts of phospholipid:diacylglycerol
acyltransferase (PDAT, EC: 2.3.1.158) in D. tertiolecta, an enzyme that uses
phospholipids as acyl donors for biosynthesis of TAGs. This provides further evidence
that some microalgae might have the potential to channel the fatty acids incorporated in
membrane lipids (e.g. phosphatidylcholine), into the TAG synthesis. The identification of
this alternative route for the flux of fatty acids into and out of TAG synthesis could also
explain accumulation of TAGs when microalgae are exposed to stress conditions.
The major lipid classes in microalgae are the polar lipids which are common membrane
components(mostly phospholipids and glycolipids), and the triacylglycerols which are a
reserve of fatty acids for cellular division, metabolic energy, membrane maintenance,
synthesis and a variety of physiological uses.
The relative amounts of each lipid class in microalgal cells can change considerably with
variations in culture conditions (Roessler, 1990). Under optimal growth conditions, cells
primarily synthesize polar lipids, such as membrane phospholipids. Some strains respond
to stress conditions (e.g. photo-oxidative stress) with the accumulation of neutral lipids,
mainly TAGs (Dillschneider et al., 2013).
It is well known that under photo-oxidative stress, excess electrons are accumulated in the
electron transport chain, inducing a production of reactive oxygen species (ROS), which
may inhibit the photosynthesis process and/or damage to other macromolecules.
The de novo TAG synthesis and the consequent formation of a C18 fatty acid consumes
approximately 24 NADPH derived from the electron transport chain, which is twice that
required for synthesis of a carbohydrate or protein molecule of the same mass, and thus
relaxes the overreduced electron transport chain under stressing light (Hu et al., 2008).
The C18 compounds, oleate (18:1Δ9), linoleate (18:2 Δ9, 12) and α-linolenate (18:3 Δ9,
12, 15) together represent over 80% of economically important storage oils (Yu et al.,
2011) and Yoshioka et al., (2012) recorded that blue light induced the accumulation of
large amounts of the most desirable lipid classes, and the PUFA content was increased.
Monochromatic lights, in particular blue LEDs coupled with PAR, demonstrated to be an
efficient method to induce storage lipid accumulation.
The lower growth rates, and the high NPQ values obtained under blue light for all strains
in both experiments, indicated that microalgae were in stress conditions. The high lipid
Chapter 4
86
production observed principally in I. galbana under blue light plus PAR was coordinated
with carotenoid synthesis in our studies. Zhekisheva et al., (2002) speculated that the
molecules (e.g. β-carotene, lutein or astaxanthin) over-produced in the carotenoid
pathway could be esterified with neutral lipids, namely TAGs, and sequestered into
cytosolic lipid bodies (Přibyl et al., 2012). The peripheral distribution of carotenoid-rich
lipid bodies could serve as a ‘sunscreen’ to prevent or reduce excess light striking the
chloroplast under stress.
No qualitative analyses were carried out on the samples, but nevertheless it seems
appropriate to assume that the lipids accumulated by the strains during the experiments
(when this occurred) were primarily TAGs.
Conclusions
This work demonstrated that optimization of culture conditions may affect the production
of both biomass and lipids. In particular, mixing gave positive results because it
prevented mutual shading of the cells in the suspension, and rendered the nutrients and
the light equally available to all of them. Moreover, it has been proved that, depending on
the species, the addition of monochromatic lights to PAR can further improve these
results.
It was seen that microalgae can feature species-specific responses, based on their
sensitivity/resistance/tolerance to stress conditions.
Relying on these results, we can assume that Isochrysis galbana could be an ideal
candidate for biodiesel production on industrial scale, especially if it is properly mixed
and blue light is added to the lighting system.
From an industrial point of view, it can be concluded that a high yield in biomass or an
high initial lipid content not always translates into a profitable biodiesel productivity, as
in the case of D. tertiolecta. However, it cannot be excluded the possibility of employing
Dunaliella for these purposes. More tests should be carried out in order to improve its
growth rate, so to exploit its large amount of intracellular lipids.
After these considerations, it could be ultimately pointed out that lipid productivity (for
biodiesel production purposes) is primarily affected by biomass productivity rather than
by lipid content in the cell.
Chapter 4
87
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5 Conclusions and future perspectives
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CONCLUSIONS AND FUTURE PERSPECTIVES
In 1987 The World Commission on Environment and Development (WCED) defined
‘sustainable development’ as development that ‘meets the needs of the present without
compromising the ability of future generations to meet their own needs’ (United Nations,
1987). Sustainable energy is the need of the 21st century, not because of the numerous
environmental and political reasons but because it is necessary to human civilization's
energy future. Sustainable energy is loosely grouped into renewable energy, energy
conservation, and sustainable transport disciplines.
As a result of this impending energy crisis, both governments and private industry are
examining alternative sources of energy apart from fuels. Ironically, most renewable
energy initiatives are focused on electricity generation, while the majority of world
energy consumption, about two thirds, is derived from liquid fuels (Hankamer et al.,
2007).
When comparing biofuels with petroleum, all the effects of alternative choices on the four
‘sustainability pillars’ must be considered: good governance, social development,
environmental integrity and economic resilience (Scharlemann and Laurance, 2008).
Studies must consider impacts arising from all the steps that compose the biofuel
production chain, following a life cycles assessment (LCA) approach. LCA is a
methodology to assess all environmental impacts associated with a product, process or
activity identifying, quantifying and evaluating all the resources consumed and all
emissions and wastes released into environment (Brentrup et al., 2001).
Microalgae have received considerable interest as a potential feedstock for producing
sustainable transport fuels. The perceived benefits provide the driving reason for much of
the public support directed towards microalgae research.
High oil content species cultured in growth-optimized conditions of PBRs have the
potential to yield 19,000–57,000 litres of microalgal oil per acre per year. The yield of oil
from algae is over 200 times the yield from the best performing oleaginous crops
(Demirbas, 2010)
However, estimating the extent to which algal biofuel could reduce oil imports is
difficult, giving the many different variables surrounding species, growth rate,
illumination, open pond vs. PBR, and land availability (Adenle et al., 2013).
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In this work we examined several aspects of microalgae production: the correct choice of
the strains, a methodology to extract lipid content and the right culture conditions in order
to increase biomass and lipid production. Optimizing the growth conditions is a critical
step to develop an economical route for sustainable algal biomass production (Bechet et
al., 2013).
Biodiesel has great potential; however, the high cost and limited supply of organic oils
prevent it from becoming a serious competitor for petroleum fuels. As petroleum fuel
costs rise and supplies dwindle, alternative fuels will become more attractive to both
investors and consumers. For biodiesel to become the alternative fuel of choice, it
requires an enormous quantity of cheap biomass (Campbell, 2008). Using innovative
techniques for cultivation, algae may allow biodiesel production to achieve the price and
scale of production needed to compete with, or even replace, petroleum.
Impediments to large-scale culture of microalgae are mainly economic. The global cost
associated with biodiesel production from microalgae may be split into the partial costs
associated with biomass growth, harvesting (including dewatering and concentration of
biomass to a suitable level for further processing), oil extraction and oil
transesterification. Furthermore, the traditional project costs of engineering, licensing,
infrastructure build-up, equipment purchase, installation and integration, and contractor
fees are also to be considered. In terms of other operating and maintenance costs,
expenses for nutrients (generally nitrogen and phosphorus sources), enriched CO2 supply,
water replenishment due to evaporative losses, other power utilities, components
replacement and labor costs are to be considered as well – besides land rent or capital
investment rate of leasing (Singh and Gu, 2010).
The costs in biofuel production from algal biomass amount approximately to 50 €/l,
which is very unlikely to attract the commercial production of algal biofuels. Biofuels
will need to be cost-competitive with fossil fuels for their commercial scaling-up (Ahrens
and Sander, 2010).
Most laboratory-scale approaches take advantage of fluorescent lamps, which have a
relatively high power consumption, coupled with high capital costs: for a given total light
intensity, replacement of fluorescent lamps by light emitting diodes (LED) may lead to
about a 50% decrease in power investment, and a lower cost per unit of time of useful
life. Obviously, an investigation of the cost of more extensive approaches for algal
biofuel production is needed.
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Much of the research addressing algae production is currently confined to the laboratory.
Although many companies have moved from laboratory- and bench-scales to small pilot-
scale, the major challenges of nutrient supply, land or infrastructures, water availability,
light delivery, gas exchange, environment control, and culture integrity have limited
further scale-up, and the number of studies and companies operating at demonstration-
and full-scale is limited.
Further efforts on microalgae production should concentrate in reducing costs in small-
scale and large-scale systems. This could be achieved in many ways: for example one
promising opportunity seems to be the production of algal biomass in wastewater,
providing a readily available medium for the production of algal biomass at almost no
cost (Ahrens and Sander, 2010), while removing nutrients from the wastewater and
reducing the environmental pollution; or by adopting cheaper-design culture systems with
automated process control and with fewer manual labor; or else by integrating the
production of algae at a power-plant, in order to take advantage of waste carbon dioxide,
and possibly the waste heat from the power-plant to increase algal yields.
A defined set of technology breakthroughs will be required to develop the optimum
utilization of algal biomass for the commercial production of biofuel. If these
technological breakthroughs occur, biofuels based on algal biomass will play a role in the
future energy systems.
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98
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