THE INTEGRATION OF AUTOTROPHIC AND HETEROTROPHIC MICROBIAL PROCESSES FOR
BIOFUEL PRODUCTION
By
Yingkui Zhong

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Biosystems Engineering -Master of Science
2017

ABSTRACT
THE INTEGRATION OF AUTOTROPHIC AND HETEROTROPHIC MICROBIAL PROCESSES
FOR BIOFUEL PRODUCTION
By
Yingkui Zhong
Biofuel is an alternative energy source that has drawn much attention. Microbes that can utilize
various types of carbon sources are considered as potential biofuel producers. Umbelopsis isabellina, a
fungal strain that consumes sugars in a corn hydrolysate in the presence of inhibitors, showed excellent
potential for biofuel production in our previous study. However, some disadvantages in this energy
production process still exist, such as costly nitrogen sources for fungal culture and the lack of an efficient
lipid extraction method. To address these problems, this study has developed two processes that could
make large scale production using this strain more feasible. First, in order to further reduce the substrate
cost, algal biomass was added to a corn stover hydrolysis process to eliminate the cost of the yeast extract
used for fungal culture. The addition of the algal biomass had the same effect as the addition of yeast
extract on biomass accumulation and lipid yield after hydrolysis. The algal hydrolysate could also be
prepared separately and used for fungal culture. In addition to reducing the substrate cost of the fungal
culture, this process also provides another use for the algal biomass, which could help to further shrink
the cost of the algae-based biofuel. After fungal biomass accumulation, lipid extraction is another critical
step in biofuel production. The traditional Bligh & Dyer method, which uses a highly toxic and dangerous
solvent system (methanol and chloroform) was considered the best method for fungal lipid extraction.
Instead of using that solvent system, the less toxic solvent hexane was selected in this study as an
alternative, and a three-stage lipid extraction method for the fungus Umbelopsis isabellina was developed.
When applied to 1 g of biomass, this method extracted the same amount of lipids as the Bligh & Dyer
method, and the lipid profile was similar.

Copyright by
YINGKUI ZHONG
2017

ACKNOWLEDGEMENTS

I would like to take this opportunity to express my gratitude to my dear parents, who raised and
supported me throughout my college life at Michigan State University. I am thankful for their inspiring
guidance, invaluably constructive criticism and friendly advice.

I would like to express my warm thanks to Dr. Yan Liu for her excellent mentoring throughout my
graduate studies. Under her leadership, not only have I gained professional research skills and improved
my laboratory experimental techniques and attention to detail, but I also received excellent advice about
my graduate life at MSU. I would also like to thank my committee member, Dr. Wei Liao, for his
guidance during my studies. Many thanks to him and Dr. Liu for making this lab a big family. I also thank
Dr. David Hodge for serving on my committee and providing advice throughout my studies. Special
thanks are due to Dr. Dana Kirk and Dr. Steve Safferman for their academic guidance and for providing
research opportunities in ADREC.

Sincere thanks to Yuan Zhong, Dr. Mauricio Bustamante, Dr. Zhenhua Ruan, Dr. Rui Chen, Dr.
Zhiguo Liu, and Dr. Xiaoqing Wang for their help with my projects and the mentorship they provided.
Thanks to Christine Isaguirre, Austin Mashburn, Jack Blackhurst, Carly Daiek, and Aayushman
Srivastava for their friendship and assistance in the lab. Thanks to David Pavlik, Robert Morgan, and
William Clary for their help and support on the PHYCO2 project.

Thanks to the technical staff at MSU Mass Spectrometry, Dr. Daniel A. Jones, Dr. Scott Smith, Dr.
Lijun Chen and Dr. Tony Schilmiller for their help and contributions.

iv

TABLE OF CONTENTS

LIST OF TABLES ...................................................................................................................... vii
LIST OF FIGURES ................................................................................................................... viii
CHAPTER 1. LITERATURE REVIEW .................................................................................... 1
1.1
1.2
1.2.1
1.2.2
1.2.3
1.2.4
1.3
1.3.1
1.3.2
1.3.3
1.4
1.5

Introduction ..........................................................................................................................1
The use of microbes for energy production .......................................................................2
Bacteria and bacterial lipids ...............................................................................................2
Yeast ..................................................................................................................................3
Algae and algal lipid ..........................................................................................................4
Fungus and fungal lipids ....................................................................................................5
Biofuel from lignocellulosic material .................................................................................6
Lignocellulosic material.....................................................................................................6
Yeast culture with lignocellulosic material........................................................................7
Fungal culture with lignocellulosic material......................................................................9
Algal hydrolysate .................................................................................................................9
Lipid extraction ..................................................................................................................10

CHAPTER 2. THE INTEGRATION OF AUTOTROPHIC AND HETEROTROPHIC
MICROBIAL PROCESSING FOR BIOFUEL PRODUCTION ........................................... 12
2.1
2.2
2.3
2.3.1
2.3.2
2.3.3
2.3.4
2.3.5
2.3.6
2.3.7
2.4
2.4.1
2.4.2
2.4.3
2.5

Abstract ...............................................................................................................................12
Introduction ........................................................................................................................12
Materials and methods ......................................................................................................15
Algal and fungal strains and seed culture medium ..........................................................15
Pilot-scale algae photobioreactors to accumulate biomass ..............................................16
Dilute acid pretreatment ...................................................................................................17
Enzymatic Hydrolysis ......................................................................................................18
Fungal culture to accumulate lipids .................................................................................18
Analysis methods .............................................................................................................20
Statistical analysis ............................................................................................................20
Results and discussion .......................................................................................................20
Algal growth and biomass details ....................................................................................20
Hydrolysis of the algal biomass, corn stover, and a mixture of both...............................21
Fungal culture in different hydrolysates ..........................................................................23
Conclusion ..........................................................................................................................28

CHAPTER 3. A HIGH-EFFICIENCY EXTRACTION APPROACH TO RECOVER
LIPIDS FROM THE OLEAGINOUS FUNGUS UMBELOPSIS ISABELLINA ................ 29
3.1
3.2
3.3
3.3.1
3.3.2
3.3.3
3.3.4

Abstract ...............................................................................................................................29
Introduction ........................................................................................................................29
Material and methods ........................................................................................................31
Fungal culture ..................................................................................................................31
Lipid extraction ................................................................................................................32
Lipid profile .....................................................................................................................33
Statistical analysis ............................................................................................................33
v

3.4
3.4.1
3.4.2
3.4.3
3.4.4
3.5

Results and discussion .......................................................................................................34
Comparison of lipid extraction using different extraction methods ................................34
Optimization of the hexane extraction method ................................................................34
Three stage extraction with a larger amount of biomass .................................................38
Fatty acid profile of the extracted lipids ..........................................................................39
Conclusion ..........................................................................................................................41

CHAPTER 4. CONCLUSION AND FUTURE WORK.......................................................... 42
4.1
4.2

Conclusion. .........................................................................................................................42
Future work ........................................................................................................................43

APPENDICES ............................................................................................................................. 44
APPENDIX A: data ...............................................................................................................................45
APPENDIX B: statistics analysis ..........................................................................................................54

BIBLIOGRAPHY ....................................................................................................................... 80

vi

LIST OF TABLES

Table 1. Sugar and nitrogen concentration of the algal biomass hydrolysate .............................................21
Table 2. Sugar and nitrogen concentration of the corn stover hydrolysate and the mixed corn stover and
algal biomass hydrolysate ............................................................................................................................22
Table 3. Sugar consumption rate for different media ..................................................................................23
Table 4. Algae concentration for figure 3 ....................................................................................................45
Table 5. Sugar concentration data for figure 4 ............................................................................................46
Table 6. Lipid concentrations and standard deviations for figure 5 ............................................................47
Table 7. Biomass yield and lipid data for figure 6 .......................................................................................48
Table 8. Lipid yield and standard deviation data for figure 7 ......................................................................49
Table 9. Lipid yield and standard deviation for figure 8 .............................................................................50
Table 10. 3 stage lipid yields for different first stage reaction time (figure 9) ............................................51
Table 11. Scale up lipid yield data for figure 10..........................................................................................52
Table 12. Fatty acid profile data for figure 11 .............................................................................................53
Table 13. Data for appendix B1 ...................................................................................................................54

vii

LIST OF FIGURES

Figure 1. Integration of autotrophic and heterotrophic microbial processing for biofuel production .........15
Figure 2. Fungal cultivation medium preparation........................................................................................19
Figure 3. Biomass concentration with 20% harvesting everyday ................................................................21
Figure 4. Carbon source consumption by the fungal culture on (a) corn stover hydrolysate, (b) corn stover
hydrolysate with yeast extract, (c) corn stover hydrolysate with algal biomass hydrolysate, (d) corn stover
and algal biomass mixed hydrolysate, (e) control with pure sugar..............................................................24
Figure 5. Lipid concentration (g lipid/g biomass) in biomass using different culture media ......................26
Figure 6. Biomass yield and lipid yield (g/g total sugar consumed) on different medium..........................28
Figure 7. Lipid concentration of same fungal biomass using different extraction methods ........................34
Figure 8. The effects of different biomass: hexane ratios and extraction time on lipid yield .....................36
Figure 9. Staged extraction of different first stage extraction times ............................................................37
Figure 10. Scaling up the three stage hexane extraction ..............................................................................38
Figure 11. Fatty acid profiles for different extraction methods: (a) major fatty acids; (b) C16 and C18; (c)
Saturated fatty acids and unsaturated acids .................................................................................................39

viii

Chapter 1. Literature Review
1.1 Introduction
As societies around the world continue to develop, alternative energy sources are needed to replace
limited fossil fuel resources and reduce greenhouse gas emissions. In addition to wind, hydropower, solar
energy and other types of renewable energy sources, biodiesel has drawn much attention. Common raw
materials for biodiesel production include soybean, sunflower, coconut, peanut, and rapeseed oils (Shay
1993). To convert those oils into biodiesel, vegetable oil or animal fat is transesterified to convert it into
alkyl esters, which make up biodiesel. The biodiesel fuel B20, which is a blend of 6-20% biodiesel and
petroleum diesel, is currently in wide use all over the world (Knothe et al. 2005). The benefits of using
biodiesel are lower SOx and NOx emissions, the conversion of CO2 into biomass, and a reduced reliance
on fossil fuels (Shay 1993).
Although the use of biodiesel is environmentally beneficial, biodiesel production might cause a rise in
greenhouse gas emissions. When land is cleared during the conversion process of a carbon-rich habitat
into a bioenergy cropland, the habitat is usually burned to prepare it for the bioenergy species and an
enormous amount of greenhouse gases are emitted. The greenhouse gases produced from burning and the
degradation of the underground roots is huge, and it can take up to hundreds of years for a habitat to
recover from biodiesel production (Joseph Fargione 2008). Additionally, biodiesel production from
vegetable oil has also posed a threat to food production. The use of edible oil for biodiesel production
might create an imbalance between food and energy. The use of land for energy crop growth might limit
the land area available for food cultivation (Yusuf, Kamarudin, and Yaakub 2011).
Such concerns have resulted in more attention to a different type of biodiesel - microbial biodiesel.
The most common microbes used for biodiesel production are microalgae, bacteria, yeast, and fungi
(Meng et al. 2009). The advantages of microbial biodiesel include a shorter life cycle, less land usage,
1

less impact due to environmental changes, and ease of maintenance without intensive labor (Q. Li, Du,
and Liu 2008).

1.2 The use of microbes for energy production
Microbes that can accumulate lipids and contain more than 20-25% lipid in their biomass are
considered oleaginous species (C. Ratledge 1991). The major oils from microbes are triglycerides, which
is the same as the vegetable oil that is commonly used for biodiesel production. In biodiesel production,
this kind of microbial oil can be used to produce fatty acid methyl esters that are known as FAMEs
(Vicente, Martínez, and Aracil 2004).
Many microbial lipids have been recently studied. Microbial lipids can be used to produce cocoa
butter substitutes (Papanikolaou et al. 2001; Davies, Holdsworth, and Reader 1990), γ-linolenic acid
(Fakas et al. 2007; Papanikolaou, Komaitis, and Aggelis 2004; Dyal, Bouzidi, and Narine 2005; Jang,
Lin, and Yang 2005), docosahexaenoic acid (Wu, Yu, and Lin 2005; Chi et al. 2007; Bigogno et al.
2002), eicosapentaenoic acid (Tsunehiro Aki et al. 1998; Guo et al. 1999), and biodiesel (Easterling et al.
2009; Yonghong Li, Zhao, and Bai 2007; L. Y. Zhu, Zong, and Wu 2008; Chiu et al. 2009; Angerbauer et
al. 2008). Polyunsaturated fatty acids (PUFAs) are types of fatty acids that exist in humans and other
higher organisms. This type of fatty acid has been demonstrated to be beneficial for several health issues,
such as cardiovascular disease, brain disorders, cancer, inflammatory disease, obesity, autoimmune
disease, and diabetes. The primary sources of PUFA production are fungi and algae. Yeast is preferred in
industry, but it cannot synthesize PUFAs unless the strains are genetically modified. Bacterial fatty acids
are not exploitable (Bellou et al. 2016; Simopoulos 2006; Abedi and Sahari 2014).

1.2.1 Bacteria and bacterial lipids
Because they reduce land use and have high productivity, bacteria have been considered as a potential
biodiesel source. The average lipid content of bacterial dry biomass is approximately 30%, for example,

2

the oil content of Arthobacter sp. can achieve 40%. Compared with other microbes, bacteria that have a
rapid growth rate are easy to cultivate. The bacterial strain Rhodococcus opaacus PD630 can even
accumulate fatty acids in acylglycerols up to 87% of its dry weight. High lipid yields seem to be a
characteristic of only certain bacterial groups - most bacteria do not produce high lipid yields. Since most
lipids exist in the bacterial outer membrane, they are difficult to extract, which in turn makes it difficult to
commercially produce biodiesel from bacteria (Meng et al. 2009; Alvarez and Steinbüchel 2003).

1.2.2 Yeast
The major biofuel product from yeast cultures is ethanol. Metabolically engineered yeast strains are
currently used for ethanol production. Via fermentation, yeast can convert sugar from a substrate into a
dilute ethanol solution, which can then be concentrated via distillation. Genetically modified strains can
even produce bio-butanol, which has a higher energy content and is more similar to gasoline than ethanol
(Coyle 2010). The use of yeast to produce lipids has been studied for a long time. The advantages of
oleaginous yeast strains are a high lipid content, rapid growth, a high cell concentration, the utilization of
all carbohydrates in the hydrolysate, and a high hydrolysate inhibitor tolerance (Yu et al. 2011).
In addition to bioenergy production, yeast has been widely cultured by humans to produce alcoholic
beverages, bread dough, and food ingredients (Boulton 2001; Tanguler and Erten 2008; Peppler 1982;
Walker 1998). Yeast extract, collected from autolyzed yeast, is often used as a nitrogen source in a
microbial culture for the growth of the microbe. It contains peptides, amino acids, carbohydrates, and
soluble vitamins. It is used in many types of media for various microbial cultures; such media include
Sigma LB medium, Sigma Minimal salts (M9) medium, Terrific Broth, SOB medium, SOC medium, and
2X YT medium (Sigma-Aldrich 2016). Degradative enzymes in the yeast itself can be activated via
autolysis, and can solubilize different cellular components. During this process, insoluble molecules such
as nucleic acids and proteins are converted to nucleotides and amino acids, which are essential for
microbial growth (Sommer 1998; Reed, Gerald 1991).

3

1.2.3 Algae and algal lipid
In addition to yeast, algae also have excellent potential as an alternative energy source because they
can fix carbon dioxide using sunlight as an energy source. Algae also exhibit a higher oil content and
higher production rates than traditional energy crops (Chisti 2007a; Q. Li, Du, and Liu 2008). Several
types of biofuel can be produced from microalgal cultures, including methane (Chisti 2007a; Spolaore et
al. 2006), biodiesel (Chisti 2007a; Gavrilescu and Chisti 2005; Sawayama et al. 1995; Roessler et al.
1994), and bio-hydrogen (Akkerman, Janssen, Rocha, & Wijffels, 2002; Chisti, 2007; Ghirardi et al.,
2000; Melis, 2002). Much less land use is necessary for algal growth than for any vegetable, and several
types of algae have excellent potential for algal oil production due to their high oil content. The oil
content of certain algae can achieve 80%, and their biomass accumulation time is short. It usually takes
less than one day for an algae to double its biomass (Metting 1996; Spolaore et al. 2006). In addition to
producing biofuel, algae can also be used in human nutrition due to their high protein content and
nutritional value (Spolaore et al. 2006; Soletto et al. 2005; Radmer 1996; Desmorieux and Decaen 2005),
as a feed additive for many types of animals, which is an industry that comprises 30% of global algal
production (Spolaore et al. 2006; Richmond 2004), and in the production of cosmetic products, highvalue molecules, fatty acids, and pigments (Spolaore et al. 2006).
Several disadvantages of algal cultures for biodiesel production exist. An algal culture usually
occupies much space, because when the concentration of algae is high, light cannot penetrate the algal
solution, which slows down the growth rate. Reliance on light results in shorter growth periods per day
compared to other microbes. Even though an external light source can be used for culture, additional
energy is required (Chisti 2007a). Additionally, high water usage and a low cell concentration after
harvest are also problems that must be solved to economically to use algae as an alternative biodiesel
source. (Q. Li, Du, and Liu 2008).

4

1.2.4 Fungus and fungal lipids
Fungi have recently been drawing much attention as a potential biodiesel source. Their lipid content
can achieve up to 80% under certain conditions (Murphy 1991; Subramaniam et al. 2010). Fungal lipid
content is affected by several factors - the C/N ratio, the carbon source, the nitrogen source, mixing, the
pH, and the temperature. Fungal lipids contain high concentrations of PUFAs, such as arachidonic acid
(AA) and γ-linolenic acid (GLA), which are fatty acids also used to produce high-value products other
than biofuels. Mortierella alpine can generate 4.5 g/L of AA, which is a significant portion (18%) of its
dry biomass (Eroshin et al. 2000). Mortierella alliance also produced 7.1 g/L of AA when cultured in a
50 L jar (T. Aki et al. 2001). The capacity to produce such high-value fatty acids does increase the value
of fungal biomass, but the lipid production rate of a fungus is usually lower than that of a yeast. It usually
takes fungus longer to produce the same amount of lipids as yeast. For example, Mortierella ramanniana,
MM15-1 can accumulate 68% lipid in its biomass in 9 days with a glucose-only medium in a Maxblend
Fermentor (Hiruta et al. 1997). Fakas et al. (Fakas et al. 2009) cultured two fungal strains,
Cunninghamella echinulate and Umbelopsis isabellina (previously known as Mortierella isabellina) in
glucose, xylose, and glycerol media. Both strains showed similar lipid yields in the glucose medium (g
lipid/g sugar consumed) and Umbelopsis isabellina had a very high biomass yield (27 g/L).
Cunninghamella echinulate demonstrated a better lipid yield in the xylose medium and Umbelopsis
isabellina had a better lipid yield in glycerol medium. Umbelopsis isabellina ATHUM 2935 produced 4456% oleic acid and 10-16% linoleic acid, which qualifies it as a potential biodiesel production strain.
The production cost must be reduced to use microbial biomass to produce commercial biodiesel
instead of vegetable oil and animal fat. Two major components must be improved – the culturing cost
and the transesterification efficiency. To reduce the cost of culturing microbes, the primary cost, which is
the substrate cost, must be decreased. Instead of pure sugar as a carbon source, an alternative substrate is
essential for the development of microbial lipids. Studies have explored the viability of several types of
alternative substrates, including a whey substrate for the growth of Cryptococcus curvatus ATCC 20509

5

and Candida bombicola ATCC 22214 cultures (Daniel et al. 1999), Umbelopsis isabellina with glycerol
(Fakas et al. 2009), Cunninghamella echinulata and Umbelopsis isabellina with molasses (Chatzifragkou
et al. 2010), Lipomyces starkeyi with sewage sludge (Angerbauer et al. 2008), Lipomyces starkeyi with
olive oil mill wastewaters (Yousuf et al. 2010), Mortierella alpina with maize starch hydrolysate (M.
Zhu, Yu, and Wu 2003), and Cryptococcus curvatus with N-acetylglucosamine (Zhang et al. 2011).
Although a potential for lignocellulosic material to be utilized by different types of the fungus has been
indicated, a limited supply and a high transportation cost are still problems (C. Huang, Chen, Xiong,
Chen, et al. 2013). The cost of raw materials for biodiesel production is approximately 75% of the total
production cost (Srinivasan 2009). Therefore, a cheap and abundant raw material is important.
Lignocellulose is considered a potential substrate, because it is a more available biofuel source and has
been studied by many researchers (C. Huang, Chen, Xiong, Chen, et al. 2013), which includes fungal
cultured with corn stover hydrolysate (Ruan et al. 2012).

1.3 Biofuel from lignocellulosic material
1.3.1 Lignocellulosic material
Lignocellulosic material is the most abundant resource for microbial lipid production. The low cost
and high availability of this material make it an ideal substrate for energy production (Srinivasan 2009).
Over 1.3 billion tons of dry lignocellulosic material that can be used for biofuel production are produced
in the US every year (Robert D. Perlack, Lynn L. Wright, Anthony F. Turhollow, Robin L. Graham,
Bryce J. Stokes 2005). If this much material were transformed into energy, the energy produced would be
equivalent to 3.8 billion barrels of oil (Kumar, Jones, and Hanna 2009). Therefore, it is very important to
study the best way to use this energy source for optimized energy production.
Lignocellulosic biomass usually has three main parts: cellulose, lignin, and hemicellulose. The
concentration of those three components varies depending on the biomass (Reddy and Yang 2005). Since

6

lignocellulosic biomass cannot be directly used by microbes, the material must be degraded before use in
bioconversion and fermentation (Rubin 2008). Acid is usually used to degrade the biomass during the
breakdown process. Long-chain polysaccharides are generated during this process, and then converted to
the corresponding monosaccharides (F. LaForge 1918). During the breakdown of lignocellulosic
material, inhibitors such as weak acids, aromatic compounds, and aldehydes are produced. Those
compounds are usually toxic to microbes. Most microbes cannot grow in the presences of such inhibitors
(Palmqvist and Hahn-Hägerdal 2000). Hence, the discovery of microbes that can tolerate these inhibitors
while producing energy sources is critical for renewable energy development. Lignocellulosic biomassdegrading microbes are being considered as a novel way to breakdown a lignocellulosic biomass, and the
enzymes extracted from those microbes can be further applied in industrial production (Gilbert 2007).
Due to the difficulty of culturing the microbes that can produce these enzymes, the cost of this process is
still currently higher than acid treatment (Hugenholtz 2002).
Various fermentable sugars are produced by the hydrolysis of a lignocellulosic biomass. The primary
sugars are hexoses and pentoses and the hexose concentration is usually 1.5 to 3 times higher than that of
pentoses (Balan et al. 2009; Lau and Dale 2009; Sassner, Galbe, and Zacchi 2005; Rahman, Choudhury,
and Ahmad 2006). Because both sugars are present in the hydrolysate, the microbes selected for biofuel
production should have the ability to use those sugars efficiently and to grow well in the presence of
inhibitors. Screening or mutagenesis are strategies that scientists can employ to find the best strain for
culturing with a lignocellulosic hydrolysate. Therefore, the ability to accumulate lipids or other types of
high-value chemical products from xylose is critical for the discovery of suitable microbes since most of
them cannot use xylose as an energy source (C. Huang, Chen, Xiong, Chen, et al. 2013).

1.3.2 Yeast culture with lignocellulosic material
Yeasts are currently the primary microbes studied for use with lignocellulose material for biofuel
production. Several yeast strains have been studied. Trichosporon dermatitis CH007 and Trichosporon

7

corymbiform were cultured with corncobs, and their lipid concentrations achieved 9.8 and 7.7 g/L,
respectively (C. Huang, Chen, et al. 2012; C. Huang, Chen, Xiong, Yang, et al. 2013). In addition to
corncobs, several types of yeast have been cultured with corn stover, and Rhodotorula garminis showed
excellent utilization of sugar with 14.1 g/L of lipid produced (Hu et al. 2011; X. Huang et al. 2011; Gong
et al. 2013; Galafassi et al. 2012). Rice straw has also been used with Hosporon fermentans CICC 1368
and 12.5/L of lipid was accumulated (C. Huang et al. 2009). Trichosporon fermentans and Yarrowia
lipolytica have been cultured on sugarcane bagasse and accumulated 15.8 and 6.7 g/L of lipids
respectively (C. Huang, Wu, et al. 2012; Tsigie et al. 2011). E. veralis (G.pullulans) achieved a 45% lipid
content when cultured with waste sulfite liquor (Lindner 1922). R.gracilis (R. toruloides) achieved a 64%
lipid content when cultured with wood or molasses hydrolysates (Lundin 1950; Tornqvist 1951). For most
yeast fermentations with lignocellulose material, the primary substrates have usually been detoxified due
to the sensitivity of the yeast to the inhibitors in the substrate, such as furan derivatives, weak acids, and
phenolic compounds. Not many yeasts that can be cultured in non-detoxified substrates have been
reported. Yu et al. succeeded in culturing Cryptococcus curvatus, Rhodosporidium toruloides,
Rhodotorula glutinis, Yarrowia lipolytica, and Lipomyces starkeyi in a non-detoxified hydrolysate.
Cryptococcus curvatus accumulated 5.8 g/L of lipids. The primary inhibitor of growth was HMF, while 1
g/L furfural reduced the lipid content by 62% (Yu et al. 2011). Inhibitors produced from the degradation
of lignin and carbohydrates are the major inhibitors of yeast lipid accumulation. Those inhibitors are
generated by pretreatment methods and the lignocellulosic biomass cell wall composition (Helene B.
Klinke et al. 2002; H. B. Klinke, Thomsen, and Ahring 2004). Since most oleaginous yeast cannot
accumulate lipids in xylose media, the development of oleaginous microbes that can utilize sugar
produced from lignocellulosic material that have high inhibitor resistance are necessary for biodiesel
production from lignocellulosic material.

8

1.3.3 Fungal culture with lignocellulosic material
Yeasts are not the only microbe that can utilize lignocellulosic material for biofuel production - some
other fungi are also considered potential “lignocellulosic utilizers”. The filamentous fungus Mucor
hiemalis can produce over 50 g/L of ethanol in a high glucose concentration (up to 190 g/L) wheat
hydrolysate. The high value byproduct chitosan has also been produced in this fermentation (Heidary
Vinche et al. 2013). Hohenbuehelia sp. ZW-16 has been cultured in a corn straw hydrolysate and a
corncob hydrolysate. The highest yield was achieved in the corn straw hydrolysate, which produced 4.6
g/L of bioethanol in 8 days (Liang et al. 2013). It has been reported that 11 fungal strains were cultured in
synthetic media containing glucose and xylose and 6 fungal strains were selected for culture in detoxified
and non-detoxified acid-pretreated wheat straw media. The fungal strain Umbelopsis isabellina showed
the highest lipid yield (39.4%) in a non-detoxified liquid hydrolysate (Zheng et al. 2012). Umbelopsis
isabellina has also been grown in a rice hull hydrolysate and has accumulated oil comprising up to 64.3%
of the biomass with a C/N ratio of 57 (Economou et al. 2011). The same strain was studied by Zhenhua
Ruan, who combined acid and alkali pretreated corn stover and treated it with enzymes to generate a
hydrolysate without the need for pH adjustment. In this case, the fungus could accumulate biomass and
lipids in the presence of inhibitors (Ruan et al. 2014).

1.4 Algal hydrolysate
Carbon sources and nitrogen sources are critical for fungal cultures. Many studies have explored the
use of different lignocellulosic materials as carbon sources for fungal culture. However, few studies have
focused on alternative nitrogen sources for fungal culture. Yeast extract is still the major nitrogen source
currently used in microbial cultures, and it is quite expensive.
In a study by Maurya, a harmful bloom-forming algal biomass (Lyngbya majuscule) was hydrolyzed
and used for oleaginous microalgal culture. The use of the hydrolysate significantly increased the dry cell
weight and the productivity of the algae C. vulgaris during the culture (Maurya et al. 2016). In a study by

9

Kightlinger, an autolyzed algae (Chlamydomonas reinhardtii) biomass showed similar or even better
effects than yeast extract for the culturing of common lavatory strains such as E. coli and S. cerevisiae. If
algal extract could bring the same price as yeast extract, algae-based biofuel products would be more
compatible (Kightlinger et al. 2014). These studies showed the potential of using algae hydrolysate as a
substitute for yeast extract. More ways to utilize an algal biomass would make the large-scale production
of algae-based bioenergy more feasible.

1.5 Lipid extraction
Extraction is one of the most energy-intensive stages of the microbial lipid production process (de
Boer et al. 2012). Therefore, the discovery of a stable, economical, environmentally friendly, and easy
extraction method is critical for the development of microbial lipids. Organic solvent extraction and
SCCO2 extraction are two current, popular extraction methods. The advantages of the SCCO2 extraction
method are neutral lipid selectivity, the total lipid yield, the extraction time, hazard and toxicity, and
reactivity with lipids. The advantages of the organic solvent extraction method are the energy
requirements, the installation cost, and the operation cost. Organic solvent extraction is more commonly
used in industry due to the high installation cost for high pressure vessels for SCCO2 extraction (Halim,
Danquah, and Webley 2012).
Various other extraction methods are used in the laboratory and in industry. The Bligh & Dyer
method (E. G. Bligh 1959) is one of the most popular extraction methods for all living tissue lipids. Two
organic solvents, chloroform and methanol, are used in this method. By using polar and non-polar
solvents, this extraction method can completely extract both types of lipids. First, chloroform, methanol,
and water in a ratio of 1:2:0.8 (v/v/v) is used to extract the lipid from the tissue. Then, additional
chloroform and water is added to a total ratio of 2:2:1.8 (v/v/v) to form a biphasic structure. The bottom
layer contains all the lipids while the top layer contains all the non-lipids. Homogenization may be used
depending on the biomass extracted. The advantage of this method is that both polar and non-polar lipids

10

are recovered. The disadvantage is that the solvents are extremely toxic and flammable (Medina et al.
1998). Hexane-isopropanol at a ratio of 3:2 (v/v) can also be used for lipid extraction. The solvent in this
method is less toxic compared to those in the Bligh & Dyer method. After extraction, the extract is
washed in sodium sulfate to further remove the non-lipid contaminants. Since the density of the solvent is
low, a centrifuge can be used to separate the solids and liquids instead of filtration as in the Bligh & Dyer
method. This method has been reported to have a good lipid extraction rate for rat or mouse brain lipids.
However, when applied to various algae and fungal strains, the yields were not as high as those of the
Bligh & Dyer method (Grima et al. 1994; Halim, Danquah, and Webley 2012; Hussain et al. 2014).
Extraction with hexane alone has been used for the high oil content algae Chlorella protothecoides (Miao
and Wu 2006). Hexane has a low affinity for non-lipid materials, and it is cheaper and much less toxic
than the solvents used in the Bligh & Dyer method (Halim et al. 2011).
Due to different cell structures, lipid compositions, strain physiologies, and other uncertain variables,
the best extraction method varies by strain. For example, for the algae Botryococcus braunii, the
chloroform/methanol method has resulted in a higher lipid yield compared to four other organic solvent
extraction methods, including a dichloroethane-based organic solvent mixture, which is an extraction
method recommended for the algae Cladofora (Lee et al. 2010; Halim, Danquah, and Webley 2012).
Therefore, selecting the appropriate solvent and procedure for the target strain is very important. Javid
Hussain studied four solvent-based extraction methods for the fungus Umbelopsis isabellina, including a
modified Bligh & Dyer method, hexane and isopropanol, dichloromethane & methanol, and hexane
extraction. The Bligh & Dyer method gave the best lipid yield for this fungus.

11

Chapter 2. The integration of autotrophic and heterotrophic
microbial processing for biofuel production
2.1

Abstract
With an increasing energy demand, an alternative energy source is needed for the sustainability of

this world. Biofuel produced from microbes has excellent potential because it produces less pollution, is a
renewable energy source, and has a smaller carbon footprint. The filamentous, oleaginous fungus
Umbelopsis isabellina was studied for its ability to utilize carbon sources in a corn stover hydrolysate in
the presence of inhibitors. To further reduce the substrate cost, this study investigated the possibility of
adding an algal biomass to the corn stover hydrolysis process to reduce the subsequent addition of yeast
extract. The fungus was successfully cultured on the hydrolysate containing an algal biomass and corn
stover. The lipid yield was comparable to the corn stover hydrolysate medium with yeast extract.

2.2

Introduction
Biodiesel is attracting more interest recently as a renewable energy source. The conventional sources

for biodiesel production are peanut oil, soybean oil, coconut oil and rapeseed oil. Vegetable oil-based
biodiesel has environmental and social advantages over petroleum diesels such as low sulfur oxides (SOx)
emissions, low nitrogen oxide (NOx) emissions, CO2 sequestration from crop growth, and the production
of valuable byproducts from the biomass. Despite its benefits, biofuel has several drawbacks including
low fuel production yields, performance disadvantages compared to fossil-based diesel, and a high
production cost (Shay 1993). Additionally, increasing concern about crop land use and emissions
produced from cultivation raise questions as to whether plant-based biodiesel is truly environmentally
beneficial (Joseph Fargione 2008). Microbial biodiesel, which is produced from microalgae, fungi, and
yeast, is becoming a more environmentally friendly alternative for biodiesel production. For example,
Yanqun Li (Yanqun Li et al. 2008) claimed that with a high-value co-product strategy, an advanced

12

reactor design, and cost-effective harvesting and drying technology, algal biofuel production could fulfill
the increasing energy demand. Yeast and fungi are also considered as potential microorganisms for fuel
production. Some yeasts can accumulate up to 80% of their biomass as lipids, and the fatty acids
produced from fungi and yeast are similar to those produced from fish oil and other animal sources (C
1993)
Microalgae are considered an ideal candidate for microbial biodiesel generation due to their
ability to utilize CO2 to generate lipids and their high photosynthetic efficiency (Chisti 2007b; Yanqun Li
et al. 2008). The rapid growth of algae requires a significant amount of CO2. Since power plants are one
of the largest CO2 contributors, the abundant CO2 from power plant flue gas could potentially be used as a
carbon source for algal growth. Vunjak-Novakovic used an air-lift reactor to culture microalgae. Flue gas
was pumped into the reactors to provide the carbon source for algal growth and the biomass was
harvested during the growth phase. Light intensity played a major role in the CO2 reduction rate (VunjakNovakovic et al. 2005). The system could reduce the CO2 concentration of the incoming flue gas by
82.3% on a sunny day and the CO2 reduction rate dropped to 50.1% on a cloudy day. In addition to CO2
reduction, microalgae can also be used as a biofuel source. Depending on the culture medium
composition, the algal protein, carbohydrate, and lipid composition can vary significantly. The algal
biomass produced from continuous culturing usually has a lower lipid content because algae accumulate
more lipids or carbohydrates in an environment that has a low nitrogen concentration and a high protein
content (Wang et al. 2015). On the other hand, algae grow rapidly on a nitrogen-rich medium, and a
significant amount of protein is naturally present in most algae species that can be used for human
consumption and animal feed, making algae a more desirable biofuel (Becker 2007). Although several
benefits and uses for culturing microalgae exist, commercialization of algal cultivation is still not feasible
due to the high cost of operation, nutrients, and extraction (Wijffel, Barbosa, and Eppink 2010). To make
algal production more cost efficient, several studies have been performed to identify more uses for algal
biomass. Algal hydrolysate was used as a medium to improve the hydrolysis processes for other

13

biomasses such as anaerobic digestion fiber and poplar for glucan conversion (Chen et al. 2014). An
autolyzed algal biomass (Chlamydomonas reinhardtii) was demonstrated to provide effects similar to
yeast extract for general laboratory microorganism culturing except for ethanol production from yeast
(Kightlinger et al. 2014).
Oleaginous fungi have also been studied as an alternative energy source. Ostensibly, fungi have
some clear advantages - their growth does not require light, they have high lipid yields (C. Ratledge
1991), and can utilize different types of sugar (Fakas et al. 2009). However, one of the greatest problems
with fungal culture is the medium cost. To make it more affordable, pure substrates must be replaced by
an alternative source such as a lignocellulosic biomass (Ruan et al. 2013). In a previous study,
Umbelopsis isabellina (previously known as Mortierella isabellina) tolerated inhibitors such as furfural
and hydroxymethylfurfural (HMF), while consuming carbon sources in an acid-pretreated corn stover
hydrolysate. This study indicated a further improved possibility of using fungal biomass as a potential
biodiesel feedstock, because it replaced an expensive culture media with abundant corn stover. It is
remarkable that this strain can tolerate inhibitors while accumulating lipids. In these fungal culture
experiments, yeast extract was used as the nitrogen source for the fungal cultivation, which would
increase the production cost. Other cheap organic nitrogen sources could be used to replace yeast extract
to make fungal lipid production more economically feasible (Ruan et al. 2012; Ruan et al. 2013; Ruan et
al. 2014; Ruan et al. 2015).
With the previous research in mind, the objectives of this study are to evaluate the hydrolysis of
corn stover and an algal biomass and to investigate fungal ability to utilize nitrogen from an algal extract
as a nitrogen source. The improved process demonstrates an alternative strategy for nitrogen source
production, and a feasible way to combine nitrogen and carbon source production for a fungal culture.

14

2.3

Materials and methods

2.3.1 Algal and fungal strains and seed culture medium
Figure 1. Integration of autotrophic and heterotrophic microbial processing for biofuel production

The microalga Chlorella vulgaris 395 was purchased from the UTEX Culture Collection of Algae
(Austin, TX) and stored on Tris-Acetate-Phosphate (TAP) agar medium (Wang et al. 2015) at room
temperature under constant fluorescent light. Liquid TAP medium (without agar) was used for the seed
cultures. Modified TAP medium was used as the photoautotrophic culture medium and contained the
following substances:	7.5 mmol L-1 of NH4Cl, 0.34 mmol L-1 of CaCl2 · 2H2O, 0.4 mmol L-1 of MgSO4 ·
7H2O, 0.68 mmol L-1 of K2HPO4 (anhydrous), 0.45 mmol L-1 of KH2PO4 (anhydrous), and 1 mL of TAP
trace elements solution.

15

The fungal strain U. isabellina (ATCC 42613) was used for this experiment. First, the spores of
this strain were cultured on potato dextrose agar for 14 days at room temperature. After good growth had
occurred the plate, the spores were transferred into a sealed bottle with autoclaved DI Water and
refrigerated at 4°C. To prepare the seed for this experiment, 1 mL of spore solution (4.2×107 spore·mL-1)
was added to 100 mL seed medium with 8 g/L yeast extract and 24 g/L potato dextrose broth for two days
(Ruan et al. 2012).

2.3.2

Pilot-scale algae photobioreactors to accumulate biomass

An algal culture system (algae photobioreactors APB), which could convert the carbon dioxide in the
power plant flue gas to a carbon source for algal growth, was designed by PHYCO2 and installed in the
Michigan State University T. B. Simon Power Plant. The PHYCO2 APB unit (US Patent #8,476,067 B2,
Canada Patent #2,712,862) has a total volume of 118 L with a working volume of 100 L. The goal of this
reactor is to decrease the carbon dioxide emissions from the power plant and accumulate algal biomass
for biofuel and animal feed production. A portion of flue gases produced from the plant was pumped from
the exhaust into the reactor via a vacuum pump to provide a carbon source for algal growth. The reactor
was filled with the algal culture medium including approximately 100 mg/L nitrogen, 20 mg/L
phosphorus, and 1.7 mg/L iron during the experiments. The pH of the culture was kept at 6.5±0.3. The
flue gas and the design of the reactor created a flow in the reactor without the use of a pump, which
helped the recirculation and mixing of the algae without any energy use. Since the system was located
inside of the plant, high-intensity LEDs lights were used to provide a constant light source for the reactor.
The LED panel included 20% blue and 80% red light, which was designed by PHYCO2 to provide
enough light energy for photosynthesis. The Chlorella strain was stored in a solid Tris-Acetate-Phosphate
(TAP) medium. Liquid TAP medium without acetate was used for seed culture under an LED light panel,
which was set up with the same light penetration and design as the one in the power plant. The LED lights
were the only light source and were turned on 24 hours a day. The seed was then inoculated into the
reactor, which was filled with the same TAP medium without acetate. With 24 hours of LED lighting and

16

a continuous gas input (7% CO2), the concentration of the algae could achieve higher than 2.5 g/L. 20%
of the volume, and it was harvested every day for the different harvesting tests until the algal
concentration achieved stationary phase. Each time after harvesting, the same amount of fresh medium
was added to replace the volume removed. The total iron and nitrogen content of the medium were
monitored daily and maintained at their original level. The harvested algal solution was centrifuged in a
disc centrifuge (Alfa Laval MAB 104B) at 7350 rpm to collect the biomass. After drying at 105°C
overnight, the biomass was cooled to room temperature, ground in a coffee grinder, and stored in a sealed
container for future experiments.

2.3.3 Dilute acid pretreatment
The corn stover used for this hydrolysis experiment was collected from the Michigan State University
Crop and Soil Science Teaching and Research Field Facility. The samples were collected after harvesting
in 2015, air dried, and ground in a mill (Willey Mill, Standard Model No. 3, Arthur H. Thomas,
Philadelphia, PA). The average particle size of the sample was 2 mm.
Diluted acid pretreatment was used to extract the sugar from the biomass[3]. DI water, sulfuric acid,
and biomass were added to a 2 L beaker and mixed well. The total weight of the mixture was 700 g.
Three types of biomass were designed for this experiment. The first was a mixture, which included 10%
(w/w) corn stover and 1% (w/w) algal biomass. The second was 10% (w/w) corn stover, and the third was
10% (w/w) algal biomass. The pretreatment solution was prepared from 98% sulfuric acid, and the final
acid concentration was 2% (w/w). The remaining mass comprised DI water. Three replicates were
prepared for each treatment. After mixing thoroughly, the beakers were covered with aluminum foil and
autoclaved at 120ºC for 1 hour. Afterwards, the beakers were cooled to room temperature, and the pH of
each beaker was adjusted to 6 using a 30% (w/w) Sodium Hydroxide solution.

17

2.3.4 Enzymatic Hydrolysis
After acid pretreatment, the mixtures were transferred into a 1 L sealed bottle for enzyme hydrolysis.
Cellulase from Trichoderma reesei ATCC 26921 was used for the hydrolysis experiment, and the enzyme
activity was 120FPU/ml enzyme. The dosage used for the hydrolysis was 30 FPU cellulose per gram of
corn stover. The same amount of enzyme was added to the pretreated algal biomass and the mixed
biomass. After the addition of enzyme, the bottles were sealed and mixed on a temperature controlled
shaker (Thermal Scientific) for three days. The temperature was 50ºC, and the shaking speed was 150
rpm. After enzyme hydrolysis, the samples were separated with a centrifuge, and the liquid components
were collected and stored at -18C.

2.3.5 Fungal culture to accumulate lipids
After analyzing the sugar concentration and total nitrogen of the hydrolysate of the various
treatments, media were prepared as follows:
Medium 1, 100 mL corn stover enzymatic hydrolysate only;
Medium 2, 100 mL corn stover enzymatic hydrolysate and 0.489 g yeast extract;
Medium 3, 88.5 mL corn stover enzymatic hydrolysate and 11.5 mL algal biomass enzymatic
hydrolysate;
Medium 4, 100 mL corn stover and algal biomass mixture enzymatic hydrolysate;
Medium 5, 100 mL control medium with 25.5 g/L glucose, 16.6 g/L xylose, 0.93 g/L sodium acetate,
and 4.98 g/L yeast extract.
The detailed medium preparation steps are shown in Figure 2. Each medium was autoclaved for 15
minutes at 121ºC and cooled to room temperature before seed inoculation. Each flask was then inoculated
with 10% (v/v) inoculum, and cultured on a temperature controlled shaker (Thermal Scientific). Samples

18

were taken each day for HPLC sugar analysis. When the total sugar concentration achieved
approximately 0 g/L, the biomass was collected by filtration and dried overnight, then the biomass
concentration of each treatment was determined.
Figure 2. Fungal cultivation medium preparation

19

2.3.6 Analysis methods
Medium samples were taken each day from each treatment and filtered through a 0.22 µm syringe filter.
Glucose, xylose, acetate, furfural, and hydroxymethylfurfural (HMF) were determined via HPLC (Agilent
1100). A refractive index detector and a Biorad Aminex HPX-87H analytical column were used for the
determination. A mobile phase of 0.005 M sulfuric acid with a 0.6 mL/min flow rate was used for the
column, and the column temperature was at 65°C. Glucose, xylose, sodium acetate, furfural, and
hydroxymethylfurfural (HMF) from Sigma were diluted with DI water and used as standards. The fungal
biomass was collected by filtration. DI water was used to wash off the residual sugars attached to the
biomass by rinsing the biomass twice. The biomass collected from the filtration was dried at 105C
overnight. The biomass was then ground with a mortar for lipid extraction. The lipid extraction method
was the Bligh and Dyer method (E. G. Bligh 1959). The nitrogen content was analyzed using the HACH
High Range Nitrogen (Total) TNTplus Vial Test.

2.3.7 Statistical analysis
Statistical analysis was performed by using Minitab Express 2016. A two sample t test and a one-way
ANOVA test was chosen for the treatment comparisons for each dataset. The confidence level was 95%.

2.4

Results and discussion

2.4.1 Algal growth and biomass details
Daily harvesting was done after the algal concentration had achieved 2.4 g/L to accumulate biomass.
Twenty percent of the total reactor volume was harvested every day. In the beginning, the biomass
concentration decreased until it achieved 1.2 g/L. After the decline, the concentration increased until it
achieved 1.8 g/L. After 20 days of harvesting, the biomass concentration achieved equilibrium at
approximately 1.5 g/L

20

Figure 3. Biomass concentration with 20% harvesting everyday
3.00
2.50

Biomass	(g/L)

2.00
1.50
1.00
0.50
0.00
0.00

50.00

100.00

150.00

200.00

250.00

300.00

350.00

400.00

450.00

500.00

Time	(h)

As the harvest amount increased, the algal concentration dropped due to the growth rate of the algae.
In future experiments or production, it is important to discover the balance point between the amount
harvested and growth rate, which can help optimize the algal biomass production. After harvesting the
biomass, it was dried, ground, and ready for the hydrolysis process.

2.4.2 Hydrolysis of the algal biomass, corn stover, and a mixture of both
Table 1. Sugar and nitrogen concentration of the algal biomass hydrolysate

Total
Treatment

Experiment

Acid

10% algal

Pretreatment

biomass

Glucose

Xylose

Acetate

Total Sugar

Nitrogen

3.51±0.05

4.47±0.04

0.15±0.01

8.13±0.01

3.98±0.29

The sugar concentration of the algal biomass hydrolysate was 3.51 g/L glucose, 4.47 g/L xylose, and
0.15 g/L acetate. The nitrogen concentration achieved 3.98 g/L after hydrolysis. Compared to the corn
stover hydrolysate, the sugar concentration of the algal biomass was very low, but the nitrogen

21

concentration was much higher. This result showed the potential for using this hydrolysate as a nitrogen
source for fungal culture.
The glucose, xylose, acetate, and total sugar concentrations were not significantly different between
the pretreated mixed hydrolysate and pretreated corn stover hydrolysate. The glucose, xylose and acetate
concentrations of the mixed hydrolysate were 25.47 g/L, 16.56 g/L, 0.93 g/L, respectively. The sugar
concentrations of the corn stover hydrolysate were 26.46 g/L, 17.44 g/L, and 0.95 g/L, respectively. The
results showed that no significant differences existed for glucose (P-value=0.5011, for a for a detailed
statistical analysis, see Appendix B.1), xylose (P-value=0.0950, for a detailed statistical analysis, see
Appendix B.1), acetate (P-value=0.4512, for a detailed statistical analysis, see Appendix B.1), and the
total sugar concentrations (P-value=0.2714, for a detailed statistical analysis, see Appendix B.1) when 1%
(w/w) algal biomass was added to a 10% (w/w) corn stover pretreatment.
Table 2. Sugar and nitrogen concentration of the corn stover hydrolysate and the mixed corn stover and
algal biomass hydrolysate

Total
Treatment

Experiment

Glucose

Xylose

Acetate

Total Sugar

Nitrogen

25.47±1.05

16.56±0.48

0.93±0.03

42.97±0.62

1.2±0.24

26.46±1.99

17.44±0.15

0.95±0.00

44.86±2.09

0.66±0.06

10% Corn Stover
Enzyme
Hydrolysis

+ 1% Algal
Biomass
10% Corn Stover

The total nitrogen contents of the mixed enzymatic hydrolysate and corn stover enzymatic
hydrolysate were 1.2 g/L and 0.66 g/L, respectively. An extra 0.54 g/L of nitrogen was extracted from the
10%(w/w) corn stover hydrolysis with 1%(w/w) algal biomass added, which was higher than the nitrogen
concentration of the 10%(w/w) algal hydrolysate. The nitrogen in the corn stover could be the reason for

22

the higher nitrogen concentration. This experiment showed that it is beneficial to hydrolyze a mixture of
corn stover and algal biomass. The addition of the algal biomass did not show significant inhibition of the
sugar production due to hydrolysis. The extra nitrogen showed that the mixed hydrolysate could be
potentially used for fungal culture without an extra nitrogen source such as yeast extract.

2.4.3 Fungal culture in different hydrolysates
Table 3. Sugar consumption rate for different media

Medium
number
(#)
1
2
3
4
5

Total sugar at
Detatil
beginning (g/L)
corn stover hydrolysate
43.08
corn stover hydrolysate with yeast extract
42.33
corn stover hydrolysate with algal biomass hydrolysate
39.18
corn stover and algal biomass mixture hydrolysate
39.76
control with pure sugar
35.12

Time when total
sugar is lower
than 5g/L (day)
5
6
5
6
3

Sugar
consumption
rate (g/L*day-1)
7.74
6.51
7.14
6.16
10.84

Table 3 shows the sugar consumption rate for different media. The control medium had the best sugar
consumption rate due to the absence of inhibitors generated during hydrolysis.
With all of the media, glucose was consumed first. On the first day, which comprised the lag phase of
the fungal culture, both glucose and xylose consumption were low. On the second day, the glucose
consumption rate peaked, and the peak xylose consumption rate occurred on the third day when glucose
became limited. Acetate was consumed simultaneously with glucose. At the end of the fermentation, all
of the sugars in each medium were consumed by the fungus. The sugar utilization trend was similar with
all media. Since control medium contained no inhibitors, it had the highest sugar consumption rate and
was the first in which all of the available sugar was consumed.

23

Figure 4. Carbon source consumption by the fungal culture on (a) corn stover hydrolysate, (b) corn
stover hydrolysate with yeast extract, (c) corn stover hydrolysate with algal biomass hydrolysate, (d) corn
stover and algal biomass mixed hydrolysate, (e) control with pure sugar

a
Concentration (g/L)

30
25
20
15
10
5
0
0

1

2

3

4

5

6

7

8

Time (day)
Glucose (g/L)

Xylose (g/L)

Acetate (g/L)

b
Concentration (g/L)

30
25
20
15
10
5
0
0

1

2

Glucose (g/L)

3

4
Time (day)
Xylose (g/L)

24

5

6

Acetate (g/L)

7

8

Figure 4 (cont’d)

c
Concentration (g/L)

30
25
20
15
10
5
0
0

1

2

3

Glucose (g/L)

4
Time (day)

5

6

Xylose (g/L)

7

8

Acetate (g/L)

d
Concentration (g/L)

30
25
20
15
10
5
0
0

1

2

Glucose (g/L)

3

4
Time (day)
Xylose (g/L)

25

5

6

Acetate (g/L)

7

8

Figure 4 (cont’d)

e
Concentration (g/L)

30
25
20
15
10
5
0
0

1

2

3

4

5

6

7

8

Time (day)
Glucose (g/L)

Xylose (g/L)

Acetate (g/L)

The lipid content of the biomass is shown in Figure 5. No significant difference (P-value = 0.8518,
for a detailed statistical analysis, see Appendix B.2) of the lipid concentration occurred in any of the
treatments. The highest lipid concentration was found in medium 5 (34.2%), and the lowest was found in
medium 4 (29.5%).

Lipid Concentration (g lipid/g
biomass)

Figure 5. Lipid concentration (g lipid/g biomass) in biomass using different culture media

45%
40%
35%
30%
25%
20%
15%
10%
5%
0%

26

The biomass yield (g biomass produced/ g sugar consumed) and the lipid yield (g lipid produced/ g
sugar consumed) were calculated after the experiment based on biomass/lipid production and sugar
consumption.
Medium 3 (corn stover hydrolysate and algal biomass hydrolysate) had the highest biomass yield
(0.45 g biomass/ g sugar), which was significantly higher than in medium 1 (corn stover hydrolysate
alone) (0.35 g biomass/ g sugar) and the control (0.35 g biomass/g sugar). A comparison of medium 2 to
medium 3 indicated no significant differences in biomass yield if an algal biomass hydrolysate or yeast
extract was used as the nitrogen source for fermentation. The addition of an algal biomass to corn stover
and hydrolyzing the mixture did not significantly affect the biomass yield. This could be a new approach
for preparing a fungal medium in the future since it simplified the process.
None of the media showed a significant difference in lipid yield (P-value= 0.5767, for a detailed
statistical analysis, see Appendix B.2). The algal enzymatic hydrolysate could be a replacement for yeast
extract because the same lipid production was achieved. Furthermore, mixing corn stover and algal
hydrolysate did not affect the fungal lipid yield.

27

Figure 6. Biomass yield and lipid yield (g/g total sugar consumed) on different medium

50%
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%

Biomass Yield (g biomass/ g sugar consumption)
Lipid Yield (g lipid/ g sugar consumption)

2.5

Conclusion
This study demonstrated that U. isabellina ATCC 42613 can utilize an acid pre-treated algal

hydrolysate as a nitrogen source, and it can replace the yeast extract in a cell culture. The use of the algal
biomass has no negative influence on the lipid concentration. In addition, no inhibition was detected in a
culture that had algal hydrolysate as the nitrogen source. By hydrolyzing a mixture of algal biomass and
corn stover, the hydrolysate can be directly used for cell culture without an external nitrogen source. The
fungi cultured on the mixed hydrolysate showed a similar sugar utilization trend to the corn hydrolysate
medium with yeast extract. In the future, algal hydrolysis using different hydrolysis methods should be
tested to archive a higher nitrogen recovery rate. Additionally, the addition of algal hydrolysate to
different microbial cultures should be tested. Other sources such as other algae strains, a mixed culture of
algae, and the biomass collected from an algal bloom should be used for algal hydrolysate production.

28

Chapter 3. A high-efficiency extraction approach to recover lipids
from the oleaginous fungus Umbelopsis isabellina
3.1

Abstract
An increasing demand for alternative energy sources has brought much current attention to biofuel.

Umbelopsis isabellina, an oleaginous fungal strain, was considered as a potential biofuel producer due to
its ability to use sugars in a non-detoxified, acid pretreated corn stover hydrolysate. The Bligh & Dyer
lipid extraction method that uses highly toxic and dangerous solvents has been suggested for use as the
extraction method. This method is difficult to scale up due to the solvent properties. In this study, a
method using the less toxic solvent hexane was studied as a replacement for the Bligh & Dyer method. By
shaking the ground biomass with hexane in three stages, this method could achieve same lipid content as
the Bligh & Dyer method. The lipid profile of the extract is also comparable with that from the Bligh &
Dyer method. This method could be used as an extraction method for the fungus Umbelopsis isabellina.

3.2

Introduction
An increasing demand for alternative energy sources has brought much current attention to biofuel

because it is carbon neutral and can be produced from a renewable feedstock. However, biodiesel
production from vegetables and other plant-based sources potentially has negative environmental impacts
for various reasons, including excessive land use for large scale production and massive greenhouse gas
emission during land conversion (Shay 1993; Joseph Fargione 2008). Biodiesel derived from lipids from
microorganisms such as fungi, algae and bacteria can be sustainably produced because they require less
land use, do not cause food source competition, and have a high lipid content (Meng et al. 2009). In
addition to biodiesel production, other value-added products such as PUFAs, and essential fatty acids for
humans and animals can be generated from these microorganisms. Fungi are the predominant
microorganisms for PUFA production compared to algae, bacteria, and yeasts (C 1993). Furthermore,

29

fungi also has the most rapid biomass accumulation compared to algae and bacteria (Colin Ratledge and
Wynn 2002). Fungi have the potential for high-value lipid production, and our previous studies showed
that the fungal strain Umbelopsis isabellina (previously known as Mortierella isabellina) can utilize
lignocellulosic material and convert the carbon source in corn stover hydrolysate to lipids in the presence
of inhibitors such as furfural and hydroxymethylfurfural (HMF). Demonstrating that this fungal strain can
produce lipids from a renewable carbon source caused the use of fungal lipids for biodiesel and other
high-value fatty acids productions to become more realistic (Ruan et al. 2012). Since different extraction
methods performs differently for different microorganisms, the discovery of a highly efficient,
economically feasible, and environmentally friendly extraction method is essential for microbial biodiesel
production and necessary for the further development of this particular fungal strain (Medina et al. 1998;
Forfang et al. 2017).
Lipids can be extracted from biomass in several different ways - organic solvent extraction,
supercritical fluid extraction, organic solvent extraction with a Soxhlet apparatus (Soxhlet 1879),
ultrasound-assisted organic solvent extraction, and microwave-assisted organic solvent extraction. None
of these methods are very scalable due to the complicated extraction setup or the large amount of organic
solvents required. Organic solvent extraction is the traditional extraction method that is widely used in
many laboratories (Halim, Danquah, and Webley 2012). Several organic solvent methods are generally
used for the extraction of microbial lipids: The Bligh & Dyer method uses methanol and chloroform (E.
G. Bligh 1959), the Atsushi method uses hexane & isopropanol (Hara and Radin 1978), the Soxhlet
method uses hexane (Soxhlet 1879), and the Jordi method uses methanol and chloroform (Folch, Lees,
and Sloane Stanley 1957). The extraction methods vary for different biomasses. For example,
dichloroethane-based organic solvent mixtures show excellent potential for the algae Cladofora.
However, limitations were found when this method was applied to the algae B. braunii (Halim, Danquah,
and Webley 2012). Therefore, the discovery of the appropriate extraction method for a specific
microorganism for biodiesel production is essential. For the lipid extraction of Umbelopsis isabellina

30

biomass, our previous study suggested that the Bligh & Dyer method was better than the hexane &
isopropanol method, the CH2Cl2 & methanol method, and the hexane method (Hussain et al. 2014).
However, the solvents used in this method are highly toxic and a large quantity of solvents is required
(Halim, Danquah, and Webley 2012). Furthermore, this method showed high variation when conducted in
different labs (Manirakiza, Covaci, and Schepens 2001). Therefore, the discovery of an alternative lipid
extraction method which uses a less toxic solvent, and has an easier and more stable procedure, is
essential for the further development of fungal lipid production. Hexane is the most widely used solvent
for oil extraction in industry for primary oil seeds such as soybeans and canola seeds. Compared to the
chloroform and methanol used in the Bligh & Dyer method, hexane is less toxic and more
environmentally friendly (Capello, Fischer, and Hungerbuhler 2007). Furthermore, hexane can be
evaporated and condensed after extraction, then reused in the next round of extraction. In the economic
feasibility report of Delmer L. Helgeson, large-sized extraction equipment from 500 tons to 2000 tons per
day was surveyed, and hexane was used as the primary extraction solvent. (Helgeson, D., D. Cobia, R.
Coon, W. Hardie, L. Schaffner 1977).
Hexane therefore plays a major role as a solvent in industrial extraction methods. The development of
an efficient, and stable extraction method for fungal biomass could contribute to the development of
biodiesel production from oleaginous fungi.

3.3

Material and methods

3.3.1 Fungal culture
The fungal strain used for this experiment was U. isabellina ATCC 42613. U. isabellina spores
were cultured on potato dextrose agar (Sigma, USA) at 30°C for 14 days, washed with sterile distilled
water, and stored at 4°C. To generate the seed for the culture, 1 mL of spore solution (4.2×107 spore·mL1

) was first cultured for two days in 100 mL medium with 24 g/L potato dextrose broth and 8 g/L yeast

extract as a seed for fermentation. Seed inoculum was added at 10% to a 7.5 L New Brunswick Bioflo

31

115 fermenter with 4.0 L of fermentation medium and cultured at 1 vvm and 25°C for 4 days. The
fermentation medium included 20 g/L glucose, 20 g/L xylose, 4 g/L acetate, 1 g/L furfural and 1 g/L
HMF to mimic a pretreated corn stover hydrolysate. The biomass was collected After each batch was
cultured using a centrifuge and washed three times with DI water (Beckman, Allegra X-12R). The
washed biomass was then oven-dried for 24 hours at 100°C. Several batches of culture were harvested to
accumulate enough biomass for the experiment. The biomass from each batch was mixed and ground with
a Waring Blender and then stored at room temperature in a sealed bottle for future use.

3.3.2 Lipid extraction
The biomass and hexane were mixed in different gram to milliliter ratios in a 2 mL Denvile
microtube. Three ratios were tested in this study (1:4, 1:8, and 1:12). The tubes were shaken on an
Innova 2000 platform shaker for various amounts of time (1 minute, 3 minutes, 5 minutes, 10 minutes, 20
minutes, 60 minutes, and 1800 minutes) at room temperature. The shaking speed used for this experiment
was 400rpm. After shaking, the samples were centrifuged at 13000 rpm for 5 minutes using an Eppendorf
Refrigerated Microcentrifuge (5417R). After centrifugation, the supernatant, which contained hexane and
extracted lipid, was poured onto pre-weighed aluminum trays and dried in a fume hood overnight. The
weight of the aluminum trays and lipid was measured after the hexane was evaporated to determine the
mass of the lipid extracted.
The process was also studied for multiple extraction stages. To perform the second and third
stage, the same amount of hexane was added to the biomass left in the microtube after it was centrifuged
and the supernatant was removed, and same methods were repeated. After each stage, the hexane layer
was poured into the same aluminum tray so that all of the lipid extracted from one sample could be
accumulated and recorded.
To test on a larger scale with a larger amount of biomass, 1 g of biomass and 4 mL hexane were
mixed in a 50 mL centrifuge tube and shaken on the shaker. Two layers were formed After shaking, the

32

hexane layer and a solid layer. The hexane layer was transferred to several Denvile microtubes using a 1
mL pipette, and the settled solids were left in the tube and dried. The microtubes were centrifuged for five
minutes in the microcentrifuge to separate the liquid and solid. The supernatants from all of the tubes that
contained the same sample were poured into the same aluminum tray, and the solid was dried and
transferred back to the original 50 mL centrifuge tube for the next stage of extraction. The same amount
of hexane was added for the second and third stages, and the same protocols for mixing and separation
were employed. The liquid fraction, containing lipid and solvent in the aluminum trays, was dried in the
fume hood overnight and then weighed to determine the total lipid concentration. The Bligh & Dyer
method with a modified methanol: chloroform: water ratio of 2:1:0.8 (v/v/v) was conducted as a positive
control and the total lipid content of the same biomass was determined (Bligh and Dyer 1959).

3.3.3 Lipid profile
Fatty acid methyl ester (FAME) synthesis was used to analyze the fatty acid profile of the lipids
extracted by the various methods. The lipids were first treated with a conventional transesterification
procedure to form FAMEs. The lipids were treated with methanol, sulfuric acid, and chloroform. The
chloroform layer, which included the FAMEs, was collected and stored at -18°C for GC–MS analysis
(Indarti et al. 2005). A Thermo GC-MS equipped with an Agilent DB-23 column (30 m, 0.25 mm, 0.25
µm, 7-inch cage) was used to analyze the fatty acids. The standard used for this analysis was a Supelco 37
Component FAME Mix.

3.3.4 Statistical analysis
Statistical analysis was performed by using the Minitab Express 2016. A two sample t test and a one-way
ANOVA was chosen for the treatment comparisons for each dataset. The confidence level was 95%.

33

3.4

Results and discussion

3.4.1 Comparison of lipid extraction using different extraction methods
Figure 7. Lipid concentration of same fungal biomass using different extraction methods

concentration (g lipid/ g biomass)

60.0%
50.0%
40.0%
30.0%
20.0%
10.0%
0.0%

Bligh & Dyer

Hexane w/o shaking

Hexane w/ shaking

Methods

The Bligh & Dyer method was conducted to determine the total extractable lipids in the biomass. The
lipid yield was 54.2±3%. Two experiments using hexane as the solvent were performed and compared
with the Bligh & Dyer method, one with and one without shaking using the same hexane ratio (1:4).
Shaking the mixture significantly increased the lipid yield from 27.0±1.7% to 34.3±1.3%. This
experiment showed that hexane extraction has the potential to extract part of the lipids but not 100% of
the total extractable lipids. It did however demonstrate that hexane had the potential to extract some of the
lipids and that mixing is critical for lipid extraction with hexane. The shaking time, the extraction
protocol, and the biomass to hexane ratio were optimized in future experiments.

3.4.2 Optimization of the hexane extraction method
The biomass and hexane were mixed in three ratios (1:4, 1:8 and 1:12) and shaken at 400 rpm for
various amounts of time (1 minute, 3 minutes, 5 minutes, 10 minutes, 20 minutes, 60 minutes and 1800

34

minutes). As the shaking time increased, the lipid yield increased from 27.1% to 40.0% for the 1:4 ratio,
33.4% to 48.1% for the 1:8 ratio, and 32.5% to 50.3% for the 1:12 ratio. The standard fungal lipid
extraction method (i.e., the Bligh and Dyer method) was conducted on the same biomass and the lipid
yield was 54%±2.5%. The lipid ratio increased rapidly during the first five minutes of shaking time. After
the first five minutes, the lipid yield exhibited a lag phase. From five minutes to sixty minutes, the lipid
content remained steady for the 1:4 and 1:8 ratios. As the mixing time increased, the extracted lipid yield
increased. For all of the ratios, 1800 minutes of shaking was best. A larger amount of lipids were
extracted with a higher amount of solvent. The 1:8 biomass: hexane ratio had the highest lipid yield at
five minutes, No significant differences were seen between the 1:8 and the 1:12 ratios. No significant
difference was found between the 1:4 and 1:12 ratios (for a detailed statistical analysis, see Appendix
B.3). The 1:4 ratio was chosen for future experiments because it had a good lipid extraction yield and
required the least amount of hexane, and all three ratios extracted more than half of the lipids extracted by
the Bligh & Dyer method.
Although the 1:12 biomass: hexane ratio showed a comparable result after 1800 minutes, the long
extraction time, and the energy consumed by the shaking was not ideal. Therefore, hexane cannot extract
as much lipid as the Bligh & Dyer method in a one stage extraction. However, the lipid yield showed that
a hexane extraction solvent could eventually achieve a yield comparable to the Bligh & Dyer method. To
shorten the extraction time and achieve a similar or even higher yield than the Bligh & Dyer method,
multiple stage extraction was considered as the next step. The inspiration for multiple stage extraction
came from Soxhlet method, in which hexane is evaporated and then condensed to continuously wash the
biomass so that during the extraction period, the biomass contacts the hexane, but not the lipid.

35

Figure 8. The effects of different biomass: hexane ratios and extraction time on lipid yield
60.0%
1 min

50.0%

3 mins

Lipid Yield

40.0%

5 mins
10 mins

30.0%

20 mins
20.0%

60 mins
1800 mins

10.0%

Bligh and Dyer
0.0%
1:04

1:08
Biomass:Hexane Ratio

1:12

To further increase the yield, the extraction processes was performed in three stages. Since the first
stage could extract more than half of the lipid; it was important to ensure that the highest yield was
achieved in a short time. Four first stage mixing times (1 minute, 5 minutes, 10 minutes, and 20 minutes)
were tested, followed by two stages of extraction for 5 minutes. The biomass: hexane ratio was 1:4 for all
three of these stages. Figure 9 shows the lipid yield from the first stage, which was processed for 1 minute
and was significantly lower than the yield after 5, 10, or 20 minutes of extraction. No significant
difference was found for 5, 10, and 20 minutes for the first stage extraction (for a detailed statistical
analysis, see Appendix B.3), and no significant difference was found for 1, 5, 10, 20 minutes for second
stage lipid yields (P-value=0.0936, for a detailed statistical analysis, see Appendix B.3). After the second
and third stages, the final lipid yield for those four experiments was respectively 47%, 49%, 50%, and
50% and t no significant difference was found for any treatments (P-value=0.2944, for a detailed
statistical analysis, see Appendix B.3).

36

Figure 9. Staged extraction of different first stage extraction times

Lipid Yield (g lipid/ g biomass)

60.00%
First Stage Yield

50.00%

Second Stage Yield

40.00%

Third Stage Yield

30.00%
* Second & third
stage time: 5
minutes each

20.00%
10.00%
0.00%
1

5
10
20
First Stage Time (minute)

Since there was no significant difference in the final lipid yield for 1, 5, 10, and 20 minutes, 5
minutes was selected for the first stage. The reason 5 minutes was chosen instead of 1 minute was that
more lipids were extracted after 5 minutes than 1 minute. This could help when applied to a biomass
with a higher lipid content. In addition, because all three stages of extraction repeated the same
protocol for the same time, it was easier to conduct the experiment. After three extraction stages of 5
minutes each, this multiple stages extraction method extracted over 90% of the lipids extracted by the
Bligh & Dyer method.

37

3.4.3 Three stage extraction with a larger amount of biomass
Figure 10. Scaling up the three stage hexane extraction

Concentration (g lipid/ g biomass)

58%
56%
54%
52%
50%
48%
46%
44%

3 Stage Hexane Extraction3 Stage Hexane Extraction
with 0.1g Biomass
with 1g Biomass

Bligh & Dyer

Method

After extracting 0.1 g biomass, a larger amount of biomass (1 g) was tested for verification,
because 0.5 g biomass was used for the Bligh & Dyer method since it is difficult to perform
accurately on a smaller scale. The lipid yield after three stages of extraction increased as the biomass
amount increased. The final yield of hexane method showed no significant differences from the Bligh
& Dyer yield (P-value=0.9099, for a detailed statistical analysis, see Appendix B.4). The method also
showed less variation between the three replicates. A possible explanation for the increase in the
lipids extracted from 50% to 54% is that the mixing was likely more effective in the 1 g experiment
because the sample was in a 50 mL centrifuge tube. It appeared that a larger tube size and a larger
head space for the mixture allowed the biomass and hexane to mix better. Therefore, the three-stage
extraction method can extract the same amount of lipid as the Bligh & Dyer method for the fungus U.
isabellina biomass.

38

3.4.4 Fatty acid profile of the extracted lipids
Figure 11. Fatty acid profiles for different extraction methods: (a) major fatty acids; (b) C16 and C18; (c)
Saturated fatty acids and unsaturated acids

a
70%

Concentration (g/ g lipid)

60%
50%

3 Stage Hexane
Method

40%
30%

Bligh & Dyer
Method

20%
10%
0%
C16:0

C18:0
Major Fatty Acids

C18:1

b

Concentration (g/g lipid)

70%
60%
50%

3 Stage Hexane
Method

40%
30%

Bligh & Dyer
Method

20%
10%
0%
C16
C18
Major Fatty Acid Group

39

Figure 11 (cont’d)

c
70%

Concentration (g/g lipid)

60%
50%
3 Stage Hexane
Method

40%
30%
20%

Bligh & Dyer
Method

10%
0%
Saturated Fatty Acids

Unsaturated Fatty
Acids
Fatty Acids

Different fatty acids were analyzed using the FAME method to determine differences between
solvents for fatty acid extraction. In Figure 11, different fatty acid profiles were analyzed for these two
methods. Compared with Bligh & Dyer, no significant differences were found for the two methods for the
extraction of the major fatty acids: C16:0 (P-value=0.1287, for a detailed statistical analysis, see
Appendix B.5), C18:0 (P-value=0.0990, for a detailed statistical analysis, see Appendix B.5), and C18:1
(P-value=0.0635, for a detailed statistical analysis, see Appendix B.5). Oleic acid (C18:1) was the most
abundant fatty acid, followed by Palmitic acid (C16:0) and stearic acid (C18:0). The lipid profile was
comparable with our previous study (Ruan et al. 2012). Additionally, as seen in Fig. 11b, no significant
differences were seen for C16 (P-value=0.1432, for a detailed statistical analysis, see Appendix B.5) and
C18 (P-value=0.1425, for a detailed statistical analysis, see Appendix B.5), which are the major carbon
chains for biodiesel production. Additionally, no significant differences were seen for saturated (P-

40

value=0.1009, for a detailed statistical analysis, see Appendix B.5) and unsaturated fatty acids (Pvalue=0.1028, for a detailed statistical analysis, see Appendix B.5) (Fig. 11c).

3.5

Conclusion
This study demonstrated that three-stage extraction process with hexane can be to extract lipids the

fungus U. isabellina. This method is easier to conduct and more environmentally friendly compared to the
standard fungal lipid extraction method of Bligh & Dyer. This study only tested 0.1 g and 1 g of biomass.
When this method was applied to 0.1 g of biomass, over 90% of lipid was extracted compared to the
Bligh & Dyer method. This approach could be helpful when not much biomass is available and only a
rough estimate of the lipid yield is required. When applied to 1 g of biomass, the lipid yield achieved the
same level as the Bligh & Dyer method with a lower standard deviation. This study demonstrated that
hexane could be used to extract lipids from U. isabellina. In the future, larger amounts of biomass should
be tested, as well as the reuse of hexane, and eventually an industry level reactor could be used with U.
isabellina biomass. This could potentially make biofuel products extracted from U. isabellina biomass
more feasible because hexane extraction is currently a mature industrial technology.

41

Chapter 4. Conclusion and future work
4.1

Conclusion.
U. isabellina, a filamentous oleaginous fungus, can utilize non-detoxified corn stover hydrolysate for

lipid production. To further promote this strain as feasible for the production of high-value biofuel
products, an economical and abundant substrate, and a highly efficient, environmentally friendly
extraction method are required
A low lipid content algal biomass was mixed with corn stover, pre-treated with acid, and
enzymatically hydrolyzed. The hydrolysate could provide a nitrogen source for fungal growth and the
addition of algal biomass did not inhibit growth. Since no significant differences in lipid production were
found for the algal hydrolysate and yeast extract as a nitrogen source, this approach could save the
expense of an external nitrogen source for fungal culture. The substrate cost was also reduced.
Additionally, the results of this study suggest that the algal hydrolysate can be sold as a nitrogen
supplement for microbial culture, which would make algal biofuel products more economically practical.
Lipid extraction was another critical process in fungal lipid production that was studied in this
research. The most popular laboratory method is the Bligh & Dyer method, which is a complex method
using two solvents. To simplify the process, this study revealed that a three-stage extraction method that
used hexane alone can replace of the Bligh & Dyer method for the lipid extraction of U. isabellina
biomass. This method can extract the same amount of lipid as the Bligh & Dyer method for 1 g of
biomass. Using hexane as the only solvent is desirable due to less environmental impact and a less
potential for human error compared to the Bligh & Dyer method. Furthermore, pilot scale extraction
systems for major oil seed extraction using hexane already exist in industry (Ayorinde et al. 1990).

42

4.2

Future work
The following future studies may be useful for microbial lipid production with fungal fermentation.
1. Optimization of algal hydrolysis with different hydrolysis methods to achieve a high nitrogen
content and the application of the hydrolysate to different microbes.
2. Investigation of different algae strains, mixed algal cultures, or biomass collected from an algal
bloom for algal hydrolysate production.
3. A scale-up of the fungal extraction to an industrial level reactor and an energy balance analysis
for multi-stage hexane extraction.

43

APPENDICES

44

APPENDIX A: DATA

Chapter 2 Data
Table 4. Algae concentration for figure 3
Time (h)

Dry Biomass (g/L)
0.0
0.4
24.2
24.8
48.0
48.5
72.0
72.5
96.0
96.4
120.0
120.4
144.0
168.0
168.4
192.0
192.5
216.0
216.5
240.0
240.4
264.0
264.4
288.0
288.4
312.0
312.4
336.0
336.4
360.0
360.4
384.0
384.5
408.0
408.4
432.0
432.4

2.39
1.85
1.74
1.43
1.32
1.08
1.16
0.98
1.30
1.06
1.44
1.16
1.53
1.76
1.42
1.72
1.35
1.63
1.31
1.57
1.28
1.67
1.34
1.71
1.35
1.69
1.33
1.64
1.29
1.52
1.18
1.48
1.23
1.48
1.19
1.49
1.18

45

Table 5. Sugar concentration data for figure 4
Time (Day)

0

1

5

6

7

22.41
15.42
1.48
39.31
21.52
14.59
1.42
37.54
17.44
12.41
1.26

2
3
4
Sugar Concentration (g/L)
11.62
3.24
0.30
14.67
10.60
7.81
0.00
0.14
0.00
26.29
13.98
8.10
11.98
3.19
0.94
14.40
15.87
7.80
0.05
0.63
0.00
26.43
19.69
8.74
8.46
0.76
0.33
12.69
9.86
5.94
0.05
0.37
0.00

Glucose (g/L)
Xylose (g/L)
Acetate (g/L)
Total
Glucose (g/L)
Xylose (g/L)
Acetate (g/L)
Total
Glucose (g/L)
Xylose (g/L)
Acetate (g/L)

25.28
15.61
2.20
43.08
24.97
15.19
2.17
42.33
22.98
14.18
2.02

0.00
4.41
0.00
4.41
0.00
7.10
0.00
7.10
0.04
3.43
0.00

0.00
1.09
0.00
1.09
0.00
3.26
0.00
3.26
0.00
0.53
0.00

0.00
0.00
0.00
0.00
0.00
0.66
0.00
0.66
0.00
0.00
0.00

Total
Glucose (g/L)
Xylose (g/L)
Acetate (g/L)

39.18
23.51
14.17
2.08

31.11
20.68
13.98
1.46

21.20
11.71
13.78
0.00

11.00
3.71
10.19
0.22

6.27
0.98
7.97
0.00

3.46
0.00
6.36
0.00

0.53
0.00
2.75
0.00

0.00
0.00
0.59
0.00

Total
Glucose (g/L)
Xylose (g/L)
Acetate (g/L)
Total

39.76
21.17
13.27
0.69
35.12

36.12
16.88
14.09
0.00
30.97

25.48
0.00
10.66
0.00
10.66

14.12
0.00
2.59
0.00
2.59

8.95
0.00
0.00
0.00
0.00

6.36
0.00
0.00
0.00
0.00

2.75
0.00
0.00
0.00
0.00

0.59
0.00
0.00
0.00
0.00

Medium

Corn Stover
Hydrolysate
Corn Stover
Hydrolysate
with Yeast
Extract
Corn Stover
Hydrolysate
with Algal
Biomass
Hydrolysate
Corn Stover
And Algal
Biomass
Mixture
Hydrolysate

Control with
Pure Sugar

46

Table 6. Lipid concentrations and standard deviations for figure 5

Lipid Concentration
(g lipid/g biomass)

Standard Deviation

Medium 1

33.24%

7.92%

Medium 2

31.13%

2.71%

Medium 3

32.60%

0.95%

Medium 4

30.84%

4.18%

Medium 5

34.22%

8.61%

47

Table 7. Biomass yield and lipid data for figure 6

Biomass Yield (g
biomass/ g sugar
consumption)

Lipid Yield
(g lipid/ g sugar
consumption)

Biomass Yield
Standard Deviation

Lipid Yield
Standard Deviation

Medium 1

34.90%

11.71%

2.80%

3.42%

Medium 2

41.24%

12.85%

1.80%

1.51%

Medium 4

42.99%

12.69%

2.16%

1.51%

Medium 3

44.98%

14.66%

1.33%

0.34%

Medium 5

34.64%

11.93%

1.39%

3.38%

48

Chapter 3 Data
Table 8. Lipid yield and standard deviation data for figure 7

Lipid Yield
(g lipid/ g biomass)

Lipid Yield Standard
Deviation

0.1g Biomass Extraction

50.25%

1.14%

1g Biomass Extraction

54.41%

0.95%

Bligh & Dyer

53.64%

2.51%

49

Table 9. Lipid yield and standard deviation for figure 8

Ratio

Time

1:04

1:08

1:12

Average Lipid Yield
(g lipid/ g biomass)

1:04

1:08

1:12

Standard Deviation

1 min

27.06%

33.45%

32.52%

1.68%

0.68%

1.04%

3 mins

31.44%

31.55%

37.45%

0.70%

1.12%

2.09%

5 mins

34.31%

39.25%

36.62%

1.29%

1.73%

0.33%

10 mins

35.10%

39.97%

41.91%

1.93%

3.23%

0.36%

20 mins

35.76%

41.25%

42.44%

1.38%

2.39%

1.19%

60 mins

37.10%

41.92%

41.32%

1.71%

2.41%

2.74%

1800 mins

40.03%

48.06%

50.35%

1.10%

1.36%

0.53%

Bligh and Dyer

54.20%

54.20%

54.20%

2.51%

2.51%

2.51%

50

Table 10. 3 stage lipid yields for different first stage reaction time (figure 9)

First Stage Time
(minute)

1

5

10

20

Lipid Yield (g lipid/ g biomass)
First Stage Yield

27.06%

34.31%

35.10%

35.76%

Second Stage Yield

42.04%

44.25%

45.97%

45.49%

Third Stage Yield

47.15%

49.26%

50.34%

49.62%

51

Table 11. Scale up lipid yield data for figure 10

3 Stage Hexane Extraction
with 0.1g Biomass
Lipid Yield (g lipid/ g biomass)
Standard Deviation

3 Stage Hexane Extraction
with 1g Biomass

Bligh & Dyer

50.03%

53.99%

54.20%

1.14%

0.95%

2.51%

52

Table 12. Fatty acid profile data for figure 11

Graph

a

b

c

C16:0

C18:0

C18:1

C16

C18

Saturated
Fatty
Acids

3 Stage Hexane
Method

33.74%

9.50%

49.69%

35.10%

60.72%

43.24%

52.58%

Bligh & Dyer
Method

36.02%

10.60%

45.69%

37.15%

58.49%

46.62%

49.01%

Hexane Method
Standard Deviation

1.09%

0.24%

1.12%

1.00%

1.00%

1.33%

1.33%

Bligh & Dyer
Method Standard
Deviation

1.55%

0.60%

2.13%

1.50%

1.68%

2.12%

2.30%

53

Unsaturated
Fatty Acids

APPENDIX B: STATISTICAL ANALYSIS

B1. Statistical analysis for different sugar concentration (glucose, xylose, acetate,
and total sugar) of hydrolysate in chapter 2 section 2.4.2
Table 13. Data for appendix B1

Hydrolysate

Glucose (g/L)

Xylose (g/L)

Acetate (g/L)

Total Sugar
(g/L)

Corn Stover Hydrolysate

25.28

16.4

0.93

42.61

Corn Stover Hydrolysate

26.6

16.19

0.91

43.69

Corn Stover Hydrolysate

24.53

17.11

0.97

42.6

Corn Stover + Algal Biomass Hydrolysate

28.32

17.61

0.95

46.88

Corn Stover + Algal Biomass Hydrolysate

26.72

17.32

0.95

44.99

Corn Stover + Algal Biomass Hydrolysate

24.35

17.4

0.96

42.71

54

2-Sample t: Glucose by Hydrolysate
Method
µ₁: mean of Glucose when Hydrolysate = Corn Stover + Algal Biomass Hydrolysate
µ₂: mean of Glucose when Hydrolysate = Corn Stover Hydrolysate
Difference: µ₁ - µ₂
Equal variances are not assumed for this analysis.
Descriptive Statistics: Glucose
Hydrolysate

N

Mean

StDev

SE Mean

Corn Stover + Algal Biomass Hydrolysate

3

26.463

1.997

1.153

Corn Stover Hydrolysate

3

25.4700

1.0480

0.6051

Estimation for Difference
Difference

95% CI for Difference

0.993

(-3.151, 5.138)

Test
Null hypothesis

H₀: µ₁ - µ₂ = 0

Alternative hypothesis

H₁: µ₁ - µ₂ ≠ 0

T-Value

DF

P-Value

0.76

3

0.5011

55

2-Sample t: Xylose by Hydrolysate
Method
µ₁: mean of Xylose when Hydrolysate = Corn Stover + Algal Biomass Hydrolysate
µ₂: mean of Xylose when Hydrolysate = Corn Stover Hydrolysate
Difference: µ₁ - µ₂
Equal variances are not assumed for this analysis.
Descriptive Statistics: Xylose
Hydrolysate

N

Mean

StDev

SE Mean

Corn Stover + Algal Biomass Hydrolysate

3

17.4433

0.14978

0.08647

Corn Stover Hydrolysate

3

16.5667

0.4821

0.2783

Estimation for Difference
Difference

95% CI for Difference

0.8767

(-0.3774, 2.1308)

Test
Null hypothesis

H₀: µ₁ - µ₂ = 0

Alternative hypothesis

H₁: µ₁ - µ₂ ≠ 0

T-Value

DF

P-Value

3.01

2

0.0950

56

2-Sample t: Xylose by Hydrolysate
Method
µ₁: mean of Xylose when Hydrolysate = Corn Stover + Algal Biomass Hydrolysate
µ₂: mean of Xylose when Hydrolysate = Corn Stover Hydrolysate
Difference: µ₁ - µ₂
Equal variances are not assumed for this analysis.
Descriptive Statistics: Xylose
Hydrolysate

N

Mean

StDev

SE Mean

Corn Stover + Algal Biomass Hydrolysate

3

17.4433

0.14978

0.08647

Corn Stover Hydrolysate

3

16.5667

0.4821

0.2783

Estimation for Difference
Difference

95% CI for Difference

0.8767

(-0.3774, 2.1308)

Test
Null hypothesis

H₀: µ₁ - µ₂ = 0

Alternative hypothesis

H₁: µ₁ - µ₂ ≠ 0

T-Value

DF

P-Value

3.01

2

0.0950

57

2-Sample t: Total Sugar by Hydrolysate
Method
µ₁: mean of Total Sugar when Hydrolysate = Corn Stover + Algal Biomass Hydrolysate
µ₂: mean of Total Sugar when Hydrolysate = Corn Stover Hydrolysate
Difference: µ₁ - µ₂
Equal variances are not assumed for this analysis.
Descriptive Statistics: Total Sugar
Hydrolysate

N

Mean

StDev

SE Mean

Corn Stover + Algal Biomass Hydrolysate

3

44.860

2.088

1.206

Corn Stover Hydrolysate

3

42.9667

0.6264

0.3617

Estimation for Difference
Difference

95% CI for Difference

1.893

(-3.522, 7.309)

Test
Null hypothesis

H₀: µ₁ - µ₂ = 0

Alternative hypothesis

H₁: µ₁ - µ₂ ≠ 0

T-Value

DF

P-Value

1.50

2

0.2714

58

B2. Statistical analysis for lipid concentration, biomass yield, and lipid yield of
different hydrolysate mediums (with control) in chapter 2 section 2.4.3

One-Way ANOVA: Lipid Con (g lipid/g biomass) versus Medium
Method
Null hypothesis

H₀: All means are equal

Alternative hypothesis

H₁: At least one mean is different

Equal variances were assumed for the analysis.
Factor Information
Factor

Levels

Medium

5

Values
control with pure sugar, corn stover and algal biomass mixture
hydrolysate, corn stover hydrolysate, corn stover hydrolysate with algal
biomass hydrolysate, corn stover hydrolysate with yeast extract

Analysis of Variance
Source

DF

Adj SS

Adj MS

F-Value

P-Value

4

0.0041067

0.00102667

0.33

0.8518

Error

10

0.0311333

0.00311333

Total

14

0.0352400

Medium

Model Summary
S

R-sq

R-sq(adj)

R-sq(pred)

0.0557973

11.65%

0.00%

0.00%

Means
Medium

N

Mean

StDev

control with pure sugar

3

0.34333

0.08963

(0.27155,
0.41511)

corn stover and algal biomass mixture
hydrolysate

3

0.29667

0.02517

(0.22489,
0.36845)

corn stover hydrolysate

3

0.33000

0.07810

(0.25822,
0.40178)

59

95% CI

corn stover hydrolysate with algal
biomass hydrolysate

3

0.330000

0.010000

(0.258221,
0.401779)

corn stover hydrolysate with yeast extract

3

0.31000

0.02646

(0.23822,
0.38178)

Pooled StDev = 0.0557973

60

One-Way ANOVA: Biomass Yield versus Medium
Method
Null hypothesis

H₀: All means are equal

Alternative hypothesis

H₁: At least one mean is different

Equal variances were assumed for the analysis.
Factor Information
Factor

Levels

Medium

5

Values
control with pure sugar, corn stover and algal biomass mixture
hydrolysate, corn stover hydrolysate, corn stover hydrolysate with
algal biomass hydrolysate, corn stover hydrolysate with yeast
extract

Analysis of Variance
Source

DF

Adj SS

Adj MS

F-Value

P-Value

4

0.02676

0.00669

16.73

0.0002

Error

10

0.00400

0.00040

Total

14

0.03076

Medium

Model Summary
S

R-sq

R-sq(adj)

R-sq(pred)

0.02

87.00%

81.79%

70.74%

Means
Medium

N

Mean

StDev

control with pure sugar

3

0.346667

0.015275

(0.320938,
0.372395)

corn stover and algal biomass mixture
hydrolysate

3

0.42667

0.02082

(0.40094,
0.45239)

corn stover hydrolysate

3

0.34667

0.03055

(0.32094,
0.37239)

corn stover hydrolysate with algal
biomass hydrolysate

3

0.450000

0.010000

(0.424272,
0.475728)

61

95% CI

corn stover hydrolysate with yeast extract

3

0.410000

0.017321

(0.384272,
0.435728)

Pooled StDev = 0.02
Grouping Information Using the Tukey Method and 95% Confidence
Medium

N

Mean

Grouping

corn stover hydrolysate with algal biomass hydrolysate

3

0.450000

A

corn stover and algal biomass mixture hydrolysate

3

0.42667

A

corn stover hydrolysate with yeast extract

3

0.410000

A

corn stover hydrolysate

3

0.34667

B

control with pure sugar

3

0.346667

B

Means that do not share a letter are significantly different.
Tukey Simultaneous Tests for Differences of Means
Difference
of Means

SE of
Difference

TValue

Adjusted
P-Value

corn stover and algal
biomass mixture
hydrolysate-control with
pure sugar

0.08000

0.01633

(0.02631,
0.13369)

4.90

0.0044

corn stover hydrolysatecontrol with pure sugar

0.00000

0.01633

(-0.05369,
0.05369)

0.00

1.0000

corn stover hydrolysate
with algal biomass
hydrolysate-control with
pure sugar

0.10333

0.01633

(0.04964,
0.15703)

6.33

0.0006

corn stover hydrolysate
with yeast extract-control
with pure sugar

0.06333

0.01633

(0.00964,
0.11703)

3.88

0.0201

corn stover hydrolysatecorn stover and algal
biomass mixture
hydrolysate

-0.08000

0.01633

(-0.13369,
-0.02631)

-4.90

0.0044

Difference of Levels

62

95% CI

corn stover hydrolysate
with algal biomass
hydrolysate-corn stover
and algal biomass
mixture hydrolysate

0.02333

0.01633

(-0.03036,
0.07703)

1.43

corn stover hydrolysate
with yeast extract-corn
stover and algal biomass
mixture hydrolysate

-0.01667

0.01633

(-0.07036,
0.03703)

-1.02

0.8405

corn stover hydrolysate
with algal biomass
hydrolysate-corn stover
hydrolysate

0.10333

0.01633

(0.04964,
0.15703)

6.33

0.0006

corn stover hydrolysate
with yeast extract-corn
stover hydrolysate

0.06333

0.01633

(0.00964,
0.11703)

3.88

0.0201

corn stover hydrolysate
with yeast extract-corn
stover hydrolysate with
algal biomass
hydrolysate

-0.04000

0.01633

(-0.09369,
0.01369)

-2.45

0.1791

Individual confidence level = 99.18%

63

0.6248

One-Way ANOVA: lipid yield versus Medium
Method
Null hypothesis

H₀: All means are equal

Alternative hypothesis

H₁: At least one mean is different

Equal variances were assumed for the analysis.
Factor
Information
Factor

Levels

Medium

5

Values
control with pure sugar, corn stover and algal biomass mixture
hydrolysate, corn stover hydrolysate, corn stover hydrolysate with
algal biomass hydrolysate, corn stover hydrolysate with yeast extract

Analysis of Variance
Source

DF

Adj SS

Adj MS

F-Value

P-Value

4

0.00169333

0.00042333

0.76

0.5767

Error

10

0.00560000

0.00056000

Total

14

0.00729333

Medium

Model Summary
S

R-sq

R-sq(adj)

R-sq(pred)

0.0236643

23.22%

0.00%

0.00%

Means

Medium

N

Mean

StDev

control with pure sugar

3

0.12000

0.03464

(0.08956,
0.15044)

corn stover and algal biomass mixture
hydrolysate

3

0.123333

0.015275

(0.092891,
0.153776)

64

95% CI

corn stover hydrolysate

3

0.11667

0.03215

(0.08622,
0.14711)

corn stover hydrolysate with algal
biomass hydrolysate

3

0.146667

0.005774

(0.116224,
0.177109)

corn stover hydrolysate with yeast
extract

3

0.130000

0.017321

(0.099558,
0.160442)

Pooled StDev = 0.0236643

65

B3. Statistical analysis for lipid yield of different hexane ratio at 5 minutes in
chapter 3 section 3.4.2

One-Way ANOVA: Lipid Yield versus Hexane ratio
Method
Null hypothesis

H₀: All means are equal

Alternative hypothesis

H₁: At least one mean is different

Equal variances were assumed for the analysis.
Factor Information
Factor

Levels

Values

3

4, 8, 12

Hexane ratio

Analysis of Variance
Source

DF

Adj SS

Adj MS

F-Value

P-Value

2

0.00650771

0.00325386

18.11

0.0003

Error

11

0.00197626

0.00017966

Total

13

0.00848397

Hexane ratio

Model Summary
S

R-sq

R-sq(adj)

R-sq(pred)

0.0134037

76.71%

72.47%

64.26%

Means
Hexane ratio

N

Mean

StDev

95% CI

4

6

0.343167

0.012881

(0.331123, 0.355211)

8

5

0.392000

0.016432

(0.378807, 0.405193)

12

3

0.366667

0.005774

(0.349634, 0.383699)

Pooled StDev = 0.0134037
Grouping Information Using the Tukey Method and 95% Confidence
Hexane ratio

N

Mean

Grouping

66

8

5

0.392000

A

12

3

0.366667

A

4

6

0.343167

B
B

Means that do not share a letter are significantly different.
Tukey Simultaneous Tests for Differences of Means
Difference of
Levels

Difference of
Means

SE of
Difference

TValue

Adjusted PValue

8-4

0.048833

0.008116

(0.026910,
0.070757)

6.02

0.0002

12-4

0.023500

0.009478

(-0.002101,
0.049101)

2.48

0.0727

12-8

-0.025333

0.009789

(-0.051774,
0.001107)

-2.59

0.0605

Individual confidence level = 97.94%

67

95% CI

One-Way ANOVA: First Stage (1/5/10/20minute) versus First
Stage Time
Method
Null hypothesis

H₀: All means are equal

Alternative hypothesis

H₁: At least one mean is different

Equal variances were assumed for the analysis.
Factor Information
Factor

Levels

First Stage Time

Values

4

1, 5, 10, 20

Analysis of Variance
Source

DF

Adj SS

Adj MS

F-Value

P-Value

3

0.0150754

0.00502513

21.97

<0.0001

Error

11

0.0025162

0.00022875

Total

14

0.0175916

First Stage Time

Model Summary
S

R-sq

R-sq(adj)

R-sq(pred)

0.0151245

85.70%

81.80%

71.64%

Means
First Stage Time

N

Mean

StDev

95% CI

1

3

0.270600

0.016802

(0.251381, 0.289819)

5

6

0.343167

0.012881

(0.329577, 0.356757)

10

3

0.35097

0.01928

(0.33175, 0.37019)

20

3

0.357533

0.013761

(0.338314, 0.376753)

Pooled StDev = 0.0151245
Grouping Information Using the Tukey Method and 95% Confidence
First Stage Time

N

Mean

Grouping

68

20

3

0.357533

A

10

3

0.35097

A

5

6

0.343167

A

1

3

0.270600

B

Means that do not share a letter are significantly different.
Tukey Simultaneous Tests for Differences of Means
Difference of
Levels

Difference of
Means

SE of
Difference

TValue

Adjusted PValue

5-1

0.07257

0.01069

(0.04035,
0.10478)

6.79

0.0002

10-1

0.08037

0.01235

(0.04317,
0.11757)

6.51

0.0002

20-1

0.08693

0.01235

(0.04973,
0.12413)

7.04

0.0001

10-5

0.00780

0.01069

(-0.02442,
0.04002)

0.73

0.8833

20-5

0.01437

0.01069

(-0.01785,
0.04658)

1.34

0.5566

20-10

0.00657

0.01235

(-0.03063,
0.04377)

0.53

0.9495

Individual confidence level = 98.82%

69

95% CI

One-Way ANOVA: Second Stage (5 minutes) versus First Stage
Time
Method
Null hypothesis

H₀: All means are equal

Alternative hypothesis

H₁: At least one mean is different

Equal variances were assumed for the analysis.
Factor Information
Factor

Levels

First Stage Time

Values

4

1, 5, 10, 20

Analysis of Variance
Source

DF

Adj SS

Adj MS

F-Value

P-Value

3

0.00278307

0.00092769

2.74

0.0936

Error

11

0.00371934

0.00033812

Total

14

0.00650241

First Stage Time

Model Summary
S

R-sq

R-sq(adj)

R-sq(pred)

0.0183881

42.80%

27.20%

0.00%

Means
First Stage Time

N

Mean

StDev

95% CI

1

3

0.42040

0.02219

(0.39703, 0.44377)

5

6

0.442467

0.017232

(0.425944, 0.458989)

10

3

0.45970

0.02233

(0.43633, 0.48307)

20

3

0.454933

0.011235

(0.431567, 0.478300)

Pooled StDev = 0.0183881

70

One-Way ANOVA: Third Stage (5 minutes) versus First Stage
Time
Method
Null hypothesis

H₀: All means are equal

Alternative hypothesis

H₁: At least one mean is different

Equal variances were assumed for the analysis.
Factor Information
Factor

Levels

First Stage Time

4

Values
1, 5, 10, 20

Analysis of Variance
Source

DF

Adj SS

Adj MS

F-Value

P-Value

3

0.00169894

0.00056631

1.40

0.2944

Error

11

0.00444621

0.00040420

Total

14

0.00614515

First Stage Time

Model Summary
S

R-sq

R-sq(adj)

R-sq(pred)

0.0201047

27.65%

7.91%

0.00%

Means
First Stage Time

N

Mean

StDev

95% CI

1

3

0.47153

0.02425

(0.44599, 0.49708)

5

6

0.492633

0.021365

(0.474568, 0.510698)

10

3

0.50347

0.02014

(0.47792, 0.52901)

20

3

0.496200

0.009412

(0.470652, 0.521748)

Pooled StDev = 0.0201047

71

B4. Statistical analysis for lipid yield of 1g hexane extraction and Bligh & Dyer in
chapter 3 section 3.4.3

2-Sample t: Lipid Yield by Method
Method
µ₁: mean of Lipid Yield when Method = Bligh & Dyer
µ₂: mean of Lipid Yield when Method = Hexane Method (1g)
Difference: µ₁ - µ₂
Equal variances are not assumed for this analysis.
Descriptive Statistics: Lipid Yield
Method

N

Mean

StDev

SE Mean

Bligh & Dyer

3

0.54199

0.02506

0.01447

Hexane Method (1g)

3

0.540000

0.010000

0.005774

Estimation for Difference
Difference

95% CI for Difference

0.00199

(-0.06502, 0.06901)

Test
Null hypothesis

H₀: µ₁ - µ₂ = 0

Alternative hypothesis

H₁: µ₁ - µ₂ ≠ 0

T-Value

DF

P-Value

0.13

2

0.9099

72

B.5. Statistical analysis for lipid profile of hexane extraction and Bligh & Dyer in
chapter 3 section 3.4.4

2-Sample t: C16:0 by Method
Method
µ₁: mean of C16:0 when Method = 3 Stage Hexane
µ₂: mean of C16:0 when Method = Bligh & Dyer
Difference: µ₁ - µ₂
Equal variances are not assumed for this analysis.
Descriptive Statistics: C16:0
Method

N

Mean

StDev

SE Mean

3 Stage Hexane

3

0.337393

0.010935

0.006313

Bligh & Dyer

3

0.360207

0.015509

0.008954

Estimation for Difference
Difference

95% CI for Difference

-0.02281

(-0.05768, 0.01205)

Test
Null hypothesis

H₀: µ₁ - µ₂ = 0

Alternative hypothesis

H₁: µ₁ - µ₂ ≠ 0

T-Value

DF

P-Value

-2.08

3

0.1287

73

2-Sample t: C18:0 by Method
Method
µ₁: mean of C18:0 when Method = 3 Stage Hexane
µ₂: mean of C18:0 when Method = Bligh & Dyer
Difference: µ₁ - µ₂
Equal variances are not assumed for this analysis.
Descriptive Statistics: C18:0
Method

N

Mean

StDev

SE Mean

3 Stage Hexane

3

0.095030

0.002399

0.001385

Bligh & Dyer

3

0.106013

0.006017

0.003474

Estimation for Difference
Difference

95% CI for Difference

-0.010983

(-0.027075, 0.005108)

Test
Null hypothesis

H₀: µ₁ - µ₂ = 0

Alternative hypothesis

H₁: µ₁ - µ₂ ≠ 0

T-Value

DF

P-Value

-2.94

2

0.0990

74

2-Sample t: C18:1 by Method
Method
µ₁: mean of C18:1 when Method = 3 Stage Hexane
µ₂: mean of C18:1 when Method = Bligh & Dyer
Difference: µ₁ - µ₂
Equal variances are not assumed for this analysis.
Descriptive Statistics: C18:1
Method

N

Mean

StDev

SE Mean

3 Stage Hexane

3

0.496887

0.011187

0.006459

Bligh & Dyer

3

0.45695

0.02125

0.01227

Estimation for Difference
Difference

95% CI for Difference

0.03994

(-0.00418, 0.08406)

Test
Null hypothesis

H₀: µ₁ - µ₂ = 0

Alternative hypothesis

H₁: µ₁ - µ₂ ≠ 0

T-Value

DF

P-Value

2.88

3

0.0635

75

2-Sample t: C16 by Method
Method
µ₁: mean of C16 when Method = 3 Stage Hexane
µ₂: mean of C16 when Method = Bligh & Dyer
Difference: µ₁ - µ₂
Equal variances are not assumed for this analysis.
Descriptive Statistics: C16
Method

N

Mean

StDev

SE Mean

3 Stage Hexane

3

0.351000

0.009987

0.005766

Bligh & Dyer

3

0.371500

0.014981

0.008649

Estimation for Difference
Difference

95% CI for Difference

-0.02050

(-0.05358, 0.01258)

Test
Null hypothesis

H₀: µ₁ - µ₂ = 0

Alternative hypothesis

H₁: µ₁ - µ₂ ≠ 0

T-Value

DF

P-Value

-1.97

3

0.1432

76

2-Sample t: C18 by Method
Method
µ₁: mean of C18 when Method = 3 Stage Hexane
µ₂: mean of C18 when Method = Bligh & Dyer
Difference: µ₁ - µ₂
Equal variances are not assumed for this analysis.
Descriptive Statistics: C18
Method

N

Mean

StDev

SE Mean

3 Stage Hexane

3

0.607200

0.009974

0.005759

Bligh & Dyer

3

0.584867

0.016836

0.009720

Estimation for Difference
Difference

95% CI for Difference

0.02233

(-0.01362, 0.05829)

Test
Null hypothesis

H₀: µ₁ - µ₂ = 0

Alternative hypothesis

H₁: µ₁ - µ₂ ≠ 0

T-Value

DF

P-Value

1.98

3

0.1425

77

2-Sample t: saturated fatty acids by Method
Method
µ₁: mean of saturated fatty acids when Method = 3 Stage Hexane
µ₂: mean of saturated fatty acids when Method = Bligh & Dyer
Difference: µ₁ - µ₂
Equal variances are not assumed for this analysis.
Descriptive Statistics: saturated fatty acids
Method

N

Mean

StDev

SE Mean

3 Stage Hexane

3

0.432433

0.013282

0.007669

Bligh & Dyer

3

0.46623

0.02115

0.01221

Estimation for Difference
Difference

95% CI for Difference

-0.03380

(-0.07969, 0.01209)

Test
Null hypothesis

H₀: µ₁ - µ₂ = 0

Alternative hypothesis

H₁: µ₁ - µ₂ ≠ 0

T-Value

DF

P-Value

-2.34

3

0.1009

78

2-Sample t: unsaturated fatty acids by Method
Method
µ₁: mean of unsaturated fatty acids when Method = 3 Stage Hexane
µ₂: mean of unsaturated fatty acids when Method = Bligh & Dyer
Difference: µ₁ - µ₂
Equal variances are not assumed for this analysis.
Descriptive Statistics: unsaturated fatty acids
Method

N

Mean

StDev

SE Mean

3 Stage Hexane

3

0.525800

0.013251

0.007650

Bligh & Dyer

3

0.49013

0.02306

0.01331

Estimation for Difference
Difference

95% CI for Difference

0.03567

(-0.01320, 0.08453)

Test
Null hypothesis

H₀: µ₁ - µ₂ = 0

Alternative hypothesis

H₁: µ₁ - µ₂ ≠ 0

T-Value

DF

P-Value

2.32

3

0.1028

79

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