EFFECTS OF DIFFERENT LIGHT SPECTRA ON THE GROWTH,

COMPOSITION, AND PRODUCTIVITY OF MICROALGAE

FROM 4 DIFFERENT TAXA WITH DIFFERENT PIGMENT PROFILES

By

Ganjar Saefurahman

BSc Marine Science (Bogor Agricultural University, Indonesia)

This thesis is presented for the degree of Master of Philosophy of

Murdoch University

2015

ii

DECLARATION

I declare that this thesis is my own account of my research and contains as its main

content work which has not previously been submitted for a degree at any tertiary

education institution.

Ganjar Saefurahman

iii

ABSTRACT

Microalgae are renewable sources for the production of high-value products, biofuels

and environmental applications. Microalgae are photosynthetic plant-like organisms

with a diversity of light-harvesting pigments. Light is the main limit to the growth of

microalgae. However, photosynthesis only uses part of the solar spectrum (400-700 nm)

called photosynthetically active radiation (PAR). Characterization of promising species,

optimum photosynthetic productivity and efficiency have become a significant aspect in

further development of efficient lighting designs/filters for microalgal culture systems.

In this study, effects of three different light spectra: white (400-700 nm), blue (407-488

nm), and red (621-700 nm) on the key parameters of Nannochloropsis sp., Botryococcus

braunii, Amphora sp., and Pleurochrysis carterae were investigated. The cultures

received an equal light energy (2.23±0.10 W.m-2) so that the main effect was the light

quality, and were grown and acclimated to the changes of spectral conditions.

All species responded differently to the light spectra in their key parameters, i.e.

photosynthetic and respiration rates, growth, biomass, lipid, carbohydrate, protein,

chlorophyll content, and productivity. The use of narrower PAR, i.e. blue and red,

significantly increased particular parameters in 4 tested species compared to the full

spectrum (white light). High photosynthetic rates in particular spectrum were not

always followed by a higher growth rate so that the growth of microalgae was not only

related to the photosynthesis mechanisms, but also influenced by other cellular

processes which are also spectrally dependent. The low levels of oxygen concentration

significantly increased the photosynthetic rates of 4 species. This study found that the

chlorophyll c containing algae all have heavier cells and higher cellular content of lipid,

carbohydrate, and protein under red light. In general, the effects of tested spectra were

different and species-dependent based on the variability of pigment profiles, absorption

iv

and action spectra, photoregulation of enzymes, chromatic adaptation, and

photoacclimation responses.

v

TABLE OF CONTENTS

DECLARATION ............................................................................................................. ii

ABSTRACT .................................................................................................................... iii

TABLE OF CONTENTS................................................................................................ v

ACKNOWLEDGEMENTS.......................................................................................... vii

1 INTRODUCTION ................................................................................................... 1

1.1 Microalgae .......................................................................................................... 1

1.2 Why culture microalgae ..................................................................................... 2

1.2.1 Productivity ................................................................................................. 2

1.3 Potential uses ...................................................................................................... 2

1.4 Microalgae culture methods ............................................................................. 10

1.4.1 Autotrophic, heterotrophic, and mixotrophic culture................................ 11

1.4.2 Open and closed culture ............................................................................ 13

1.5 Limits to growth of microalgae ........................................................................ 20

1.5.1 Light and photosynthesis........................................................................... 20

1.5.2 Other limits to growth ............................................................................... 46

1.6 Microalgae used in this study ........................................................................... 53

1.6.1 Nannochloropsis sp. .................................................................................. 54

1.6.2 Botryococcus braunii ................................................................................ 55

1.6.3 Amphora sp. .............................................................................................. 58

1.6.4 Pleurochrysis carterae .............................................................................. 61

1.7 Rationale and aims of this thesis ...................................................................... 64

2 MATERIALS AND METHODS.......................................................................... 68

2.1 Sources of algae................................................................................................ 68

2.2 Experimental set-up .......................................................................................... 70

2.3 Analytical methods ........................................................................................... 73

2.3.1 Cell density and growth............................................................................. 73

2.3.2 Biomass determination .............................................................................. 73

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2.3.3 Total lipid determination ........................................................................... 74

2.3.4 Total carbohydrate assay ........................................................................... 75

2.3.5 Total protein assay .................................................................................... 75

2.3.6 Productivity ............................................................................................... 76

2.3.7 Chlorophyll determination ........................................................................ 76

2.3.8 Photosynthetic and dark respiration rate measurement............................. 77

2.4 Data analysis..................................................................................................... 79

3 EFFECTS OF DIFFERENT LIGHT SPECTRA .............................................. 81

3.1 Results .............................................................................................................. 81

3.1.1 Photosynthesis, respiration, and growth.................................................... 81

3.1.2 Biomass and proximate composition ........................................................ 94

3.1.3 Productivity ............................................................................................. 100

3.1.4 Overview and comparison of the 4 species ............................................. 103

3.2 Discussion....................................................................................................... 111

3.2.1 Photosynthesis, respiration, and growth.................................................. 111

3.2.2 Biomass and proximate composition ...................................................... 128

3.2.3 Productivity ............................................................................................. 140

4 CONCLUSION.................................................................................................... 142

5 APPENDICES ..................................................................................................... 146

6 REFERENCES .................................................................................................... 150

vii

ACKNOWLEDGEMENTS

Firstly, I would like to thank my supervisors Professor Michael Borowitzka and Dr.

Navid Moheimani for their boundless guidance, encouragement, and support throughout

the course of my master study. I am very pleased to work and learn with them as a part

of my precious research and phycological journey that I will never forget.

Special thanks go to Mrs. Indrayani, who guided me through all laboratory and

microalgal cultivation techniques, and supported me throughout my research and life

experiences in Australia.

Many thanks must also go to Phillip Nowotny, Raluca Frazer, and Dr. David Parlevliet

for their support and kindness during the light experiment period. I could not

accomplish this without you guys.

The students and members of the “United Nations” of Algae R&D Centre, Murdoch

University, Eric, Andreas, Jasper, Jason Webb, Dr. Karne, Kazuki, Luke, Jeremy,

Ashiwin, Dr. Jeffrey, Ankitha, Jason Crisp, Carolina, Nick, Katrin and many friends

also deserve my faithful appreciation. Thank you for all cooperation, kindness and

friendship. Cheers!

Many thanks also to Murdoch University Indonesian Students’ Association and

Indonesian communities in Perth for their encouragement, support, and greatest

comradeship over the years.

I would like to thank Professor Anthony Larkum and Dr. M. del Pilar Sánchez Saavedra

for examining my thesis and providing very useful comments and corrections to the

thesis manuscript.

viii

I would also like to thank Dr. Mujizat Kawaroe, Dahlia, Dina, and Ito, the greatest

microalgal research team ever. They introduced and made me falling in love with these

tiny marvelous microalgae. It changed my life, and I enjoy it a lot.

My most humble and greatest gratitude must go to my family, my beloved parents, Mr.

Ruhiyat and Mrs. Ida, Mr. Muharman and Mrs. Irwati, my darling wife Intan Dwita

Kemala, thank you for your infinite love and patience, and my baby boy Hanzhalah, my

brothers Mas Aan, Iman, Mas Sofjan, my sisters Elis, Heny, Uni Jippi, and all my big

family in Indonesia. They are the utmost reason for all achievement in my life.

“Alhamdulillah” This success is for them.

Finally, I thank the Australian Development Scholarship program for the financial

support and great opportunity to study in Australia.

1

1 INTRODUCTION

1.1 Microalgae

Algae are very diverse assemblage of (mainly) photosynthetic plant-like organisms that

have neither roots nor leafy shoots, and lack of vascular tissues which distinguish them

from higher plants (van den Hoek et al. 1995). Algae most commonly exist in fresh,

marine, or brackish water. However, they can also be found in almost every other

environment on earth, from the algae growing in snow, to algae living in lichen

associations on bare rocks, to unicellular algae in desert soils, and to algae living in hot

springs (Lee 2008). Microalgae are the (mainly) unicellular microscopic algae (Barsanti

and Gualtieri 2006; Lee 2008). Almost all algal phyla have microalgal representatives

with an estimated 35,000 species having been described to date, and it is estimated that

the actual number of species is higher (Borowitzka 2013d).

The names of the divisions and classes of algae often refer to the colour or pigments of

the organisms, such as Cyanophyceae (blue-green algae, cyanobacteria), Rhodophyceae

(red algae), Chlorophyceae (green algae), Chrysophyceae (golden algae), and

Phaeophyceae (brown algae). Therefore, the kinds and combinations of photosynthetic

pigments have an important role in algal classification (van den Hoek et al. 1995).

Microalgae can be either autotrophic, heterotrophic or mixotrophic (Becker 1994;

Tuchman 1996). Autotrophic algae require only inorganic compounds, such as carbon

dioxide (CO2), nutrients, and light energy for growth, while for heterotrophic growth

they need an external source of organic compounds and nutrients as their energy source.

Some photosynthetic microalgae are mixotrophic, in which they have the ability to

perform both photosynthesis as well as using organic compounds in the light (Barsanti

and Gualtieri 2006; Brennan and Owende 2010).

2

1.2 Why culture microalgae

1.2.1 Productivity

Microalgae provide the potential benefits of photosynthetic organisms associated with

high productivities supporting large-scale production and applications. They have the

same photosynthetic mechanism as higher plants (Barsanti and Gualtieri 2006). Most

microalgae are phototrophs, requiring only light, water, and simple inorganic sources

for the metabolism and growth, which are available at essentially zero cost (Malcata

2011). Microalgae have a higher overall areal productivity than other photosynthetic

organisms, such as trees, and also have the potential to be grown using saline water and

on non-arable land (Borowitzka and Moheimani 2013b). For many regions suffering

low productivity due to poor soils or the freshwater shortage (almost all places with

high solar radiation), the microalgae that can be grown using sea or brackish water may

be the only way to increase productivity and secure a basic protein supply (Vonshak

1990; Borowitzka and Moheimani 2013b). Different microalgae species are adapted to

live in a variety of environmental conditions (Guschina and Harwood 2013). Therefore,

it is possible to find species best suited to local environments or specific growth

characteristics (Mata et al. 2010). The productivity of microalgal products, such as

biomass, lipid, carbohydrate, protein or pigments, is an important characteristic for

microalgal production, and is expressed as g.L-1.day-1 or g.m-2.day-1. Productivity is

defined as: Productivity = µ x Q, where µ is the specific growth rate (day-1) and Q is the

quantity of the microalgal product per unit volume (L) or area (m2) (Borowitzka 2013d).

1.3 Potential uses

Microalgae have been cultured worldwide and considered as the potential source for

commercial high value products and biofuels for the last few decades (Borowitzka

2013b). These organisms present a diversity of form, chemistry, genetic diversity and

3

range of habitats, and this diversity is exploitable for commercial processes (Nonomura

1988). The lack of a requirement for an exogenous carbon source for energy potentially

makes the large-scale production of microalgae in open ponds comparatively cheap

(Apt and Behrens 1999). The relatively ease of microalgae cultivation and simple

harvesting for some strains (i.e. Spirulina) has a number of advantages from industrial

perspective that has led to an increased commercial interest in the biotechnology of

these organisms (Walker et al. 2005). For commercial applications, any selected species

must demonstrate high productivities of the targeted product when they are grown at

commercial scale in the selected culture system (Borowitzka 2013d). As a result of

microalgae screening in terms of their capability as sources for high-value products and

applications, a large variety of microalgae sample have been collected and cultured.

During the past decades, extensive collections and developments of microalgae cultures

both in the laboratory and outdoors for commercial applications have been established

in different countries (Borowitzka 2013b).

Early studies were on the use of unicellular microalgae for human food and other useful

high-value products and applications (Tamiya 1957; Krauss 1962). Some microalgae

have been exploited for hundreds of years, e.g. Nostoc in China and Spirulina in Chad

and Mexico (Spolaore et al. 2006). There are several developments from human food

(Krauss 1962; Becker 1988), animal nutrition (Becker 1988), fertilizers and soil

conditioners (Metting 1988), and the production of high-value products, e.g. poly-

unsaturated fatty acids, anti-oxidants, pigments and colouring substances,

bioflocculants, biodegradable polymers, cosmetics, pharmaceuticals, antibiotics, and

stable isotopes biochemicals (Borowitzka 1988b; Cohen 1999; Spolaore et al. 2006). A

large number of different commercial products have been derived from microalgae

(Table 1).

4

Despite their high content of protein, dried microalgae have not gained significant

importance as food or food substitute. The major obstacles are the powder-like

consistency of the dried biomass, its dark green colour, smell, and the cost of drying

which limit the incorporation of the microalgae biomass into conventional food

products (Becker 2007). In addition, conventional and alternative protein sources with

much cheaper cost of production, e.g. eggs and soya, are available (Becker 2007). The

consumption of microalgae biomass as important raw materials for human health food

supplements is currently applied to few species, e.g. Spirulina, Nostoc and

Aphanizomenon for high protein content, Chlorella for β-1,3-glucan, and Dunaliella

salina for β-carotene (Spolaore et al. 2006). There is incentive for using microalgae as

alternative high quality protein supplements to replace conventional protein sources on

poultry, pigs, ruminants, and insects (Becker 1988). It is estimated that about 30% of

the current world algae production is sold for animal feed applications (Becker 2007).

Microalgae produce a diverse range of fine chemicals which have commercial

application and have been proposed as sources of carotenoid pigments, vitamins,

proteins, lipids, and polysaccharides (Borowitzka 1988b). Phycobiliproteins,

phycoerythrin, phycocyanin, and allophycocyanin produced by the cyanobacteria are

used as food dyes, pigments in cosmetics, and as fluorescent reagents in clinical or

research laboratories (Viskari and Colyer 2003; Singh et al. 2005).

Another expanding market is the utilization of microalgae in aquaculture (Borowitzka

1997; Muller Feuga 2013). Several species are considered as a good food sources for

aquaculture species, such as Isochrysis galbana, Chaetoceros spp., Skeletonema spp.,

Thalassiosira spp., Tetraselmis spp., Nannochloropsis spp., Pavlova lutheri, Nitzschia

spp., and Navicula spp. (Regan 1988; Borowitzka 1997). The green water technique

(GWT), that maintains some algae cultures in larval-rearing tanks, is a common practice

5

in hatcheries of most cultured species including finfish, shrimp, and crabs (Neori 2011;

Zmora et al. 2013).

6

Table 1. Summary of existing and potential high-value products from microalgae, alternative sources and the application of these products

(from Borowitzka 2013c).

Product Potential or existing algae source Some alternate source(s) Applications Selected references

Carotenoids β-carotene Dunaliella salina Blakesleya trispora, synthetic Pigmenter (food), pro-vitamin A, antioxidant

(Borowitzka and Borowitzka 1989b; Choudhari et al. 2008; Borowitzka 2010b)

Astaxanthin Haematococcus pluvialis, Chlorella

zofingiensis

Xanthophyllomyces,

dendrorhous, synthetic Pigmenter (aquaculture), anti-oxidant

(Cysewski and Lorenz 2004; Lemoine and

Schoefs 2010; Rodríguez Sáiz et al. 2010;

Schmidt et al. 2011)

Canthaxanthin Chlorella spp., other green algae Dietzia natronolimnaea, synthetic

Pigmenter (aquaculture, poultry and food)

(Arad et al. 1993; Hanagata 1999; Nasrabadi and Razavi 2010)

Zeaxanthin Chlorella ellipsoidea; Dunaliella salina

(mutant)

Paprika (Capsicum annuum);

Tagetes erecta, synthetic Anti-oxidant, food pigmenter (Jin et al. 2003; Koo et al. 2012)

Lutein Scenedesmus spp., Muriellopsis sp.,

other green algae Tagetes sp., Blakesleya trispora Anti-oxidant

(Piccaglia et al. 1998; Blanco et al. 2007;

Choudhari et al. 2008; Sánchez et al. 2008; Fernández Sevilla et al. 2010)

Phytoene, phytofluene Dunaliella Tomato (Solanum lycopersicum) Anti-oxidant, cosmetics (von Oppen Bezalel and Shaish 2009)

Echinenone Botryococcus braunii, cyanobacteria

Anti-oxidant (Matsuura et al. 2012)

Fucoxanthin Phaeodactylum tricornutum Brown algae Anti-oxidant (Kim et al. 2012)

Phycobilins (phycocyanin,

phycoerythrin,

allophycocyanin)

Cyanobacteria, Rhodophyta,

Cryptophyta, Glaucophyta

Natural pigment (e.g. cosmetics and food

products), fluorescent conjugates, anti-

oxidant, etc.

(Oi et al. 1982; Glazer and Stryer 1984;

Eriksen 2008a)

Fatty acids Arachidonic acid Parietochloris incisa Mortiriella spp. Nutritional supplement (Bigogno et al. 2002; Solovchenko et al. 2008; Streekstra 2010)

Eicosapentaenoic acid Nannochloropsis spp., Phaeodactylum

tricornutum, Monodus subterraneus etc. Fish oil Nutritional supplement

(Hu et al. 1997; Molina Grima et al. 1999;

Sukenik 1999; Lu et al. 2001)

Docosahexaenoic acid Crypthecodinium cohnii,

Schizochytrium spp., Ulkenia spp. Fish oil Nutritional supplement

(Mendes et al. 2009; Barclay et al. 2010;

Wynn et al. 2010)

Sterols Many species Various plants Nutraceutical (Fabregas et al. 1997; Volkman 2003;

Francavilla et al. 2010)

Squalene Aurantiochytrium sp. Shark liver Cosmetics (Kaya et al. 2011)

Polyhydroxyalkonates Nostoc spp., Synechocystis and other

cyanobacteria

Ralstonia sp; GM Escherichia

coli Biodegradable plastics

(Vincenzini and De Philippis 1999; Philip

et al. 2007; Haase et al. 2012)

Polysaccharides Porphyridium spp., Rhodella spp., various cyanobacteria

Guar gum, xanthan Thickeners, gelling agents etc., cosmaceuticals

(De Philippis et al. 2001; Pereira et al. 2009; Arad and Levy Ontman 2010)

Mycosporine-like amino acids Cyanobacteria, Dinophyta and other

algal phyla Sunscreens

(Garcia Pichel and Castenholz 1993;

Llewellyn and Airs 2010)

7

Furthermore, numerous species from various microalgae groups, such as diatoms and

dinoflagellates, are a rich source of long-chain poly-unsaturated fatty acids (LCPUFA)

(Apt and Behrens 1999; Spolaore et al. 2006). The most commonly considered PUFAs

of value as nutritional supplements for humans and animals are arachidonic acid (AA),

docosahexaenoic acid (DHA), γ-linolenic acid (GLA), and eicosapentaenoic acid (EPA)

(Spolaore et al. 2006). Several companies market algae-derived LCPUFA preparations

as healthcare products or as a source of LCPUFA in aquaculture feeds (Apt and Behrens

1999). Phaeodactylum tricornutum is one of the most persistent microalgae cultured on

the outdoor large-scale cultures as rich sources of marine oils and essential fatty acids,

but has never been produced commercially (Regan 1988). However, AA has been

shown to be synthesized by Porphyridium, DHA by Crypthecodinium and

Schizochytrium, GLA by Spirulina, and EPA by Nannochloropsis, Phaeodactylum and

Nitzschia (Cohen 1999; Sukenik 1999; Spolaore et al. 2006), and these algae are

currently being explored for commercial use.

Nowadays, the partnership between microalgae cultivation and biofuel production is

promising because of the intrinsic autotrophic capacity of the former (Malcata 2011).

Potential microalgae biofuels include biodiesel from algal lipids, bioethanol or

biobutanol from algal sugars, long-chain hydrocarbons (Botryococcus), hydrogen,

methane, and crude oils from the pyrolysis and hydrothermal liquefaction of algal

biomass (Borowitzka 1988a; Dermibas 2006; Chisti 2007; Hankamer et al. 2007; de

Boer et al. 2012). The U.S. National Renewable Energy Laboratory (NREL), through

the Aquatic Species Program (ASP), launched a specific R&D program of alternative

renewable fuels, including biodiesel from microalgae between 1978 and 1996 (Sheehan

et al. 1998). This work is now being continued by very many other researchers and

companies.

8

Biofuel from the photosynthetic microalgae which grow on CO2 has great potential. For

instance, biodiesel production from microalgae provides the potential of high net energy

because converting oil into biodiesel is less energy-intensive than methods for

conversion to other fuels (Parmar et al., 2011). Some microalgae have a high starch

content and potential for bioethanol production (Sastre 2012). These simple sugars can

be converted to ethanol by anaerobic fermentation (John et al. 2011; Parmar et al.

2011).

However, there is still a wide gap between existing technologies (especially in the

extraction/fractionation process) and an industrial scale economic microalgae-based

biofuel production (Cooney et al. 2009). The key technologies, in terms of producing

microalgae for biofuel, include identification of optimum culture conditions for high

lipid productivity, development of effective and economical microalgae culture

production, harvesting, extraction of microalgae biomass, and efficient conversion of

the lipids to fuels on a very large-scale and at low-cost (Chen et al. 2011; Fon Sing et al.

2013). Improved strains are important to enhance the reliability of the cultures and the

economics of the whole production process in terms of optimum temperature,

temperature tolerance, carbon supply, pH, oxygen tolerance, respiration rate, salinity,

morphology, competitive strains, lipid composition and quality, and co-products

(Borowitzka 2013d). Developments of bioreactor designs in terms of operation at high

cell densities, gaseous mass transfer, light availability, and less expensive downstream

processing are also required (Malcata 2011).

de-Boer et al. (2012) reported an energy-based assessment of the various conversion

methods available for algal biomass to fuel. Methods were classified as conversion of

the whole algae, in situ, and extract then convert. The outcomes of this study highlight

that to date, hydrothermal liquefaction is the best method for converting algae to

9

biofuel. This method is shown to be energetically feasible, but requires large economies

of scale, high capital costs, and produces a low volume of fuel relative to the lipid

content in the algal biomass (de Boer et al. 2012).

In addition, organic material such as algal biomass can also be used to produce biogas

via anaerobic digestion and fermentation (Hankamer et al. 2007). The production of

hydrogen gas (H2) from water and sunlight using microalgae through biophotolysis has

been a subject of applied research since the early 1970s (Benemann 2000). Biological

hydrogen production has several advantages over hydrogen produced by

photoelectrochemical or thermochemical processes (Parmar et al., 2011). However,

microalgae hydrogen production has several issues. H2 production by direct

biophotolysis only takes place at very low levels of dissolved O2. Thus, these processes

require the presence of O2 consuming reactions, such as respiration, or the purging of

the culture with an inert gas, which make such a process impractical (Benemann 2004).

Indirect biophotolysis processes carry out the O2 and H2 production reactions in

separate stages: the first involving CO2 fixation into storage carbohydrates, and the

second involving carbohydrate fermentations to H2 (Benemann 2000). The first reaction

can be established in low-cost open ponds, but the fermentative step involves a light-

driven H2 evolution reaction, which still requires complex and high-cost

photobioreactor system (Benemann 2004; Geier et al. 2012).

Some microalgae cultures are promising for environmental applications, such as CO2

mitigation and bioremediation (Huntley and Redalje 2007; Wang et al. 2008;

Borowitzka 2013b; Solovchenko and Khozin Goldberg 2013), and wastewater treatment

(Hammouda et al. 1995; Robinson 1998). Some species, such as Chlorococcum littorale

(Kodama et al. 1993; Murakami and Ikenouchi 1997), Pleurochrysis carterae

(Moheimani and Borowitzka 2006, 2007), and Chlorella (Usui and Ikenouchi 1997;

10

Doucha et al. 2005; Borkenstein et al. 2011), have been successfully cultured for long

periods for biological CO2 sequestration.

Although microalgae are not yet produced at large-scale for commercial applications,

except for high value products, recent developments, particularly in systems biology,

material sciences, genetic engineering, and biorefining, present opportunities to upgrade

this process in an economical and sustainable way within the next 10-15 years (Wijffels

and Barbosa 2010).

1.4 Microalgae culture methods

There are three basic types of microalgae culture systems in terms of the method, i.e.

batch, continuous, and semi-continuous (fed-batch) cultures (Lee et al. 2013). Many of

the methods and basic culture medium concepts that are used today were developed in

the late 1800s and early 1900s (Preisig and Andersen 2005).

Batch culture consists of a single inoculation of cells into a container of fertilized water

or seawater followed by a growing period of several days and finally harvesting when

the microalgae cells reach their maximum or near-maximum density (Coutteau 1996).

In practice, microalgae are transferred to larger culture volumes prior to reaching the

stationary phase, and the larger culture volumes achieve a maximum density and can be

harvested (Barsanti and Gualtieri 2006). In continuous culture, fresh culture medium is

continuously pumped to the homogenously mixed culture close to the maximum growth

rate, and the excess culture is washed out continuously or intermittently (Lee et al.

2013). The continuous cultures are mostly operated based on the concentration of

particular chemicals (chemostat) or turbidity (turbidostat) of the culture medium

(Coutteau 1996). Semi-continuous culture prolongs the use of large culture vessels by

partial periodic harvesting, followed immediately by topping up to the original volume

and supplying with nutrients to achieve the original level of enrichment (Barsanti and

11

Gualtieri 2006). When the culture is grown up again, then it is partially harvested and

the harvested medium is replaced (Coutteau 1996).

Advantages of batch culture systems are their operational simplicity, flexibility, and

low-cost (Barsanti and Gualtieri 2006). However, batch culture is not considered as the

most efficient method because the quality of the harvested biomass might be less

predictable or inconsistent than that in continuous or semi-continuous systems (Barsanti

and Gualtieri 2006). Another disadvantage is the need to prevent contamination during

the initial inoculation and early growth phase. This is because the density of the desired

microalgae is low and the concentration of nutrients is high, in which any contaminant

with a faster growth rate is capable of outgrowing the culture (Coutteau 1996).

Continuous culture has the advantages of producing algae of more predictable quality,

but this system has relatively high cost and complexity (Barsanti and Gualtieri 2006).

Semi-continuous culture is used in most microalgal production systems, e.g. in the Asia-

Pacific (Lee 1997). This method is relatively easier and cheaper than continuous culture,

and more efficient and reliable compared to batch culture (Coutteau 1996).

1.4.1 Autotrophic, heterotrophic, and mixotrophic culture

Autotrophic culture is when microalgae use light, such as sunlight, as the energy source,

inorganic carbon (carbon dioxide) as the carbon source, and macro and micro-nutrients

for their metabolism through photosynthesis (Becker 1994). A potential advantage of

using autotrophic culture to produce microalgae biomass is the consumption of CO2 as

carbon source for the cell growth and biochemical production (Mata et al. 2010).

However, when CO2 is the only carbon source, the culture facility should be close to

factories or power plants which can supply a large quantity of CO2. The main reason of

using autotrophic growth for microalgae production is to avoid using organic carbon,

i.e. sugars. Therefore, outdoor large-scale microalgae culture systems, e.g. open ponds

12

and raceway ponds, are usually operated under autotrophic conditions (Borowitzka

1999; Mata et al. 2010).

Some microalgae species not only grow under autotrophic conditions, but can also use

organic carbon under dark conditions (Droop 1974). Heterotrophic cultures is when

microalgae use organic carbon, such as glucose, ethanol, glycerol, and fructose as both

the energy and carbon source in the dark (Tuchman 1996; Chojnacka and Marquez-

Rocha 2004). This type of culture method can avoid the problems associated with light

limitation that hinders high cell density in large-scale autotrophic cultures (Huang et al.

2010).

The main disadvantages are that heterotrophic culture is not possible for all microalgae

and the chemical composition of the microalgae often changes under heterotrophic

conditions (Borowitzka 1999). In addition, a major cost factor in the production of

heterotrophic culture is the cost of the organic substrate (Barclay et al. 2013). The

production costs of heterotrophic culture system have been shown to be uneconomical

for most applications, and the product is often inferior to autotrophically grown algae

(Borowitzka 1999). However, some recent successful commercial production have been

achieved, e.g. Chlorella for nutritional supplements, and Crypthecodinium and

Schizochytrium for DHA production (Barclay et al. 2013).

Mixotrophic culture is defined as a growth regime, in which both CO2 and organic

carbon are assimilated, both respiratory and photosynthetic metabolism operate

simultaneously (Lee 2004). The advantages of mixotrophic culture compared to other

methods are low light sensitivity, higher biomass and lipid productivity (Zhao et al.

2012; Wang et al. 2014). Cheirsilp and Torpee (2012) reported that mixotrophic

cultures of marine Chlorella sp. and Nannochloropsis sp. produced much higher yields

of biomass and lipid production than photoautotrophic and heterotrophic cultures. Das

13

et al. (2011) also found that the maximum specific growth rate, total FAME, biomass

and volumetric FAME yield of Nannochloropsis sp. in mixotrophic culture were higher

than in phototrophic culture. The disadvantage is the problem of controlling possible

bacterial contamination during culture incubation (Mitra et al. 2012). For production

scale-up, it is difficult to achieve an aseptic environment for algae culture (Yen and

Chang 2013).

In summary, for large-scale microalgae production, autotrophic culture is by far the

most frequently used (or proposed to be used), generally in open or raceway pond

systems, because these are the most economical culture systems (Borowitzka and

Moheimani 2013a).

1.4.2 Open and closed culture

Microalgae cultures, especially the large-scale systems, are classified into a) Open

systems where the culture is directly exposed to the environment, and b) Closed systems

where the whole culture is enclosed within the culture vessel (Borowitzka and

Moheimani 2013a). Commercial-scale culture of microalgae mostly requires the ability

to economically produce large quantities of microalgal biomass. This requires culture

volumes of 10,000 to greater than 1,000,000 L, and therefore almost all commercial-

scale culture is established in outdoor open systems (Borowitzka 2005).

Open pond culture systems are the main systems used to produce microalgae

commercially that can be classified as shallow lagoons and ponds, inclined systems,

circular central-pivot ponds, mixed ponds, and raceway ponds (Borowitzka and

Moheimani 2013a). Open raceway ponds appear to be the most suitable cultivation

system for economical biomass production. On the other hand, closed photobioreactors

are too expensive to construct, and they also have a high energy requirement for the

14

operation of the microalgae culture and for cooling during the day under high solar

irradiance (Borowitzka 1999; Stephenson et al. 2010).

An example of large-scale open pond system are the extensive, shallow, unlined, and

unmixed open ponds at Hutt Lagoon (Western Australia) and Whyalla (South Australia)

used by BASF for the cultivation of Dunaliella salina. Pond areas range from 5 ha to

more than 200 ha, with an average depth of 20 to 30 cm and extreme high salinity

environment (Borowitzka 2005; Borowitzka and Moheimani 2013a). Both facilities

with a very high annual irradiance, a warm climate and a low rainfall, produce

Dunaliella salina biomass for β-carotene extraction (Borowitzka 2013a).

Other facilities using raceway pond systems are those operated by Cyanotech Co. in

Hawaii and Earthrise Farms in California for the production of Haematococcus and

Arthrospira biomass (Cysewski and Lorenz 2004). In both cases, large paddle-wheel

mixed raceway ponds from 1,000 to 5,000 m2 are used. Raceway ponds are also used

for intensive cultivation of Dunaliella salina by Nature Beta Technologies Ltd. in Israel

(Ben Amotz and Avron 1990).

Most of the commercial open pond cultivation systems use solar energy as the light

source, which is the cheapest light source available, being directly utilized (Pulz 2001).

In general, the productivity of outdoor open ponds is relatively poor compared to closed

photobioreactors, due to the problems of it being difficult to control the culture

conditions, direct exposure to ultra violet (UV) irradiation, contamination, local

climatological variations, physical properties of the design, day-night cycles, diurnal

variation, and the need for a large area of land (Oswald 1988; Chen et al. 2011).

However, calculations indicate that the biomass productivity of an open-air culture

system using paddle-wheel raceway ponds can be very competitive with the closed

system if located in a sunnier, warmer climate, and constructed of cheaper materials

15

(Borowitzka 1999). The important properties of different large-scale algal culture

systems are described in Table 2.

16

Table 2. Comparison of the properties of some large-scale algal culture systems (from Borowitzka 1999).

Reactor type Mixing Light utilisation

efficiency

Temperature

control

Gas

transfer

Hydrodynamic stress

on algae

Species

control Sterility Scale-up Ref.*

Unstirred Very poor Poor None Poor Very low Difficult None Very difficult a

shallow ponds

Tanks Poor Very poor None Poor Very low Difficult None Very difficult b

Circular Fair Fair-good None Poor Low Difficult None Very difficult c

stirred ponds

Paddle-wheel Fair-good Fair-good None Poor Low Difficult None Very difficult d

Raceway ponds

Stirred Tank

reactor

Largely

uniform Fair-good Excellent Low-high High Easy

Easily

achievable Difficult e

Air-Lift reactor Generally

uniform Good Excellent High Low Easy

Easily

achievable Difficult f

Bag Culture Variable Fair-good Good (indoors) Low-high Low Easy Easily

achievable Difficult g

Flat-Plate reactor Uniform Excellent Excellent High Low-high Easy Achievable Difficult h

Tubular reactor Uniform Excellent Excellent Low-high Low-high Easy Achievable Reasonable i

(Serpentine)

Tubular reactor Uniform Excellent Excellent Low-high Low-high Easy Achievable Easy j

(Biocoil)

*a) Borowitzka and Borowitzka (1989a), b) Fox (1983), c) Tamiya (1957), d) (Weissman and Goebel (1987); Oswald (1988)), e) Pohl et al. (1988), f) Juttner (1977), g) Baynes et al. (1979), h) (Hu et al. (1996); Tredici and Zittelli (1997)), i) (Richmond et al. (1993); Torzillo (1997)), j) Borowitzka (1996).

17

The closed microalgae cultivation systems are classified as photobioreactors or

fermenters. A photobioreactor is a closed or mostly closed vessel for phototrophic

production where energy is supplied via solar energy or artificial lights, whereas a

fermenter is a closed vessel for heterotrophic production where energy is supplied in the

form of organic carbon (Behrens 2005) (Table 3). The closed reactor systems have some

advantages, such as high light utilization efficiency leading to relatively high biomass

productivities, as well as light and temperature control (Borowitzka 1999).

Table 3. Comparison of closed culture systems: photobioreactor and fermenter

features (from Behrens 2005).

Feature Photobioreactor Fermenter

Energy source Light Organic carbon

Cell density/dry weight Low High

Limiting factor for growth Light Oxygen

Harvestability Dilute, more difficult Denser, less difficult

Vessel geometry Dependent on light penetration

Independent of energy source

Control of parameters High High

Sterility Usually sanitized Can be completely sterilized

Availability of vessels Often made in-house Commercially available

Technology base Relatively new Centuries old

Construction costs High per-unit volume Low per-unit volume

Operating costs High per-kg biomass Low per-kg biomass

Applicability to algae Photosynthetic algae Heterotrophic algae

Most commercial production of microalgae is in open ponds where the culture is mixed

either by paddle wheels or by a centrally pivoted rotating arm (Borowitzka and

Moheimani 2013a). However, some industrial production of microalgae operate closed

systems, e.g. the culture of Haematococcus pluvialis in Israel and Chlorella in

Germany, both of which are grown in tubular photobioreactors, the culture of H.

pluvialis in Hawaii using dome-shaped photobioreactors, and the heterotrophic

production of the thraustrochytrid Crypthecodinium in closed fermenters (Fon Sing et

al. 2013). In addition, a number species of microalgae, e.g. Isochrysis, Nannochloropsis,

Tetraselmis, and Chaetoceros produced for feeding in aquaculture at a wide range of

18

scales, uses both open and closed culture systems, mostly large bags or tanks

(Borowitzka 1997; Zmora et al. 2013).

For economic and sustainable development of high-value products from microalgae,

high and reliable annual algae biomass yield and productivity are important

(Borowitzka and Moheimani 2013b). Therefore, the selection and optimization of

microalgae culture systems is essential to achieve this (Chen et al. 2011; Fon Sing et al.

2013). Microalgae biomass yield and productivity may also vary, depending on the

season and meteorological conditions (López Elias et al. 2003). Table 4 summarises

biomass yields and productivities in open and closed systems reported in literatures. In

respect to biomass productivity, open pond systems generally are less efficient when

compared with closed photobioreactors (Table 4). The range of open ponds areal

productivity of selected reported results is from 2 to 40 g.m-2.day-1, while for closed

photobioreactors, it is from 10.2 to 47.7 g.m-2.day-1. The range of volumetric

productivity of open ponds is from 0.003 to 3 g.L-1.day-1, whereas for closed

photobioreactors, it is from 0.05 to 3.8 g.L-1.day-1.

19

Table 4. Biomass productivity figures for open ponds and closed photobioreactors

as P-areal (g.m-2.day-1) and P-volume (g.L-1.day-1) (adapted from Brennan and

Owende 2010; Borowitzka and Moheimani 2013a).

Microalgae species Cultivation system Volume

(L) P-areal P-volume Reference

Anabaena sp. Raceway 300 9.4-23.5 0.031-

0.078 (Moreno et al. 2003)

Chlorella sp. Raceway (in greenhouse)

260 13.2 0.05 (Hase et al. 2000)

Cyclotella sp. wild type Raceway - 12 - (Huesemann et al.

2009)

Tetraselmis sp. Raceway 600 5-40 0.008-

0.060

(Matsumoto et al.

1995)

Dunaliella salina Raceway 110 20-37 0.22-0.34 (Moheimani and

Borowitzka 2006)

Gloeotrichia natans Raceway 200 14.7-18.1 0.183-

0.226

(Querijero Palacpac et

al. 1990)

Muriellopsis sp. Raceway 100 12.9 0.129 (Blanco et al. 2007)

Pleurochrysis carterae Raceway 160-200 16-33.5 0.11-0.21 (Moheimani and Borowitzka 2006)

Scenedesmus obliquus Raceway - 15 - (Payer et al. 1978)

Spirulina platensis Raceway 750 15-27 0.06-0.18 (Richmond et al.

1990)

Spirulina platensis Raceway 13,200-

19,800 14.5 0.03-0.12 (Ayala et al. 1988)

Spirulina sp. Raceway 135,000 2-17 0.006-0.07 (Jimenez et al. 2003)

Tetraselmis sp. Raceway 500 11.2 0.024 (Matsumoto et al.

1995)

Tetraselmis suecica Raceway 300-600 5-26 0.01-0.05 (Pedroni et al. 2004)

Porphyridium cruentum Raceway 120 5-24 0.04-0.20 (Cohen et al. 1988)

Chlorella sp. Inclined thin layer

pond 1,000 10-30 1-3

(Doucha and Lívanský

2006)

Scenedesmus obliquus Inclined thin layer pond

2,500 19 - (Dilov et al. 1985)

Phaeodactylum

tricornutum

Continuous flume

(raceway) 4,150 2.4-11.3 0.003-0.13 (Laws et al. 1983)

Chlorella sp. Circular central

pivot pond 1,960 1.61-16.47 0.02-0.16

(Kanazawa et al.

1958)

Chlorella sp. Open culture system 2,400-

16,200 19-22 - (Tsukuda et al. 1977)

Phaeodactylum

tricornutum Airlift tubular 200 20 1.2

(Acién Fernández et

al. 2001)

Phaeodactylum tricornutum

Airlift tubular 200 32 1.9 (Molina et al. 2001)

Chlorella sorokiniana Inclined tubular 6 - 1.47 (Ugwu et al. 2002)

Spirulina platensis Undular row tubular 11 47.7 2.7 (Carlozzi 2003)

Phaeodactylum

tricornutum

Outdoor helical

tubular 75 - 1.4 (Hall et al. 2003)

Haematococcus

pluvialis Parallel tubular 25,000 13 0.05 (Olaizola 2000)

Haematococcus

pluvialis Bubble column 55 - 0.06

(Garcia-Malea Lopez

et al. 2006)

Nannochloropsis sp. Flat plate 440 - 0.27 (Cheng-Wu et al.

2001)

Haematococcus pluvialis

Flat plate 25,000 10.2 - (Huntley and Redalje 2007)

Spirulina platensis Tubular 5.5 - 0.42 (Converti et al. 2006)

Spirulina Tubular 146 25.4 1.15 (Carlozzi 2000)

Chlorella Flat plate 400 22.8 3.8 (Doucha et al. 2005)

Tetraselmis Column 1,000 38.2 0.42 (Zittelli et al. 2006)

Chlorococcum Parabola 70 14.9 0.09 (Sato et al. 2006)

20

1.5 Limits to growth of microalgae

Although the focus of this thesis is the use and adaptation of different types of

microalgae to different light spectra, it is also essential to consider other limits to the

growth, composition, productivity, and photosynthesis of microalgae cultures. In the

following section, light and photosynthesis, as well as other important limits to growth

of microalgae, such as temperature, oxygen, nutrients (N, P, Si), salinity, carbon

dioxide, pH, and mixing will be discussed.

1.5.1 Light and photosynthesis

The source of light

Light is electromagnetic radiation that can be produced by a variety of energy-

conversion processes (Falkowski and Raven 1997; Hall and Rao 1999). The sun is the

global source of light energy in the biosphere. About 99% of the sunlight is in the

wavelength region from 300 to 4000 nm, and this is called the total solar radiation.

Within this broadband, different forms of energy occur, which can be associated with

specific characteristics, such as harmful ultraviolet radiation (UV 100-400 nm), vision

and photosynthesis (visible light 400-700 nm), and heat (infrared radiation 700-4000

nm) (Barsanti and Gualtieri 2006). According to quantum theory of Max Planck, light

energy is distributed in the form of packages called photons or quanta (Masojídek et al.

2004). Planck’s quantum theory is expressed as E=h.v, where E is the energy of a single

quantum of light (photon), v is the frequency of the radiation (the number of waves

transmitted per unit time), and h is a constant (Hall and Rao 1999). Since frequency is

inversely related to wavelength, so that photons short-wave light are more energetic

than photons of light of longer wavelength, e.g. photons of blue light (400 nm) of the

visible spectrum are more energetic than those of red light (700 nm). Furthermore, as

light penetrates through the water column, it decreases in its intensity (attenuation), and

21

a narrowing of the radiation band is caused by the combined absorption and scattering

of everything in the water column (Barsanti and Gualtieri 2006). The attenuation of

light in the sea is the result of absorption by four components, which are the water itself,

dissolved yellow pigments, microalgae, and inorganic particulate matter (Joint 1990).

Different spectra of light penetrate differently within the visible spectrum (400-700

nm); red light is absorbed first within the first 5 m. In clear water, the deepest

penetration is by the blue-green region of the spectrum (450-550 nm), whereas under

turbid conditions, e.g. coastal water, the penetration of blue is often reduced to a greater

extent than that of the yellow-red wavelengths (550-700 nm) (Barsanti and Gualtieri

2006) (Figure 1). Phytoplankton have adapted to this changing light environment, and

photosynthesis and fluorescence by microalgae show strong wavelength dependence

(Sathyendranath and Platt 1990).

In both indoor and outdoor microalgae culture systems, the light sources are critical

factors affecting the performance of the phototrophic growth of microalgae (Mata et al.

2010). The energy of solar radiation as received on the earth at a particular geographical

location is considered as the first limitation to the development process of microalgae

large-scale culture, while photosynthesis and the physiology of the alga can be

considered as the second (Cook 1951). Moreover, biotechnological applications of

microalgae biomass, as well as biofuel production and carbon sequestration, require

utilization of strains which can utilise the available light efficiently in large-scale

cultures, especially under bright sunlight (Mitra and Melis 2008).

22

Figure 1. Depth profiles for downward irradiance of blue (○), green (●), and red

(∆) light in a tropical oceanic, Pacific Ocean (a); and three inland freshwater

systems: San Vicente Reservoir, USA (b), Corin Dam, Australia (c), and

Georgetown billabong, Australia (d) (from Kirk 2010).

Light availability and efficient use by the cells are considered the main factors affecting

microalgae productivity (Cuaresma et al. 2011; Beardall and Raven 2013). Light

availability as a limiting factor of energy supply can decrease the inorganic carbon

fixation rate, and cells grown under light limited conditions have a lower capacity for

accumulating CO2 (Beardall et al. 1998). Supply, distribution, and utilization of light in

microalgae cultures are the central aspects, which require particular attention in the

design of culture vessels (Eriksen 2008b).

A microalgae cultivation system can be illuminated by solar light, artificial light or

combinations of different light sources. Solar energy is free and abundant. However,

23

direct solar light use for microalgal production has some disadvantages, as the light

intensity of sunlight varies greatly with the weather, season, location, and operating

time of culture systems, and the possibility of photoinhibition due to excessive light

(Blanken et al. 2013). Therefore, artificial light sources, such as fluorescent lights, high

intensity discharge lamps (HID), light-emitting diodes (LEDs), optical fiber excited by

metal halide lamp (OF-MH), optical fiber excited by solar energy (OF-solar), and

LED/OF-solar combined with wind power/solar panel can be promising alternative

lighting systems (Chen et al. 2011; Blanken et al. 2013; Schulze et al. 2014).

A mixture of low-cost cool white and warm white fluorescent tubes has been used in

many indoor culture facilities (Lorenz et al. 2005). LEDs are potential artificial sources,

which are mercury-free, fast-responding artificial light sources emitting nearly

monochromatic light at various wavelengths, and small enough to fit any culture system

(Das et al. 2011; Abiusi et al. 2014; Schulze et al. 2014). Other advantages of LEDs

include a longer life-expectancy, lower heat generation, and higher conversion

efficiency (Chen et al. 2011). In addition to LEDs and HID lamps, optical fiber excited

by artificial lights is another potential light source to improve microalgae culture

systems. Small optical fiber-based photobioreactors have been used for growing algae

(Matsumaga et al. 1991). However, the high-cost of most artificial light installations and

their operation, remain a major problem when compared to sunlight (Chen et al. 2011;

Blanken et al. 2013).

Photosynthesis of microalgae

Photosynthesis is the only significant solar energy storage process on Earth, and is the

major source of human food and energy resources (Blankenship 2010). Microalgae and

other phototrophic organisms do not use all wavelengths of solar radiation.

Photosynthesis is restricted to wavelengths from 400 to 700 nm, the range of

24

wavelengths termed photosynthetically active radiation (PAR) (Figure 2), and different

wavelengths of PAR are used with different efficiencies (Hill 1996; Barsanti and

Gualtieri 2006). Microalgae use the light in two main ways: firstly as information in

sensing processes, supported by the photoreceptor systems; and secondly as energy in

transduction processes, supported by chloroplasts in photosynthesis (Barsanti and

Gualtieri 2006).

Figure 2. The spectrum of electromagnetic radiation (from Masojídek et al. 2004).

Photosynthesis involves two major types of reactions (Figure 3). The first type, the

“light-dependent reactions”, comprises the capture of the light energy and its conversion

to energy currency as nicotinamide adenine dinucleotide phosphate (NADPH) and

adenosine triphosphate (ATP) (Barsanti and Gualtieri 2006). These reactions are the

absorption and transfer of photon energy, the capture of this energy by photosynthetic

pigments, and the generation of a chemical potential coupled with the release of oxygen.

The latter reaction generates NADPH due to the passage of the high energy excited

electron along an electron transport system, whereas the second one generates ATP by

means of a proton gradient across the thylakoid membrane. The second type of reactions

are the “light-independent reactions” of the Calvin-Benson cycle, in which this chemical

25

potential is used to fix and reduce inorganic carbon in triose phosphates (Barsanti and

Gualtieri 2006).

Figure 3. The process of oxygenic photosynthesis showing integration of the light-

dependent and light-independent reactions (from Tuchman 1996).

The photosynthetic apparatus of microalgae consists of chloroplasts, their membranes

and particles, light harvesting pigment complexes, reaction centre and the energy

transfer (Kirk 1983). The chloroplasts contain the pigments which capture the light, the

electron carriers which use the absorbed energy to generate reducing power in the form

of NADPH and biochemical energy in the form of ATP, and the enzymes which use the

NADPH and the ATP to convert CO2 and water to carbohydrate (Kirk 1983).

Photosynthetic light-dependent reactions take place in a specialized type of membrane

called the thylakoid, where chromophore-protein complexes and membrane-bound

enzymes are situated (Barsanti and Gualtieri 2006) (Figure 4). The thylakoid

membranes contain five major complexes: light harvesting antennae, photosystem II

(PS II), photosystem I (PS I) and both reaction centre, cytochrome b6/f, and ATP

26

synthase, which maintain photosynthetic electron transport and photophosphorylation

(Masojídek et al. 2013).

The enzymes of CO2 fixation are distributed throughout the chloroplast stroma or, in

certain algal chloroplasts, some of the enzymes may be located in a specific structure

within the chloroplast known as the pyrenoid (Kirk 1983). PS II and PS I exist within

the thylakoid membrane, each containing light harvesting pigment complexes and

specific types of electron transfer cofactors in the reaction centre (Nugent et al. 2003).

PS I is associated with the reduction of NADP to NADPH, whereas PS II is responsible

for the splitting of water and the consequent evolution of oxygen (Hill 1996). The

important step within PS II and PS I is the use of the absorbed light energy to transfer

an electron from a donor molecule to an acceptor molecule (Kirk 2010).

Figure 4. The arrangement of thylakoid membranes (from Masojídek et al. 2013).

The NADPH and ATP generated by the electron transport chain in the thylakoid

membranes couple the light reactions to carbon fixation and cell growth. For

photoautotrophic microalgae, approximately 95% of the NADPH and more than 60% of

the generated ATP are used to assimilate and reduce inorganic carbon (Falkowski and

27

Raven 1997). The light- independent reactions pathway of inorganic carbon fixation

involves the enzyme ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco),

which uses CO2 as a substrate, through the Calvin-Benson cycle (Falkowski and Raven

1997; Kirk 2010) (Figure 5).

Figure 5. The Calvin-Benson or photosynthetic carbon fixation pathways (from

Masojídek et al. 2004).

The Calvin-Benson cycle has four different phases which are: carboxylation phase (i),

reduction phase (ii), regeneration phase (iii), and production phase (iv) (Masojídek et al.

2013). The carboxylation phase is a reaction of CO2 addition to the 5-carbon sugar,

ribulose bisphosphate (Ribulose-bis-P), to form two molecules of phosphoglycerate

(Glycerate-P). This reaction is catalysed by Rubisco. The reduction phase converts

glycerate-P to 3-carbon products (Triose-P), and the energy must be added in the form

of ATP and NADPH in two steps: the phosphorylation of glycerate-P to form

diphosphoglycerate (Glycerate-bis-P), and the reduction of glycerate-bis-P to

phosphoglyceraldehyde (Glyceraldehyde-P) by NADPH. In the regeneration phase,

ribulose-P is regenerated for further CO2 fixation in complex reactions combining 3-, 4-

28

, 5-, 6-, and 7-carbon sugar phosphates. Finally, the primary end-products of

photosynthesis in the production phase are considered to be carbohydrates, but fatty

acids, amino acids, and organic acids are also synthesised in this processes.

From the first identification of the photosynthetic process in plants, it has been

recognized that it was the pigmented regions which were involved in the conversion of

light energy to chemical energy (Rowan 1989). Light harvesting pigment-protein

complexes are a diverse group of proteins and pigments which transfer absorbed

excitation energy of photons to a photosynthetic reaction centre for photochemistry

(Falkowski and Raven 1997; Masojídek et al. 2004) (Table 5). The quality and quantity

of pigments in algae are the primary chemical factors which influence the amount of

light harvested for photosynthesis by the algae (Dring 1990).

Table 5. Distribution of some microalgae major pigments: (+) contains, (-) lacks

(from Kirk 2010).

Algae group Chlorophyll

Carotenoids Phycobilins Phycocyanin a b c1 c2 c3 d

Chlorophyta (+) (+) (-) (-) (-) (-) (+) - -

Euglenophyta (+) (+) (-) (-) (-) - (-) - -

Heterokontophyta (+) - (+/-) (+/-) (-/+) - (+/-) - -

Haptophyta (+) - (+/-) (+) (+/-) - - - -

Dinophyta (+) - (-/+) (+) - - (+) - -

Phaeophyta (+) - (+) (+) - - - - -

Cryptophyta (+) - - - - - - (+) (+)

Rhodophyta (+) - - - - - - (+) (+)

Cyanophyta (+) - - - - (-/+) - (+) (+)

Prochlorophyta (+) (+) - - - - - - -

There are three chemically distinct types of light harvesting pigment-protein complexes:

the chlorophylls, the carotenoids, and the biliproteins (Kirk 1983; Rowan 1989). The

chlorophylls and carotenoids are lipophilic and associated in Chl-protein complexes,

whereas phycobilins are hydrophilic (Masojídek et al. 2004). The chlorophylls are

cyclic tetrapyrrole compounds with a magnesium atom chelated at the centre of the ring

29

system (Kirk 1983). Five major types of chlorophylls are chlorophyll a, b, c, d, and f

(Larkum 2003; Willows et al. 2013). All chlorophylls have two major absorption bands

of blue or blue-green and red with different absorption peaks, e.g. chlorophyll a (430

and 670-690 nm), chlorophyll b (455 and 650-660nm), chlorophyll c (442-444, 630nm),

and chlorophyll d (380, 440 and 700-720 nm) (Larkum 2003). The carotenoids are

another type of photosynthetic pigment with an absorption range between 400 and 550

nm, which consist of the carotenes and the xanthophylls (Rowan 1989; Masojídek et al.

2004). They have similar chemical structures of C40 isoprenoid compounds, absorb

blue light, transmit yellow and red, and are weakly fluorescent (Round 1973; Dring

1990). Carotenoids also play important roles in the protection against excess irradiance,

chlorophyll triplets and reactive oxygen species (Masojídek et al. 2004).

The biliprotein chloroplast pigments are found only in certain algae, i.e. Rhodophyta,

Cryptophyta, and Cyanophyta (Kirk 1983). They are classified into four types:

phycocyanin, phycoerythrin, allophycocyanin, and phycoerythrocyanin (Rowan 1989).

In contrast to the Chl-proteins and carotenoids, phycobiliproteins are water-soluble, and

the pigments are covalently bound to apoprotein (Masojídek et al. 2004).

Accessory pigments can modify the light field, e.g. carotenoids in diatom communities

reduce the penetration of 450 to 500 nm wavelengths, whereas phycocyanins in

cyanobacteria reduce the penetration of 620 nm wavelengths to underlying cells (Hill

1996). Some algae pigments do not transfer excitation energy, for example, the

secondary carotenoids, such as orange-red coloured xanthophylls, astaxanthin and

canthaxanthin (Masojídek et al. 2013). They are overproduced in some algal species,

e.g. Haematococcus pluvialis when grown under unsuitable conditions (Masojídek et al.

2004). The intrinsic antioxidant activity of these carotenoids is the basis for their

protective action against oxidative stress (Guedes et al. 2011).

30

Ability of photosynthetic organisms including algae to optimize its photosynthetic

productivity and growth depends on its capacity to sense, examine, and respond to

changing light quality, quantity, and direction (Briggs and Olney 2001; Depauw et al.

2012). As a consequence, they have evolved an extremely sophisticated system of

photoreceptors and signal transduction pathways for growth, development and

physiological responses (Hegemann 2008; Kianianmomeni and Hallmann 2014). The

main photoreceptor gene families, which are generally found in plants, algae, and

microorganisms comprise: 1) Phytochromes, 2) The ultraviolet-A (UV-A)/blue light-

sensing photoreceptors (e.g. phototropins and cryptochromes), 3) Blue light- light,

oxygen, voltage (LOV) photoreceptors (e.g. aureochromes and neochromes), 4) Other

blue light photoreceptors using flavin adenine dinucleotide (BLUF), and 5) The UV-B

photoreceptor UVR8 (Hegemann 2008; Jenkins 2014; Rockwell et al. 2014; Li et al.

2015b).

Phytochrome, the first photoreceptor identified in plants and algae, are red/far-red light

sensors that assess changes in light quality in the red and far-red regions of the visible

spectrum, regulating shade avoidance, light-dependent development, and

photomorphogenesis (Rockwell et al. 2006; Franklin and Quail 2010; Li et al. 2015a).

However, Rockwell et al. (2014) reported that algal phytochromes are not limited only

to red and far-red responses. Different algal phytochromes were also able to sense

orange, green, and even blue light (Rockwell et al. 2014).

Phototropins are blue-light photoreceptors for phototropism that regulate important

physiological responses under blue light control in plants and algae (Hegemann 2008;

Li et al. 2015b). In green algae, phototropins mediate the blue light- induced chloroplast

photoorientation (Suetsugu et al. 2005). Phototropins are also involved in regulation of

photoresponses and light- induced developmental processes, such as conversion of

31

pregametes to gametes during gametogenesis, and cell size regulation in the green alga

Chlamydomonas reinhardtii (Huang et al. 2002; Huang and Beck 2003; Oldenhof et al.

2006).

Cryptochromes are flavoproteins-blue light receptors that are involved in growth,

cellular and physiological processes in plants and algae (Chaves et al. 2011).

Cryptochromes were identified in the genomes of the multicellular green alga Volvox

carteri (Prochnik et al. 2010), the unicellular green alga Chlamydomonas reinhardtii

(Merchant et al. 2007), green alga Ostreococcus tauri (Heijde et al. 2010), and the

diatom Phaeodactylum tricornutum (Coesel et al. 2009). Aureochromes represent a

blue-light receptor of photosynthetic stramenopile algae (Heterokontophyta), e.g.

Vaucheria frigida (Xanthophyceae), Fucus distichus (Phaeophyceae), and Thalassiosira

pseudonana (Bacillariophyceae); whereas neochrome is a chimeric photoreceptor gene-

phototropin derivative, which are fusing blue and red light sensing proteins in plants

and green algae, e.g. regulating blue and red light- induced photoorientation of

chloroplasts in Mougeotia scalaris (Kagawa and Suetsugu 2007; Takahashi et al. 2007;

Hegemann 2008; Kianianmomeni and Hallmann 2014).

BLUF is another blue light flavin-based photosensing unit that is solely found in

Euglenoids flagellate and bacteria, and binds flavin adenine dinucleotide (FAD)

(Gomelsky and Klug 2002; Losi and Gartner 2011). UV Resistance Locus 8 (UVR8) is

a recently discovered ultraviolet-B (UV-B) photoreceptor protein identified in plants

and algae, e.g. in the green algae Chlamydomonas reinhardtii and Volvox carteri

(Rizzini et al. 2011; Jenkins 2014; Miyamori et al. 2015). UVR8 mediates

photomorphogenic responses to UV-B light, e.g. the change in biochemical

composition, photosynthetic competence, morphogenesis, defense mechanisms, and

promotes UV-photoprotective responses (Jenkins 2014).

32

Effects of light quality

This thesis is mostly focused on the light quality (spectra) as the primary factor of

microalgal production. Light, both quality and quantity, is the main limit to the growth

and productivity of microalgae, but the requirements vary with species, culture depth,

and the density of the microalgae culture (Soeder and Stengel 1974; Borowitzka and

Moheimani 2013a). In fact both the quality and intensity of the light field change

simultaneously, and the algae must adapt to both (Kirk 1983). In their natural

environment, phytoplankton, such as diatoms, are exposed to rapidly changing light

regimes when they are transported from deep water layers below the euphotic zone to

full sunlight at the water’s surface (Lepetit et al. 2010). Microalgae are also capable of

modifying their photosynthetic electron flow capacity, by changing the maximum rate

and or by diverting photogenerated electrons towards different sinks depending on their

growth status (Cardol et al. 2011).

The absorption spectrum is the variation of some measure of light absorption by light-

harvesting pigments in microalgae with wavelength (Kirk 1983) (Figure 7 and Figure

8), whereas the wavelength dependence of a photochemical reaction is called the action

spectrum, and the ratio of the product formed per unit light absorbed is called the

quantum yield (Falkowski and Raven 1997). Absorption spectra give us information

about the spectral range in which pigment molecules organized in the thylakoid

membranes capture photons. Absorption spectra in the PAR range have been measured

in vivo on photosynthetic compartments (thylakoid membranes, chloroplasts) of single

cells belonging to each algal division (Barsanti and Gualtieri 2014) (Figure 7). The

variation in quantum yield with wavelength is considered to be primarily due to the fact

that there are two photosynthetic reactions, which both must be energized for

photosynthesis to occur, and have different light harvesting pigment arrays with various

absorption spectra within microalgal species (Kirk 2010).

33

A graph showing the rate of photosynthesis as O2 evolution or CO2 fixation by

monochromatic light as a function of the light wavelength is known as the action

spectrum graph of photosynthesis (Hall and Rao 1999) (Figure 6). It was used in the

1940s by Emerson and associates to determine the action spectra of photosynthesis for

various algae by measuring the maximum quantum yield of photosynthesis as a function

of the monochromatic light that illuminated the algae (Hall and Rao 1999). The

Emerson’s study also revealed the so-called red drop in photosynthesis in Chlorella,

which is a significant decrease of the quantum yield of photosynthesis with the

increasing wavelength beyond 685 nm, although chlorophylls still absorb light at this

spectrum (Emerson and Lewis 1943; Hall and Rao 1999).

Figure 6. Action spectra of relative oxygen evolution of A. Nannochloropsis oculata

(Eustigmatophyceae) (from Tamburic et al. 2014); and action spectra of PS II

oxygen evolution of B. Chaetoceros gracilis (Diatoms) (from Neori et al. 1986).

Selective absorption of different wavelengths of PAR by certain photosynthetic

pigments, coupled with variation in the spectral distribution of light in aquatic habitats,

presents the potential for light quality effects (Larkum and Barrett 1983; Hill 1996).

According to the chromatic adaptation theory of Theodor W. Engelmann (1883), it is

34

the spectral variation of the light with depth which determines algal distribution so that

as the predominant colour changes due to selective absorption, those algae which have

absorption bands corresponding best to the spectral distribution of the surviving light

can perform photosynthesis most effectively and predominate the ecosystem (Kirk

2010). Chromatic adaptation, which increases the ability of an alga to absorb radiation

in a specific light field, was described as the complementary chromatic adaptation

(Dring 1990).

Chromatic adaptation may be phylogenetic or ontogenetic; the former is adaptation that

has taken place during phylogeny, i.e. during the evolution of the species, while the

second is adaptation due to the alteration of the proportion of the different pigments

with significant effects on absorption properties in accordance with the environmental

conditions during growth and development (Kirk 1983). There are many reports of

algae showing chromatic adaptation by developing pigments complementary to the light

transmitted by the medium (Rowan 1989).

35

Figure 7. In vivo absorption spectra (black line) of the photosynthetic

compartments (thylakoid membranes and chloroplasts) in algae culture, i.e. A.

Arthrospira (Cyanobacteria), B. Porphyridium (Rhodophyta), C. Chlorella

(Chlorophyta), D. Dunaliella (Chlorophyta), E. Pavlova (Haptophyta), F.

Nannochloropsis (Heterokontophyta), G. Phaeodactylum (Diatoms,

Heterokontophyta) and H. Prorocentrum (Dinophyta). Chlorophyll a (bright green

line), chlorophyll b (olive-green line), chlorophyll c (blue line), carotenoids and

xanthophylls (orange line) and phycobiliproteins (purple lines) (from Barsanti and

Gualtieri 2014).

36

Figure 8. In vivo absorption spectra of carotenoids and xanthophylls: alloxanthin,

astaxanthin, β-carotene, canthaxanthin, diadinoxanthin, echinenone, fucoxanthin,

lutein, neoxanthin, peridinin, violaxanthin, and zeaxanthin (from Barsanti and

Gualtieri 2014).

Furthermore, the adjustment of light quality also can lead to successful production of

high cell density cultures and biochemical synthesis (Soeder and Stengel 1974). Light

quality is a key factor for controlling microalgal growth, biochemical synthesis, and

pigment composition (Senger and Bishop 1966; Pickett 1971; Wallen and Geen 1971b;

Voskresenskaya 1972; Jeffrey and Vesk 1977; Kowallik and Schatzle 1980; Humphrey

37

1983; Kowallik and Bartling 1984; Kowallik and Schürmann 1984; Holdsworth 1985;

Kowallik 1987; Aidar et al. 1994; Sánchez Saavedra and Voltolina 1994, 1996; You and

Barnett 2004; Sánchez Saavedra and Voltolina 2006; Das et al. 2011; Baba et al. 2012;

Cao et al. 2013; Marchetti et al. 2013), cell settlement and division (Oldenhof et al.

2004; Cao et al. 2013), cell cycle (Oldenhof et al. 2006), enzyme activity (Conradt and

Ruyters 1980; Ruyters 1980a, b, 1981, 1982; Kowallik and Grotjohann 1984; Kowallik

and Neuert 1984; Ruyters 1984), and photosynthesis and respiration (Kowallik and

Gaffron 1966; Kowallik 1982; Humphrey 1983; Aidar et al. 1994; Mercado et al. 2004;

Baba et al. 2012).

For instance, several enzymes related to microalgae photosynthesis have already been

reported to be under blue light control (Voskresenskaya 1972; Ruyters 1984) (Table 6).

Photoregulation of metabolic reactions in photosynthetic organisms by blue light is

possible by a regulation of enzyme syntheses or by a direct effect of this spectrum on

the enzyme activity itself, with either phytochrome or yellow pigments, e.g. FMN

(flavin mononucleotide) or carotenoids as possible photoreceptors (Schmid 1980).

These large numbers of enzymes reported to be influenced by blue light can be divided

into two main groups: photosynthetic enzymes including those of pigment synthesis and

photorespiration, and carbohydrate degrading enzymes (Ruyters 1984).

38

Table 6. Enzymes reported to be under blue light control for both enhancement (+)

and inhibition (-) in microorganisms and algae (modified from Ruyters 1984).

Enzyme Algae Effect Reference

ALA dehydratase Chlorella M 20 + (Ruyters 1984)

Scenedesmus C-2A' + (Senger et al. 1980)

ALA synthetase Scenedesmus C-2A' + (Senger et al. 1980)

Aldolase Euglena gracilis + (Russell et al. 1978)

DOVA-dehydrogenase Scenedesmus C-2A' + (Senger et al. 1980)

DOVA-transaminase Scenedesmus C-2A' + (Senger et al. 1980)

Fumarase Euglena gracilis + (Horrum and

Schwartzbach 1980)

Glyceraldehyde phosphate

dehydrogenase (NAD-dep.) Chlorella M 20 - (Ruyters 1984)

Chlorogonium elongatum + (Stabenau 1972)

Scenedesmus obliquus +

(Kulandaivelu and Sarojini

1980)

Glyceraldehyde phosphate

dehydrogenase (NADP-dep.) Chlamydomonas reinhardii + (Ruyters 1984)

Chlorella vulgaris +

(Kowallik and Grotjohann

1984)

Chlorogonium elongatum + (Stabenau 1972)

Euglena gracilis + (Russell et al. 1978)

Scenedesmus obliquus -

(Kulandaivelu and Sarojini

1980)

Isocitratase Chlorogonium elongatum - (Stabenau 1972)

Nitrate reductase Chlamydomonas reinhardii - (Azuara and Aparicio

1983)

Nitrite reductase Chlorella pyrenoidosa + (Ruyters 1984)

Phosphoenolpyruvate

carboxylase Chlorella ellipsoidea +

(Ogasawara and Miyachi

1970)

Chlorella M 20 + (Ruyters 1980b)

Chlorella M 125 +

(Kamiya and Miyachi

1975)

Chorogonium elongatum + (Stabenau 1972)

Scenedesmus obliquus +

(Kulandaivelu and Sarojini

1980)

Phosphoglycerate kinase Euglena gracilis + (Russell et al. 1978)

Pyruvate kinase Acetabularia mediterranea + (Schmid 1984)

Chlorella M 20 + (Ruyters 1980a)

Scenedesmus C-2A' + (Ruyters 1982)

Ribulosebisphosphate

carboxylase Anabaena flos-aquae - (Codd and Stewart 1980)

Chlamydomonas reinhardii + (Ruyters 1984)

Chlorogonium elongatum +

(Roscher and Zetsche

1986)

Euglena gracilis + (Russell et al. 1978)

Microcystis aeruginosa - (Codd and Stewart 1980)

Succinate dehydrogenase Euglena gracilis + (Horrum and

Schwartzbach 1980)

UDPG-pyrophosphorylase Acetabularia mediterranea + (Vettermann 1973; Schmid

1984)

Carbonic anhydrase Chlamydomonas reinhardtii + (Dionisio et al. 1989)

39

Previous researches also revealed a strong indication of blue light effect on

carbohydrate degradation by enhancement in the activity of pyruvate kinase (Kowallik

and Schatzle 1980; Kowallik 1987). This enzyme catalyses the formation of pyruvate

and ATP, phosphoenolpyruvate (PEP) and ADP being the substrates (Ruyters 1980a). It

can be speculated that blue light somehow increases the outflow of carbohydrates from

their storage compartment into the cytosol. This event may lead to a substrate-induced

biosynthesis of bottle neck enzymes, which result in an acceleration in the total flow of

carbohydrates through their catabolic pathway (Kowallik and Schatzle 1980).

A typical characteristic of these blue light effects is light of very low intensities which is

absorbed by small amounts of a yellow pigment leads to such amplified outcomes as

enzymic activation or inactivation (Schmid 1980). Ruyters (1980a) proposed a dual

effect of blue light on pyruvate kinase, i.e. first in a change of the enzyme conformation

resulting in a higher PEP affinity, and second in a de novo synthesis of enzyme protein.

In addition, Kamiya and Miyachi (1975) indicated that subsequent illumination with

blue light specifically induced the PEP carboxylase activity in colourless mutant cells of

Chlorella vulgaris. The enhancement of a de novo synthesis of the enzyme proteins

might then be a consequence of an increased production of specific mRNA's, which

somehow promoted by the short wavelength visible quanta (Kowallik and Bartling

1984). The wavelength dependence of this phenomenon has been found in agreement

with that of the increased protein synthesis and enhanced enzyme activity (Kowallik

1965; Senger and Bishop 1968; Kowallik and Neuert 1984).

Conradt and Ruyters (1980) also mentioned that blue light mediated the enhancement of

a microalgal chloroplast enzyme, i.e. the glyceraldehyde 3-phosphate dehydrogenase

(GAPDH), in a chlorophyll- free Chlorella mutant, whereas red light illumination of

different wavelength from 665-730 nm and of different intensities up to 1000 µW.cm-2

40

proved to be completely ineffective. The enhancement activity can be explained either

of GAPDH by an increase in enzyme level or by an activation of pre-existing enzyme

molecules (Conradt and Ruyters 1980). The metabolic pathways of carbohydrate

degradation include the glycolysis, tricarboxylic acid (TCA) cycle, and its blue light-

enhanced enzymes are described in Figure 9.

41

Figure 9. The pathways of carbohydrate degradation include the glycolysis,

tricarboxylic acid (TCA) cycle, and its blue light-enhanced enzymes (in full

frames) (adapted from Ruyters 1984).

The presence of blue light influences 9 enzymes of carbohydrate degradation pathways

in algae, which are the uridine diphosphoglucose pyrophosphorylase (UDPG-PPase),

42

glucose-6-phosphate dehydrogenase (G-6-P-DH), 6-phosphogluconate dehydrogenase

(6-PG-DH), glyceraldehyde-3-phosphate dehydrogenase (GAPDH-NAD), Pyruvate

kinase, phosphoenolpyruvate (PEP) carboxylase, isocitratase, fumarase, and succinate

dehydrogenase (succinate-DH).

Furthermore, Schmid (1980) presented the possible blue light effects in the following,

which are all mediated by FMN as the photoreceptor. If FMN is the photoreceptor, the

effect of light on the enzyme is generally mediated by one of the three mechanisms

described or by any possible simultaneous combination of these three reaction types: the

first type, triplet FMN is directly quenched by the apoprotein leading to an inhibition or

stimulation of enzyme activity. This reaction does not involve oxygen, proceeds

consequently under anaerobic conditions, and has rather to be absent under higher

partial pressures of oxygen. This light effect might be fully reversible.

In contrast, the second and third mechanisms both involve oxygen. In the second type,

triplet FMN reacts with oxygen forming FMN peroxide which then via oxygen transfer

oxidizes the substrate, which is the apoenzyme in this case. The light effect is generally

an irreversible inactivation of the enzyme. In the third type, triplet FMN leads to singlet

oxygen formation which then as the reactive species alters the apoprotein, therefore

generating in general to an irreversible inactivation (Schmid 1980). The metabolic

pathways of photosynthetic carbon metabolism, Calvin cycle, and its blue light-

enhanced enzymes are described in Figure 10.

43

Figure 10. The pathways of photosynthetic carbon metabolism, Calvin cycle, and

its blue light-enhanced enzymes (in full frames) (adapted from Ruyters 1984).

The presence of blue light affects 8 enzymes of photosynthetic carbon metabolism and

Calvin cycle pathways in algae, which are the catalase, ribulose-1,5-bisphosphate

carboxylase (RubP-Case), phosphoglycerate kinase (PGK), glyceraldehyde-3-phosphate

dehydrogenase (GAPDH-NADP), aldolase, glycolate oxidase, glyoxylate

aminotranferase, and hydroxypyruvate reductase.

Growing algae in different types of monochromatic spectra of light has been considered

as an important and interesting field of study for at least 50 years. However, most

microalgae photobiology studies have been conducted in laboratory settings and have

not been optimally utilized in long-term large-scale microalgae cultivation systems.

Some modern developments of this application in microalgal production systems, in

addition to the use of filters and artificial light (e.g. fluorescent lamps and Light-

Emitting Diodes (LEDs)), are the use of laser diodes (Kuwahara et al. 2011), solar

44

concentrators (Mohsenpour et al. 2012), solar spectral converter (Wondraczek et al.

2013), and the integration of photovoltaic modules (Moheimani and Parlevliet 2013;

Parlevliet and Moheimani 2014).

Microalgae production enhancement and manipulation using monochromatic spectra

has been studied by several researchers. For example, Das et al. (2011) found that the

highest specific growth rate for Nannochloropsis sp. was reached in blue, white, green,

and red light regimes, respectively, using LEDs light sources. This phototrophic culture

of Nannochloropsis sp. produced 14.26%, 15.11%, 14.78%, and 14.32% of fatty acid

methyl esters (FAME) as dry biomass weight equivalent when grown in red, green,

blue, and white light, respectively. The exposure of Nannochloropsis sp. to a

monochromatic LED source of blue light resulted in higher biomass productivity than

green or red light, as well as multichromatic white light LED exposure (Das et al.

2011). Baba et al. (2012) reported that the growth of a Botryococcus braunii (race B)

was higher in order of red, blue, and green light indicating that red and blue light were

more effective for growth, photosynthetic CO2 fixation, and hydrocarbon production

than green light. Therefore, red light was considered as the most effective light source

for the production of hydrocarbons from this B. braunii according to the calculation of

photoenergy utilization efficiency (Baba et al. 2012). In addition, Marchetti et al. (2013)

found that the relative carbohydrate content of Isochrysis sp. was lower under blue light

than white light, whereas chlorophyll a and photosynthesis activity were higher. In

contrast, protein content was higher under blue light than white light at a dilution rate of

0.7 d-1. Kuwahara et al. (2011) also reported that Chlamydomonas reinhardtii

successfully grew and divided under the 655 and 680 nm red lasers as well as under the

white light control. Supplementation with either red with blue laser, interestingly,

resulted in an increased algae cell count that significantly exceeded those under both red

lasers and the white light on average by 241%.

45

Effects of light intensity and photoperiod

The importance of light intensity and photoperiod (light/dark cycle) on the growth,

metabolism, and proximate composition of microalgae has been reported by many

(Soeder and Stengel 1974; Sánchez Saavedra and Voltolina 2002; Khoeyi et al. 2012).

For instance, high intensity of 230-250 µmol photons m-2 light sources, led to higher

biomass yield of Nannochloris oculata culture than low intensity of 160-180 µmol

photons m-2 (Park et al. 2012). Light intensity also affects the fatty acid and lipid class

composition of saline microalgae. Guihéneuf et al. (2009) found that the lowest cell

lipid contents of Pavlova lutheri cultures in bicarbonate or acetate medium were

obtained under low light intensity. The proportions of PUFAs, especially EPA, were

significantly higher under low light, but saturating fatty acids and DHA levels were

significantly higher under high light.

Microalgae growth is limited by too little light, but too much light can result in growth

inhibition (Soeder and Stengel 1974), photoinhibition, and can potentially damage the

photosystems (Masojídek et al. 2004; Grobbelaar 2010). Photoinhibition is the decline

in photosynthetic rates after prolonged exposure of super-optimal irradiancies and a

major factor in limiting total net photosynthesis and primary productivity in algae

culture (Grobbelaar 2007; Ritchie and Larkum 2012).

Most outdoor cultures are exposed to a changing environment in which light intensity is

uncontrolled. During spring and summer in outdoor cultures, photosynthesis will

already saturate early in the morning, while during solar noon, sunlight levels especially

at the closed reactor surface become over-saturating and can even lead to

photoinhibition (Cuaresma et al. 2011). Thus, the culture depth and cell density are

important factors for the optimum productivity of algae production using outdoor open

ponds and photobioreactors (Ritchie and Larkum 2012; Richmond 2013). For open

46

ponds, this requires a compromise between the need to provide adequate light to the

microalgae cells (the shallower, the more light is available to the cells) and the need to

maintain an adequate mixing and changes in evaporation (Borowitzka 1999). Ritchie

and Larkum (2012) reported the calculations of total net photosynthesis and optimum

depths of three microalgae species, i.e. Chlorella sp., Dunaliella salina and

Phaeodactylum sp. in shallow algal ponds. The results showed that optimal ponds

should be very shallow with insignificant algal biomass below the compensation depth,

and have high algal density to absorb as much as possible useful irradiance in the photic

zone (Ritchie and Larkum 2012). However, the light required to saturate photosynthesis

varies from one species to another, and depends also on the CO2 concentration and

temperature (Kirk 2010). In addition, the photoperiod is the key factor affecting

microalgae growth, physiology, and photosynthesis kinetics (Khoeyi et al. 2012).

Variations in the light/dark regime also control changes in the cell content of proteins,

carbohydrates, lipids, and pigments of microalgae (Tzovenis et al. 1997; Fabregas et al.

2002; Seyfabadi et al. 2011).

1.5.2 Other limits to growth

Temperature

Temperature is an important factor that regulates cellular, morphological, physiological,

and various metabolic processes in microalgae (Soeder and Stengel 1974). Most

cultured species of microalgae tolerate temperatures between 16 and 27°C, with

temperatures lower than 16°C slowing growth, while temperatures higher than 35°C are

lethal for a number of species and strains cultured (Coutteau 1996). Temperature also

strongly influences the chemical composition, for example, lipids and fatty acids

(Guschina and Harwood 2013). Marine microalgae generally respond to a decrease in

47

temperature by accumulating lipids and increasing the ratio of unsaturated to saturated

fatty acids (Pahl et al. 2010).

Oxygen

High oxygen concentrations are often a critical limiting factor for achieving rapid

growth rates and a high cell concentration of microalgae in large-scale cultures (Behrens

2005). As important it is to provide CO2, it is equally important attempt to remove the

O2 produced by photosynthesis. Therefore, in closed photobioreactors, optimization of

the degassing configuration is an important requirement (Norsker et al. 2011).

Excess O2 also leads to photo-oxidative damage, the formation of reactive oxygen

species which can damage the PS II, and increase rates of photorespiration, therefore are

detrimental to overall algal productivity (Behrens 2005; Borowitzka 2013d).

Photorespiration is a competing process to carboxylation, when the organic carbon is

converted into CO2 without any metabolic gain (Masojídek et al. 2004).

Photorespiration depends on the relative concentrations of O2 and CO2 where a high

concentration of O2 and low concentration of CO2 stimulates this process, while a low

O2/CO2 ratio promotes carboxylation (Masojídek et al. 2004). In an outdoor culture of

Pleurochrysis carterae, photosynthesis was strongly inhibited in cultures at high oxygen

concentrations (26-32 mg O2.L-1) at both low and high irradiances, and the degree of

inhibition increased with increasing temperature, especially in the outdoor grown cells

in a raceway pond (Moheimani and Borowitzka 2007).

Nutrients (N, P, Si)

The important nutrients for the growth of microalgae are macronutrients, such as

nitrogen, phosphorus, silicate (for diatoms, silicoflagellates, chrysophytes), trace metals,

vitamins, pH buffers, and chelators (Harrison and Berges 2005). Nitrogen (N) is

quantitatively the most important element in microalgal nutrition (Becker 1994). It is an

48

essential nutrient for all organisms, and is required for the biosynthesis of

macromolecules, such as proteins, nucleic acids, and chlorophyll (Hockin et al. 2012).

In the diatom Phaeodactylum tricornutum, synthesis of triglycerides is clearly triggered

by nitrogen stress. The yield of triglycerides is higher at the lower levels of nitrogen

supply and nitrogen use per cell despite lower growth rates (Parrish and Wangersky

1987). The relationship between N-limitation and triglyceride synthesis has now been

demonstrated for many algae (Zhila et al. 2005; Griffiths et al. 2012; Ördög et al. 2013).

Huang et al. (2011) observed that there were significant differences in the chlorophyll a

and protein contents of a mixed culture of Dunaliella salina and Phaeodactylum

tricornutum under different inoculation densities and nitrogen concentrations.

Chlorophyll a and protein content increased with the increase of N concentrations. Park

et al. (2012) found that the biomass productivity of Nannochloris oculata was correlated

with the increasing nitrogen concentrations up to 37.5 ppm. In addition, Hoffmann et al.

(2010) investigated the influence of different nitrate concentrations in combination with

three culture temperatures on the total fatty acids (TFA) and eicosapentaenoic acid

(EPA) content of Nannochloropsis salina. It was clearly demonstrated that nitrate and

temperature can be used as stimuli for Nannochloropsis salina to synthesize and

accumulate high TFA and EPA concentrations (Hoffmann et al. 2010).

Phosphate (P) is an essential nutrient required for normal growth of microalgae and

important for almost all cellular processes, biosynthesis of nucleic acids, and energy

transfer (Becker 1994). In an aerobic conditions and low pH, phosphates are released

into the water, and most phosphorus fertilizers precipitate, especially in salt water ponds

(Baert et al. 1996).

Not all microalgae are limited by the same nutrient, but it occurs at the species level,

e.g. all diatoms are limited by silicate (Werner 1977). Silicate (Si) is specifically used

49

for the growth of diatoms (i.e. Amphora sp.) which use this compound for excretion of

their external frustule (Lee 2008). The requirement of silicate for the construction of

diatoms frustules and the cells metabolism makes these microalgae subject to silicate

limitation (Werner 1977). As silicic acid uptake, silica frustule formation, and the cell

division cycle are all tightly linked, under silica limitation, the diatom cell cycle

predominantly stops before the completion of cell division (Barsanti and Gualtieri

2006). Furthermore, an inhibition of cell division linked to an inability to synthesize

new cell wall material under silicon limitation can lead to an increase in the volume per

cell by the formation of auxospores with a larger cell diameter (Barsanti and Gualtieri

2006). Growth limitation in diatoms by either nitrate or phosphate had little effect on

skeletal silicification compared to silicate (Shimada et al. 2009).

Alternative enrichment media that are suitable for mass production of microalgae in

large-scale extensive systems contain only the most essential nutrients and are

composed of agriculture-grade rather than laboratory-grade fertilizers (Coutteau 1996).

In order to achieve maximum growth, nutrients elements need to be supplied in

sufficient quantity. To produce 1 ton of microalgal biomass, approximately 50-80 kg of

nitrogen and 5 kg of phosphate are required (Borowitzka and Moheimani 2013b).

Microalgae also often require more nutrients when light and temperature conditions are

less than optimum for growth (Borchardt 1996). Although microalgae cultures use

nutrients more efficiently than crop plants because they are grown in closed containers,

such as ponds or photobioreactors, which minimize losses of the nutrients from the

system through run off into groundwater, the culture system must be optimized for

nutrient use. Therefore, recycling of the medium is a critical part of the systems

(Borowitzka and Moheimani 2013b).

50

Salinity

Saline water or saline groundwater is the preferred water sources for sustainable

commercial scale culture of microalgae as it does not compete the freshwater supply for

land based agricultural production especially food crops (Borowitzka and Moheimani

2013b). Every microalga has a different optimum salinity range (Brand 1984). Many

algae show an inhibition of photosynthesis after transferred to a medium of higher

salinity or elevated osmotic pressure (Batterton and Van Baalen 1971), but some algae

can also have an excellent ability to tolerate high salt concentrations (Guschina and

Harwood 2013). Marine microalgae are extremely tolerant to changes in salinity

(Barsanti and Gualtieri 2006). If the microalgae have only a narrow range of salinity

tolerance, as is the many case for marine species, then the culture system must be

regularly partially blow-down or completely discharged (Borowitzka and Moheimani

2013b).

Salinity can affect the growth and cell composition of microalgae (Gomez et al. 2003;

Zhila et al. 2011). In general, an increase in salinity leads to reduced growth rates in

almost all species (Ben Amotz et al. 1985). Trobajo et al. (2011) mentioned that salinity

also significantly affected the morphology of five diatoms. Photosynthesis of algae is

inhibited by osmotic stress (Vonshak and Richmond 1981; Gilmour et al. 1984). A

decrease in photosynthesis by salinity may be associated with the inhibition of PS II

activity (Gilmour et al. 1984; Endo et al. 1995). Most species grow best at a salinity that

is slightly lower than that of their native habitat, which is obtained by diluting seawater

with tap water (Coutteau 1996). If microalgae are cultured in saline water, it is

necessary to consider the effects of evaporation, which means that the salinity of the

ponds will gradually rise for long periods of time affecting microalgae growth

(Borowitzka and Moheimani 2013b).

51

Carbon dioxide and pH

The supply of inorganic carbon to microalgae mass culture systems is one of the

principal difficulties and limitations that must be considered (Benemann et al. 1987;

Oswald 1988). In water, inorganic C exists in four forms: CO2, H2CO3, HCO3-, and

CO32-, and is the main buffering system. If the pH is unregulated, photosynthetic CO2

uptake results in a rise in the pH of the medium that leads to a reduction in the ratio of

the inorganic C in the form of CO2 and an increase of HCO3- and CO3

2-, in which

photosynthesis will be reduced and discontinued when no CO2 is available in the

medium for the algae to utilize (Borowitzka 2013d).

For the optimum growth of microalgae, the range of CO2 concentration also needs to be

considered. Both high and low CO2 concentrations may lead to growth inhibition, and

these concentrations vary from one species to another, and are not adequately known

(Sobczuk et al. 2000). For instance, addition of CO2 at constant pH (pH-stat) resulted in

an increase in Pleurochrysis carterae biomass and coccolith productivity, while CO2

addition lowered Emiliania huxleyi biomass and coccolith production (Moheimani and

Borowitzka 2011).

Cyanobacteria and microalgae have a significant environmental adaptation, known as a

CO2-concentrating mechanism (CCM), that improves photosynthetic performance and

survival under limited CO2 (Price et al. 2008). Ihnken et al. (2011) investigated the

impact of photon flux and elevated CO2 concentrations on growth and photosynthetic

electron transport on the marine diatom Chaetoceros muelleri and looked for evidence

for the presence of a CCM. The pH drift experiments clearly showed that C. muelleri

had the capacity to use bicarbonate to acquire inorganic carbon through one or multiple

CCMs (Ihnken et al. 2011).

52

CO2 limitation in dense cultures of most microalgae can be overcome by CO2 addition

(Borowitzka 2010a). Waste CO2 from the flue gas of power stations or other industrial

sources can be used as a carbon source, provided the chosen species could tolerate the

content of CO2, NOx, SOx, dust, and trace elements in the gas (Stephenson et al. 2010).

Muradyan et al. (2004) reported that even one day-long increase in the CO2

concentration (from 2 to 10%) triggered an increase in the total fatty acids of Dunaliella

salina on the dry weight basis by 30%. After 7 day-long growth at 10% CO2, this value

was 2.7-fold higher than that at 2% CO2. However, increasing biomass production and

lipid content may not always occur when the cultures are aerated with higher CO2

concentrations. For example, the optimum condition for long-term biomass and lipid

yield of Nannochloropsis oculata has been achieved with only 2% CO2 aeration in a

particular semi-continuous culture system of one-day (24 hours) harvest interval (half

culture was harvested and fresh medium was replaced) (Chiu et al. 2009).

The pH range for most cultured microalgae species is between 7 and 9, with the

optimum range being 8.2-8.7 (Coutteau 1996). pH is one of the important factors

determining the solubility of carbon dioxide and minerals in the culture, and also

directly and indirectly influences the metabolism of the algae (Becker 1994). Complete

culture collapse due to the disruption of many cellular processes can result from a

failure to maintain an acceptable pH (Coutteau 1996). For example, the growth of

Scenedesmus obliquus culture in Olive-mill wastewater medium was found to be

significantly affected by pH both in the exponential growth phase and in the

deceleration of growth. The biomass productivity declined with the reduction in pH, this

effect being very sharp in the pH interval 5.0-6.0 (Hodaifa et al. 2009).

The pH of microalgae cultures can be influenced by various factors, such as the

composition and buffering capacity of the medium, amount of dissolved CO2,

53

temperature (which controls CO2 solubility), and metabolic activity of the algal cells

(Becker 1994). In case of a high-density microalgae culture, the addition of CO2 can be

used to correct increased pH, which may reach limiting values of up to pH 9 during cell

growth (Coutteau 1996).

Mixing

An early study by Winokur (1948) showed that mixing enhances productivity of

Chlorella cultures. It provides a positive effect especially on the photosynthetic process

that enhances the production of outdoor microalgal cultures (Bosca et al. 1991).

Moreover, the mode of mixing may also affect the algae species composition in the

ponds (Becker 1988). Mixing is important to prevent sedimentation of the algae, to

ensure that all cells are equally exposed to the light and nutrients, to avoid thermal

stratification especially in outdoor cultures, and to improve gas exchange between the

culture medium and the air (Lebeau and Robert 2003). The level of cell damage is also

correlated to the shear rate. An increase in shear rate up to a certain value may be

beneficial in enhancing growth due to physiological effects or enhancement of heat and

mass transfer, but excessively high shear levels can damage cells (Contreras et al.

1998).

1.6 Microalgae used in this study

To compare the effects of different light spectra on different taxa of microalgae, four

microalgae species from different classes with different pigment characteristics were

examined. These microalgae were also selected because they are potential for high-

value products and applications. The selected species were Nannochloropsis sp. MUR

266 (Eustigmatophyceae; chlorophyll a), Botryococcus braunii CCAP 807/2

(Trebouxiophyceae; chlorophyll a&b, race A), Amphora sp. MUR 258

(Bacillariophyceae; chlorophyll a&c), and Pleurochrysis carterae CCMP 647

54

(Prymnesiophyceae; chlorophyll a&c). In the following section, the characteristics and

applications of each species will be discussed.

1.6.1 Nannochloropsis sp.

Nannochloropsis sp. is the marine, non-flagellate, spherical to slightly ovoid cells, 2-4

µm in diameter with one chloroplast per cell, which does not have a pyrenoid (van den

Hoek et al. 1995) (Figure 11). It was first described by Hibberd (1981), who removed it

from the class Chlorophyceae and placed it in the class Eustigmatophyceae in the family

Monodopsidaceae (Sukenik 1999). Previously known as “marine Chlorella” widely

distributed in the oceans, it was for a long time confused with the coccoid marine green

alga Chlorella, and was identified on the basis of its ultrastructure as Nannochloropsis

(Maruyama et al. 1986).

Figure 11. Ultrastructure of Nannochloropsis oculata in the interphase (A) and

prophase (B) showing the outer nuclear envelope (long arrow) and the

epiplastididial rough endoplasmic reticulum membrane (short arrow), Bars: 200

nm (from Murakami and Hashimoto 2009).

Species in the genus Nannochloropsis are characterized by several particular

ultrastructure and biochemical features of Eustigmatophyceae, such as the absence of

chlorophyll b or c and the composition of the xanthophyll pigments (Whittle and

Casselton 1975). The carotenoid composition of Nannochloropsis sp. consists of the

55

major xanthophyll pigments violaxanthin, a vaucheriaxanthin- like pigment, and β-

carotene, ketocarotenoids canthaxanthin and astaxanthin, and small amounts of

zeaxanthin (Whittle and Casselton 1975; Antia and Cheng 1982; Karlson et al. 1996).

Antia and Cheng (1982) reported the ketocarotenoid composition of two species, N.

oculata and N. salina, and found that canthaxanthin and astaxanthin contents were

higher in aged cultures, although violaxanthin and vaucheriaxanthin remained the major

xanthophylls (Lubián et al. 2000; Larkum and Vesk 2003).

There are six recognized species in this genus that are phylogenetically divided into two

clades: one consisting of N. gaditana and N. salina, and the second of N. granulata, N.

limnetica, N. oceanica, and N. oculata (Jinkerson et al. 2013).

Nannochloropsis spp. are of ecological and potential industrial importance. From an

ecological perspective, they are abundant and contribute to the base of food web in

marine ecosystems, and can accumulate significant amounts of eicosapentaenoic acid,

which is an essential fatty acid source of nutrition for marine organisms (Srinivas and

Ochs 2012). The high quality of Nannochloropsis sp. as a feed in the aquaculture

industry is attributed to its high EPA content that makes it a preferred nutritional feed

for rotifers in an artificial food chain for many fish hatcheries (Sukenik 1999).

Nannochloropsis spp. are also potential sources of commercially valuable pigments

(Lubián et al. 2000). This species is also considered as leading autotrophic microalgae

for the production of biofuels (Moazami et al. 2012; Jinkerson et al. 2013). Several

isolates grow rapidly, produce large quantities of triacylglycerols, and can be cultivated

at large industrial scales (Jinkerson et al. 2013).

1.6.2 Botryococcus braunii

The unicellular colonial microalga Botryococcus braunii is a member of the

Trebouxiophyceae, in the Chlorophyta (Senousy et al. 2004; Graham et al. 2009). They

56

are widespread in freshwater and brackish lakes, reservoirs, ponds, or even ephemeral

lakes situated in continental, temperate, alpine, or tropical zones (Metzger and Largeau

1999). This alga consists of colonies of oval or spherical cells embedded in though,

irregular, amber-coloured mucilage which contains numerous lipid globules excreted

from cells (Graham et al. 2009). The colonies range in size from 30 µm up to 2 mm

appear to consist of single or multiple cell clusters united by transparent strands

(Metzger and Largeau 1999).

The chloroplast is netlike, parietal and contains one pyrenoid and starch. Reproduction

of B. braunii is by fragmentation and production of autospores (Graham et al. 2009).

The major pigments of B. braunii are chlorophyll a and b, with β-carotene and lutein as

the major carotenoids (Dayananda et al. 2007; Graham et al. 2009; Kirk 2010). Seven

carotenoids have been identified in the race L of B. braunii, which are echinenone, (3S)-

3-hydroxiechinenone, canthaxanthin, (3S, 3’S)-astaxanthin, (3S, 3'R)-adonixanthin,

lutein, and zeaxanthin (Grung et al. 1994). Okada et al. (1996; 1997, 1998) in a more

detailed study, examining 3 strains of B. braunii, discovered 5 new carotenoids

containing etheric bonds. The botryoxanthin A, α-botryoxanthin and botryoxanthin B

were identified in two strains: Berkeley and Kawaguchi-1 (Okada et al. 1996; Okada et

al. 1998). Braunixanthins 1 and 2 were isolated from Kawaguchi-1 strain, which are

composed of echinenone, alkylphenol, and tetramethylsqualene derivative (Okada et al.

1997). The main carotenoid which presents in the extracellular colony matrix is the

ketocarotenoid echinenone (Matsuura et al. 2012). Botryococcus braunii cells and their

surrounding extracellular matrices are described in Figure 12.

57

Figure 12. Colour Differential Interference Contrast microscopy image of a partial

B. braunii colony (A); and a model of B. braunii cell and its surrounding

extracellular matrices (B), which consist of a polysaccharide colony sheath (a), cell

wall (b), drape (c), cross-linked hydrocarbon network (d), lipid body (e), liquid

hydrocarbon filling cross-linked network (f), “balloon” (g), secreted hydrocarbons

(h), starch (i), chloroplast (j), plasma membrane (k), nucleus (l), fenestrated

cortical ER (m), apical Golgi (n), granules (o), and retaining wall (p); Bars: 10 µm

(from Weiss et al. 2012).

B. braunii is characterized by an obvious ability to synthesize and accumulate various

lipid substances including numerous hydrocarbon compounds, predominantly the

botryococcenes (Brown et al. 1969) and a number of specific ether lipids (Metzger and

Casadevall 1992). The majority of botryococcenes are secreted into the extracellular

matrix, and it has been estimated that only 7% of the botryococcenes are intracellular

(Wolf et al. 1985). Largeau et al. (1980) reported that 95% of the hydrocarbons

produced by B. braunii are located in the extracellular matrix. Botryococcus is believed

to have contributed substantially to the deposition of high quality oil shales and coals

around the world (Graham et al. 2009).

This alga can be differentiated into four races, i.e. A, B, L and S, generally based on the

characteristic of the hydrocarbons they produce (Banerjee et al. 2002; Kawachi et al.

2012; Weiss et al. 2012). The hydrocarbon content in culture varies with the species, the

race to which it belongs, and physiological conditions from 2 to 86% (Brown et al.

58

1969; Dayananda et al. 2005). Race A produces odd-number C25-C31, alkadienes (two

double bonds) and alkatrienes (three double bonds) derived from fatty acids (Metzger et

al. 1985; 1986), Race B produces two triterpenoids, tetramethylsqualene as a minor

component, and botryococcenes (CnH2n-10, n=30-37) (Metzger et al. 1987; 1988),

whereas Race L produces a single hydrocarbon a C40H78, a tetraterpenoid, known as

lycopadiene (Metzger et al. 1990). Race S produces epoxy-n-alkane and saturated n-

alkane chains with carbon numbers 18 and 20 (Kawachi et al. 2012).

1.6.3 Amphora sp.

Amphora sp. is a pennate diatom which belongs to the class Bacillariophyceae (Round

et al. 1990). One of the special characteristics of the strain of Amphora sp. used in this

study is that this diatom has wide tolerance of salinity, i.e. from 0.5% to 17.5% (weight

of total salt per volume, g.100 mL-1) (Clavero et al. 2000). Diatoms are unicellular

microalgae in the Heterokontophyta, whose peculiarity amongst other microalgae is

their siliceous cell wall (Lebeau and Robert 2003). There are more than 1,250 genera of

diatoms in the class Bacillariophyceae (Seckbach and Kociolek 2011). Diatoms are a

major group of algae and one of the most widespread classes that can be found in the

freshwater, brackish, marine waters, and soil (diatomite) (Nagy 2011). They occur in all

oceans from the poles to the tropics, in which temperature is the overriding

environmental factor latitudinally (Guillard and Kilham 1977).

Diatoms can be divided artificially in centric and pennate because of the symmetry of

their cell wall structure (van den Hoek et al. 1995). In centric diatoms, the symmetry is

radial, in which the structure of the valve is arranged in reference to a central point

(Barsanti and Gualtieri 2006). However, within the centric series, there are also oval,

triradiate, quadrate, and pentagonal variation of this symmetry, with a valve arranged in

reference to two, three, or more points. Pennate diatoms are bilaterally symmetrical

59

about two axes, apical and trans-apical, or only in one axis, whereas some genera have

rotational symmetry (Barsanti and Gualtieri 2006) (Figure 13).

Figure 13. The ultrastructure of Amphora sp. consists of raphe eccentric,

positioned along ventral margin (1), raphe ledge on both sides of raphe (3), striae

on dorsal margin interrupted (4), and dorsal fascia present (5) (from Spaulding

2011).

Identification of diatoms is mostly based on the morphology of the silica shell surrounds

the cell, the frustules (Duke and Reimann 1977). This silica wall constrains and protects

the protoplast, but also provide routes for nutrient uptake, gaseous exchange, and the

secretion of cellular products, e.g. polysaccharides (Cox 2011). The inelastic nature of

the silicified lateral walls is responsible for the fact that on each division the cells of

most species become smaller, in average dimensions, until the cells of a population tend

to die out unless they go through certain reproduction, in which they regain their

original size (Borowitzka 2012).

The chloroplasts contain chlorophyll a, c1, and c2 with the major carotenoid

fucoxanthin, neofucoxanthin, diatoxanthin, diadinoxanthin, and β-carotene (Lewin and

Guillard 1963; Lee 2008). The carotenoid neofucoxanthin A and B, and the chlorophyll

a derivatives, e.g. chlorophyllide a, chlorophyll a allomer, chlorophyll a isomer, and

60

phaeophytin a have been observed in diatom cultures (Lewin and Guillard 1963;

Mantoura and Llewellyn 1983; Hallegraeff and Jeffrey 1985; Klein 1988). These

microalgae exhibit a particular golden-brown colour due to a high amount of the

xanthophyll fucoxanthin which plays an essential role in the light-harvesting complex of

photosystems in addition to chlorophyll a and c (Jeffrey 1980). Diadinoxanthin and

diatoxanthin are important in short term photo-protective mechanism in photosynthesis

(Bertrand 2010; Latowski et al. 2011).

Diatoms reproduce by normal asexual binary division of one cell into two, the valves of

the parent cell becoming the ephitecae of the daughter cells (Lee 2008). Each daughter

cell receives one parent cell theca as epitheca, and cell division is terminated by the

formation of a new hypotheca for each of the daughter cells (Hasle and Syvertsen

1996). They have a diplontic life cycle which has a single predominant vegetative

diploid phase, and the meiosis gives rise to haploid gametes (Barsanti and Gualtieri

2006).

Diatoms play a vital role in the oceans as an important source of biomass as well as CO2

fixation and O2 production (Rasala et al. 2013). They are by far the most significant

producer of biogenic silica dominating the marine silicon cycle, and it is estimated that

over 30 million km2 of ocean floor are covered with sedimentary deposits of diatom

frustules (Barsanti and Gualtieri 2006). They are also important in oceans that their

abundance means they are significant producers of organic matter being responsible for

20-25% of the total primary production in the ocean (Geider et al. 2001; Borowitzka

2012). These microalgae have an important role in the biological carbon pump that

draws carbon down into the deep ocean through the settling of cells (Smetacek 1999;

Geider et al. 2001; Hockin et al. 2012).

61

Diatoms are a popular tool for environmental monitoring, past and present, and are

commonly used in studies of water quality (Stoermer and Smol 2004). These algae are

very responsive to environmental changes, and analysis of diatom communities can be

used to study long-term changes (Seckbach and Kociolek 2011). Diatoms have proven

to be extremely powerful tools to explore and interpret many ecological and practical

problems (Stoermer and Smol 2004). They are also important commercial sources for

aquaculture feed and high-value oils, such as ω-3 fatty acids (Apt and Behrens 1999).

With respect to several aspects of the production process, the specific morphology of

diatoms can provide both advantages and drawbacks. The nature of diatom silica valve

covering can make the cells heavier so they can settle easily thus possibly simplifying

the harvesting of these algae, but more energy is required to keep the cells suspended

during culture (Borowitzka 2013d). Further development at the industrial scale will

depend on optimization of the culture process with the aim of reducing costs (Lebeau

and Robert 2003).

1.6.4 Pleurochrysis carterae

The marine Pleurochrysis carterae belongs to the class Prymnesiophyceae

(Coccolithophores), in the Haptophyta (van den Hoek et al. 1995). All haptophyte

chloroplasts lack girdle lamellae and most contain chlorophylls a and c1/c2,

fucoxanthin, β-carotene, diatoxanthin and diadinoxanthin (Jordan and Chamberlain

1997). However, there is interspecific and intraspecific diversity in the fucoxanthin

derivatives, and in the presence/absence of chlorophyll c3 (Jordan and Chamberlain

1997; Andersen 2004). Four major subgroups have been determined, i.e. type 1 has

fucoxanthin, type 2 has fucoxanthin and chlorophyll c3, type 3 has 19’-

hexanoyloxyfucoxanthin and chlorophyll c3, and type 4 has 19’-

butanoyloxyfucoxanthin, chlorophyll c3, and variable traces of fucoxanthin and 19-

hexanoyloxyfucoxanthin (Jeffrey and Wright 1994). Furthermore, Zapata et al. (2004)

62

conducted a more detailed research of photosynthetic pigments in 37 species (65

strains) of Haptophyta, and classified 8 pigment types based on the distribution of 9

chlorophyll c pigments and 5 fucoxanthin derivatives. P. carterae was identified as type

1, which contains chlorophyll a, chlorophyll c1 and c2, and Mg-2,4-divinyl

phaeoporphyin a5 monomethyl ester (MgDVP) (Zapata et al. 2004).

The coccolithophores may be spherical, ovoid to oval, elongated cylinders, or spindle-

shaped cells tapering gradually toward one or both ends, whose longest dimensions

rarely exceed 30 µm and are most often < 10 µm (Heimdal 1993). 200 living species of

coccolithophorids in nearly 70 genera have been described (Heimdal 1993). One of the

most distinctive features of the coccolithophore cell is the presence of highly

characteristic calcified scales called coccoliths, and the haptonema, and they usually

possess one or two plastids surrounded by a double unit-membrane chloroplast envelope

(Pienaar 1994) (Figure 14).

Figure 14. A complete coccosphere (a) and an isolated mature coccolith in the

distal view (b) of Pleurochrysis carterae (from Saruwatari et al. 2011).

Coccoliths are divided into two general groups: the heterococcoliths and holococcoliths

(Siesser and Winter 1994). The inorganic component of the coccolith is CaCO3 and is

deposited in the form of calcite (Pienaar 1994). Heterococcoliths are the most common

coccolith types that produce calcareous structures, which mainly consist of radial arrays

63

of complex crystal units (Barsanti and Gualtieri 2006). Coccolith production is a light-

dependent process, and in heterococcolithophorids it occurs within the Golgi apparatus,

while in some holococcolith species, calcification takes place externally (Rowson et al.

1986). Several possible functions of coccolith formation are cell-membrane protection,

protection from predation, cellular buffering, acceleration of sinking, deceleration of

sinking, light concentration and calcification as a support to photosynthesis (Young

1994).

Christian Gottfried Ehrenberg (1795-1876) made the first recorded observation of

coccoliths in 1836, while examining chalk from the island of Rugen in the Baltic Sea

(Siesser 1994). He identified the objects as elliptical, flattened discs, having a ring or

few concentric rings on their surfaces (Siesser 1994). Later, the term coccolith was

proposed by Huxley in 1858 for the calcareous remains he found in ocean sediments,

and Wallich in 1861 used the term coccosphere for the coccolith-covered globules he

identified in sediment samples (Heimdal 1993). Coccolithophores have been classified

by their external structures (flagellar type, haptonema, scales, and coccoliths) and their

pigmentation (chlorophylls a and c, fucoxanthin derivatives) (Jordan and Chamberlain

1997; Zapata et al. 2004).

These algae multiply vegetatively by binary fission (Heimdal 1993). Many

coccolithophores are motile or produce motile cells as a part of their life cycle (Pienaar

1994). The life cycles of coccolithophores include a non-motile benthic stage which

alternates with one or more motile stages (Pienaar 1994). P. carterae has a

heteromorphic, diplohaplontic life cycle that consists two main phase: the

Hymenomonas phase, which is the diploid sporophyte generation, and the Apistonema

phase, which is the haploid gametophyte (van den Hoek et al. 1995). The life cycle of P.

64

carterae involves alternation between a benthic filamentous phase with either scale-

bearing swarmers of flagellated coccolith-bearing cells (Heimdal 1993).

Most coccolithophores species live in the stratified waters of the temperate and tropical

regions of the world, and present during the entire year in the tropics where the water

column is permanently stratified, whereas in temperate regions, they are abundant only

in the summer (Brand 1994). They were very abundant in both coastal and oceanic

waters, and in both polar and equatorial waters (Brand 1994). They are the major

primary producers that convert dissolved carbon dioxide in the ocean to CaCO3

(Steinmetz 1994). The fossil coccolithophorids are important marker in the

stratigraphical correlation and dating of marine sediments (van den Hoek et al. 1995). In

addition, P. carterae is a potential species for CO2 bioremediation with added

advantage of producing calcium carbonate as well as organic biomass with a high lipid

content (Moheimani and Borowitzka 2006).

1.7 Rationale and aims of this thesis

Microalgae are among the most promising renewable sources for the production of

high-value products, chemicals, and biofuels (Borowitzka 1988b, a; Metzger and

Largeau 1999; Sukenik 1999; Spolaore et al. 2006; Borowitzka 2013b, c). They are

unique photosynthetic organisms in the diversity of their light-harvesting pigments in

each phylum and in many of their classes (Rowan 1989; Douglas et al. 2003).

Microalgae are considered for converting light energy to chemical energy through

photosynthesis. Light (both quality and quantity) is the main limit to the growth,

productivity, composition, and distribution of microalgae (Soeder and Stengel 1974;

Kirk 1983; Borowitzka and Moheimani 2013a). However, photosynthesis only uses the

parts of the solar spectrum in the range of 400 to 700 nm, the PAR (Hall and Rao 1999;

Masojídek et al. 2004).

65

The PAR spectrum is absorbed by various pigments with different efficiency depending

on their absorption spectra (Barsanti and Gualtieri 2006). The quality and intensity of

the light change simultaneously in outdoor environments, and the microalgae must

adapt to both (Kirk 1983). The rate of microalgal photosynthesis depends on the rate of

captured quanta from the light field, which is determined by light absorption properties

of microalgae cells, and the intensity and spectral quality of the light field (Moheimani

and Parlevliet 2013). Moreover, the efficiency of algal photosynthesis depends on the

spectral overlap between solar irradiation and the pigments’ absorption spectrum

(Wondraczek et al. 2013). If the light source has a narrow spectral output that overlaps

the photosynthetic absorption spectrum, the emission of light at unusable frequencies

can be eliminated, therefore improving the overall energy conversion (Chen et al. 2011).

Several novel developments in the improvement of solar energy conversion to chemical

and electrical energy in microalgal production system have been proposed and

developed, e.g. the application of luminescent acrylic sheets solar concentrators

containing fluorescent dyes (Mohsenpour et al. 2012), the solar spectral converter

technology using a photoluminescent phosphor material (Wondraczek et al. 2013), and

the combination of photovoltaic modules with microalgal culture system (Moheimani

and Parlevliet 2013; Parlevliet and Moheimani 2014; Vadiveloo et al. 2015).

The achievable light-to-product conversion efficiency and photosynthetic productivity

are the most important factors in determining cost in most microalgal production

systems (Mitra and Melis 2008). In addition, strain selection and characterization are an

important part in any developments of applied phycology (Borowitzka 2013d). A

careful screening and characterization of the best targeted species and expected products

(i.e. biomass, lipid, carbohydrate, and protein) becomes a significant aspect in further

development of an efficient photovoltaic (PV)/filter design for microalgal production

66

systems and electricity generation. The useful part of light for photosynthesis can be

supplied to algae, and the rest energy of the available solar spectrum can generate

electricity (i.e. the method proposed by Moheimani and Parlevliet (2013)). The

produced electricity can be used on site (for plant operation or extra light to the

microalgae culture) or can be sold back to the grid.

Illumination by transmitting only the most effective parts of the PAR spectrum can

optimize light utilization for production of particular microalgae. In this study, the

effect of three different light spectra [white (full spectrum), blue (407-488 nm), and red

(621-700 nm)] on the growth, composition (lipid, carbohydrate, protein, and chlorophyll

content), productivity, photosynthesis, and respiration of four microalgae with different

photosynthetic pigment profiles grown in batch and in semi-continuous cultures was

investigated. Furthermore, it is the captured energy (irradiances) that clearly drives light

conversion by the photosynthetic apparatus and all metabolic pathways in microalgae

through photosynthesis (Barsanti and Gualtieri 2006; Kirk 2010).

According to Planck’s quantum theory, photons of different wavelengths of each

spectral region of PAR transmit different levels of energy. In fact, most of previous

findings in comparing different light quality effects only employed equivalent photon

flux density (mol photons. m-2.s-1) of light spectra into the cultures. The radiant flux

density or irradiance (W.m-2) of supplied light into the algae were not really measured

and was not the same for each light spectrum. Therefore, it is important to note that in

this study the amount of transmitted energy by each light spectrum was the same

(2.23±0.10 W.m-2), and the algae were grown and acclimated to the particular spectrum,

i.e. white, blue and red, for at least 20 days before they were grown in semi-continuous

culture mode for 109 days. In a semi-continuous mode, nutrients should not be a

limiting factor so that the main effect will be the light.

67

The main aim of this study was to compare the effect of different light spectra (i.e.

white, blue, and red) supplied at equal energy on the key parameters (i.e.

photosynthesis, respiration, growth, biomass, lipid, carbohydrate, protein, chlorophyll,

and productivity) of microalgae species from 4 different taxa with different pigment

profiles in a semi-continuous culture. This study also aimed to investigate the optimal

use of narrower PAR spectra (i.e. blue and red) and to determine the best spectrum that

significantly increases the selected key parameters for each tested species.

The research hypotheses are: 1) Different light spectra within the PAR, i.e. white, blue,

and red supplied at equal energy, differently affect (either to increase or decrease) one

or more key parameters of 4 tested microalgae species; and 2) Narrower PAR

wavelengths, i.e. blue and red, significantly increase particular key parameters

compared to full PAR (white light).

68

2 MATERIALS AND METHODS

2.1 Sources of algae

The unialgal non-axenic cultures of Nannochloropsis sp. MUR 266, Pleurochrysis

carterae CCMP 647, Amphora sp. MUR 258, and Botryococcus braunii CCAP 807/2

race A were obtained from the Algae R&D Centre Culture Collection, Murdoch

University, Western Australia. Nannochloropsis sp. MUR 266 and Amphora sp. MUR

258 were isolated from Western Australia. Botryococcus braunii CCAP 807/2 and

Pleurochrysis carterae CCMP 647 were obtained originally from the Culture Collection

of Algae and Protozoa, UK (CCAP), and the Centre for Culture of Marine

Phytoplankton, Bigelow Laboratory, Maine USA (CCMP).

Nannochloropsis sp. MUR 266 was cultured in modified f/2-Si medium (Table 7) at a

salinity of 3.3% NaCl (w/v), Pleurochrysis carterae CCMP 647 was cultured in

modified f/2-Si+Se medium (Moheimani and Borowitzka 2006) at a salinity of 3.3%

NaCl, Amphora sp. MUR 258 was cultured in modified f+Si medium (Table 7) at a

salinity of 10% NaCl, and Botryococcus braunii CCAP 807/2 was cultured in modified

CHU-13 freshwater medium (Table 8). The media and salinities used were based on

preliminary experiments which showed these to be optimum for the particular species.

Seawater used for medium preparation was from Hilary’s Beach in Perth, Western

Australia, and was stored in a 10,000 L holding tank at Murdoch University in the dark.

Before use, the seawater was filtered through activated charcoal and cotton layers. The

filtered seawater was then stored at room temperature in dark polycarbonate or

polypropylene containers. Deionized water was used for preparing the stock solutions

and freshwater medium.

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The stock solutions (except for the vitamin stock solution) were autoclaved at 121°C,

103.35 kPa for 20 minutes. Vitamin stock solutions were filter sterilized through a 0.2

µm cellulose nitrate Whatman filter paper in a sterile laminar flow cabinet. The stock

solutions were added to seawater (modified f/2 and f medium) at 3.3% and 10% NaCl

salinity, or freshwater (modified CHU-13 medium), autoclaved (except for the

phosphate and vitamins which were added after autoclaving), and stored for 24 h. The

phosphate and vitamin solutions were then added aseptically. The stock solutions and

culture media were kept refrigerated prior to use.

Table 7. Modified f/2 medium** (Guillard and Ryther 1962).

Component Stock solution

[g.L-1]

Quantity

[L-1]

NaNO3 75.0 1 mL

NaH2PO4.H2O 5.0 1 mL

Na2SiO3.9H2O 30.0 1 mL

SeO2 0.00645 1 mL

Trance metal solution:

1 mL

FeCl3.6H2O - 3.15 g

Na2EDTA.6H2O - 4.36 g

CuSO4.5H2O 9.8 1 mL

Na2MoO4.2H2O 6.3 1 mL

ZnSO4.7H2O 22.0 1 mL

CoCl2.6H2O 10.0 1 mL

MnCl2.4H2O 180.0 1 mL

Vitamin solution:

0.5 mL

Thiamine HCl (vit. B1) - 200 mg

Biotin (vit. H) 0.1 10 mL

Cyanocobalamin (vit. B12) 1.0 1 mL

*For f medium, double concentration of all stock solutions was added. **Nannochloropsis sp. was cultured without Na2SiO3.9H2O and SeO2, Amphora sp. was cultured without SeO2, Pleurochrysis carterae was cultured without

Na2SiO3.9H2O.

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Table 8. Modified CHU-13 medium (Yamaguchi et al. 1987).

Component Concentration

(mg.L-1)

Stock Solution

(Concentrated time)

KNO3

K2HPO4 CaCl2.2H2O

MgSO4.7H2O

400

80 107

200

×1000

×1000 ×1000

×1000

Ferric Citrate Citric Acid

20 100

×1000 ×1000

Trace Element:

CoCl2 H3BO3

MnCl2.4H2O

ZnSO4.7H2O CuSO4.5H2O

Na2MoO4.2H2O

0.02 5.72 3.62

0.44 0.16

0.084

×1000 ×1000 ×1000

×1000 ×1000

×1000

Adjust pH to 7.5 with KOH solution

The stock cultures of all species were maintained in 150 mL medium in 250 mL conical

flasks, or 300 mL medium in 500 mL Schott bottles, and were sub-cultured every

month. They were grown in a constant temperature growth room at 25±2°C under an

irradiance of ~30 µmol photons.m-2.s-1 provided by cool white fluorescence lights with

a 12 h:12 h light:dark period. The irradiance was measured using a Li-cor, Inc

quantum/radiometer/photometer (model LI-185B) with photodiode detector

Kipp&Zonen SP Lite2 sensor. The pH of the cultures was measured using a TPS pH

electrode, and the salinity was measured with an ATAGO portable refractometer.

2.2 Experimental set-up

All culture systems were chemically sterilized using sodium hypochlorite solution or by

autoclaving. All glassware used for stock cultures, culture medium, and experimental

cultures were soaked in a dilute 5 to 6% (v/v) sodium hypochlorite overnight, washed

with Decon-90 detergent, then cleaned and rinsed 12 times using tap water, and dried.

Glassware was then autoclaved at 121°C, 103.35 kPa for 20 minutes, dried, and re-

autoclaved before starting the experiments.

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For the experiments, all species were grown in semi-continuous culture indoor in 500

mL Erlenmeyer flasks inside dark boxes with illumination from below and with 12.5

L.h-1 aeration using an air pump (Figure 15). Semi-continuous culture mode was used to

maintain the culture in a steady-state and to study the productivity of the culture. In this

mode, the culture was maintained at certain volume (Vculture) and at a cell density range

between A cells.mL-1 and B cells.mL-1 where B>A. When the culture reached B

cells.mL-1, a certain volume (Vharvest) was harvested, and same volume of fresh medium

was added into the culture system resulting in A cell density. The harvesting volume

Vharvest was calculated by:

𝑉𝒉𝒂𝒓𝒗𝒆𝒔𝒕 (𝑚𝐿) =𝐴 (𝑐𝑒𝑙𝑙𝑠 𝑚𝐿−1)

𝐵 (𝑐𝑒𝑙𝑙𝑠 𝑚𝐿−1) 𝑥 𝑉𝒄𝒖𝒍𝒕𝒖𝒓𝒆 (𝑚𝐿)

The light:dark photoperiod was 12 h:12 h, and culture temperature was 27±3°C. The

flasks were inoculated with microalgae at approximately the same initial cell density of

5 x 104 cells.mL-1.

Figure 15. The experimental culture set-up. The vertical separation covering the

cultures is not shown.

Illumination was provided by cool white fluorescent lights from the bottom of the

culture system with the specific light spectrum achieved by filters attached to the glass

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panel between the light source and the culture flask (Figure 15). The amount of light

energy was adjusted by an additional layer of copy paper for the white spectrum

surface, and black fly screen mesh for the red filter surface. All cultures received an

equal amount of light energy of 2.23±0.10 W.m-2 at the specific photosynthetically

active radiation (PAR) wavelength. The transmission spectra profiles of blue and red

filters are shown in Figure 16.

Figure 16. Transmission spectra profiles of blue and red filters.

The full-width half-maximum (FWHM), photon flux density of the unfiltered white

light (FWHM 400-700 nm) was 33.75 mol photons.m-2.s-1, of the blue light (FWHM

407-488 nm) it was 34.13 mol photons.m-2.s-1, and for the red light (FWHM 621-700

nm) it was 47.87 mol photons.m-2.s-1. The filters used were from Lee filters (Numbers:

LEE 363 Medium Blue and LEE 026 Bright Red, webpage:

http://www.leefilters.com/lighting/colour- list.html). To minimise the possibility of any

‘edge’ effects, the position of the cultures in each light spectrum group was randomly

swapped every day to make sure that each culture received the same amount of light

energy.

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2.3 Analytical methods

2.3.1 Cell density and growth

Cell densities were determined using a Neubauer haemocytometer. The specific growth

rates (µ, day-1) of the cultures were determined by measuring the doubling time in

exponential growth phase from a semi-log cell density plot (Moheimani et al. 2013).

The specific growth rate was calculated using the following equation:

𝜇 (𝑑𝑎𝑦−1) =0.693

𝑡2

where t2 is the number of days taken to double the cell density (doubling time).

2.3.2 Biomass determination

The total biomass, as total ash-free dry weight, was determined as follows: Whatman

GF/C (2.5 cm) filters were washed with deionised water, dried at 75°C for 24 h, and

stored in a vacuum desiccator over silica gel until used. The filters were weighed

(Wfilter) to 4 decimal places on an analytical balance. 5 mL of culture was filtered until

the filters were dry using a Millipore filtration apparatus. The filters were then washed

with 5 mL 0.65 M ammonium formate solution to remove excess salts, dried at 75°C for

5 h, and then placed in a vacuum desiccator over silica gel overnight. Filters were then

weighed (Wfilter+algae) to four decimal places. Dry weight was calculated as g.L-1 after

subtracting the filter weight from filter and total weight of sample using:

𝐷𝑟𝑦 𝑊𝑒𝑖𝑔ℎ𝑡 (𝑔 𝐿−1) = (𝑊𝑓𝑖𝑙𝑡𝑒𝑟+𝑎𝑙𝑔𝑎𝑒 − 𝑊𝑓𝑖𝑙𝑡𝑒𝑟 ) 𝑥 200

For organic or ash-free dry weight determination, the above filters were ashed at 450°C

for 5 h and cooled overnight in a vacuum desiccator before weighing (Wash). The ash-

free dry weight was calculated as g.L-1 after subtracting the filter weight from the total

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weight. Then this was further subtracted from the total microalgal dry weight to get the

ash-free dry weight.

𝐴𝑠ℎ − 𝑓𝑟𝑒𝑒 𝐷𝑟𝑦 𝑊𝑒𝑖𝑔ℎ𝑡 (𝑔 𝐿−1) = (𝑊𝑓𝑖𝑙𝑡𝑒𝑟+𝑎𝑙𝑔𝑎𝑒 − 𝑊𝑎𝑠ℎ) 𝑥 200

2.3.3 Total lipid determination

The total lipid method used was adapted from Bligh and Dyer (1959) as modified by

Kates and Volcani (1966) and Mercz (1994). 5 mL of culture was filtered using

Whatman 2.5 cm GF/C filters then rinsed with isotonic 0.65 M ammonium formate

solution (saline microalgae only) and kept in a freezer prior to further extraction. For

extraction, the filters were thawed and placed in a 4 mL glass tube, and approx. 2 mL of

liquid nitrogen was added. The filters were homogenized with 1 mL of solvent mixture

methanol:chloroform:water (2:1:0.8, v:v:v). Another 1 mL solvent was then added. The

extract was transferred to a plastic centrifuge tube and centrifuged. It was then made up

to 5.7 mL with the solvent mixture and centrifuged at 1107 x g for 10 min. The

supernatant was carefully transferred to a 20 mL glass tube with screw cap.

For the second extraction, 5.7 mL of the solvent mixture was added to the pellet in the

plastic centrifuge tube and centrifuged at 1107 x g for 10 min. The supernatant was

carefully transferred to the glass tube containing the original extract, and 3 mL

deionised water followed by 3 mL chloroform were added and stirred. The samples

were stored 24 h in a dark and cool place for phase separation. The green bottom

chloroform layer was carefully transferred to a dry, pre-weighed 4 mL glass vial, and a

few drops of toluene were added to remove any remaining aqueous phase. The extract

was then dried with pure nitrogen gas for evaporation on a heating plate at 38ºC. The

vials were stored over KOH pellets overnight in a vacuum desiccator and then weighed.

Total lipid was calculated as g.L-1 and ng.cell-1.

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2.3.4 Total carbohydrate assay

Total carbohydrate was determined by the phenol-sulphuric acid method based on the

method of Kochert (1978) and Ben-Amotz et al. (1985) as modified by Mercz (1994). 5

mL of culture was filtered onto 2.5 cm GF/C glass fibre filters and rinsed with 0.65 M

ammonium formate solution (saline microalgae only). Filters were stored in a freezer

prior to use. The filter containing microalgae was homogenized in 0.5 mL 1 M H2SO4 in

a 10 mL acid resistant plastic test tube with screw lid. 1 M H2SO4 was topped up to 5

mL, and the samples were incubated in a water bath at 100ºC for 60 min. The samples

were cooled to room temperature for approximately 30 min and centrifuged at 1107 x g

for 10 min. 2 mL of the supernatant was pipetted into another acid-resistant plastic test

tube.

A set of tubes containing 0, 40, 80, 120, 160 and 200 μg glucose were prepared as

standards. 1 mL of 5% (w/v) phenol solution was added and mixed well rapidly on a

vortex stirrer. 5 mL concentrated H2SO4 was added carefully in light angle and against

the test tube wall to avoid splashing. The test tubes were closed, tightened, and shaken

three times or vortexed. After 30 min at room temperature, the absorbance at 485 nm

was measured using a Shimadzu UV-Visible spectrophotometer, and the carbohydrate

content was calculated from the standard curve. Total carbohydrate was calculated as

g.L-1 and ng.cell-1.

2.3.5 Total protein assay

Total protein was determined using the method of Lowry et al. (1951) as adapted by

Dorsey et al. (1978). 5 mL of culture was filtered onto 2.5 cm GF/C glass fibre filters

and rinsed with 0.65 M ammonium formate solution (saline microalgae only). Filters

were stored in a freezer prior to use. The filter and sample was placed in a 4 mL glass

tube, and approx. 2 mL of liquid nitrogen was added. The filter containing the

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microalgae was homogenized in the 4 mL glass tube with a glass rod. 1 mL Biuret

reagent was added into the 4 mL glass tube and mixed well with the glass rod. After

mixing, the contents were carefully transferred to a 10 mL centrifuge tube. Another 1

mL Biuret reagent was poured over the glass rod into the 4 mL glass tube and, after

mixing, the content was transferred to the 10 mL centrifuge tube. 3 mL Biuret reagent

was added to the 10 mL centrifuge tube.

The centrifuge tubes containing sample together with the centrifuge tubes with the

protein standard were placed in a 100ºC water bath for 60 min. The centrifuge tubes

were removed from the water bath, and immediately 0.5 mL Folin-phenol reagent was

added while mixing on a vortex stirrer. The centrifuge tubes were placed in a cold water

bath (10-15ºC) to cool and then allow to equilibrate to room temperature for another 15

min. The sample in the centrifuge tubes was centrifuged at 1107 x g for 5 min. The

supernatant was removed carefully, and the absorbance at 660 nm was measured using a

Shimadzu UV-Visible spectrophotometer. The protein content of the samples was

determined from a standard curve prepared using bovine serum albumin. The percent

protein content was calculated using protein content and dry weight. Total protein was

calculated as g.L-1 and ng.cell-1.

2.3.6 Productivity

The biomass, lipid, carbohydrate, and protein productivity of algae were calculated

using the following equation:

𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 (𝑔 𝐿−1𝑑𝑎𝑦−1) = 𝑇𝑜𝑡𝑎𝑙 𝑦𝑖𝑒𝑙𝑑 (𝑔 𝐿−1) 𝑥 𝑠𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝑔𝑟𝑜𝑤𝑡ℎ 𝑟𝑎𝑡𝑒 (𝑑𝑎𝑦−1)

2.3.7 Chlorophyll determination

Chlorophyll concentration was determined using the method of Jeffrey and Humphrey

(1975). 5-15 mL of culture was filtered onto 2.5 cm GF/C glass fibre filters. The filters

77

were then extracted or stored in a freezer in the dark prior to extraction. For chlorophyll

extraction, 2 mL of liquid nitrogen was added and homogenized with the filters. The

filters were then homogenized in 1 mL of ice cold acetone containing a little MgCO3

(90% acetone (v/v) for Nannochloropsis sp. and B. braunii, 100% (v/v) for Amphora sp.

and P. carterae) in low light. The chlorophyll extracts were transferred to 15 mL

centrifuged tubes, and 3 mL acetone was added. After centrifugation at 1107 x g for 10

min, the absorbance of the supernatant was measured using a Shimadzu UV-Visible

spectrophotometer according to Jeffrey and Humphrey (1975):

For green algae which contain chlorophylls a and b (Nannochloropsis sp. and

Botryococcus braunii):

𝐶ℎ𝑙 𝑎 (𝑚𝑔 𝐿−1) = 11.93 𝐸664 − 1.93 𝐸647

𝐶ℎ𝑙 𝑏 (𝑚𝑔 𝐿−1) = 20.36 𝐸647 − 5.50 𝐸664

For diatoms and coccolithophorid algae which contain chlorophylls a and c (c1+c2)

(Amphora sp. and Pleurochrysis carterae):

𝐶ℎ𝑙 𝑎 (𝑚𝑔 𝐿−1) = 11.47 𝐸664 − 0.40 𝐸630

𝐶ℎ𝑙 𝑐 (𝑚𝑔 𝐿−1) = 24.36 𝐸630 − 3.73 𝐸664

The chlorophyll concentration (μg.mL-1) was calculated using the following equation:

𝑇ℎ𝑒 𝑐ℎ𝑙𝑜𝑟𝑜𝑝ℎ𝑦𝑙𝑙 𝑐𝑜𝑛𝑐𝑒𝑛𝑡𝑟𝑎𝑡𝑖𝑜𝑛 = (𝐶ℎ𝑙 𝑎, 𝑏, 𝑐) 𝑥 𝑉𝑜𝑙𝑢𝑚𝑒 𝐸𝑥𝑡𝑟𝑎𝑐𝑡𝑒𝑑 (𝑚𝐿)

𝑉𝑜𝑙𝑢𝑚𝑒 𝐹𝑖𝑙𝑡𝑒𝑟𝑒𝑑 (𝑚𝐿)

2.3.8 Photosynthetic and dark respiration rate measurement

The algae cultures were maintained in batch then semi-continuous mode for 18 weeks,

and the photosynthesis and dark respiration measurements were performed on day 129.

The photosynthetic and dark respiration rates were determined by indoor experiment

using a Rank Brothers (UK) polarographic Clark-type oxygen electrode as outlined in

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Moheimani and Borowitzka (2007) (Figure 17). The electrode was calibrated with

100% air saturated deionized water, seawater at 3.3% and 10% NaCl salinity (25°C, 0

altitude) using the formula of oxygen solubility

(http://www.seabird.com/application_notes/an64.htm), and 0% oxygen with pure

nitrogen gas. A slide projector and filters were used to provide the required

illumination. The irradiance of 2.23±0.10 W.m-2 was obtained approximately the same

for each light spectrum. The irradiance used was the same irradiance which was used in

the semi-continuous culture for each light spectrum in order to maintain similar light

condition. A controlled temperature water bath maintained a constant temperature in the

glass electrode chamber jacket at same temperature as the microalgae culture. Light was

supplied to the chamber by a Hanimex 150 slide projector fitted with 150 W, Syl-167

quartz halogen bulb. Pure nitrogen gas was gently bubbled into the chamber to reduce

the oxygen levels if required.

Figure 17. Photosynthetic and dark respiration rate measurement set-up.

The range of oxygen concentrations used was 1-4 mg O2.L-1 (low oxygen level) and 5-8

mg O2.L-1 (high oxygen level). For the respiration rate, the electrode was covered by a

thick box and a thick black towel to eliminate any light. Samples were kept in the dark

for 10 min prior to each measurement at the same temperature as the measurement

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temperature. The oxygen measurement started with an initial dark measurement of

respiration rate, then continued with photosynthetic rates at low and high oxygen, and

ended by remeasuring the dark respiration rate. Two mL culture was used with 3

replicate samples. For each sample, the cell density was determined, and the culture was

harvested for chlorophyll a determination after the O2 measurement. The rates were

calculated as µmol O2.(mg.chl a)-1.h-1.

2.4 Data analysis

The relationships between light spectra (white, blue, and red) as the selected limits to

growth, and the key outputs, such as photosynthetic and dark respiration rates,

maximum cell densities, growth rates, biomass yields, contents and productivities, lipid,

carbohydrate, protein yields, contents and productivities, and chlorophyll a contents,

were examined using the repeated measures one-way analysis of variance (ANOVA)

(Dytham 2003). Statistical significance was set at P<0.05. Further multiple comparison

tests (Holm-Sidak method or Tukey Test) were used to determine the group or groups

(light spectra) that statistically significant differed from the others. Analyses were

performed using SigmaPlot for Windows (version 12.5 and 13.0).

In this study, effects of different light spectra supplied at equal energy on the key

parameters of 4 tested species were determined and analyzed in a semi-continuous

culture mode and not in a batch mode because of several rationales. In semi-continuous

mode, nutrients should not be a limiting factor so that the main effect will be the light.

In addition, the culture parameters are generally maintained in a stable condition as a

batch culture may result more variations on the parameters. The semi-continuous mode

is more reliable than batch mode in order to sustain the statistical approach using the

repeated measures ANOVA. Finally, in semi-continuous mode, the microalgae and its

photosynthetic apparatus had been acclimated to the particular light field, allowing

80

potential chromatic adaptation in tested species to enhance the light quality effects.

Therefore, the data set and statistical analysis of selected key parameters, determined in

semi-continuous mode, were more reliable to interpret the outcomes of this experiment.

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3 EFFECTS OF DIFFERENT LIGHT SPECTRA

The microalgae Nannochloropsis sp. MUR 266 (Eustigmatophyceae; chlorophyll a),

Botryococcus braunii CCAP 807/2 (Trebouxiophyceae; chlorophyll a&b, race A),

Amphora sp. MUR 258 (Bacillariophyceae; chlorophyll a&c), and Pleurochrysis

carterae CCMP 647 (Prymnesiophyceae; chlorophyll a&c) were grown in batch and

semi-continuous mode in the laboratory using white (W), blue (B) between 407 and 488

nm, and red (R) between 621 and 700 nm light to determine effects of different light

spectra on the photosynthesis and dark respiration, growth, biomass, proximate

composition, and productivity (see chapter 2.2 for experimental set-up).

3.1 Results

3.1.1 Photosynthesis, respiration, and growth

To examine the effect of different light spectra and oxygen concentrations on

photosynthesis, the photosynthetic rate was measured at low (PL, 1-4 mg O2.L-1) and

high (PH, 5-8 mg O2.L-1) oxygen levels. The dark respiration rate first was measured on

the dark adapted algae sample before they were illuminated by either white, blue, and

red light. The respiration rate then was measured on the light adapted sample after the

exposure of those different light to examine any differences in the respiration rate

between dark adapted samples and light adapted samples after illumination (see chapter

2.2 for experimental set-up).

Nannochloropsis sp.

The highest photosynthetic rates under the different spectra for Nannochloropsis sp. at

both oxygen levels were in the order Bb > Rba > Wa (Figure 18) where the different

superscript letters indicate statistically significant differences between the means

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(P<0.05). The low levels of oxygen concentration significantly increased the

photosynthetic rates of Nannochloropsis sp. in white, blue, and red spectra (PL1 > PH2).

Figure 18. Photosynthetic and dark respiration rates of Nannochloropsis sp.

culture grown in semi-continuous mode under white (W), blue (B), and red light

(R) (mean ± range, n=3); R1 (the first dark respiration rate), PL (photosynthetic

rate at low oxygen level), PH (photosynthetic rate at high oxygen level), R2 (the

second dark respiration rate). Values with different letter indicate significant

differences between the means within the spectra (lowercase for PL and uppercase

for PH), while values with different number (n): Wn, Bn, and Rn indicate

significant differences between the means within oxygen concentrations for each

spectrum: white (W), blue (B) or red light (R) (Repeated Measures, One Way

ANOVA, Tukey, P<0.05).

The highest respiration rates of Nannochloropsis sp. for the first dark respiration and the

second dark respiration measurement were Bb > Wa = Ra (Figure 19).

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Figure 19. Dark respiration rates of Nannochloropsis sp. culture grown in semi-

continuous mode under white (W), blue (B), and red light (R) (mean ± range, n=3);

R1 (the first dark respiration rate) and R2 (the second dark respiration rate).

Values with different letter indicate significant differences between the means

(lowercase for R1 and uppercase for R2, Repeated Measures, One Way ANOVA,

Holm-Sidak, P<0.05).

Botryococcus braunii

The highest photosynthetic rate of B. braunii at the low oxygen level was Bb > Ra = Wa,

whereas at the high oxygen level the photosynthetic rates were the same (Wa = Ba = Ra)

(Figure 20). There was no significant difference in the photosynthetic rates of B. braunii

at high oxygen level with different colour light (Holm-Sidak, P>0.05). The levels of

oxygen concentration significantly affected the photosynthetic rates of B. braunii in

white, blue and red spectra, with the photosynthetic rate being higher under low oxygen

concentrations (PL1 > PH2).

84

Figure 20. Photosynthetic and dark respiration rates of Botryococcus braunii

culture grown in semi-continuous mode under white (W), blue (B), and red light

(R) (mean ± range, n=3); R1 (the first dark respiration rate), PL (photosynthetic

rate at low oxygen level), PH (photosynthetic rate at high oxygen level), R2 (the

second dark respiration rate). Values with different letter indicate significant

differences between the means within the spectra (lowercase for PL and uppercase

for PH), while values with different number (n): Wn, Bn, and Rn indicate

significant differences between the means within oxygen concentrations for each

spectrum: white (W), blue (B) or red light (R) (Repeated Measures, One Way

ANOVA, Holm-Sidak, P<0.05).

The highest respiration rate of B. braunii at the first dark respiration was Bb > Wa = Ra,

while the second dark respiration rate was Wa = Ba = Ra (Figure 21).

85

Figure 21. Dark respiration rates of Botryococcus braunii culture grown in semi-

continuous mode under white (W), blue (B), and red light (R) (mean ± range, n=3);

R1 (the first dark respiration rate) and R2 (the second dark respiration rate).

Values with different letter indicate significant differences between the means

(lowercase for R1 and uppercase for R2, Repeated Measures, One Way ANOVA,

Holm-Sidak, P<0.05).

Amphora sp.

Unlike Nannochloropsis sp. and B. braunii, the highest observed photosynthetic rate of

Amphora sp. at the low oxygen level was Ra > Wb > Bc (Figure 22). At high oxygen

level, i.e. 5-8 mg O2.L-1, the oxygen concentration in the salt water was saturated (no

increase of oxygen concentration) due to high NaCl salinity (10%) used in Amphora sp.

culture. Therefore, the photosynthetic rate at high oxygen was lower compared to the

rate at low oxygen (PL > PH).

86

Figure 22. Photosynthetic and dark respiration rates of Amphora sp. culture grown

in semi-continuous mode under white (W), blue (B), and red light (R) (mean ±

range, n=3); R1 (the first dark respiration rate), PL (photosynthetic rate at low

oxygen level), PH (photosynthetic rate at high oxygen level), R2 (the second dark

respiration rate). Values with different letter indicate significant differences

between the means within the spectra (lowercase for PL and uppercase for PH)

(Repeated Measures, One Way ANOVA, Holm-Sidak, P<0.05).

The highest respiration rate of Amphora sp. at the first dark respiration was unaffected

by the light spectrum the algae had been grown under (Wa = Ba = Ra), whereas at the

second dark respiration it was Rb > Wa = Ba (Figure 23).

87

Figure 23. Dark respiration rates of Amphora sp. culture grown in semi-continuous

mode under white (W), blue (B), and red light (R) (mean ± range, n=3); R1 (the

first dark respiration rate) and R2 (the second dark respiration rate). Values with

different letter indicate significant differences between the means (lowercase for

R1 and uppercase for R2, Repeated Measures, One Way ANOVA, Holm-Sidak,

P<0.05).

Pleurochrysis carterae

The observed highest photosynthetic rate of P. carterae at the low oxygen levels was Rb

> Bba > Wa, while at high oxygen levels it was Rb > Ba = Wa (Figure 24). The low levels

of oxygen concentration significantly increased the photosynthetic rates of P. carterae

in white, blue, and red spectra (PL1 > PH2).

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Figure 24. Photosynthetic and dark respiration rates of Pleurochrysis carterae

culture grown in semi-continuous mode under white (W), blue (B), and red light

(R) (mean ± range, n=3); R1 (the first dark respiration rate), PL (photosynthetic

rate at low oxygen level), PH (photosynthetic rate at high oxygen level), R2 (the

second dark respiration rate). Values with different letter indicate significant

differences between the means within the spectra (lowercase for PL and uppercase

for PH), while values with different number (n): Wn, Bn, and Rn indicate

significant differences between the means within oxygen concentrations for each

spectrum: white (W), blue (B) or red light (R) (Repeated Measures, One Way

ANOVA, Holm-Sidak, P<0.05).

The highest respiration rates of P. carterae at the first dark respiration and the second

dark respiration measurement were Wa = Ba = Ra (Figure 25).

89

Figure 25. Dark respiration rates of Pleurochrysis carterae culture grown in semi-

continuous mode under white (W), blue (B), and red light (R) (mean ± range, n=3);

R1 (the first dark respiration rate) and R2 (the second dark respiration rate).

There was no significant differences between the means of R1 as well as R2

(lowercase for R1 and uppercase for R2, Repeated Measures, One Way ANOVA,

Repeated Measures, One Way ANOVA, Holm-Sidak, P<0.05).

During the batch and semi-continuous culture, microscope observations were performed

frequently for all experimental cultures to monitor the growth and culture conditions. In

general, the microscope observation showed no cross contaminations of 4 tested

microalgae and no significant growth of bacteria in the experimental cultures

(data/images were not documented). The growth of all species grown using white, blue,

and red light is shown in Figure 26. The maximum cell density and specific growth rate

of all species are summarized in Figure 27.

Nannochloropsis sp.

The growth of Nannochloropsis sp. started to reach the stationary phase in 13 days

when grown under the white light, 7 days under blue light, and 10 days under red light.

90

All cultures were in batch mode until day 20. The cultures were then operated semi-

continuously with harvesting frequency of every 3 days. During 20 days of batch

culture, Nannochloropsis sp. under white light reached the highest cell density

compared to the cultures grown in blue or red light (Figure 26). When grown semi-

continuously, the maximum cell densities were Wa > Bb > Rc. The specific growth rate

was highest under white light in batch mode. In semi-continuous mode,

Nannochloropsis sp. specific growth rate was Bb > Wa = Ra (Figure 27).

Botryococcus braunii

The growth of B. braunii was relatively slow compared to the other species and similar

under the three different light spectra. In semi-continuous culture, the cell density

decreased even at a 5 day harvesting frequency (Figure 26). In both batch and semi-

continuous cultures, the maximum cell densities were similar in white, blue, and red

light (Wa = Ba = Ra). The highest specific growth rate of B. braunii in batch mode was

observed under white light, whereas in semi-continuous culture, the specific growth rate

was Wa = Ba = Ra (Figure 27).

Amphora sp.

Amphora sp. reached stationary phase in 17 days when grown under white light, and in

20 days under blue and red light. From day 20 the algae were cultured in semi-

continuous culture mode with a harvesting frequency of every 3 days (Figure 26). The

growth of Amphora sp. under blue and white light was similar, and achieved a higher

average cell density than the red light culture.

The maximum cell density of Amphora sp. was obtained under white and blue light in

batch mode, while in semi-continuous mode it was the highest under blue light. The

lowest cell density was observed under red light in both culture modes. When grown

semi-continuously, the maximum cell density was Ba > Wb > Rc. The specific growth

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rate of Amphora sp. was the highest when grown using red light in batch mode. In semi-

continuous culture, the specific growth rate of Amphora sp. was Wa = Ba = Ra (Figure

27).

Pleurochrysis carterae

Pleurochrysis carterae showed a different growth pattern compared to the other species.

Growth still increased to the stationary phase, even in the semi-continuous mode when

grown under the white and blue light, conditions in which the other algae had entered

the stationary phase. In contrast, the cells under the red light were observed not growing

and already entered stationary phase in 17 days. From day 20, the algae were then

cultured in semi-continuous mode with a harvesting frequency of every 4 days until the

third harvest (Figure 26). The harvesting interval was then reduced to 3 days for the

fourth harvest.

The maximum cell density of P. carterae was obtained under blue light in batch culture,

while the lowest cell density was observed under red light. When grown semi-

continuously, the maximum cell density was also Ba > Wb > Rc. The highest specific

growth rate was observed under blue light in batch mode, while the specific growth rate

of P. carterae in semi-continuous mode was Wa > Bab > Rb (Figure 27).

92

Figure 26. Growth curves of all species grown using white ( ), blue ( ),

and red light ( ) (mean ± range, n=3).

93

Figure 27. The maximum cell density in the 2 culture modes (mean ± range, n=3),

and specific growth rate in batch mode (n=1, no statistical analysis) and semi-

continuous mode (mean ± SE, n=4) of all species grown using white (W), blue (B),

and red (R) light. Values with different letter indicate significant differences

between the means (Repeated Measures, One Way ANOVA, Holm-Sidak, P<0.05).

94

3.1.2 Biomass and proximate composition

The biomass yield (g.L-1) and cell weight (ng.cell-1) of all species grown using white,

blue, and red light are shown in Figure 28. The lipid, carbohydrate, and protein yield

(g.L-1), cell content (ng.cell-1), and composition (as % of dry weight) of all species

grown semi-continuously under different light spectra are summarized in Figure 29. The

chlorophyll contents (pg.cell-1) of all species are presented in Figure 30.

Nannochloropsis sp.

Nannochloropsis sp. achieved similar biomass yield when grown using white, blue, and

red light in batch mode (Wa = Ba = Ra, Repeated Measures, One Way ANOVA,

P>0.05). In semi-continuous mode, Nannochloropsis sp. biomass yield was also Wa =

Ba = Ra.

Nannochloropsis sp. obtained similar cell weight when grown using white, blue, and red

light in batch mode (Wa = Ba = Ra, Repeated Measures, One Way ANOVA, P>0.05). In

semi-continuous mode, the highest cell weight of Nannochloropsis sp. was Rb > Bba >

Wa.

In semi-continuous mode, the lipid yield of Nannochloropsis sp. was Wa = Ba = Ra, the

carbohydrate yield was Rb > Wba > Ba, whereas the protein yield was Wa = Ba = Ra.

Further multiple comparison test found no statistically significant difference within lipid

and protein yield of the alga with different colour light. The highest lipid and protein

contents of Nannochloropsis sp. were Bb > Rba > Wa, whereas the carbohydrate was Rb

> Bba > Wa.

The lipid, carbohydrate, protein, and ash composition of Nannochloropsis sp. were

similar when grown under white and blue light. However, under red light

Nannochloropsis sp. accumulated less lipid and protein, but more carbohydrate. In

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contrast, under blue light Nannochloropsis sp. accumulated less carbohydrate, but more

lipid and protein. The highest chlorophyll a content of Nannochloropsis sp. was Ba >

Wab > Rb in semi-continuous mode.

Botryococcus braunii

In batch mode, B. braunii achieved similar biomass yield when grown using white,

blue, and red light (Wa = Ba = Ra, Repeated Measures, One Way ANOVA, P>0.05). In

semi-continuous mode, B. braunii biomass yield was also Wa = Ba = Ra.

B. braunii obtained similar cell weight when grown using white, blue, and red light in

batch mode (Wa = Ba = Ra, Repeated Measures, One Way ANOVA, P>0.05). In semi-

continuous mode, the cell weight of B. braunii was also Wa = Ba = Ra.

In semi-continuous mode, the lipid and protein yields of B. braunii were Wa = Ba = Ra,

while the highest carbohydrate yield was Rb > Wba > Ba. The highest lipid content of B.

braunii was Ba > Wab > Rb, whereas the carbohydrate and protein contents were Wa =

Ba = Ra.

Under white and blue light, B. braunii accumulated more lipid, but less carbohydrate

and protein. In contrast, B. braunii accumulated less lipid, but more carbohydrate and

protein composition in red light. The chlorophyll a and b of B. braunii in semi-

continuous mode were Wa = Ba = Ra.

Amphora sp.

Similar biomass yield of Amphora sp. was also obtained when grown using white, blue,

and red light in batch mode (Wa = Ba = Ra, Repeated Measures, One Way ANOVA,

P>0.05). In semi-continuous mode, the highest Amphora sp. biomass yield was Ba >

Wab > Rb.

96

In batch mode, Amphora sp. achieved similar cell weight when grown using white, blue,

and red light (Wa = Ba = Ra, Repeated Measures, One Way ANOVA, P>0.05). In semi-

continuous mode, the highest cell weight of Amphora sp. was Rb > Wa = Ba.

In semi-continuous mode, the lipid and carbohydrate yields of Amphora sp. were Wa =

Ba = Ra, while the highest protein yield was Ba > Wab > Rb. The highest lipid content of

Amphora sp. was Rb > Wa = Ba, while the highest carbohydrate and protein contents

were Rb > Wa = Ba.

Amphora sp. produced more lipid and protein, and contained less ash and carbohydrate

under blue light. In contrast, under red light, Amphora sp. accumulated less lipid and

protein, but more carbohydrate. The chlorophyll a content of Amphora sp. was Wa = Ba

= Ra, and a very small amount of chlorophyll c (c1+c2) was detected under blue light.

Pleurochrysis carterae

In batch mode, P. carterae achieved similar biomass yield when grown using white,

blue, and red light (Wa = Ba = Ra, Repeated Measures, One Way ANOVA, P>0.05). In

semi-continuous mode, the highest biomass yield was Bb > Wa = Ra.

P. carterae obtained similar cell weight when grown using white, blue, and red light in

batch mode (Wa = Ba = Ra, Repeated Measures, One Way ANOVA, P>0.05). In semi-

continuous mode, the highest cell weight of P. carterae was Rb > Wa = Ba.

In semi-continuous mode, the lipid, carbohydrate, and protein yields of P. carterae were

similar (Wa = Ba = Ra). In contrast, the highest lipid and carbohydrate contents of P.

carterae in semi-continuous mode were Rb > Wa = Ba, while the highest protein content

of P. carterae was Rb > Wba > Ba.

P. carterae accumulated more lipid and protein under blue light, while under red light

P. carterae accumulated more carbohydrate. The total ash was the lowest under blue

97

light, but under white and red light the ash content was similar. The highest chlorophyll

a was Rb > Bba > Wa, and chlorophyll c (c1+c2) was found under blue light.

98

Figure 28. The biomass yield and cell weight in the 2 culture modes (mean ± SE, n

batch=2, n semi-continuous Nannochloropsis sp., Amphora sp., and P. carterae=4, n

semi-continuous B. braunii=3) of all species grown using white (W), blue (B), and

red (R) light. Values with different letter indicate significant differences between

the means (Repeated Measures, One Way ANOVA, Holm-Sidak, P<0.05).

99

Figure 29. The proximate yield, content, and composition in semi-continuous mode

(mean ± SE, n Nannochloropsis sp., Amphora sp., and P. carterae=4, n B.

braunii=3) of all species grown using white (W), blue (B), and red light (R). Values

with different letter (lipid and carbohydrate), or number (protein) indicate

significant differences between the means (Repeated Measures, One Way ANOVA,

Holm-Sidak, P<0.05). No statistical analysis for proximate composition: lipid (L),

carbohydrate (C), protein (P), and ash (A), as % of dry weight.

100

Figure 30. The chlorophyll a content ( , left y axis) and chlorophyll b or c

content ( , right y axis) in semi-continuous mode (mean ± SE, n=3) of all species

grown using white (W), blue (B), and red (R) light. Values with different letter

(chlorophyll a) indicate significant differences between the means (Repeated

Measures, One Way ANOVA, Holm-Sidak, P<0.05).

3.1.3 Productivity

The biomass, lipid, carbohydrate, and protein productivities (mg.L-1.day-1) of all species

grown using white, blue, and red light spectra are summarized in Figure 31.

Nannochloropsis sp.

The biomass productivity of Nannochloropsis sp. was similar when grown using white,

blue, and red light in batch mode (Wa = Ba = Ra, Repeated Measures, One Way

ANOVA, P>0.05). In semi-continuous mode, the biomass productivity of

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Nannochloropsis sp. was also Wa = Ba = Ra. The lipid and carbohydrate productivities

of Nannochloropsis sp. were also similar (Wa = Ba = Ra), whereas the highest protein

productivity was Bab = Wa> Rb.

Botryococcus braunii

The biomass productivity of B. braunii was similar when grown using white, blue, and

red light in batch mode (Wa = Ba = Ra, Repeated Measures, One Way ANOVA,

P>0.05). In semi-continuous mode, the biomass, lipid, carbohydrate, and protein

productivities of B. braunii were all also similar under 3 different spectra (Wa = Ba =

Ra).

Amphora sp.

Similar biomass productivity of Amphora sp. was achieved when grown using white,

blue, and red light in batch mode (Wa = Ba = Ra, Repeated Measures, One Way

ANOVA, P>0.05). In semi-continuous mode, Amphora sp. obtained the highest

biomass productivity of Ba > Wab > Rb. The lipid, carbohydrate, and protein

productivities were all similar under 3 different spectra (Wa = Ba = Ra).

Pleurochrysis carterae

Similar biomass productivity of P. carterae was achieved when grown using white,

blue, and red light in batch mode (Wa = Ba = Ra, Repeated Measures, One Way

ANOVA, P>0.05). In semi-continuous mode, P. carterae obtained the highest biomass

productivity of Wa = Ba > Rb. The lipid and protein productivities of P. carterae were

Wa = Ba = Ra, while the highest carbohydrate productivity was Ba > Wab > Rb.

102

Figure 31. The biomass productivity in 2 culture modes, and lipid, carbohydrate,

and protein productivities in semi-continuous mode (mean ± SE, n batch=2, n

semi-continuous Nannochloropsis sp., Amphora sp., and P. carterae=4, n semi-

continuous B. braunii=3) of all species grown using white (W), blue (B), and red

(R) light. Values with different letter: lower case (biomass in batch and lipid in

semi-continuous), upper case (biomass and carbohydrate in semi-continuous), or

number (protein in semi-continuous) indicate significant differences between the

means of each parameter (Repeated Measures, One Way ANOVA, Holm-Sidak,

P<0.05).

103

3.1.4 Overview and comparison of the 4 species

The results of Nannochloropsis sp., B. braunii, Amphora sp., and P. carterae cultures

grown in semi-continuous mode using white (W), blue (B), and red (R) light are

summarized in Table 9 and APPENDICES. The results of this study showed that,

among the tested species, Pleurochrysis carterae under white and blue light was the

best species with respect to the growth rate, whereas Amphora sp. under white and blue

light was the best species with respect to the productivity of biomass, and under white,

blue, and red with respect to the productivity of lipid, carbohydrate, and protein. The

optimum spectral sources for the highest parameters of each species were also found

(Table 9 and Table 10).

In Nannochloropsis sp., B significantly increased growth rate, respiration rate,

chlorophyll a, and protein productivity; R significantly increased carbohydrate yield;

while B/R significantly increased photosynthetic rate, cell weight, cellular lipid,

carbohydrate, and protein. In B. braunii, B significantly increased photosynthetic and

respiration rate, and cellular lipid; whereas R significantly increased carbohydrate yield.

In Amphora sp., R significantly increased photosynthetic and respiration rate, cell

weight, cellular lipid, carbohydrate, and protein; while B/W significantly increased

biomass yield and productivity, and protein yield. In P. carterae, R significantly

increased cell weight, cellular lipid, carbohydrate, and protein; B significantly increased

biomass yield; W/B significantly increased growth rate, biomass and carbohydrate

productivity; whereas B/R significantly increased photosynthetic rate and and

chlorophyll a.

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Table 9. Summary of the results of four microalgae in semi-continuous mode.

Parameter Nannochloropsis sp. B. braunii Amphora sp. P. carterae

Max cell density (cells.mL-1

) Wa > B

b > R

c W

a = B

a = R

a B

a > W

b > R

c B

a > W

b > R

c

Specific growth rate (day-1

) Bb > W

a = R

a W

a = B

a = R

a W

a = B

a = R

a W

a > B

ab > R

b

Biomass yield (g.L-1

) Wa = B

a = R

a W

a = B

a = R

a B

a > W

ab > R

b B

b > W

a = R

a

Cell weight (ng.cell-1

) Rb > B

ba > W

a W

a = B

a = R

a R

b > W

a = B

a R

b > W

a = B

a

Biomass productivity (mg.L-1

.day-1

) Wa = B

a = R

a W

a = B

a = R

a B

a > W

ab > R

b W

a = B

a > R

b

Lipid yield (g.L-1

) Wa = B

a = R

a W

a = B

a = R

a W

a = B

a = R

a W

a = B

a = R

a

Lipid content (ng.cell-1

) Bb > R

ba > W

a B

a > W

ab > R

b R

b > W

a = B

a R

b > W

a = B

a

Lipid productivity (mg.L-1

.day-1

) Wa = B

a = R

a W

a = B

a = R

a W

a = B

a = R

a W

a = B

a = R

a

Carbohydrate yield (g.L-1

) Rb > W

ba > B

a R

b > W

ba > B

a W

a = B

a = R

a W

a = B

a = R

a

Carbohydrate content (ng.cell-1

) Rb > B

ba > W

a W

a = B

a = R

a R

b > W

a = B

a R

b > W

a = B

a

Carbohydrate productivity

(mg.L-1

.day-1

) W

a = B

a = R

a W

a = B

a = R

a W

a = B

a = R

a B

a > W

ab > R

b

Protein yield (g.L-1

) Wa = B

a = R

a W

a = B

a = R

a B

a > W

ab > R

b W

a = B

a = R

a

Protein content (ng.cell-1

) Bb > R

ba > W

a W

a = B

a = R

a R

b > W

a = B

a R

b > W

ba > B

a

Protein productivity (mg.L-1

.day-1

) Bab

= Wa > R

b W

a = B

a = R

a W

a = B

a = R

a W

a = B

a = R

a

Chl-a content (pg.cell-1

) Ba > W

ab > R

b W

a = B

a = R

a W

a = B

a = R

a R

b > B

ba > W

a

Chl-b content (pg.cell-1

) - Wa = B

a = R

a - -

Chl-c content (pg.cell-1

) - - Wa = B

a = R

a W

a = B

a = R

a

Photosynthesis at low oxygen

(µmol O2.[mg chl a]-1

.h-1

) B

b > R

ba > W

a B

b > R

a = W

a R

a > W

b > B

c R

b > B

ba > W

a

Photosynthesis at high oxygen

(µmol O2.[mg chl a]-1

.h-1

) B

b > R

ba > W

a W

a = B

a = R

a - R

b > B

a = W

a

1st

dark respiration

(µmol O2.[mg chl a]-1

.h-1

) B

b > W

a = R

a B

b > W

a = R

a W

a = B

a = R

a W

a = B

a = R

a

2nd

dark respiration

(µmol O2.[mg chl a]-1

.h-1

) B

b > W

a = R

a W

a = B

a = R

a R

b > W

a = B

a W

a = B

a = R

a

*Values with different superscript letters indicate statistically significant differences between the means (P<0.05).

This study found that oxygen concentrations, i.e. low oxygen (PL) and high oxygen

(PH), significantly affected the photosynthetic rates of Nannochloropsis sp., B. braunii,

Amphora sp., and P. carterae in white, blue, and red spectra (PL1 > PH2).

Photosynthetic and dark respiration rates (µmol O2.[mg chl a]-1.h-1) of 4 species varied.

The highest range of photosynthetic rates at low oxygen level was obtained in B.

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braunii culture (7,019-39,956 µmol O2.[mg chl a]-1.h-1), followed by Nannochloropsis

sp. (1,173-13,422 µmol O2.[mg chl a]-1.h-1). The range of photosynthetic rates at low

oxygen level of Amphora sp. and P. carterae were lower and similar, i.e. 131-779 and

137-279, respectively. Similar to the results at low oxygen, the highest range of

photosynthetic rates at high oxygen level was also achieved in B. braunii cultures

(1,749-10,319 µmol O2.[mg chl a]-1.h-1), followed by Nannochloropsis sp. (546-4,693

µmol O2.[mg chl a]-1.h-1) and P. carterae (71-137 µmol O2.[mg chl a]-1.h-1). At 5 mg

O2.L-1, the oxygen concentration in Amphora sp. had been saturated due to high NaCl

salinity (10%) used in the culture, so that the photosynthetic rate at high oxygen was not

measured. Moreover, a significant effect of different light spectra used was found in all

species to increase the photosynthetic rates, i.e. Nannochloropsis sp. (blue and red light

at low and high oxygen), B. braunii (blue light at low oxygen), Amphora sp. (red light at

low oxygen), and P. carterae (red and blue light at low oxygen, and red light at high

oxygen).

For the dark respiration rate, the highest range of the first respiration rates was obtained

in Nannochloropsis sp. culture (-133 to -1,400 µmol O2.[mg chl a]-1.h-1), followed by B.

braunii (-34 to -144 µmol O2.[mg chl a]-1.h-1), Amphora sp. (-19 to -48 µmol O2.[mg chl

a]-1.h-1), and P. carterae (-5 to -7 µmol O2.[mg chl a]-1.h-1), respectively. Similar to the

previous results, the highest range of the second respiration rates was achieved in the

same following order of Nannochloropsis sp. culture (-84 to -1,059 µmol O2.[mg chl a]-

1.h-1), B. braunii (-39 to -123 µmol O2.[mg chl a]-1.h-1), Amphora sp. (-18 to -50 µmol

O2.[mg chl a]-1.h-1), and P. carterae (-5 to -11 µmol O2.[mg chl a]-1.h-1), respectively. A

significant effect of different light spectra was observed in Nannochloropsis sp. (blue

light at the first and second rate), Botryococcus braunii (blue light at the first rate), and

Amphora sp. (red light at the second rate) to increase the dark respiration rates.

106

As shown in Figure 27, the highest cell density among all species in semi-continuous

mode was in blue light (Amphora sp.) > white light (Nannochloropsis sp.) > blue light

(P. carterae) > white, blue, and red (B. braunii). On the other hand, the highest specific

growth rate was in white and blue light (P. carterae) > blue light (Nannochloropsis sp.)

> white, blue, and red (Amphora sp.) > white, blue, and red (B. braunii) (Figure 27).

Different patterns of biomass yield and cell weight under white, blue, and red light were

observed in all species in semi-continuous mode. Nannochloropsis sp. achieved a

similar biomass yield (Wa = Ba = Ra), whereas the highest cell weight was Rb > Bba >

Wa. In contrast, B. braunii obtained both similar biomass yield and cell weight (Wa = Ba

= Ra). On the other hand, the highest biomass yield of Amphora sp. was obtained in the

order of Ba > Wab > Rb, whereas the highest biomass yield of P. carterae was Bb > Wa =

Ra. However, Amphora sp. and P. carterae obtained the same values of cell weight of

Rb > Wa = Ba. As shown in Figure 28, the highest biomass yield among all species in

semi-continuous mode was in white and blue light (Amphora sp.) > blue light (P.

carterae) > white, blue, and red (B. braunii) > white, blue, and red (Nannochloropsis

sp.). On the other hand, the highest cell weight among all species was in red light (P.

carterae) > white, blue, and red (B. braunii) > red light (Amphora sp.) > blue and red

light (Nannochloropsis sp.) (Figure 28).

Various patterns of lipid, carbohydrate, and protein yields, and cellular contents were

also observed in all species. For the lipid yield, a similar pattern was indicated in all

species, in which none of the light spectrum significantly affected the lipid yield (Wa =

Ba = Ra). As shown in Figure 29, the highest lipid yield among all species was in white,

blue, and red (Amphora sp.) > white, blue, and red (B. braunii) > white, blue, and red

(Nannochloropsis sp.) > white, blue, and red (P. carterae). On the other hand, the

107

highest lipid content was in red light (P. carterae) > white and blue light (B. braunii) >

red light (Amphora sp.) > blue and red light (Nannochloropsis sp.) (Figure 29).

For the highest carbohydrate yield, Nannochloropsis sp. and B. braunii had a similar

trend of Rb > Wba > Ba, while Amphora sp. and P. carterae shown a similar trend of Wa

= Ba = Ra. As shown in Figure 29, the highest carbohydrate yield among all species was

in white, blue, and red (Amphora sp.) > white and red light (B. braunii) > white, blue,

and red (P. carterae) > white and red light (Nannochloropsis sp.). On the other hand,

the highest carbohydrate content was in red light (Amphora sp.) > red light (P. carterae)

> white, blue, and red (B. braunii) > blue and red light (Nannochloropsis sp.) (Figure

29). However, this study found that all species mostly accumulated the highest

carbohydrate inside their cells under the exposure of red light. The lowest carbohydrate

content was observed under white light for Nannochloropsis sp., and when grown using

white and blue light for Amphora sp. and P. carterae.

Furthermore, Nannochloropsis sp., B. braunii, and P. carterae had the highest protein

yield under white, blue, and red light, whereas the highest protein yields of Amphora sp.

were achieved when grown using white and blue light. A reduction in protein yield was

only observed under red light in Amphora sp. As shown in Figure 29, the highest

protein yield among all species was in white and blue light (Amphora sp.) > white, blue,

and red (B. braunii) > white, blue, and red (P. carterae) > white, blue, and red

(Nannochloropsis sp.). On the other hand, the patterns of cellular protein content were

various among all species. The highest protein content was in white, blue, and red (B.

braunii) > white and red light (P. carterae) > red light (Amphora sp.) > blue and red

light (Nannochloropsis sp.) (Figure 29).

An identical pattern of proximate yield and cellular content was only found in B.

braunii culture. The protein yield and content of B. braunii was observed in the same

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trend of Wa = Ba = Ra. In contrast, all species shown different patterns of their

proximate yields compared to the cellular contents.

For the proximate composition, all species revealed that the highest proportion of cell

content was the lipid compared to carbohydrate and protein (Figure 29). The highest

lipid composition (% of dry weight) was obtained under blue light for all species. For

the carbohydrate composition, the highest proportion was achieved under red light for

Nannochloropsis sp. and B. braunii. The carbohydrate compositions of Amphora sp.

and P. carterae were the highest under red and blue light with similar proportion. All

species had the highest protein composition under blue light, except for B. braunii

which achieved the highest under red light. In addition, the highest chlorophyll a

content was obtained in blue and red light (P. carterae) > white, blue, and red (Amphora

sp.) > white, blue, and red (B. braunii) > white and blue light (Nannochloropsis sp.)

(Figure 30). The chlorophyll c content was only determined in blue light culture for

both Amphora sp. and P. carterae.

In summary, the key findings on selected parameters of 4 species grown using white

(W), blue (B), and red (R) light, based on the experimental results which were

statistically significant, are described in Table 10.

109

Table 10. Summary of the significant effects of light quality, i.e. white (W), blue

(B), and red (R), on key parameters of cell physiology and composition.

Parameter Nannochloropsis sp. B. braunii Amphora sp. P. carterae

Photosynthesis B/R B R R/B

Respiration B B R none

Growth rate B none none W/B

Cell weight R/B none R R

Cellular lipid B/R B/W R R

Cellular carbohydrate

R/B none R R

Cellular

protein B/R none R R/W

Biomass yield none none B/W B

Lipid yield none none none none

Carbohydrate yield

R/W R/W none none

Protein yield none none B/W none

Chlorophyll a B/W none none R/B

Three different spectra significantly increased most key parameters of Nannochloropsis

sp., Amphora sp. and P. carterae. However, for B. braunii, different light spectra

significantly increased only few key parameters, i.e. photosynthesis, respiration, cellular

lipid, and carbohydrate yield. In general, white light is actually not as good as the

narrower spectrum. The important outcomes, especially on the cell physiology (i.e.

photosynthesis, respiration, and growth), biomass, and proximate composition (e.g.

lipid, carbohydrate, protein, and chlorophyll a), are that (mostly) blue and red light

significantly increased most of the cellular parameters for Nannochloropsis sp., whereas

it is red light for Amphora sp., and (mainly) red and sometimes blue light for P.

carterae (Table 10). Blue light significantly increased photosynthesis, respiration, and

cellular lipid in B. braunii, and not much else. On the other hand, the carbohydrate yield

of Nannochloropsis sp. and B. braunii was significantly increased by either red or white

light, whereas biomass, lipid, and protein yield were actually not significantly increased

by the light spectrum. Blue or white light significantly increased biomass and protein

110

yield in Amphora sp., whereas only biomass yield and chlorophyll a was significantly

increased by blue light in P. carterae.

Among 4 species, the highest biomass productivity in batch mode was achieved in

Amphora sp. > Nannochloropsis sp. > P. carterae > B. braunii (all under white, blue,

and red light). In semi-continuous mode, the highest biomass productivity was obtained

in white and blue light (Amphora sp.) > white and blue light (P. carterae) > white, blue,

and red (Nannochloropsis sp.) > white, blue, and red (B. braunii) (Figure 31). A

significant effect of different light spectra used was found in P. carterae (Wa = Ba > Rb)

and Amphora sp. (Ba > Wab > Rb) to increase the biomass productivity.

In contrast, none of the light spectra significantly increased the lipid productivity of 4

species (Wa = Ba = Ra). The highest lipid productivity among all species in semi-

continuous mode was obtained in Amphora sp. > Nannochloropsis sp. > B. braunii > P.

carterae (all under white, blue, and red light). White and blue light were considered as

the best spectra for the highest carbohydrate and protein productivities of the 4 species.

The highest carbohydrate productivity among all species in semi-continuous mode was

achieved in white, blue, and red (Amphora sp.) > white and blue light (P. carterae) >

white, blue, and red (Nannochloropsis sp.) > white, blue, and red (B. braunii). The

highest protein productivity among all species in semi-continuous mode was obtained in

white, blue, and red (Amphora sp.) > white, blue, and red (P. carterae) > white and blue

light (Nannochloropsis sp.) > white, blue, and red (B. braunii) (Figure 31). A significant

effect of different light spectra used was detected in P. carterae (white and blue light) to

increase the carbohydrate productivity, and in Nannochloropsis sp. (white and blue

light) to increase the protein productivity.

111

3.2 Discussion

3.2.1 Photosynthesis, respiration, and growth

The species growths were maintained semi-continuously (stable growth). The semi-

continuous cells had been acclimated to the changes of spectral environments. Blue and

red light adapted cells presented the highest photosynthetic rate at low oxygen

concentration for Nannochloropsis sp. and P. carterae, and at high oxygen

concentration for Nannochloropsis sp. and B. braunii. However, at high oxygen

concentration P. carterae only obtained the highest photosynthetic rate under red light,

whereas at low oxygen concentration B. braunii obtained the highest under blue light.

Amphora sp. achieved the highest photosynthetic rate at low oxygen concentration when

grown using red light. High photosynthetic rates in blue spectrum are in agreement with

those previously reported for some Chlorophyta, i.e. Chlorella (Emerson and Lewis

1943), Dunaliella tertiolecta (Wallen and Geen 1971b), and B. braunii (Baba et al.

2012). However, as observed in Nannochloropsis sp., Amphora sp., and P. carterae,

previous studies also reported that photosynthetic activities appear to be higher in

Haematococcus pluvialis (Chlorophyta) when grown in a red spectrum instead of green

and simulated daylight (whole range of PAR) (Jeon et al. 2005), in Porphyra leucosticta

(Rhodophyta), in Tetraselmis suecica and Tetraselmis gracilis (Chlorophyta) when

grown in red compared to white and blue spectra (Aidar et al. 1994; Korbee et al. 2005;

Abiusi et al. 2014). In contrast, another species of diatom Cyclotella caspia

(Heterokontophyta) showed no such differences of photosynthetic rate in red and blue-

green spectra (Aidar et al. 1994) (Table 11).

The differences of microalgal photosynthetic activities were mainly caused by the

diversity of light harvesting pigments, their absorption spectra, and the photosynthetic

action spectra profiles, which will be discussed in the following sections. Previous

112

studies reported that the high photosynthetic rates achieved in a narrower spectrum, e.g.

in Chlorella, Dunaliella tertiolecta and B. braunii, indicated the dependence of

maximum quantum yield of photosynthesis of these algae on specific PAR wavelength,

i.e. blue region (Emerson and Lewis 1943; Wallen and Geen 1971b; Baba et al. 2012).

This response of photosynthetic rates in different light qualities, e.g. blue light

enhancement of B. braunii in Baba et al. (2012), is in agreement with results obtained

for B. braunii in this study.

However, it is important to note that the various responses of light quality effects may

also be related to different experimental set-up and methodologies used in the studies.

For example, the use of different artificial light sources, i.e. LED, or the application of

particular light filters to provide specific PAR spectra into the algae cultures (Parlevliet

and Moheimani 2014; Schulze et al. 2014). A difference in amount of energy supplied

between different spectra, i.e. white, blue, and red, can also mislead the comparison. For

example, when the light is equally employed based on the same number of quanta

(photons) from each spectrum, photons of different wavelengths of each spectral region

of PAR actually transmit different levels of energy (Hall and Rao 1999).

Photoacclimation to spectral quality has also been considered to play a more important

role than variability of aquatic light field and microalgal pigments composition

(Dubinsky and Stambler 2009). Photoacclimation is significant in determining

microalgal photosynthetic performance and distribution (Sakshaug et al. 1987; Aidar et

al. 1994; Gorai et al. 2014), and optimizing biomass and target products yields in

biotechnological applications (Marchetti et al. 2013; Mulders et al. 2014). When cells

are grown under subsaturating light for a prolonged time period, they acclimate to this

light condition by increasing the number of photosystems and associated cellular

content of the primary pigments (Mulders et al. 2014). In addition, the operation of light

113

intensity is clearly significant to further define the light quality effects. For instance, the

enhancement effects of blue light are often observed under low light intensity and below

saturating intensities (Voskresenskaya 1972; Gorai et al. 2014; Tamburic et al. 2014),

which were also applied in this study. Therefore, the comparability of previous findings

should be carefully analyzed, and clearly consider the various experimental and lighting

set-ups (Table 11, Table 12, Table 13, and Table 14).

Photosynthesis is an important factor that influences microalgal growth, yield, and

productivity of the cultures. The rate of photosynthesis and respiration achieved by

microalgae cells is important, and depends on the rate of capture of quanta from the

light field (Kirk 1983). Narrower spectra of PAR, e.g. blue and red, have been

considered as the most efficient light for microalgae photosynthesis (Emerson and

Lewis 1943; Abiusi et al. 2014; Gorai et al. 2014). An early study by Emerson and

associates in the 1940s determined the action spectra of photosynthesis for various algae

as a function of the monochromatic light used to illuminate the algae (Hall and Rao

1999). They found that the most effective wavelengths for photosynthesis in Chlorella

were blue (400-460 nm) and red (650-680 nm), and both colours were the most strongly

absorbed by chlorophylls. The photosynthetic efficiency of a quantum absorbed at 680

nm was about 36% more than of a quantum absorbed at 460 nm (Hall and Rao 1999).

On the other hand, the enhancement of photosynthetic activities under prolonged blue

light exposure might be influenced by high activity of ribulose-1,5-bisphosphate

carboxylase/oxygenase (Rubisco) and activation of photosynthetic electron transfer

chain reactions (Voskresenskaya 1972). In Chlorogonium elongatum (Chlorophyta), the

stimulating effect of light on the synthesis of ribulose bisphosphate

carboxylase/oxygenase (RuBPCase) was mainly caused by blue light of wavelengths

between 430 nm and 510 nm, with a maximum effect at about 460 nm (Roscher and

Zetsche 1986). Blue light generates an increase in the amounts of the mRNAs for the

114

large and the small subunits of the RuBPCase enzyme (Roscher and Zetsche 1986).

Therefore, the changes in the mRNA levels are the main regulatory steps in the blue

light-dependent synthesis of the RuBPCase enzyme for the photosynthetic carbon

metabolism and Calvin cycle in microalgae (see also Figure 10).

115

Table 11. Comparison of photosynthesis and dark respiration (rates) of microalgae grown using monochromatic, or a mixed of blue (B), red

(R), white (W), green (G), and far red (FR) from the same classes and pigments in this study and previous findings.

Class, Phylum Major

pigments Species Photosynthesis

Dark

respiration Light colours Irradiance (photons/energy) Reference*

Eustigmatophyceae,

Heterokontophyta

Chl a,

violaxanthin Nannochloropsis sp. B

b > R

ba > W

a(i)

Bb > W

a =

Ra(i)

W, B, R (fluorescent

tubes and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study#

Trebouxiophyceae,

Chlorophyta

Chl a, b,

β-carotene

B. braunii (race A) Bb > R

a = W

a(i)

Wa = B

a =

Ra(i)

W, B, R (fluorescent

tubes and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study#

B. braunii (race B) B > R > G(ii)

- B, G, R (LEDs) Equal photon flux density

(60 µmol photons.m-2

.s-1

) 1

Chlorella vulgaris - BR > W >

BRFR(iv)

W (fluorescent

lamps), BR, BRFR

(LEDs)

Equal photon flux density

(400 µmol photons.m-2

.s-1

) 2

Bacillariophyceae,

Heterokontophyta

Chl a, c,

fucoxanthin

Amphora sp. Ra > W

b > B

c(i)

Rb > W

a =

Ba(i)

W, B, R (fluorescent

tubes and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study#

Cyclotella caspia R = B > W(iii)

- W, B, R (fluorescent

lamps and filters)

Equal photon flux density

(25 µmol photons.m-2

.s-1

) 3

Prymnesiophyceae,

Haptophyta

Chl a, c,

fucoxanthin

P. carterae Rb > B

ba > W

a(i)

Wa = B

a =

Ra(i)

W, B, R (fluorescent

tubes and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study#

Isochrysis sp. B > W(i)

- W, B (fluorescent

tubes)

Equal photon flux density

(100 µmol photons.m-2

.s-1

) 4

*1) Baba et al. (2012), 2) Kula et al. (2014), 3) Aidar et al. (1994), 4) Marchetti et al. (2013), #) at low oxygen concentration (1-4 mg O2.L-1), and at the second dark respiration, i) based on oxygen production per chlorophyll, ii) based on total 14C fixation per chlorophyll, iii) based on total 14C fixation per cell, iv) based on heat power emission.

116

When the species growth was maintained semi-continuously (stable growth), blue light

adapted cells presented the highest respiration rate in Nannochloropsis sp. and B.

braunii on the first and second dark respiration. Amphora sp. achieved the highest

respiration rate under white, blue, and red light on the first dark respiration, and under

red light on the second dark respiration. P. carterae obtained the highest respiration rate

when grown using white, blue, and red light both on the first dark respiration and the

second dark respiration. The increase of respiration under the influence of visible

radiation, especially blue light, possibly is accompanied by de novo synthesis of

bottleneck enzymes, e.g. pyruvate kinase, production of enzyme species with greater

substrate affinity, and an altered distribution of substrate and cofactors within various

cell compartments (Kowallik 1987). The first possibility of blue light-dependent

enhancement of dark respiration has been described as the regulations on respiratory

and nonrespiratory enzymes (Kowallik 1982) that are in agreement with results obtained

for Nannochloropsis sp., B. braunii, and P. carterae for both the first and second dark

respiration. In contrast, the highest dark respiration rate of Amphora sp. was achieved

under the red light for the second dark respiration. The stimulations of respiration (O2

uptake) by both blue and red light have been previously observed, e.g. in Dunaliella

tertiolecta (Chlorophyta) (Ruyters 1988; Rivkin 1989).

The blue light-enhanced respiration might be related to uptake systems for exogenous

nitrogenous compounds, e.g. nitrate, amino acids, ammonia, and urea (Kamiya and

Saitoh 2002). Kamiya (1997) reported that blue light induced uptake of exogenous

nitrate, which was accompanied by acidification of the suspension medium of a

Chlorella colourless mutant. Kamiya and Saitoh (2002) then found that in Chlorella

mutant cells grown with nitrate as sole nitrogen source, blue light enhanced the uptake

of the amino acids glycine, proline, and arginine, and of ammonia in resting cells, but it

inhibited the uptake of these amino acids in growing cells.

117

In crude extracts of nonphotosynthetic mutant of blue-irradiated Chlorella vulgaris

cells, higher turnover rates have been measured for several enzymes, e.g. amylase,

aldolase, pyruvate kinase, and NAD-dependent isocitrate dehydrogenase, with the

greatest enhancement was found for pyruvate kinase (Kowallik 1982). Two different

blue light effects on pyruvate kinase biosynthesis have been considered: firstly, an

enzyme transformation, leading to an isoenzyme with greater phosphoenolpyruvate

(PEP) affinity; and secondly, a de novo synthesis of the enzyme protein (Kowallik and

Schatzle 1980; Ruyters 1981).

The second possibility is that blue light influences the properties of intracellular

membranes (Kowallik 1982). Hypothetically, modifications of substrate and cofactor

distribution in different cell compartments of microalgae can control the enzyme

activity in vivo as well as de novo synthesis via substrate induction (Kowallik 1987).

The enhancement of respiration reveals a wavelength dependence that also corresponds

to the absorption of flavin (Kowallik and Gaffron 1966; Kamiya and Miyachi 1974).

Flavins as well as carotenoids might be incorporated in, or be attached to

compartmentalizing membranes, and modifying their permeability by influences on the

structure of neighboring proteins (Kowallik 1987). In addition, Schönbohm and

Schönbohm (1984) studied multiple effects of the flavin quencher potassium iodide (KI)

on light- and dark-processes in Mougeotia (Chlorophyta). The results showed that with

increasing incubation time, dark respiration became intensively inhibited by KI, in

which KI uptake in the blue light is much higher than in the far-red light or in the red

light during an incubation time of 15 minutes (Schönbohm and Schönbohm 1984).

For decades, the chemical nature of blue light photoreceptors and the chromophore in

blue light receptors was much disputed as to whether it was a flavin or a carotenoid (De

Fabo 1980; Senger 1984; Song 1984). This issue was partially resolved after the

118

discovery of the first blue light receptor at the molecular level, which corresponded to a

flavin protein named cryptochrome (Ahmad and Cashmore 1993). Shortly after this

finding, a disrupted gene in Arabidopsis non-phototropic hypocotyl 1 (nph1) mutants

and its homolog, non-phototropic hypocotyl- like 1 (npl1), encoded a blue light receptor

required for phototropic response (Christie et al. 1998; Kagawa et al. 2001). nph1 and

npl1 were then renamed phototropin 1 (phot1) and phot2, respectively. Phototropins

mediate diverse responses in plants and algae, e.g. chloroplast relocation movements

(Sakai et al. 2001) and blue light- induced chloroplast photoorientation in green algae

Mougeotia scalaris (Suetsugu et al. 2005). These physiological responses contribute to

enhance photosynthesis in the plant by increasing the absorption of light and CO2

(Takemiya et al. 2005). In unicellular green algae, phototropins involved in the blue

light- induced developmental processes, e.g. conversion of pregametes to gametes during

gametogenesis, and cell size regulation in Chlamydomonas reinhardtii (Huang et al.

2002; Huang and Beck 2003; Oldenhof et al. 2006).

However, visible spectrum can also cause an inhibition of respiration in several

microalgae, e.g. Chlorella and Chlamydomonas mutants, when light- induced growth

inhibition was observed (Sorokin and Krauss 1959; Gross and Dugger 1969). This

growth inhibition was found to be accompanied by an inhibition of O2 uptake and/or

CO2 output (Kowallik 1982). The possibility of some connection with biological

rhythms has been described, e.g. synchronous cell division of autotrophic Chlorella that

occurred in the dark phase of a synchronizing light-dark regime, can be delayed by

prolonging the light phase, or inhibited by additionally increasing the light phase

intensity, with blue light being most effective (Pirson and Kowallik 1964; Sorokin and

Krauss 1965).

119

Respiration rates are also a function of the size of an organism, and defined as

allometric relationship (Falkowski and Raven 1997). Allometric relationship is invariant

scaling relationships of body size to shape, anatomy, and physiology of organisms

including plants and animals (Damuth 2001; Niklas and Enquist 2001). Normally,

respiration per unit mass decreases as organism size increases, and the relationships

scale nonlinearly among metazoans (animals) and heterotrophs (Falkowski and Raven

1997). However, in the case of unicellular photoautotrophs, the relationship is mostly

absent or anomalous, in contrast to the pattern of unicellular heterotrophs (Banse 1976;

Falkowski and Owens 1978; Lewis Jr 1989).

In this study, a comparison of maximum cell density and cell weight (to determine the

cell size) in Table 9 of each species revealed that when the algae obtained the minimum

cell density in particular spectrum, at the same time they reached the maximum cell

weight. It means that the size of the cells was bigger in particular light spectra. For

instance, the biggest cell size of Amphora sp. and P. carterae was in red light culture,

the biggest cell size of Nannochloropsis sp. was achieved under blue and red light,

whereas B. braunii had similar cell size under 3 different spectra. However, Table 9

showed that the respiration rates of both Amphora sp. and P. carterae were similar in 3

different light spectra, while the highest respiration rate of Nannochloropsis sp. and B.

braunii was achieved under blue light. In this study, the outcomes of respiration rates

did not indicate a nonlinear relationship to cell size, as mentioned on the size-dependent

function of respiration for metazoans and heterotrophs. Therefore, this study

demonstrated that allometric scaling of respiration of unicellular phototrophic

microalgae Nannochloropsis sp., B. braunii, Amphora sp., and P. carterae was not

indicated, in which the respiration rate does not certainly depend on the cell size, based

on the results of the 4 tested species.

120

Furthermore, the outcomes of this study indicated that when the algae were cultured

semi-continuously (stable growth), the highest maximum cell density was achieved

under white light for Nannochloropsis sp., and blue light for Amphora sp. and P.

carterae. The lowest cell density of Nannochloropsis sp., Amphora sp. and P. carterae

was obtained when grown using red light, whereas light colour had no effect on the

maximum cell density of B. braunii. Cells grown under blue light presented the highest

growth rate (day-1) for Nannochloropsis sp., whereas for P. carterae the highest was

obtained when white light was the main source of energy. The highest growth rate of B.

braunii and Amphora sp. was achieved under white, blue, and red light. Pleurochrysis

carterae under white light was considered as the best species with respect to the specific

growth rate among the tested microalgae.

These responses of growth in different light qualities are in agreement with those

previously reported for Eustigmatophyceae, Heterokontophyta: Nannochloropsis sp.

(Das et al. 2011); Bacillariophyceae, Heterokontophyta: a) Cyclotella nana (Wallen and

Geen 1971b), b) Thalassiosira gravida, c) Phaeodactylum tricornutum (Holdsworth

1985), d) Chaetoceros sp. (Sánchez Saavedra and Voltolina 1996), and e) Navicula sp.

(Cao et al. 2013); Prymnesiophyceae, Haptophyta: a) Isochrysis sp. (Marchetti et al.

2013) and b) Isochrysis galbana (Gorai et al. 2014); and Trebouxiophyceae,

Chlorophyta: B. braunii (Baba et al. 2012) (Table 12). On the other hand, other

Chlorophyta, i.e. Tetraselmis gracilis and Tetraselmis suecica, were reported to have a

different result of higher growth rate under red light compared to white and blue (Aidar

et al. 1994; Abiusi et al. 2014).

121

Table 12. Comparison of maximum cell density and specific growth rate of microalgae grown using blue (B), red (R), white (W), or green (G)

from the same classes and pigments in this study and previous findings.

Class, Phylum Major

pigments Species

Maximum cell

density

(cells.mL-1

)

Specific growth

rate (day-1

) Light colours Irradiance (photons/energy) Reference*

Eustigmatophyceae,

Heterokontophyta

Chl a,

violaxanthin Nannochloropsis sp.

Wa > B

b > R

c B

b > W

a = R

a

W, B, R (fluorescent

tubes and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study

B > W > R B > W > R W, B, G, R (LEDs) Unequal energy 1

Trebouxiophyceae,

Chlorophyta

Chl a, b,

β-carotene

B. braunii (race A) Wa = B

a = R

a W

a = B

a = R

a

W, B, R (fluorescent

tubes and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study

B. braunii (race B) - R > B > G B, G, R (LEDs) Equal photon flux density

(60 µmol photons.m-2

.s-1

) 2

Bacillariophyceae,

Heterokontophyta

Chl a, c,

fucoxanthin

Amphora sp. Ba > W

b > R

c W

a = B

a = R

a

W, B, R (fluorescent

tubes and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study

Cyclotella nana B > W > G B > W > G W, B, R

(fluorescent lamps) Unequal energy 3

Prymnesiophyceae,

Haptophyta

Chl a, c,

fucoxanthin

P. carterae Ba > W

b > R

c W

a > B

ab > R

b

W, B, R (fluorescent

tubes and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study

Isochrysis sp. B > W - W, B

(fluorescent tubes)

Equal photon flux density

(100 µmol photons.m-2

.s-1

) 4

Isochrysis galbana - B > W W, B (fluorescent

tubes and filters)

Equal photon flux density

(60 µmol photons.m-2

.s-1

) 5

*1) Das et al. (2011), 2) Baba et al. (2012), 3) Wallen and Geen (1971b), 4) Marchetti et al. (2013), 5) Gorai et al. (2014).

122

However, there are no previous findings on effects of different light spectra of 4 species

used in this study that applied similar amount of transmitted energy into the microalgae.

Most of experimental set-up of previous studies provided equivalent photons into the

cultures in comparing effects of different light spectra, thus the algae were actually

illuminated by unequal energy.

The results of this study found that white light was not always be the suitable energy

source for optimum cell densities and growth rates of the 4 species. The narrower

spectrum, e.g. blue light, has been determined to induce the highest growth rate in

Nannochloropsis sp. culture. In addition to light harvesting pigment-protein complexes,

the light absorption system in microalgae also includes remarkably sensitive

photoreceptors, which change their structure in response to different light qualities and

induce various developmental, physiological, and behavioral responses or

photomorphogenetic responses (Kianianmomeni and Hallmann 2014). Photosynthetic

organisms use particular parts of PAR spectrum (e.g. blue light) as signals in specific

photoreceptors for certain photomorphogenetic responses (Senger 1987; Hegemann

2008). For example, the reactions mediated by blue light in photosynthetic organisms

including microalgae can be classified as photomorphogenetic and photomovement

responses, which include morphological, metabolic, and adaptational processes (Senger

1987; Kianianmomeni and Hallmann 2014).

Blue light particularly enhances a) the formation of nucleic acids in photosynthetic

organisms (Senger and Bishop 1968; Voskresenskaya 1972), b) photosynthetic enzyme

activation (Conradt and Ruyters 1980; Ruyters 1980a, 1981, 1982, 1984), c) chlorophyll

biosynthesis (Senger et al. 1980; Kowallik and Schürmann 1984; Senge and Senger

1991), d) dark respiration of some microalgae (Kowallik 1982), e) Chlorophyta and

diatom growths and cell division, as well as to form a uniform and regulated diatom cell

123

distribution (Oldenhof et al. 2004; Bowler et al. 2010; Cao et al. 2013), and f) the

gametogenesis of brown algae (Pearson et al. 2004).

Three major sensory photoreceptors family of algae, which are utilized in nature to

regulate growth, developmental and photomorphogenetic processes in the visible

spectrum, are: 1) Red/far-red light photoreceptors (i.e. phytochromes), 2) UV-A)/blue

light photoreceptors (e.g. cryptochromes and phototropins), and 3) Blue light- light,

oxygen or voltage (LOV) photoreceptors (e.g. aureochromes and neochromes) (Depauw

et al. 2012; Shimazaki and Tokutomi 2013; Kianianmomeni and Hallmann 2014; Li et

al. 2015b). Recently, algal phytochromes was found to extend the light sensing from

red/far-red into the orange or yellow spectrum in prasinophyte algae (e.g. Nephroselmis

pyriformis and Prasinoderma coloniale), into the green spectrum in heterokont algae

(e.g. E. siliculosus), and into the blue spectrum in glaucophyte algae (e.g. Cyanophora

paradoxa) (Rockwell et al. 2014).

Differences in light response on the maximum cell density and growth by major

taxonomic categories of algae have also been suggested because taxonomic categories

are in part determined by differences in light-harvesting pigments and membranes (Hill

1996). The 4 different species used in this study are from 4 different classes with

different pigment compositions, photosynthetic action and absorption spectra profiles

(see chapter 1.6, Figure 6, Figure 7, and Figure 8). The marine microalga

Nannochloropsis in the Eustigmatophyceae is a unique species, which does not contain

accessory chlorophyll in addition to chlorophyll a with the major carotenoid

violaxanthin (Whittle and Casselton 1975; Antia and Cheng 1982). In this alga,

violaxanthin constitutes 60% of the total carotenoids, and the excitation spectrum of

chlorophyll a in whole cells peaks at 490 nm (blue region), which corresponds to the in

vivo peak absorption of violaxanthin (Owens et al. 1987; Dring 1990) around 475-500

124

nm (Figure 8). Nannochloropsis sp. (Heterokontophyta) also has higher in vivo

absorption peak of blue spectrum than in vivo absorption peak of red spectrum (Figure

7. F). Vadiveloo et al. (2015) reported that the most efficient light to biomass

conversion for Nannochloropsis sp. was found to be between 400 and 525 nm (blue

light), which parallels with the spectral regions of light filters used in this study (i.e.

blue filter: 407-488 nm, red filter: 621-700 nm) (Figure 16).

Furthermore, the maximum peak of action spectrum of photosynthesis for

Nannochloropsis was determined to be at blue light of 414 nm and was higher than the

maximum peak obtained under red spectrum (Tamburic et al. 2014) (Figure 6. A). Light

at this blue maximum was absorbed more effectively, and directed more efficiently

towards PS II than at the red maximum of 679 nm at light intensities below the

photosaturation limit (Tamburic et al. 2014). In consequence, the photosynthetic rate

under blue spectrum was higher compared to red in Nannochloropsis. In addition, the

biomass productivity per photons and light energy supplied were found highest under

blue spectrum (Vadiveloo et al. 2015). The influence of blue light was also possibly

because of the complementary chromatic adaptation of Nannochloropsis sp. in blue

light adapted culture. When grown using blue light, the chlorophyll a content of

Nannochloropsis sp. was reached the highest compared to white and red, and the

chlorophyll a under blue light was significantly higher than red light (Figure 30).

Therefore, the irradiation of blue light particularly effectively enhances the growth of

Nannochloropsis sp., especially when illumination is maintained below saturating

intensities (Tamburic et al. 2014; Vadiveloo et al. 2015).

Similar with Nannochloropsis sp., Amphora sp. (Diatoms, Heterokontophyta) also has

higher in vivo absorption peak of blue spectrum than in vivo absorption peak of red

spectrum (Figure 7. G). The high amount of the xanthophyll fucoxanthin plays an

125

essential role in the light-harvesting complex of photosystems in addition to chlorophyll

a and c (Jeffrey 1980). An early study by Dutton and Manning (1941) and Wassink and

Kersten (1946) shown that light absorbed by the major accessory pigment of diatoms,

fucoxanthin, is utilized for photosynthesis with the same efficiency as that absorbed by

chlorophyll. Furthermore, Chauton et al. (2004) indicated that diatoms and

prymnesiophytes might be more efficient at light harvesting and transport to PS II by

fucoxanthins and chlorophyll c, as long as light is not limiting. In addition, Neori et al.

(1986) reported the photosynthetic action spectrum of a diatom, Chaetoceros gracilis,

and found that the blue-violet and blue PAR regions (centered at 470 nm) show higher

PS II O2 evolution activity than in the green and red regions (Figure 6. B). The

complementary chromatic adaptation of Amphora sp. in blue spectrum was also

indicated by a strong development of chlorophyll c in blue light adapted culture, which

increased the light absorption (Figure 30).

Pleurochrysis carterae (Prymnesiophyceae, Haptophyta), with the presence of

accessory pigment fucoxanthin, enhances the capacity of light absorption wider than the

narrow blue or red spectrum with relatively greater absorption in the 500-560 nm region

(Kirk 1983) (Figure 7. E and Figure 8), thus the culture under white light performed a

higher growth rate. Haxo (1985) reported that the action spectrum of effective

photosynthesis of a marine coccolithophorid was high in spectral interval of 500-550

nm, where the 19’hexanoyloxyfucoxanthin accounted mostly for the photon capture. In

addition, this finding is also in agreement with in vivo absorption spectrum of

Haptophyta. P. carterae (Haptophyta) has higher in vivo absorption peak of blue

spectrum than in vivo absorption peak of red spectrum. The absorption spectrum of

Haptophyta comprises a blue region from 400 nm to 550 nm, and includes a small

portion of red light between 650 nm and 700 nm (Figure 7. E). Among some marine

algae, e.g. diatoms, coccolithophorids, and green algae, carotenoids can be more

126

important for photosynthesis and are frequently obtained in higher concentrations

relative to chlorophylls (Kirk 1983). For example, 19’hexanoyloxyfucoxanthin is

considered to be an efficient antenna pigment for photosynthesis in marine

coccolithophorid, and preferentially associated with PS II, which might induce

photosynthesis in a wider PAR higher than blue or red (Haxo 1985).

In contrast, none of the light spectrum significantly increased both maximum cell

density and growth of B. braunii. The influence of accessory pigments echinenone, β-

carotene, and lutein in addition to chlorophyll a and b (Figure 7. C, D, and Figure 8)

enhances the light absorption ability of Chlorophyta in white spectrum as well as in the

narrower spectra of blue filter (407-488 nm) and red (621-700 nm) (Figure 16).

Moreover, some algal groups (e.g. diatoms, phaeophytes, dinoflagellates, and green

algae) rely heavily on specific carotenoids for their light harvesting (Kirk 2010). In

these algae, the various major carotenoid species transfer their absorbed energy to the

reaction centres as efficiently as chlorophyll. This can increase the photosynthetic

ability of the cells to utilize light in all regions of PAR (Kirk 2010). The major

differences of light-harvesting pigment composition, which are found in 4 tested algae,

comprise chlorophyll a and violaxanthin, and absence of chlorophyll b and c in

Nannochloropsis sp. (Heterokontophyta); chlorophyll a and b, β-carotene, lutein, and

echinenone in B. braunii (Chlorophyta); chlorophyll a, c1 and c2, fucoxanthin, and

neofucoxanthin in Amphora sp. (Heterokontophyta); chlorophyll a, c1 and c2,

fucoxanthin derivatives, such as 19’hexanoyloxyfucoxanthin and Mg-2,4-divinyl

phaeoporphyin a5 monomethyl ester (MgDVP) in P. carterae (Haptophyta) (Lubián et

al. 2000; Zapata et al. 2004; Lee 2008; Graham et al. 2009; Matsuura et al. 2012).

This study also demonstrated that the high photosynthetic rate was not always followed

by a higher growth rate. Table 9 described that for Nannochloropsis sp., photosynthesis

127

and growth rate had the same optimum spectrum of blue light, whereas for B. braunii,

Amphora sp., and P. carterae, the photosynthesis and growth did not present the same

trends. For example, this study found the highest growth rate of B. braunii and Amphora

sp. when grown using white, blue, and red light, although the highest photosynthetic

rate was observed under blue light for B. braunii and red light for Amphora sp. This

finding corresponds to previous study by Baba et al. (2012) which indicated that

photosynthesis and growth of B. braunii (race B) are not directly correlated, although

the cause was not clear. Baba et al. (2012) reported that the rate of photosynthetic 14CO2

fixation calculated per chlorophyll molecule of B. braunii (race B) was higher in blue

light-grown cells than in the red and green light-grown cells, but the algal growth rates

were higher in the order of red, blue, and green.

In addition, the red light effect on photosynthetic activity and growth may be induced

by specific properties of the microalgae, which were described in previous studies of

other Chlorophyta. For instance, the specific responses of cell cycle in Scenedesmus

obliquus and Tetraselmis suecica F&M-M33 revealed the important roles of red light

effects on their growth enhancement (Cepák et al. 2006; Abiusi et al. 2014). Cepák et al.

(2006) reported variation in cell cycle duration in Scenedesmus obliquus with different

light qualities. Under red light, the daughter cells started to be released in a shorter time

than under white, blue, and green light, while the mother cells under green light were

smaller than with the other lights. A similar result was obtained in Chlamydomonas

reinhardtii (Chlorophyta) (Oldenhof et al. 2006). The cellular division of which was

delayed by blue light compared to red, and a larger cell size was required before cell

division could take place in blue light condition (Oldenhof et al. 2006).

Furthermore, a recent study by Abiusi et al. (2014) found that under red light almost all

the cells of Tetraselmis suecica in the culture are swarmers, whereas under the other

128

lights encysted cells largely dominate. These observations are in agreement with the cell

size, in which at similar biomass concentration, under red light the longitudinal section

area was much smaller and the cell density was more than double that under white,

green, and blue light. Moreover, dissimilarity of blue and red light effects on microalgae

growth can be described at the molecular level (Abiusi et al. 2014). The in vivo

absorption spectra of some green algae overestimate the ability of cells to exploit blue

light, as an important part of absorption in this spectrum region is due to the presence of

non-photosynthetic pigments, i.e. carotenoids (Kirk 2010; Abiusi et al. 2014).

Therefore, the effects of different light spectra on the growth of microalgae apparently

are a complex process, which might not entirely relate to the photosynthesis

mechanisms, but can be also stimulated by changes in photoreceptors and other cellular

metabolic processes (e.g. photomorphogenetic processes, cell division, and activation of

enzymes) which are also spectrally dependent (Senger 1987; Oldenhof et al. 2006;

Hegemann 2008; Abiusi et al. 2014).

3.2.2 Biomass and proximate composition

The outcomes of this study revealed that Amphora sp., and P. carterae achieved the

highest biomass yield under blue light, when the species growth was maintained semi-

continuously (stable growth). In contrast, the biomass yield of Nannochloropsis sp. and

B. braunii was similar under white, blue, and red light. None of the light spectrum

significantly increased the lipid yield of 4 species. Cells grown under blue light

presented the highest lipid content for Nannochloropsis sp. and B. braunii, whereas

Amphora sp. and P. carterae reached the highest lipid content under red light (Table

13). Monochromatic spectrum of blue and red light have been used to enhance the

biomass, extracellular polysaccharide, and proximate (i.e. lipid, carbohydrate, protein,

and pigments) production of microalgae (Wallen and Geen 1971b; Sánchez Saavedra

129

and Voltolina 1994; Mercado et al. 2004; You and Barnett 2004; Das et al. 2011;

Marchetti et al. 2013).

130

Table 13. Comparison of biomass and lipid yield/content of microalgae grown using monochromatic, or a mixed of blue (B), red (R), white

(W), green (G), and far red (FR) from the same classes and pigments in this study and previous findings.

Class, Phylum Major

pigments Species Biomass Lipid Light colours Irradiance (photons/energy) Reference*

Eustigmatophyceae,

Heterokontophyta

Chl a,

violaxanthin Nannochloropsis sp.

Wa = B

a = R

a(i) W

a = B

a = R

a(i)

W, B, R (fluorescent

tubes and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study

B > W > R(i)

B > W > R(i)

W, B, G, R (LEDs) Unequal energy 1

Trebouxiophyceae,

Chlorophyta

Chl a, b,

β-carotene

B. braunii (race A) Wa = B

a = R

a(i) W = B > R

(iii)

W, B, R (fluorescent

tubes and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study

B. braunii (race B) - B = R = G(iii)

B, G, R (LEDs) Equal photon flux density

(60 µmol photons.m-2

.s-1

) 2

Chlorella vulgaris W > BR =

BRFR(i)

-

W (fluorescent

lamps), BR, BRFR

(LEDs)

Equal photon flux density

(400 µmol photons.m-2

.s-1

) 3

Bacillariophyceae,

Heterokontophyta

Chl a, c,

fucoxanthin

Amphora sp. Ba > W

ab > R

b(i) W = B > R

(iii)

W, B, R (fluorescent

tubes and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study

Chaetoceros sp.

- BGW > W > BG(iii)

W, BGW, BG

(fluorescent lamps)

Equal photon flux density

(100 µmol photons.m-2

.s-1

) 4

W > BW > B(i)

BW > W > B(iii)

W, BW, B

(fluorescent lamps)

Equal photon flux density

(199 µmol photons.m-2

.s-1

) 5

Prymnesiophyceae,

Haptophyta

Chl a, c,

fucoxanthin

P. carterae Bb > W

a = R

a(i) R

b > W

a = B

a(ii)

W, B, R (fluorescent

tubes and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study

Isochrysis galbana W > B(i)

- W, B (fluorescent

tubes and filters)

Equal photon flux density

(60 µmol photons.m-2

.s-1

) 6

Isochrysis sp. - B = Wb(ii)

W, B

(fluorescent tubes)

Equal photon flux density

(100 µmol photons.m-2

.s-1

) 7

131

*1) Das et al. (2011), 2) Baba et al. (2012), 3) Kula et al. (2014), 4) Sanchez-Saavedra and Voltolina (1996), 5) Sanchez-Saavedra and Voltolina (1994), 6) Gorai et al. (2014), 7) Marchetti et al. (2013), i) based on yield (g.L-1), ii) based on content (g.cell-1), iii)

based on % of carbon/dry weight.

Furthermore, blue light particularly enhances algal metabolism of protein formation

relatively to white or red that was previously reported, e.g. in Bacillariophyceae,

Heterokontophyta: a) Cyclotella nana (Wallen and Geen 1971a), b) Chaetoceros sp.

(Sánchez Saavedra and Voltolina 1994, 1996), c) Skeletonema costatum, and d)

Thalassiosira pseudonana (Sánchez Saavedra and Voltolina 1994); Prymnesiophyceae,

Haptophyta: Isochrysis sp. (Marchetti et al. 2013); and Chlorophyta: a) Dunaliella

tertiolecta (Wallen and Geen 1971a) and b) Chlorella pyrenoidosa (Pickett 1971).

These phenomena were also observed in this study, i.e. the protein yield (g.L-1) of

Amphora sp. and the protein content (ng.cell-1) of Nannochloropsis sp. which obtained

the highest under blue light (Table 14). As a result of protein enhancement, previous

researches also reported a reduction of carbohydrate contents in algae grown under blue

light, e.g. in Bacillariophyceae, Heterokontophyta: a) Skeletonema costatum and b)

Thalassiosira pseudonana (Sánchez Saavedra and Voltolina 1994); Prymnesiophyceae,

Haptophyta: Isochrysis sp. (Marchetti et al. 2013); and Chlorophyta: a) Chlorella

(Pirson and Kowallik 1964), b) Chlorella pyrenoidosa (Pickett 1971), c) Scenedesmus

(Brinkmann and Senger 1978), and d) Dunaliella tertiolecta (Rivkin 1989), that are in

agreement with results obtained of low carbohydrate yields (g.L-1) of Nannochloropsis

sp. and B. braunii, and low carbohydrate content (ng.cell-1) of Amphora sp. and P.

carterae.

In contrast, the exposure of red light might result a decrease of protein yield and

content. Pickett (1971) reported that starvation of Chlorella pyrenoidosa in red flashing

light led to a decrease of protein content. This finding was compatible with the protein

yield (g.L-1) of Amphora sp., which was observed lower under red light than blue light.

132

However, none of the light spectrum significantly increased the protein yield of B.

braunii, Amphora sp., and P. carterae. A variation was found at the cellular level, in

which Nannochloropsis sp. achieved lower protein content (ng.cell-1) in white light

compared to blue and red, while Amphora sp. and P. carterae obtained lower protein

content in blue spectrum compared to red.

Therefore, there was an increase of carbohydrate content in Nannochloropsis sp.,

Amphora sp., and P. carterae when grown using red light. These are in agreement with

previous researches reported for several algae, such as Chlorophyta: a) Chlorella

(Ogasawara and Miyachi 1970; Miyachi et al. 1977; Miyachi et al. 1978) and b)

Dunaliella tertiolecta (Rivkin 1989), and Bacillariophyceae, Heterokontophyta:

Thalassiosira rotula (Rivkin 1989). Ogasawara and Miyachi (1970) found that blue

light enhances 14CO2 incorporation into aspartate, glutamate, malate, and fumarate,

while red light induces its incorporation into sucrose and starch in Chlorella and other

Chlorophyta. In Chlorella vulgaris 11h (wild-type cells), studies on its photosynthetic

products revealed that the rates of 14CO2 fixation into sucrose and starch were greater

under red light than under blue light, whereas blue light specifically enhanced 14CO2

incorporation into alanine, other amino and carboxylic acids, and lipid fraction (Miyachi

et al. 1977; Miyachi et al. 1978).

133

Table 14. Comparison of carbohydrate and protein content of microalgae grown using monochromatic, or a mixed of blue (B), red (R), white

(W), or green (G) from the same classes and pigments in this study and previous findings.

Class, Phylum Major

pigments Species Carbohydrate Protein Light colours Irradiance (photons/energy) Reference*

Eustigmatophyceae,

Heterokontophyta

Chl a,

violaxanthin Nannochloropsis sp.

Rb > B

ba > W

a(i) B

b > R

ba > W

a(i)

W, B, R

(fluorescent tubes

and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study

R = W > B(ii)

W = B = R(ii)

W, B, R (halogen

lamps and filters) Unequal energy 1

Trebouxiophyceae,

Chlorophyta

Chl a, b,

β-carotene

B. braunii (race A) R > W > B(ii)

R > B > W(ii)

W, B, R

(fluorescent tubes

and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study

B. braunii (race B) B = R = G(ii)

B = R = G(ii)

B, G, R (LEDs) Equal photon flux density

(60 µmol photons.m-2

.s-1

) 2

Bacillariophyceae,

Heterokontophyta

Chl a, c,

fucoxanthin

Amphora sp. R = B > W(ii)

B > W > R(ii)

W, B, R

(fluorescent tubes

and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study

Chaetoceros sp.

BW > W >

BGW(ii)

BGW > BG >

W(ii)

W, BGW, BG

(fluorescent

lamps)

Equal photon flux density

(100 µmol photons.m-2

.s-1

) 3

BW > B > W(ii)

B > W > BW(ii)

W, BW, B

(fluorescent

lamps)

Equal photon flux density

(199 µmol photons.m-2

.s-1

) 4

Prymnesiophyceae,

Haptophyta

Chl a, c,

fucoxanthin

P. carterae Rb > W

a = B

a(i) R

b > W

ba > B

a(i)

W, B, R

(fluorescent tubes

and filters)

Equal energy (2.23 W.m-2

),

White (33.75 µmol photons.m-2

.s-1

),

Blue (34.13 µmol photons.m-2

.s-1

),

Red (47.87 µmol photons.m-2

.s-1

)

This study

Isochrysis sp. W > B(i)

B > W(i)

W, B

(fluorescent tubes)

Equal photon flux density

(100 µmol photons.m-2

.s-1

) 5

* 1) Vadiveloo et al. (2015), 2) Baba et al. (2012), 3) Sanchez-Saavedra and Voltolina (1996), 4) Sanchez-Saavedra and Voltolina (1994), 5) Marchetti et al. (2013), i) based on content (g.cell

-1), ii) based on % of carbon/dry weight.

134

The enhancement of soluble proteins formation, carbohydrates decrease, and the rates of

respiration reach their maximal values during the early stage of chloroplast development

in microalgae (Senger and Bishop 1972). All of these processes followed by the

synthesis and incorporation of chlorophyll and protein into the membrane, which are

blue light-dependent (Senger and Bishop 1972). An action spectrum for the stimulation

of protein synthesis by blue light has been obtained by growing Chlorella on glucose in

monochromatic light (Soeder and Stengel 1974). One broad maximum between 450 and

490 nm was found (Kowallik 1965), and this is fairly in agreement with the action

spectra for the synthesis of nucleic acids and the induction of cell division in the same

strain (Senger and Bishop 1966; Soeder and Stengel 1974).

Several studies have reported on the visible spectrum, especially blue and red light,

effects on chloroplast development and greening processes of three genera of

Chlorophyta: Chlorella, Scenedesmus, and Chlamydomonas (Gressel 1980; Hase 1980).

Both blue light and white light of intensity and distribution equivalent to light

penetrating in the ocean were important to manage normal plastid development in

marine algae (Vesk and Jeffrey 1977).

In addition, Brinkmann and Senger (1980) studied the blue light regulation of

chloroplast development in Scenedesmus mutant. They found that the action spectrum

for total carbohydrate degradation shows peaks at 393, 450, and 461 nm as well as the

wavelength dependence for respiration enhancement shows identical peaks at 393, 450,

and 461 nm, in which both no effect was observed using green or red light. From the

wavelength dependence of the reactions it can be concluded, in accordance with other

findings, that either carotenoids or flavoproteins are the most probable primary

photoreceptors (Senger and Bishop 1972; Brinkmann and Senger 1978, 1980).

135

The regulatory effect of blue light on photosynthetic metabolism can be defined in 2

different ways of actions, such as the following: 1. Direct action, i.e. photoregulation of

enzymes taking part in carbon metabolism both in the chloroplasts and entire cell; 2.

Indirect action, i.e. photoregulation of photosynthetic and oxidative electron transport

and energy accumulating reactions, and photoregulation of the conformal state and

permeability membranes of the cell (Voskresenskaya 1972). In the case of direct action

of blue light, the blue illumination has to be absorbed by the enzyme molecule itself or

its group, whereas indirect action of blue light means that this spectrum does not act on

the enzyme molecule itself, but affects its activity, e.g. via changes in the level of

effectors or substrates (Ruyters 1984) (see chapter 1.5.1. Effects of light quality, Table

6, Figure 9 and Figure 10 for more details on photoregulation of enzymes).

This study also identified the effect of white, blue, and red light on the chlorophyll

composition of Nannochloropsis sp., B. braunii, Amphora sp., and P. carterae. When

the species growth was maintained semi-continuously (stable growth), the highest

chlorophyll a content was obtained under white and blue light in Nannochloropsis sp.,

under white, blue, and red light in B. braunii and Amphora sp., and under blue and red

light in P. carterae. The similar chlorophyll b content was achieved under white, blue,

and red light in B. braunii, whereas the chlorophyll c content was determined only

under blue light in Amphora sp. and P. carterae. A significant effect of different light

spectra to increase total chlorophyll a content was detected in Nannochloropsis sp. (blue

and white light) and P. carterae (red and blue light).

Of note, this study used the equation of Jeffrey and Humphrey (1975), one of the most

accepted chlorophyll a and b formulae for 90% acetone. Ritchie (2006) developed a set

of equations using 90% acetone, methanol, and ethanol solvents to examine algorithms

for determining chlorophyll a, accessory chlorophylls b, c2, (c1+c2), and the unique

136

cyanobacterium, Acaryochloris marina, which uses chlorophyll d as its primary

photosynthetic pigment and also has chlorophyll a. The chlorophyll estimations were

not significantly different to those calculated from the Jeffrey and Humphrey formulae

for the acetone solvent used in this study (Ritchie 2006). In addition, the chlorophyll b

equations using acetone and ethanol solvents are more reliable than the methanol

formulae because the methanol algorithms for chlorophyll b are severely affected by

any phaeophytin-a present (Ritchie 2008). The trichroic chlorophyll c equations for

acetone and ethanol solvents, e.g. Jeffrey and Humphrey (1975), are also simpler and

more reliable for algae containing chlorophyll (c1+c2), e.g. Amphora sp. and P.

carterae in this study, than for algae with only chlorophyll c2, but should only be used

where a chlorophyll extract has no significant phaeophytin-a or chlorophyll d content

(Ritchie 2008).

However, chlorophyll c compounds (c1, c2, c3 and chlorophyll c-like pigments, e.g.

MgDVP) are minor pigments and renowned to be difficult to assay in chlorophyll

extracts because their absorption peaks in the red part of the spectrum are low compared

to other chlorophylls (Ritchie 2006). Evidence for their existence in mixed chlorophyll

extracts tends to be drowned out by chlorophyll a absorbance (Ritchie 2006). Jeffrey

and Humphrey (1975) also indicated in their original paper that their methods for

chlorophyll c2 and (c1+c2) had increasing error as the abundance of the chlorophyll c

compounds decreased with reference to chlorophyll a so that the chlorophyll c

compounds became harder to detect (Ritchie 2008). This issue is likely in agreement

with the outcomes of chlorophyll c results in this study, in which very small amounts of

chlorophyll c (c1+c2) were determined in the chlorophyll c containing microalgae,

Amphora sp. and P. carterae. Furthermore, Humphrey and Jeffrey (1997) tested their

chlorophyll equations, published in Jeffrey and Humphrey (1975), on a wide range of

mixtures of pure chlorophylls. They confirmed that the chlorophyll a and b equations

137

were highly accurate for both chlorophyll a and b, but the chlorophyll a and c2, and the

chlorophyll a and (c1 + c2) overestimated the chlorophyll c compounds when their

abundance was low (Ritchie 2008). Therefore, chlorophyll c/a ratios calculated from

these equations need to be interpreted with caution (Ritchie 2008).

Few marine plants and algae appear to be able to adjust their pigment composition in

response to changes in light quality (Dring 1990). A previous finding reported that the

cellular chlorophyll a appears to be higher in a diatom Thalassiosira rotula when grown

in white light instead of blue light (Rivkin 1989). The opposite was occurred for other

diatoms, i.e. Chaetoceros sp., Nitzschia thermalis, Nitzschia laevis, and Navicula

incerta (Sánchez Saavedra and Voltolina 1994; Mercado et al. 2004); while other

diatoms, i.e. Thalassiosira gravida and Phaeodactylum tricornutum seem to reveal no

such differences (Holdsworth 1985). Pickett (1971) reported that the exposure of

monochromatic red and blue light had no significant effect on chlorophyll content of a

Chlorophyta containing chlorophyll a and b, Chlorella pyrenoidosa, that is in agreement

with results obtained in B. braunii cultures. Vadiveloo et al. (2015) found that the

highest chlorophyll a of Nannochloropsis sp. was achieved when blue light was the

main source of energy compared to red. This finding was compatible with the result of

chlorophyll a of Nannochloropsis sp. in this study, which was obtained the highest

content under blue and white light.

Microalgae may respond to changes in the spectral quality of the light field either by

altering the overall pigment content of the cells, or by altering the balance between

different photosynthetic pigments (Dring 1990; Senge and Senger 1991).

Photoacclimation of the photosynthetic apparatus due to variation in light spectra has

been seen to affect the quantity and proportion of chlorophyll a and other major light

harvesting accessory pigments (Vesk and Jeffrey 1977; Aidar et al. 1994). Short visible

138

spectrum radiation is essential to produce an optimal photosynthetic apparatus in

microalgae (Kowallik and Schürmann 1984). Kowallik and Schürmann (1984) reported

on blue-dependent changes in the ratio of major light-harvesting chlorophyll protein

(LHCP) of Chlorella vulgaris (chl-a/chl-b), which might indicate alterations in the ratio

of the two photosystems. This is in agreement with results obtained for Amphora sp. and

P. carterae chlorophyll ratios (chl-a/chl-c), in which the accessory pigment (chl-c)

achieved the highest amount under blue light illumination. However, the results of

chlorophyll a and b of B. braunii presented a different pattern that both main LHCP a

and b obtained similar content under all light spectra. As discussed in the previous

section, the influence of blue light was also possibly because of the complementary

chromatic adaptation of Nannochloropsis sp. in blue light acclimated culture.

Complementary chromatic adaptation is a response where the relative content of major

light harvesting pigments which have similar absorption spectra patterns to that of the

incident light is regulated (Mouget et al. 2004; Vadiveloo et al. 2015). Chlorophylls

formation under monochromatic light appears to be blue light-dependent, but after pre-

illumination or addition of glucose, then green and red light can also become effective

(Brinkmann and Senger 1980).

The first specific intermediate involved in tetrapyrrole biosynthesis, i.e. chlorophyll, is

known as δ-aminolevulinic acid (ALA). Therefore, the mechanism of ALA formation is

one of the key processes in the metabolism of photosynthetic organisms (Klein and

Senger 1978). Contrary to some blue light effects requiring only brief illumination

periods and low energy input for saturation as those reported by Brinkmann and Senger

(1980), the light-dependent formation of ALA requires a continuous input of light and

high intensity for saturation, and is dependent not only on blue light, but also on green

and red light (Senger et al. 1980). Similar to the photosynthetic carbon metabolism,

Calvin cycle, and carbohydrate degradation, the metabolic pathways of chlorophyll

139

biosynthesis in microalgae are also driven by photoregulation of blue light-enhanced

enzymes (Figure 32).

Figure 32. The metabolic pathways of chlorophyll biosynthesis and its blue light-

enhanced enzymes (in full frames) (adapted from Ruyters 1984).

The presence of blue light influences 4 enzymes of chlorophyll biosynthesis pathways

in algae, which are the 4,5-dioxovalerate (DOVA)-dehydrogenase, DOVA-

transaminase, δ-aminolevulinic acid (ALA)-synthetase, and ALA-dehydratase.

Furthermore, the in vivo absorbance spectrum of microalgae might also be influenced

by the size and shape of the chloroplasts, cells, and colonies (e.g. aggregates and

clumps). Therefore, it is possible that two species, with the same array of protein

pigments and absorbance spectra at the thylakoid level, may have different in vivo

absorbance spectrum in the cultures of cells or colonies at the same pigment

concentration (Moheimani and Parlevliet 2013). A spherical shape appears to be the

140

least efficient for light absorption, while elongated cells exhibit a smaller package effect

than spherical cells of the same volume and pigment content, and long thin cylinders are

almost as efficient in harvesting light as a much greater number of smaller spherical

particles of the same diameter (Dring 1990).

3.2.3 Productivity

In this study, Amphora sp. under blue light was considered as the best species with

respect to the productivity of biomass, lipid, carbohydrate, and protein. Amphora sp.

and P. carterae achieved the highest biomass productivity under white and blue light,

when the species growth was maintained semi-continuously (stable growth). The

biomass productivity of Nannochloropsis sp. and B. braunii was similar under white,

blue, and red light. None of the light spectrum significantly increased the lipid

productivity of 4 species (Wa = Ba = Ra). Furthermore, similar carbohydrate

productivity of Nannochloropsis sp., B. braunii, and Amphora sp. was also obtained

under all light spectra, while for P. carterae it was achieved under white and blue light.

Cells grown under white and blue light presented the highest protein productivity for

Nannochloropsis sp., whereas B. braunii, Amphora sp., and P. carterae reached similar

protein productivity under white, blue, and red light.

Most of previous researches on the use of different PAR spectra in various microalgae

culture systems presented neither the areal nor volumetric productivity of microalgal

biomass, lipid, carbohydrate and protein. Their results were mostly calculated as a)

volumetric biomass, lipid, carbohydrate, protein yield (g.L-1) (Pickett 1971; Das et al.

2011), b) cellular content (g.cell-1) (Aidar et al. 1994; Marchetti et al. 2013), or c) % of

total carbon or dry weight (Rivkin 1989; Sánchez Saavedra and Voltolina 1994, 1996,

2006). Some authors often misinterpret the yield as productivity, e.g. Das et al. (2011)

and Abiusi et al. (2014). A previous finding on biomass productivity of a different

141

species, i.e. Chlorella vulgaris, which is from the same class of B. braunii

(Trebouxiophyceae) used in this study, reported the highest biomass productivity when

grown using White > Blue > Red (Blair et al. 2014). In contrast, the biomass

productivity of B. braunii obtained in this study was similar (Wa = Ba = Ra). On the

other hand, a recent study by Vadiveloo et al. (2015) showed a similar biomass

productivity of Nannochloropsis sp. when grown using white, blue, and red light. This

is in agreement with the result of Nannochloropsis sp. biomass productivity in this study

(Wa = Ba = Ra). However, Vadiveloo et al. (2015) also found that for the other

parameter, i.e. growth rate, the highest growth rate of Nannochloropsis sp. was achieved

under white light compared to blue and red, while in this study the highest growth rate

of Nannochloropsis sp. was under blue light (Bb > Wa = Ra). Therefore, various patterns

of biomass productivity might also indicate a species-specific dependence on light

quality effects in microalgae.

Furthermore, for the highest productivity of target products (e.g. biomass or proximate),

microalgae cultures must achieve not only a high yield of the product, but also the

sufficient high growth rate. This requirement corresponds to results found in this study.

For instance, the carbohydrate yield (g.L-1) and content (ng.cell-1) of Nannochloropsis

sp., B. braunii, Amphora sp., and P. carterae, in general, achieved the highest

particularly in white, blue, or red illumination, however it differed in their productivity

(mg.L-1.day-1) depends on the specific growth rate of each algae under specific light

spectra. None of the light spectrum significantly increased the carbohydrate productivity

of Nannochloropsis sp., B. braunii and Amphora sp., while for P. carterae the highest

carbohydrate productivity was achieved under blue light. Various results in

carbohydrate productivity were also associated to the one-way repeated measures

ANOVA showed that there was no significant effect of the light spectra used on the

carbohydrate productivity of these species, except for the P. carterae.

142

The unconformity of the quantity (yield) and productivity was also observed in the lipid

and protein productivity of 4 species, which was obtained similar values under all light

spectra, except for protein productivity of Nannochloropsis sp. (Bab = Wa > Rb). The

protein yield of Nannochloropsis sp. was similar under different spectra (Wa = Ba = Ra).

However, the influence of growth rate of Nannochloropsis sp., which was higher under

blue light compared to white and red, although its protein yields were similar, resulted

the highest protein productivity under white and blue light. Therefore, although

particular light spectra influence the yield of biomass and proximate composition in

algae, the differences of productivity is mostly affected by their specific growth rate.

4 CONCLUSION

The important feature of this study was that the same light energy (W.m-2) was provided

to the microalgae in semi-continuous cultures. All cultures had been illuminated and

acclimated to the specific spectra (white, blue, and red) for at least 30 days, so that the

light quality was considered as the single factor affecting the analyzed parameters of

algae cultures. This study found that illumination by different light spectra within the

PAR, i.e. white, blue, and red supplied at equal energy, affected the key parameters (i.e.

photosynthesis, respiration, growth, biomass, lipid, carbohydrate, protein, chlorophyll,

and productivity) of tested microalgae from 4 different species, classes, and

photosynthetic pigment profiles. Interestingly, full PAR spectrum (white light) was not

always be the suitable and optimal spectral range for particular parameters, e.g. for

photosynthesis and respiration rate in Nannochloropsis sp., B. braunii, and Amphora

sp., and for cellular lipid and carbohydrate in Nannochloropsis sp., Amphora sp., and P.

carterae (Table 10).

143

The outcomes of this study clearly indicated that microalgae from different classes

behave differently when grown using narrower PAR wavelengths, i.e. blue and red

light, in a semi-continuous culture. This could be mainly due to their pigments and

ability to effectively absorb different parts of PAR. However, in general, growth and

productivity of most species were increased when grown using blue or white light. The

outcomes of this study clearly found that proximate composition (i.e. lipid,

carbohydrate, protein, and chlorophyll) of 4 tested algae was also affected differently

when grown using narrower PAR spectrum compared to the white light. This study

demonstrated that the growth of microalgae was not only related to the photosynthesis

mechanisms, but also influenced by other cellular processes which are also spectrally

dependent. In addition, the low levels of oxygen concentration significantly increased

the photosynthetic rates of 4 tested species.

The results of this study indicated the phenomena of blue light effects in the opposite

way toward red light to increase lipid and protein synthesis, and to reduce carbohydrate,

e.g. findings in Nannochloropsis sp. and B. braunii. Blue light exposure induced lipid

and protein yield or content, but it decreased the carbohydrate yield or content at the

same time. On the other hand, illumination of red light reduced lipid and protein yield

or content, but it increased the carbohydrate yield or content in Nannochloropsis sp. and

B. braunii. In contrast, the chlorophyll c containing algae (i.e. Amphora sp., and P.

carterae) all have heavier cells and higher cellular content of lipid, carbohydrate, and

protein under red light. These findings correspond to reported researches mostly in

Chlorophyta and diatoms. However, all the effects, which took place in the presence of

pure red light, might not be also due to direct effects from red light, but actually because

of the absence of blue light effects.

144

This study revealed that Amphora sp. MUR 258 grown under blue light was considered

as the promising species among 4 tested algae with respect to the productivity of

biomass, lipid, carbohydrate, and protein. Furthermore, the particular light spectra that

significantly increased parameters for each species were found. Notable outcomes

especially on the cell physiology, biomass, and proximate composition were that

(mostly) blue light significantly increased cell physiology (i.e. photosynthesis,

respiration, and growth) and red light significantly increased most of the proximate

composition (i.e. lipid, carbohydrate, protein, and chlorophyll a) for Nannochloropsis

sp., while it was (mostly) red light for Amphora sp., and (mainly) red and sometimes

blue light for P. carterae. Blue light significantly increased cellular lipid,

photosynthesis, and respiration in B. braunii, and not much else.

The exposure of filtered light into narrower PAR wavelengths, i.e. blue and red, can

lead to the manipulation of microalgal growth, biomass, proximate content, and

productivity both for enhancement and inhibition. The reactions of each tested species

were different and species-dependent. For instance, the identical outcomes in particular

parameters of tested species, compared to the same species used in previous studies,

were observed (e.g. specific growth rate in Nannochloropsis sp. and photosynthetic rate

in B. braunii). In general, these differences are mostly based on various pigment

profiles, absorption and action spectra, photoregulation of enzymes, photoacclimation,

and chromatic adaptive responses of tested algae.

Therefore, this study clearly indicated that the utilization of the most effective narrower

PAR spectrum is essential in the efficient lighting strategy, e.g. the use of photovoltaic

(PV)/filters, for production systems of the 4 microalgae species, and potentially

improves the light energy conversion. The overall available energy of the solar

145

spectrum can be used effectively to grow the algae for specific products, and other

potential purposes, such as electricity generation.

Future direction

To further improve the application of filtered PAR spectrum in optimizing the

microalgal production systems, it would be interesting to study:

1) The morphological and physiological changes of 4 selected microalgal cells during

the illumination of certain filtered spectrum of PAR, such as a microscopic

morphology observation and their photosynthetic characteristics of chlorophyll

fluorescence using Pulse-amplitude Modulated (PAM) fluorometry.

2) The lighting operation of PAR (blue and red) filtering system in long term outdoor

cultivation systems, e.g. raceway ponds and photobioreactors, to evaluate the actual

algal productivity and cultures reliability of 4 species based on its optimum

transmitted spectra and microalgal characteristics.

3) The calculation of energy efficiency of further incorporation of light filtering

systems and microalgal production systems, i.e. amount of PAR energy that can be

transmitted and utilized by microalgae for photosynthesis, and the rest amount of

solar energy that is not used by microalgae, which is potential for other purposes.

4) The effect of low and high oxygen levels and its important role on photosynthesis

and productivity of tested microalgae that has been initially observed in this study.

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5 APPENDICES

Table 15. The overview of the results for Nannochloropsis sp. cultures in batch (B) and semi-continuous (S) under 3 different light spectra*.

Light B/S Max. cell density

(104 cells.mL-1)

Specific growth rate

(day-1)

Biomass yield

(g.L-1)

Biomass productivity

(mg.L-1.day-1) % Lipid (of DW)

% Carbohydrate

(of DW)

White B 40 (2.122, 0.005) 0.17 (N/A) 0.05 (0.010, 0.500) 8.72 (1.677, 0.500) - -

S 36 (1.891, <0.001) 0.12 (0.038, 0.008) 0.08 (0.004, 0.802) 9.14 (3.140, 0.220) 23.27 (0.807, N/A) 11.48 (1.059, N/A)

Blue B 21 (2.163, 0.005) 0.10 (N/A) 0.05 (0.007, 0.500) 5.30 (0.747, 0.500) - -

S 29 (0.948, <0.001) 0.17 (0.029, 0.008) 0.07 (0.003, 0.802) 12.20 (2.160, 0.220) 23.88 (1.557, N/A) 10.29 (1.284, N/A)

Red B 21 (0.683, 0.005) 0.12 (N/A) 0.08 (0.003, 0.500) 8.93 (0.385, 0.500) - -

S 24 (1.886, <0.001) 0.12 (0.023, 0.008) 0.08 (0.007, 0.802) 9.09 (1.630, 0.220) 19.43 (3.567, N/A) 15.98 (2.995, N/A)

Light B/S % Protein (of DW) % Ash (of DW) Lipid content

(ng.cell-1) Carbohydrate content

(ng.cell-1) Protein content

(ng.cell-1) Chlorophyll a content

(pg.cell-1)

White S 5.93 (1.192, N/A) 59.45 (2.111, N/A) 0.13 (0.003, 0.045) 0.06 (0.006, 0.042) 0.03 (0.006, 0.005) 0.10 (0.004, 0.014)

Blue S 7.82 (1.886, N/A) 62.28 (1.091, N/A) 0.20 (0.007, 0.045) 0.08 (0.008, 0.042) 0.06 (0.017, 0.005) 0.13 (0.006, 0.014)

Red S 4.97 (0.851, N/A) 58.20 (6.888, N/A) 0.16 (0.025, 0.045) 0.13 (0.012, 0.042) 0.04 (0.011, 0.005) 0.07 (0.006, 0.014)

Light B/S Chlorophyll b content

(pg.cell-1) Chlorophyll c content

(pg.cell-1) Cell weight (ng.cell-1)

Lipid productivity (mg.L-1.day-1)

Carbohydrate productivity

(mg.L-1.day-1)

Protein productivity (mg.L-1.day-1)

White S - - 2.20 (0.100, 0.019) 5.16 (1.734, 0.069) 2.54 (0.951, 0.313) 1.39 (0.458, 0.014)

Blue S - - 3.11 (0.265, 0.019) 7.87 (1.617, 0.069) 3.26 (0.613, 0.313) 2.72 (0.796, 0.014)

Red S - - 3.41 (0.274, 0.019) 4.23 (0.841, 0.069) 3.49 (0.806, 0.313) 1.25 (0.389, 0.014)

Light B/S

Photosynthetic rate at

low oxygen (µmol O2.

(mg chl a)-1.h-1)

Photosynthetic rate at

high oxygen (µmol O2.

(mg chl a)-1.h-1)

The 1st dark respiration rate

(µmol O2.(mg chl a)-1.h-1)

The 2nd dark respiration rate

(µmol O2.(mg chl a)-1.h-1)

White S 1172.92 (140.72, 0.028) 545.72 (103.75, 0.028) -266.89 (65.13, 0.006) -84.28 (23.50, 0.014)

Blue S 13421.72 (819.95, 0.028) 4693.48 (881.38, 0.028) -1399.81 (211.75, 0.006) -1059.47 (240.79, 0.014)

Red S 7875.28 (1022.10, 0.028) 2867.90 (368.42, 0.028) -133.34 (31.09, 0.006) -135.34 (31.28, 0.014)

147

Table 16. The overview of the results for Botryococcus braunii cultures in batch (B) and semi-continuous (S) under 3 different light spectra*.

Light B/S Max. cell density

(104 cells.mL-1)

Specific growth rate

(day-1)

Biomass yield

(g.L-1)

Biomass productivity

(mg.L-1.day-1) % Lipid (of DW)

% Carbohydrate

(of DW)

White B 9 (0.765, 0.420) 0.07 (N/A) 0.12 (0.011, 0.167) 8.27 (0.739, 0.167) - -

S 7 (0.353, 0.500) 0.07 (0.026, 0.789) 0.11 (0.022, 0.337) 6.36 (2.250, 0.753) 44.62 (3.179, N/A) 15.05 (0.548, N/A)

Blue B 10 (0.898, 0.420) 0.05 (N/A) 0.14 (0.009, 0.167) 7.17 (0.469, 0.167) - -

S 7 (0.588, 0.500) 0.05 (0.024, 0.789) 0.12 (0.022, 0.337) 6.18 (3.140, 0.753) 44. 80 (1.768, N/A) 11.86 (0.955, N/A)

Red B 8 (0.267, 0.420) 0.04 (N/A) 0.11 (0.010, 0.167) 5.08 (0.432, 0.167) - -

S 7 (0.765, 0.500) 0.07 (0.009, 0.789) 0.12 (0.017, 0.337) 7.74 (0.465, 0.753) 33.47 (1.327, N/A) 17.75 (1.560, N/A)

Light B/S % Protein (of DW) % Ash (of DW) Lipid content

(ng.cell-1)

Carbohydrate content

(ng.cell-1)

Protein content

(ng.cell-1)

Chlorophyll a content

(pg.cell-1)

White S 10.69 (1.099, N/A) 38.58 (3.515, N/A) 1.10 (0.052, 0.028) 0.38 (0.058, 0.160) 0.30 (0.049, 0.312) 2.09 (0.030, 0.412)

Blue S 15.58 (4.534, N/A) 35.06 (6.043, N/A) 1.33 (0.052, 0.028) 0.35 (0.021, 0.160) 0.52 (0.188, 0.312) 2.48 (0.514, 0.412)

Red S 17.94 (7.248, N/A) 30.08 (7.495, N/A) 0.85 (0.114, 0.028) 0.48 (0.021, 0.160) 0.46 (0.189, 0.312) 2.83 (0.361, 0.412)

Light B/S Chlorophyll b content

(pg.cell-1)

Chlorophyll c

content (pg.cell-1)

Cell weight

(ng.cell-1)

Lipid productivity

(mg.L-1.day-1)

Carbohydrate productivity

(mg.L-1.day-1)

Protein productivity

(mg.L-1.day-1)

White S 0.34 (0.052, N/A) - 16.62 (3.097, 0.277) 4.61 (1.690, 0.819) 1.54 (0.570, 0.134) 1.17 (0.401, 0.654)

Blue S 0.21 (0.032, N/A) - 19.80 (2.916, 0.277) 3.99 (1.870, 0.819) 1.06 (0.481, 0.134) 1.21 (0.406, 0.654)

Red S 0.45 (0.047, N/A) - 17.98 (2.057, 0.277) 3.71 (0.566, 0.819) 2.13 (0.234, 0.134) 1.91 (0.693, 0.654)

Light B/S

Photosynthetic rate at low

oxygen (µmol O2. (mg chl a)-1.h-1)

Photosynthetic rate at

high oxygen (µmol O2. (mg chl a)-1.h-1)

The 1st dark respiration rate (µmol O2.(mg chl a)-1.h-1)

The 2nd dark respiration rate (µmol O2.(mg chl a)-1.h-1)

White S 6089.06 (460.61, <0.001) 1749.24 (608.97, 0.037) -57.52 (8.52, <0.001) -73.31 (7.895, 0.054)

Blue S 39955.75 (754.75, <0.001) 10319.13 (3535.37, 0.037) -144.11 (11.42, <0.001) -123.53 (22.452, 0.054)

Red S 7019.21 (429.05, <0.001) 2259.29 (699.55, 0.037) -34.70 (4.82, <0.001) -38.55 (4.690, 0.054)

148

Table 17. The overview of the results for Amphora sp. cultures in batch (B) and semi-continuous (S) under 3 different light spectra*.

Light B/S Max. cell density

(104 cells.mL-1)

Specific growth rate

(day-1)

Biomass yield

(g.L-1)

Biomass productivity

(mg.L-1.day-1) % Lipid (of DW)

% Carbohydrate

(of DW)

White B 33 (1.402, <0.001) 0.14 (N/A) 0.10 (0.007, 0.167) 13.90 (1.050, 0.167) - -

S 30 (0.694, <0.001) 0.12 (0.026, 0.585) 0.14 (0.023, 0.043) 17.80 (5.260, 0.021) 19.36 (1.155, N/A) 7.09 (0.699, N/A)

Blue B 37 (0.784, <0.001) 0.14 (N/A) 0.08 (0.007, 0.167) 11.10 (0.900, 0.167) - -

S 37 (1.271, <0.001) 0.13 (0.029, 0.585) 0.16 (0.032, 0.043) 21.20 (5.430, 0.021) 20.93 (1.399, N/A) 9.43 (1.913, N/A)

Red B 11 (0.674, <0.001) 0.17 (N/A) 0.08 (0.005, 0.167) 12.45 (0.850, 0.167) - -

S 11 (0.655, <0.001) 0.12 (0.025, 0.585) 0.12 (0.017, 0.043) 14.20 (4.090, 0.021) 18.67 (0.960, N/A) 9.23 (1.333, N/A)

Light B/S % Protein (of DW) % Ash (of DW) Lipid content

(ng.cell-1)

Carbohydrate content

(ng.cell-1)

Protein content

(ng.cell-1)

Chlorophyll a content

(pg.cell-1)

White S 9.15 (2.107, N/A) 65.61 (6.136, N/A) 0.29 (0.063, <0.001) 0.11 (0.023, 0.017) 0.12 (0.017, 0.002) 2.90 (0.401, 0.394)

Blue S 10.67 (1.777, N/A) 59.64 (5.760, N/A) 0.26 (0.072, <0.001) 0.11 (0.022, 0.017) 0.12 (0.015, 0.002) 2.73 (0.356, 0.394)

Red S 7.23 (1.307, N/A) 63.41 (11.000, N/A) 0.75 (0.130, <0.001) 0.39 (0.108, 0.017) 0.27 (0.044, 0.002) 2.12 (0.242, 0.394)

Light B/S Chlorophyll b content

(pg.cell-1)

Chlorophyll c content

(pg.cell-1) Cell weight (ng.cell-1)

Lipid productivity

(mg.L-1.day-1)

Carbohydrate productivity

(mg.L-1.day-1)

Protein productivity

(mg.L-1.day-1)

White S - - 4.85 (0.774, <0.001) 11.30 (3.680, 0.158) 3.99 (1.143, 0.503) 4.46 (1.330, 0.083)

Blue S - 0.034 (0.012, N/A) 4.64 (0.993, <0.001) 12.70 (3.910, 0.158) 5.49 (1.933, 0.503) 5.36 (1.060, 0.083)

Red S - - 11.60 (1.573, <0.001) 9.46 (3.030, 0.158) 4.82 (1.951, 0.503) 3.41 (1.070, 0.083)

Light B/S

Photosynthetic rate at

low oxygen (µmol O2. (mg chl a)-1.h-1)

Photosynthetic rate at

high oxygen (µmol O2. (mg chl a)-1.h-1)

The 1st dark respiration rate (µmol O2.(mg chl a)-1.h-1)

The 2nd dark respiration rate (µmol O2.(mg chl a)-1.h-1)

White S 334.97 (68.49, 0.002) - -47.47 (14.94, 0.137) -23.51 (1.97, 0.003)

Blue S 131.06 (29.40, 0.002) - -18.94 (1.86, 0.137) -18.03 (3.72, 0.003)

Red S 779.22 (97.67, 0.002) - -47.83 (3.79, 0.137) -49.57 (3.99, 0.003)

149

Table 18. The overview of the results for Pleurochrysis carterae cultures in batch (B) and semi-continuous (S) under 3 different light spectra*.

Light B/S Max. cell density

(104 cells.mL-1)

Specific growth rate

(day-1)

Biomass yield

(g.L-1)

Biomass productivity

(mg.L-1.day-1) % Lipid (of DW)

% Carbohydrate

(of DW)

White B 10 (0.481, <0.001) 0.06 (N/A) 0.10 (0.003, 0.167) 5.54 (0.153, 0.167) - -

S 24 (0.206, <0.001) 0.19 (0.040, 0.020) 0.10 (0.010, 0.002) 17.90 (2.600, 0.002) 19.35 (1.043, N/A) 7.03 (0.243, N/A)

Blue B 27 (1.176, <0.001) 0.11 (N/A) 0.08 (0.004, 0.167) 8.40 (0.403, 0.167) - -

S 34 (1.444, <0.001) 0.14 (0.020, 0.020) 0.13 (0.008, 0.002) 17.80 (1.980, 0.002) 22.41 (3.497, N/A) 9.35 (0.991, N/A)

Red B 5 (0.817, <0.001) 0.03 (N/A) 0.09 (0.002, 0.167) 3.14 (0.056, 0.167) - -

S 4 (0.098, <0.001) 0.09 (0.027, 0.020) 0.09 (0.009, 0.002) 7.43 (2.010, 0.002) 19.76 (1.746, N/A) 8.99 (1.264, N/A)

Light B/S % Protein (of DW) % Ash (of DW) Lipid content

(ng.cell-1)

Carbohydrate content

(ng.cell-1)

Protein content

(ng.cell-1)

Chlorophyll a content

(pg.cell-1)

White S 8.94 (0.750, N/A) 65.17 (4.260, N/A) 0.50 (0.188, <0.001) 0.18 (0.069, <0.001) 0.25 (0.118, 0.042) 2.76 (0.620, 0.028)

Blue S 10.06 (2.008, N/A) 58.92 (4.964, N/A) 0.23 (0.025, <0.001) 0.10 (0.012, <0.001) 0.10 (0.011, 0.042) 5.10 (0.631, 0.028)

Red S 7.48 (1.471, N/A) 68.60 (2.460, N/A) 1.39 (0.107, <0.001) 0.61 (0.022, <0.001) 0.50 (0.053, 0.042) 5.71 (0.584, 0.028)

Light B/S Chlorophyll b content

(pg.cell-1) Chlorophyll c content

(pg.cell-1) Cell weight (ng.cell-1)

Lipid productivity (mg.L-1.day-1)

Carbohydrate

productivity (mg.L-1.day-1)

Protein productivity (mg.L-1.day-1)

White S - - 7.76 (1.993, <0.001) 1.40 (0.450, 0.130) 3.58 (0.231, 0.036) 4.57 (0.452, 0.058)

Blue S - 0.29 (0.167, N/A) 4.36 (0.455, <0.001) 1.50 (0.397, 0.130) 4.06 (0.423, 0.036) 4.39 (0.914, 0.058)

Red S - - 22.58 (2.089, <0.001) 0.56 (0.190, 0.130) 2.20 (0.636, 0.036) 1.88 (0.575, 0.058)

Light B/S Photosynthetic rate at low oxygen (µmol O2.

(mg chl a)-1.h-1)

Photosynthetic rate at high oxygen (µmol O2.

(mg chl a)-1.h-1)

The 1st dark respiration rate

(µmol O2.(mg chl a)-1.h-1)

The 2nd dark respiration rate

(µmol O2.(mg chl a)-1.h-1)

White S 136.72 (8.71, 0.028) 71.05 (9.077, 0.007) -4.84 (1.35, 0.294) -4.51 (5.50, 0.578)

Blue S 225.24 (7.01, 0.028) 90.23( 16.678, 0.007) -6.29 (0.96, 0.294) -11.14 (1.73, 0.578)

Red S 279.04 (15.70, 0.028) 137.29 (23, 232, 0.007) -6.78 (0.48, 0.294) -7.47 (2.29, 0.578)

*Results of batch (B) and semi-continuous mode (S) are showed as ‘number (Standard Error of Mean, P)’, statistical significance was at P<0.05 (Repeated Measures, One Way ANOVA). Underlined numbers denote a significant effect of light spectra used. Statistical analyses was not performed (N/A).

150

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