Microbial Oil Production from Oil

Palm Empty Fruit Bunch

A thesis by publication submitted in fulfilment of the requirements for the degree of

Doctor of Philosophy (PhD)

Farah Binti Ahmad

School of Chemical, Physics and Mechanical Engineering

Science and Engineering Faculty

Queensland University of Technology

2016

i

Keywords

Accelerated Solvent Extraction

Bagasse

Biodiesel

Biofuel

Bioreactor

Empty fruit bunch

Fungi

Glucose

Glycerol

Lignocellulose

Lipid

Microalgae

Microbial oil

Multi-criteria analysis

Oil palm

Oleaginous microorganism

Sugarcane

Sustainability

Techno-economic

Xylose

Yeast

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Abstract

Oil palm empty fruit bunch (EFB) is one of the major solid wastes from palm

oil processing. However, EFB is not effectively reused and current practices for EFB

disposal may lead to environmental problems. EFB is a lignocellulosic biomass and

has the potential to be converted into oil through biochemical routes, where the oils

can be further used for biodiesel production. This research aimed to develop and

optimise a process for microbial oil production from EFB. The microbial oil

production process involves cultivation by oleaginous microorganisms on carbon

substrates. Oleaginous microorganisms (including microalgae, yeasts and fungi)

accumulate oils from carbon substrates under nitrogen-limiting conditions.

The research project identified six potential oleaginous microorganisms which

were Chlorella protothecoides and Chlorella zofingiensis (microalgae),

Cryptococcus albidus and Rhodotorula mucilaginosa (yeasts), and Aspergillus

oryzae and Mucor plumbeus (fungi). The microorganisms were cultivated on

glucose, xylose and glycerol to down-select the most suitable microorganisms for oil

production from lignocellulosic hydrolysates. The selection was performed through

multi-criteria analysis (MCA) approach using analytic hierarchy process (AHP) and

preference ranking organisation method for the enrichment of evaluations

(PROMETHEE) with graphical analysis for interactive aid (GAIA). Based on MCA,

the potential microorganisms were down-selected to the three highest ranking

microorganisms which were A. oryzae, M. plumbeus and R. mucilaginosa.

To evaluate microbial oil production from EFB, the three highest ranking

microorganisms were cultivated on EFB hydrolysates. EFB was first subjected to

dilute acid pretreatment followed by enzymatic hydrolysis of the solid residue. Two

types of feedstocks were used for the cultivation, which are EFB hydrolysates from

the pretreatment (detoxified by overliming) and enzymatic hydrolysis of solid

residue. The cultivation on EFB hydrolysates resulted in the highest oil

concentrations and oil yields by M. plumbeus. The fuel properties analysis showed

that the oils produced were suitable for biodiesel production. Techno-economic

evaluation of oil production from EFB and other oil palm biomasses (trunk and

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frond) showed that oil palm biomass had the potential to increase the total palm oil

production by 25%, at a cheaper feedstock cost.

To optimise oil production from EFB by M. plumbeus, response-surface

methodology was used to evaluate and optimised the parameters of cultivation (i.e.,

sugars concentration, yeast extract concentration, pH and spore concentration) based

on the oil concentration and oil yield. The optimum conditions for oil yield were

identified and applied to the cultivation on EFB hydrolysate in a 1 L bioreactor.

Cultivation in the bioreactor resulted in ~2 times higher oil yield in comparison to

shake-flask cultivation, likely as a result of improved mixing and oxygen-mass

transfer in the bioreactor.

Overall, this study demonstrated that EFB is a promising low-cost raw

material for oil production by M. plumbeus. The microbial oils from EFB can be

used for the production of biodiesel from non-food feedstock. The integration of

microbial oil production from oil palm biomass with existing palm oil processing

could enhance the profitability and sustainability of the palm oil industry.

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Table of Contents

2.1.1 Oil palm ..................................................................................................... 9 

2.1.2 Palm oil processing: wastes generation and problems ............................ 11 

2.1.3 Palm oil processing wastes: Potential solutions ...................................... 13 

2.2.1 Potential utilization of lignocellulosic palm oil processing wastes ......... 14 

2.2.2 Pretreatment techniques for lignocellulosic biomass .............................. 15 

2.2.3 Enzymatic hydrolysis of lignocellulosic biomass ................................... 18 

2.3.1 Microbial oil cultivation by oleaginous microorganisms ........................ 19 

2.3.2 Heterotrophic cultivation of microalgae .................................................. 23 

2.3.3 Oleaginous yeasts .................................................................................... 24 

2.3.4 Oleaginous fungi ..................................................................................... 27 

2.4.1  Introduction ............................................................................................. 29 

Keywords ...................................................................................................................... i

Abstract ........................................................................................................................ ii

Table of Contents ........................................................................................................ iv

List of Figures ............................................................................................................ vii

List of Tables ............................................................................................................... ix

List of Abbreviations ................................................................................................... xi

List of Publications ..................................................................................................... xii

Statement of Original Authorship ............................................................................. xiv

Acknowledgements .................................................................................................... xv

  Introduction ........................................................................................................... 1

1.1  Background ......................................................................................................... 1

1.2  Aims and scope of study ..................................................................................... 2

1.3  Research contribution and significance .............................................................. 3

1.4  Thesis outline ...................................................................................................... 4

  Literature Review .................................................................................................. 9

2.1  Overview of palm oil processing ........................................................................ 9

2.2  Pretreatment and hydrolysis of lignocellulosic biomass ................................... 14

2.3  Microbial cultivation for oil production from lignocellulosic biomass ............ 19

2.4  Applications of microbial oils ........................................................................... 29

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2.4.2 Energy application of microbial oil ......................................................... 29 

2.4.3 Health applications of microbial oils ...................................................... 30 

2.4.4 Food applications of microbial oils ......................................................... 31 

2.4.5 Chemicals applications of microbial oils ................................................ 31 

Abstract…………. ............................................................................................ 46 

Statement of Contribution................................................................................. 47 

3.1.1  Introduction ............................................................................................. 49 

3.1.2 Materials and Methods ............................................................................ 53 

3.1.3 Results and discussion ............................................................................. 59 

3.1.4 Conclusion ............................................................................................... 74 

3.1.5 Acknowledgements ................................................................................. 74 

3.1.6 Reference ................................................................................................. 74 

Abstract…………. ............................................................................................ 79 

Statement of Contribution................................................................................. 81 

4.1.1  Introduction ............................................................................................. 83 

4.1.2 Material and methods .............................................................................. 85 

4.1.3 Results and discussion ............................................................................. 90 

4.1.4 Conclusion ............................................................................................. 106 

4.1.5 Acknowledgements ............................................................................... 107 

4.1.6 Reference ............................................................................................... 107 

Abstract…………. .......................................................................................... 113 

Statement of Contribution............................................................................... 115 

5.1.1  Introduction ........................................................................................... 117 

5.1.2 Material and methods ............................................................................ 118 

2.5  Research gap and discussion ............................................................................ 32

2.6  Reference .......................................................................................................... 34

  Selecting oleaginous microorganisms for microbial oil production ............... 46

3.1  A multi-criteria analysis approach for ranking and selection of microorganisms for the production of oils for biodiesel production .................................................... 46

  Evaluating microbial oil production from EFB ................................................ 79

4.1  Evaluation of oil production from oil palm empty fruit bunch by oleaginous microorganisms .......................................................................................................... 79

  Optimising microbial oil production from EFB ............................................. 113

5.1  Improved microbial oil production from oil palm empty fruit bunch by Mucor plumbeus .................................................................................................................. 113

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5.1.3 Results and Discussion .......................................................................... 122 

5.1.4 Conclusion ............................................................................................. 144 

5.1.5 Acknowledgement ................................................................................. 144 

5.1.6 Reference ............................................................................................... 144 

  Conclusion .......................................................................................................... 149

6.1  Discussion ....................................................................................................... 149

6.2  Future work ..................................................................................................... 151

6.3  Conclusion ...................................................................................................... 152

Appendices .................................................................................................................... I

Appendix 1: Optimising microbial oil extraction by Accelerated Solvent ExtractionIII

Appendix 2: Microbial oil production from sugarcane bagasse hydrolysates by oleaginous yeast and filamentous fungi ................................................................. XXII

Appendix 3: Time-course graph for DO, pH, agitation speed and aeration rate for bioreactor cultivation ....................................................................................... XXXVIII

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List of Figures

Figure 1-1 Overall research plan .................................................................................. 3 

Figure 1-2 Overview of thesis ...................................................................................... 6 

Figure 2-1 (a) Average oil yield per ha per year for selected oil crops ..................... 10 

Figure 2-2 Oil palm tree, fresh fruit bunch and longitudinal section of fresh oil palm fruit ...................................................................................................... 11 

Figure 2-3 EFB from palm oil mills ........................................................................... 12 

Figure 2-4 General process for conversion of EFB into microbial oil ....................... 14 

Figure 2-5 Lignocellulosic structure of plants. .......................................................... 15 

Figure 2-6 A culture that contains filamentous fungi in pellet form. ......................... 28 

Figure 3-1 Criteria hierarchy for the evaluation of microorganisms for microbial oil production. Cluster 1 criteria were evaluated based on cultivation results on glucose (G), xylose (X) and glycerol (L). .................. 56 

Figure 3-2 (a) Biomass concentration, (b) oil content and (c) oil concentrations for growth of six microorganisms on glucose, xylose and glycerol. ........... 61 

Figure 3-3 Consumption of (a) glucose, (b) xylose and (c) glycerol over 168 h of cultivation. ............................................................................................... 63 

Figure 3-4 (a) PROMETHEE I partial ranking of alternatives and (b) PROMETHEE II complete ranking where RM denotes R. mucilaginosa, AO A. oryzae, MP M. plumbeus, CP C. protothecoides, CA C. albidus and CZ C. zofingiensis. ......................................................... 67 

Figure 3-5 GAIA plane at (a) 100% zoom and (b) 400% zoom ................................ 69 

Figure 3-6 GAIA Webs for top three alternatives from PROMETHEE which are (a) R. mucilaginosa, (b) A. oryzae and (c) M. plumbeus. Criterion C2-X is not visible due to overlapping by C6-X. ......................................... 73 

Figure 4-1 Flow chart of hydrolysates preparation from EFB for microbial cultivation. ................................................................................................... 86 

Figure 4-2 Sugars consumption of R. mucilaginosa, A. oryzae and M. plumbeus on EFB liquid (EFBLH) and enzymatic (EFBEH) hydrolysates. ................ 94 

Figure 4-3(a) Oil contents (%, w/w) and (b) oil concentrations (g/L) of yeast R. mucilaginosa, and fungi A. oryzae and M. plumbeus cultivated on EFB liquid (EFBLH) and enzymatic (EFBEH) hydrolysates. ..................... 96 

Figure 4-4 Process flow of proposed integration of microbial oil production from oil palm biomasses into the existing palm oil processes. .................. 105 

Figure 5-1 (a) Mathematical models for oil concentration (Y1) and oil yield (Y2), and the parameters of analysis of variance (ANOVA) of each model. (b-c) Plots of predicted vs. actual values (experimental data). (d-e) Internally studentised residuals vs actual values. ............................. 126 

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Figure 5-2 (a-e) Three-dimensional surface plots of binary interaction between different variables to the oil concentration. Sugar is sugar concentration, %YE is relative concentration of yeast extract, Spore is spore concentration and pH is initial pH. ................................................... 129 

Figure 5-3 (a-d) Three-dimensional surface plots of binary interaction between different variables to the oil yield. Sugar is sugar concentration, %YE is relative concentration of yeast extract, Spore is spore concentration and pH is initial pH. ................................................................................... 130 

Figure 5-4 The consumption of glucose (a) and xylose (b) for the experimental run .............................................................................................................. 133 

Figure 5-5 (a) The consumption of glucose and xylose for bioreactor cultivation ................................................................................................... 138 

Figure 5-6 Fungal morphology from the bioreactor cultivation .............................. 139 

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List of Tables

Table 2-1 Various agro-industrial hydrolysates as the feedstock for oleaginous yeasts cultivation for oil production ............................................................ 25 

Table 2-2 Various agro-industrial hydrolysates as the feedstock for oleaginous fungi cultivation for oil production .............................................................. 27 

Table 3-1 Pairwise comparison matrix with respect to goal for criteria groups of Cluster 1 and Cluster 2. ........................................................................... 57 

Table 3-2 Pairwise comparison matrix with respect to goal for criteria of Cluster 1. ...................................................................................................... 57 

Table 3-3 Fatty acid compositions of oil extracted from six different microorganisms grown on various carbon substrates. ................................. 66 

Table 3-4 Weight stability intervals for criteria with relative weight>5%. ............... 70 

Table 4-1 Chemical compositions of raw and pretreated EFB. The composition of lignin was based on the composition of acid soluble and acid insoluble lignin. ............................................................................................ 91 

Table 4-2 Sugars (glucose, xylose and arabinose), organic acids (formic acid, acetic acid and levulinic acid) and furans (5-hydroxymethylfurfural (HMF) and furfural) compositions of liquid (EFBLH) and enzymatic (solid residue) (EFBEH) hydrolysates of EFB. ........................................... 92 

Table 4-3 Biomass concentrations, oil concentrations and oil yields of different oleaginous yeasts and filamentous fungi from batch fermentation ............. 98 

Table 4-4 Fatty acids composition of microbial oils methyl ester of R. mucilaginosa, A. oryzae and M. plumbeus cultivated on EFB liquid (EFBLH) and solid residue enzymatic (EFBEH) hydrolysates, as well as fuel properties, ....................................................................................... 100 

Table 4-5 (a) The summary of technical evaluation of microbial oil production from oil palm biomasses (EFB, trunk (OPT) and frond (OPF)) through the comparison of potential microbial oil yields per hectare to oil yield of crude palm oil. ....................................................................................... 102 

Table 5-1 The coded and actual values of each variable and its levels for the experimental design ................................................................................... 120 

Table 5-2 Concentrations of sugars, organic acids and 5-hydroxylmethylfurfural (HMF) in enzymatic hydrolysates (EHs). ........... 123 

Table 5-3 Analysis of variance (ANOVA) for the response surface quadratic model of oil concentration (a) and oil yield (b) that had significant terms (Sugar concentration - X1, Relative concentration of yeast extract - X2, Spore concentration - X3, Initial pH - X4). .......................... 126 

Table 5-4 The predicted responses from the simulation of mathematical models ... 127 

Table 5-5 The concentration of ethanol accumulated at the end of the cultivation .................................................................................................. 135 

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Table 5-6 Results of different cultivation performed in this study .......................... 140 

Table 5-7 The comparison of raw materials cost (RMC) (a), production cost (b) and cost of biodiesel (c) for the production of biodiesel from EFB and glucose ................................................................................................. 142 

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List of Abbreviations

AHP Analytic hierarchy process

ANOVA Analysis of variance

ASE Accelerated solvent extraction

C/N Carbon-to-nitrogen

DO Dissolved oxygen

EFB Empty fruit bunch

EFBEH Empty fruit bunch enzymatic hydrolysate

EFBLH Empty fruit bunch liquid hydrolysate

EH Enzymatic hydrolysate

FFB Fresh fruit bunch

GAIA Graphical analysis for interactive aid

GC-MS Gas chromatography-mass spectrometry

HMF 5-hydroxymethyl furfural

HPLC High-performance liquid chromatography

MCA Multi-criteria analysis

MF Mesocarp fibre

OPF Oil palm frond

OPT Oil palm trunk

PDA Potato dextrose agar

PKS Palm kernel shell

PROMETHEE Preference ranking organization method for the enrichment of

evaluations

RSM Response surface methodology

YDP Yeast dextrose potato

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List of Publications

Peer-reviewed journal publications

1. Ahmad, F.B., Zhang, Z., Doherty, W.O.S., and O’Hara, I.M., A multi-criteria

analysis approach for ranking and selection of microorganisms for the

production of oils for biodiesel production. Bioresource Technology, 190

(2015), Pages 264-273.

2. Ahmad, F.B., Zhang, Z., Doherty, W.O.S., and O’Hara, I.M., Evaluation of

oil production from oil palm empty fruit bunch by oleaginous

microorganisms. Biofuels, Bioproducts and Biorefining, 10 (2016), Pages

378-392.

3. Ahmad, F.B., Zhang, Z., Doherty, W.O.S., Te’o, V.S.J., and O’Hara, I.M.,

Improved microbial oil production from oil palm empty fruit bunch by Mucor

plumbeus. (Accepted with modification for publication in Fuel).

4. Ahmad, F.B., Zhang, Z., Doherty, W.O.S., and O’Hara, I.M., Optimising

extraction of microalgal oil using accelerated solvent extraction by response

surface methodology. (Accepted with modification for publication in Journal

of Engineering Science and Technology).

Conference proceedings

1. Ahmad, F.B., Zhang, Z., Doherty, W.O.S., and O’Hara, I.M., Microbial oil

production from sugarcane bagasse hydrolysates by oleaginous yeast and

filamentous fungi. Proceedings of the Australian Society of Sugar Cane

Technologists, 38 (2016).

Poster presentation

1. Ahmad, F., Zhang, Z., Doherty, W., and O’Hara, I.M., Microbial oil

production from palm oil empty fruit bunch hydrolysates. In 37th Symposium

on Biotechnology for Fuels and Chemicals, 27 - 30 April 2015, San Diego,

California.

xiii

Awards

1. Denis Foster Chemistry/Chemical Engineering award from 38th Conference

of Australian Society of Sugar Cane Technologists 2016 for best paper in

Chemistry/Chemical Engineering.

Miscellaneous

1. Cover Image, Volume 10, Issue 4 in Biofuels, Bioproducts and Biorefining,

10 (2016). Based on the Modeling and Analysis Evaluation of oil production

from oil palm empty fruit bunch by oleaginous microorganisms. Photo Credit:

Farah Binti Ahmad.

xiv

Statement of Original Authorship

The work contained in this thesis has not been previously submitted to meet

requirements for an award at this or any other higher education institution. To the

best of my knowledge and belief, the thesis contains no material previously

published or written by another person except where due reference is made.

Signature: QUT Verified Signature

Date: November 2016

xv

Acknowledgements

My deepest gratitude is to my supervisors Prof Ian O’Hara, Dr Jan Zhang and

Prof William Doherty, for their invaluable guidance and assistance throughout my

research project. I am grateful to have such dynamic supervisory team for this

research. I would like to express my gratitude to Malaysia Ministry of Higher

Education and International Islamic University of Malaysia (IIUM) for my

postgraduate scholarship.

I would like to thank Shane Russell and Dr Joel Herring from Central

Analytical Research Facility (CARF) (Institute for Future Environments), Wanda

Stolz and Dr Dani Tikel (Centre for Tropical Crops and Biocommodities (CTCB))

and Dr Chris Carvalho (School of Chemistry, Physics and Mechanical Engineering

(CPME)) for their assistance for analytical work undertaken in this research. I would

also like to thank the staff from CTCB labs, CARF labs and QUT Banyo Pilot Plant

Facility for their support while I was working in those facilities. I would like to

acknowledge A/Prof Junior Te’o from the School of Earth, Environmental and

Biological Sciences (EEBS) for the opportunity to perform bioreactor experiments,

as well as Vincent Chand (EEBS) for his support while working in Junior’s lab. I

would also like to thank Vitor Kawazoe for his assistance on oil extraction work

during his internship at CTCB. I thank Anthony Brinin (CTCB), and Ada Rosier and

Beric Nott from Faculty of Health for their assistance in microscopic work

undertaken in this study.

I would like to acknowledge CTCB and the school of CPME for the travel

funding support. I thank my fellow labmates from CARF labs and CTCB labs for

their support throughout my PhD journey. I would also like to thank Dr Christian

Long from Academic Language and Learning Services for his advice. I would also

like to acknowledge Prof Roger Hellens and A/Prof Robert Speight for feedback on

thesis.

Lastly, I am deeply grateful for the support, love and prayers from my parents,

family and friends, as well as the Sisters from QUT GP Musolla. All the praises and

thanks be to the Creator.

1

Introduction

1.1 Background

The palm oil industry is a major food and oleochemical industry with palm oil

being a key source of oils and fats. The scale of the palm oil industry, however, has

contributed to the generation of large amounts of solid and liquid wastes from palm

oil processing. Only a portion of the solid wastes, known as oil palm biomass, are

used for other applications, while poor management of oil palm biomass can result in

substantial environmental problems. Empty fruit bunch (EFB) is one of the major

solid wastes generated as a by-product of palm oil mills, and is currently not

effectively used.

EFB and other lignocellulosic biomass residues have the potential to be

converted to higher value products through microbial cultivation. The oils produced

can be used as feedstocks for the production of biodiesel, health products, food

products and chemicals. As palm oil is already extensively used in the oleochemical

industry, there is the opportunity for integrating oils produced from EFB in the

existing palm oil supply chain. The proposed integration could potentially enhance

the sustainability and profitability of palm oil production.

Carbohydrates (sugars) can be converted to oils through cultivation of

oleaginous microorganisms. Oleaginous microorganisms, including certain

microalgae, yeasts, fungi and bacteria, are capable of accumulating oil in

intracellular membranes in significant quantities, generally under stress cultivation

conditions. Fermentable sugars from biomass have the potential to be used as the

carbon substrates for oil production by oleaginous microorganisms. However, due to

the recalcitrant nature of biomass, processing is necessary to disrupt the complex

hemicellulose-lignin structure, so that cellulose is accessible for enzymatic

hydrolysis to break cellulose down to monomers (i.e., fermentable sugars).

Hydrolysates from both pretreatment and enzymatic hydrolysis of lignocellulosic

biomass could be used as the cultivation media for oleaginous microorganisms.

However, there is currently limited information on microbial oil production from

EFB and other lignocellulosic biomasses or agro-industrial wastes.

2

To develop an effective microbial production process, optimising oil yield is

critical as higher yields will have a significant impact on the economics of the

process. Strain selection is critical in order to identify potential microorganisms that

are able to grow on lignocellulosic hydrolysates, which may contain a variety of

sugar monomers and potential microbial growth inhibitors. Carbon-to-nitrogen (C/N)

ratio has been proposed as one of the key factors that may enhance yield as

oleaginous microorganisms typically accumulate oil under nitrogen-limiting

condition. Cultivation in bioreactor systems is also critical in order to develop an

understanding on the potential and challenges associated with scale-up.

1.2 Aims and scope of study

The overall objective of this project is to develop and optimise a process for the

production of microbial oil from EFB. The aims of this research are:

1. To develop a method for identifying high potential strains through cultivation on

pure sugar substrates and multi-criteria analysis.

2. To screen high ranking strains through cultivation on EFB hydrolysates and

select a prospective candidate for oil production from EFB hydrolysates.

3. To assess the potential viability of microbial oil production from EFB through

techno-economic evaluation.

4. To optimise cultivation conditions on EFB hydrolysates and explore the potential

for process scale up.

The aims of this study have been addressed through a research plan that

included three phases (Figure 1-1) which are

Phase 1: Selecting oleaginous microorganisms for microbial oil production

Phase 2: Evaluating microbial oil production from EFB

Phase 3: Optimising microbial oil production from EFB

3

1.3 Research contribution and significance

The research work undertaken in this study has resulted in the generation of

new knowledge. This includes the following original contributions.

Investigation of microbial oil production from EFB hydrolysates produced via

dilute acid pretreatment and enzymatic hydrolysis.

In this study, a comprehensive evaluation of microbial oil production from EFB

has been performed through assessment of cultivation on actual EFB

hydrolysates, assessment of fuel properties and assessment of the techno-

economics of microbial oil production from EFB and other oil palm biomasses.

Techno-economic evaluation of microbial oil production from oil palm biomass.

This study is critical as it evaluates potential viability of microbial oil production

process from EFB and other oil palm biomasses (trunk and frond).

Phase 1: Selecting oleaginous microorganisms for microbial oil production Selection of potential microorganisms from various groups (microalgae, yeasts

and fungi)

Cultivation of potential microorganisms on glucose, xylose and glycerol Multi-criteria assessment of selected microorganisms for oil production from

lignocellulosic hydrolysates Down-selection of potential microorganisms to 3 highest ranking

microorganisms for Phase 2

Phase 2: Evaluating microbial oil production from EFB Production of EFB hydrolysates through dilute acid pretreatment and

enzymatic hydrolysis of EFB

Cultivation of 3 highest ranking microorganisms on EFB hydrolysates and down-selection of prospective microorganisms for Phase 3

Fuel properties assessment of microbial oils from EFB Techno-economic evaluation of microbial oil production from EFB

Phase 3: Optimising microbial oil production from EFB Evaluation of the impact of cultivation parameters (carbon concentration,

nitrogen concentration, pH and inoculum size) on oil concentration and oil yield

Optimisation of cultivation condition on EFB hydrolysate Cultivation in bioreactor under optimised condition

Figure 1-1 Overall research plan

4

Microbial oil production from different groups (i.e., microalgae, yeasts and

fungi) of microorganisms on the same carbon substrates.

Optimisation of microbial oil production from EFB hydrolysate. This study is

significant as it evaluates the impacts of different conditions of cultivation on oil

yield and oil concentration.

Investigation of microbial cultivation on EFB hydrolysate in bioreactor system.

Microbial oil production from EFB by Rhodotorula mucilaginosa, Aspergillus

oryzae and Mucor plumbeus.

Multi-criteria analysis for ranking and selecting microorganisms for oil

production from lignocellulosic hydrolysates.

Microbial oil production from glycerol by Aspergillus oryzae and Mucor

plumbeus.

Cultivation of microalgae Chlorella protothecoides and Chlorella zofingiensis on

xylose.

Microbial oil production from sugarcane bagasse by Rhodotorula mucilaginosa,

Aspergillus oryzae and Mucor plumbeus. (See Appendix 2)

Optimising microbial oil extraction from Chlorella protothecoides using

Accelerated Solvent Extraction. (See Appendix 1)

This research is important as it contributes to the future profitability and

sustainability of the palm oil industry through (1) reducing environmental problems

associated with the management of palm oil processing wastes, (2) improving

sustainable practices in the palm oil industry, (3) increasing oil yield per ha of oil

palm cultivation and (4) adding value to a by-product of the palm oil processing

industry and therefore further contributing to higher economic returns to the palm oil

industry. The outcome of this research will not only benefit the palm oil industry, but

also other agro-industries that produce lignocellulosic residues.

1.4 Thesis outline

This thesis is a thesis by publication. Figure 1-2 shows an overview of the

thesis mapping the research aims by thesis chapter.

5

Chapter 1 (Introduction) describes the background to the research problem

that originates from the palm oil processing industry, as well as the potential solution

through microbial oil production. This chapter also outlines the aims of this research,

overview the thesis and identify the novelty and contribution to knowledge of the

research.

Chapter 2 provides a literature review of palm oil processing, waste

generation and potential solutions based on previous studies on value-addition to

palm oil biomass. This chapter reviews pretreatment and hydrolysis of

lignocellulosic biomass, which includes comparisons of different pretreatment

methods that have been applied to lignocellulosic biomass. This chapter also

discusses the challenges of using lignocellulosic hydrolysates from pretreatment for

microbial cultivation. Chapter 2 provides background information on microbial oil

production and a review of the cultivation of various groups of oleaginous

microorganisms including microalgae, yeasts and fungi. This chapter reviews various

applications of microbial oil for the production of biodiesel and oleochemical

industry applications. The chapter concludes with a discussion on the research gap.

Through the literature review, six oleaginous microorganisms were selected and

investigated in Phase 1 (Chapter 3). These microorganisms were Chlorella

protothecoides and Chlorella zofingiensis (microalgae), Cryptococcus albidus and

Rhodotorula mucilaginosa (yeasts), and Aspergillus oryzae and Mucor plumbeus

(fungi).

The results of Phase 1 are presented and discussed in Chapter 3. The six

selected microorganisms were grown on glucose, xylose and glycerol. Multi-criteria

analysis (MCA) using analytic hierarchy process (AHP) and preference ranking

organization method for the enrichment of evaluations (PROMETHEE) with

graphical analysis for interactive aid (GAIA), were used to rank and select the most

preferred microorganisms for oil production to be used for the production of

biodiesel. An MCA technique was developed based on the following criteria: oil

concentration, content, production rate and yield, substrate consumption rate, fatty

acids composition, biomass harvesting and nutrient costs. From this study, the MCA

identified A. oryzae, M. plumbeus and R. mucilaginosa as the highest ranking strains

for oil production from lignocellulosic hydrolysates.

6

Chapter 4 focuses on oil production by the three highest ranking strains on

lignocellulosic hydrolysates. The chapter presents the results and discussion of the

cultivation of A. oryzae, M. plumbeus and R. mucilaginosa on EFB hydrolysates.

This chapter discusses the use of both hydrolysates from dilute acid pretreatment and

enzymatic hydrolysis, as the carbon substrates, and the challenges of using

lignocellulosic hydrolysates for microbial oil production. The fuel properties of the

oils produced are also discussed in this chapter. The microorganisms are evaluated

for their capacity to grow on EFB hydrolysates based on oil productivity, tolerance to

Chapter 2: Literature review

Microbial oil production from oil palm empty fruit bunch

Chapter 4: Evaluating microbial oil production from EFB

2. Evaluation of oil production from oil palm empty fruit bunch. Published in Biofuels, Bioproduct and

Biorefining (2016)

Chapter 3: Selecting oleaginous microorganisms for microbial oil production

1. A multi-criteria analysis approach for ranking and selection of microorganisms for the production of oils for biodiesel production. Published in Bioresource Technology (2015)

Chapter 5: Optimising microbial oil production from EFB

3. Improved microbial oil production from oil palm empty fruit bunch by Mucor plumbeus. Accepted with modification for publication

in Fuel (2016)

Research aim 1: To develop a method for identifying high potential strains through cultivation on pure sugar substrates and multi-criteria analysis.

Research aim 2: To screen high ranking strains through cultivation on EFB hydrolysates and select a prospective candidate for oil production from EFB hydrolysates.

Research aim 3: To assess the potential viability of microbial oil production from EFB through techno-economic evaluation.

Research aim 4: To optimise cultivation conditions on EFB hydrolysates and explore the potential for process scale up.

Chapter 6: Conclusion and future work

Chapter 1: Introduction

Figure 1-2 Overview of thesis

7

inhibitors, sugar consumption profiles and fuel quality. From the cultivation on both

EFB hydrolysates, M. plumbeus recorded the highest oil concentration and oil yield.

The experimental data from the cultivation of M. plumbeus on EFB hydrolysates was

used for techno-economic evaluation of microbial oil production from oil palm

biomass. This chapter also elaborates and visualises the potential integration of

microbial oil from oil palm biomass within palm oil industrial process.

Chapter 5 focusses on optimising the cultivation of M. plumbeus on EFB

hydrolysate. This chapter also describes and compares the cultivation of M. plumbeus

on an EFB hydrolysate in bioreactor system with the cultivation in shake flasks. In

this chapter, the impact of different cultivation parameters on oil production from

EFB hydrolysates was investigated. The parameters selected for optimisation are

sugars (carbon source) concentration, yeast extract (nitrogen source) concentration,

pH and inoculum size. In this chapter, the optimisation study was performed through

response-surface methodology varying these four cultivation parameters. The

optimised cultivation conditions were assessed based on oil concentration and oil

yield. This chapter discusses issues associated with ethanol accumulation produced

as a by-product of the microbial cultivation. This chapter also discusses the

morphology of the fungal system during the cultivation. The optimised cultivation

conditions were further used for the study of the cultivation on EFB hydrolysates in

bioreactor systems.

Chapter 6 (Conclusion) summarises the overall results of the research for the

selection of microorganisms for the microbial oil production from EFB hydrolysates.

This chapter also reviews the key findings of this research associated with the

research aims. This chapter also presents future work that can be developed from the

outcome of this research.

9

Literature Review

2.1 Overview of palm oil processing

2.1.1 Oil palm

Oil palm (Elaeis guineensis) is the world’s highest yielding oil crop, with

approximately eight times higher productivity than rapeseed and six times higher

than soybean (Figure 2-1(a)). Palm oil is extracted from the fruit mesocarp, which is

then fractionated into palm olein and stearin [1]. Palm olein is used in food

applications, especially as a feedstock for cooking oil, while palm stearin is mainly

used in non-food and oleochemicals production. Oil palm is widely grown in tropical

countries such as Malaysia and Indonesia with 47.6 million tonnes of palm oil

produced in 2013 (Figure 2-1(b)) [2]. Malaysia is the second largest producer of

palm oil in the world, and contributes 38% of the world’s production. Malaysia

accounts for about 10% of the global production of oils and fats, with around 4

million ha of land used for oil palm cultivation [3].

The demand for palm oil has been increasing every year, and since 2007, palm

oil has become the most widely consumed vegetable oil [4]. In 2012, 50.17 million

tonnes of palm oil was produced globally, a 5% increase from 2011 [5]. One of the

reasons for the escalating demand for palm oil is because it provides the cheapest

edible oil source (US$518/t) compared with other major vegetable oils such as

soybean (US$641/t) and rapeseed (US$784/t) [6]. Oil palm is a low energy input

crop, since it is a perennial crop and does not require annual sowing [7]. Oil palm

cultivation requires less energy input per tonne of oil produced compared to soybean

and rapeseed [3].

The increasing demand for palm oil is also being driven by its extensive

application in oleochemical industries. The fatty acids and alcohols produced from

these oils are essential raw materials for the production of surfactants [8]. The

application of these surfactants is mainly in the production of consumer products

such as laundry detergents, shampoos, soaps and cleaning products [8]. In 2005,

there were forty-eight oleochemical refineries in Malaysia, which holds a 25% share

of the global market for fatty alcohols and acids [9].

10

Indonesia

Malaysia

Thailand Nigeria Colombia

0

5

10

15

20

25

30

Pal

m o

il (

t/ye

ar)

Palm oil

Rapeseed oil

Soybean oil

Sunflower oil

0

0.5

1

1.5

2

2.5

3

3.5

Oil

yie

ld (

t/ha

/yea

r)

(a)

(b)

Figure 2-1 (a) Average oil yield per ha per year for selected oil crops from 2010-2012 [2]. (b) Top five producers of palm oil in the world with average

palm oil production from 2011-2013 [2].

Oil palm trees are replanted after an economic life of twenty-five years [10].

Harvesting of the palm fruits typically begins three years after planting, with a

maximum oil yield in the 12–14th year after which the yield continuously diminishes

until the end of the plantation’s economic life [11]. Palm fruits grow in bunches with

approximately 1000 to 3000 fruits per bunch [3]. Each bunch weighs approximately

10-15 kg with about 25% (w/w) of oil per bunch [12]. Palm oil is extracted from the

mesocarp of the palm fruit, which is the oily and fleshy outer layer of the fruit seed

or kernel shown in Figure 2-2. The palm kernel is also rich in oil, however, palm

kernel oil has different fatty acid compositions to palm oil. Palm oil mainly consists

of C16 and C18 fatty acids, while palm kernel oil comprises of C12 and C14 fatty

acids which are typically found in coconut oil [1]. Therefore, unlike palm oil, the

application of palm kernel oil is mainly in soap manufacturing [3].

11

Figure 2-2 Oil palm tree, fresh fruit bunch and longitudinal section of fresh oil palm fruit [12, 13]

Oil palm cultivation is rapidly expanding in Southeast Asia due to increasing

global consumer demand [14]. However, sustainability and environmental issues

have become one of the major concerns for palm oil expansion. As one of the

world’s leading producers of palm oil, Malaysia has adopted several measures for

enhancing sustainable palm oil production. The palm oil industry in Malaysia has

adapted Good Agricultural Practices (GAP) and Integrated Pest Management (IPG)

in order to ensure conservation of the environment and biodiversity [15]. In addition,

a no forest areas encroachment policy has been legislated in Malaysia, whereby

cultivation expansion can only occur on unused land or land converted from other

crops [15]. Zero burning was also legislated in Malaysia in 1989, as part of the drive

to more sustainable practices [16]. Through the implementation of these policies,

more than 50% of total land area in the country remains as rainforests [17].

Approximately 25% of oil palm plantation land area in the country has been

converted from land formerly used for rubber, coconut and cocoa plantations [7].

2.1.2 Palm oil processing: wastes generation and problems

Fresh fruit bunches (FFB) harvested from oil palm plantations are processed in

palm oil mills for oil extraction. FFB processing involves sterilisation, threshing and

stripping of fruits, digestion, and extraction of oil [16]. In 2011, there were

approximately 92.9 million tonnes of FFB harvested and processed in Malaysian

palm oil mills, which generated approximately 44 million tonnes of solid residues,

and 62 million tonnes of liquid waste known as palm oil mill effluent (POME) [18].

The solid residues from the palm oil extraction process comprises of, by weight,

around 53% of empty fruit bunch (EFB), 29% of shell and 18% of fibre [18]. EFB is

12

the fibrous mass left behind after the FFB stripping process (Figure 2-3). EFB

consists of a bundle of fibres with an average size of approximately 1 mm in length,

25 μm wide and 3 μm thick [19].

Figure 2-3 EFB from palm oil mills [20, 21]

The palm oil industry is one of the key biomass producers in Malaysia [18].

Aside from the abundance of residues generated by the extraction mills, there are

significant amounts of waste coming from oil palm plantations in Malaysia. For

instance, there are large amounts of oil palm frond (OPF) from the daily pruning of

the trees, and oil palm trunks (OPT) from replanting that require disposal [3]. These

wastes are typically shredded for in-situ composting [15]. Malaysian palm oil mills

have been utilising a portion of biomass wastes, particularly the palm kernel shell

(PKS) and mesocarp fibre (MF), as a source of electricity and steam generation [18].

However, the majority of EFB has not been optimally recycled for other applications

in the mills. Some millers opt to use EFB as mulch or/and fertiliser [22].

EFB is not preferred for burning or combustion as fresh EFB consists of about

60% water [23]. The high moisture content of EFB makes it unfavourable for

handling and transportation. EFB is usually left for decomposition at the mills or

plantations [18]. Another issue with the use of EFB as soil conditioner is that it can

attract oil palm pests [23]. Poor management of EFB decomposition can lead to

substantial methane emissions to the atmosphere [19]. Methane is one of the key

greenhouse gases which are known to be the major cause of global warming. In some

Southeast Asian countries, palm oil wastes are disposed of through open burning

which contributes air pollution [23]. As an alternative to disposal, these palm oil

wastes can instead be converted into higher value products and contribute to higher

economic returns to the palm oil industry.

13

2.1.3 Palm oil processing wastes: Potential solutions

Malaysia’s National Biomass Strategy 2020 has identified five main solid

biomass types from the palm oil industry, namely OPF and OPT from oil palm

plantation; EFB, PKS and MF from palm oil processing [24]. The generation of these

biomasses were expected to increase from 83 million t (dry) in 2012 to 85-110

million t (dry) by 2020 [24]. Since the oil palm biomasses (EFB, OPF, OPT, MF and

PKS) are lignocellulosic, the biomass has the potential to be converted into

bioproducts through chemical and/or biochemical processing. The use of EFB, OPF

and OPT has been reported for the production of bioethanol, biomethane,

biofertilizer, biobriquettes, biocomposite, carbon molecular sieve, activated carbon,

paper pulp, fine chemicals and fibreboards [19, 23, 25]. The utilisation of oil palm

biomass has also been discussed as a potential source of alternative energy, not only

in production of bioethanol and biomethane, but also in production of fuels through

gasification or pyrolysis [3, 23].

EFB is typically composed of 45–50% cellulose, 25–35% hemicelluloses and

25–35% lignin [19]. These carbohydrates in EFB are promising for oil production by

microbial cultivation, and the oil, subsequently can be converted to biodiesel. Once

these complex carbohydrates are broken down into simple sugars, they can be used

as carbon substrates for oleaginous microorganisms in oil production. Microbial oil

has been found in various applications such as biodiesel production, health products

manufacturing and food substitute production, depending on the fatty acid

compositions of the oil. The following flow diagram (Figure 2-4) summarises a

general process for converting EFB into microbial oil.

Oil production from palm oil biomass provides a good opportunity as the

products can be integrated into the existing palm oil supply chain. Microbial oil has

the potential to supplement fatty acids feedstocks for oleochemical and food

manufacturing. The proposed integration concept is aligned with Malaysia’s National

Biomass Strategy 2020 as lignocellulosic biomass from the palm oil sector has been

targeted for additional value creation through the production of second generation

biofuels and bio-based chemicals [24]. The proposed integration concept can

potentially improve the sustainability and profitability of the palm oil industry.

14

Figure 2-4 General process for conversion of EFB into microbial oil

2.2 Pretreatment and hydrolysis of lignocellulosic biomass

2.2.1 Potential utilization of lignocellulosic palm oil processing wastes

As has been discussed in the previous section, lignocellulosic palm oil wastes

have the potential to be utilised by microorganisms in microbial cultivation. Empty

fruit bunch (EFB) contains high level of sugars in the lignocellulosic structure that

can be the source of organic carbon for microbial cultivation. However,

microorganisms generally cannot assimilate complex sugars [26, 27]. The

polysaccharides of lignocellulosic EFB must be broken down into simple sugars

prior to microbial cultivation. Enzymatic hydrolysis is one of the options for

breaking down polysaccharides from lignocellulosic EFB into sugar monomers.

However, due to the complex nature of lignocellulose, EFB must be pretreated prior

to enzymatic hydrolysis.

Lignocellulose is comprised of cellulose fibres, connected to lignin by

hemicellulose, as shown in the figure below (Figure 2-5). Hemicellulose is a

Fresh fruit bunch (FFB)

FFB stripping

Empty fruit bunch (EFB)

Pretreatment and enzymatic hydrolysis

EFB hydrolysates

Cultivation by oleaginous microorganisms

Microbial oil

• Biodiesel• Nutritional oils• Cocoa butter equivalents

15

complex carbohydrate with branches that consists of different polymers, which are

mainly xylan for plants biomass [28]. Lignin provides structural support,

impermeability and protection against microbial action and oxidative stress to the

plants [28].

Figure 2-5 Lignocellulosic structure of plants [29].

Cellulose is a homopolymer made from D-glucose subunits linked by β-1,4

glycosidic bonds [30]. In plant biomass, cellulose consists of parts with crystalline

structure and amorphous structure [28]. Cellulose strains are bundled together

through weak hydrogen bonding [28]. Hemicelluloses are short and highly branched

heteropolymers of D-xylose, D-arabinose, D-glucose, D-galactose and D-mannose

[30]. Hemicellulose compounds start to dissolve into water at 150 °C [28]. Lignin is

an amorphous heteropolymer comprising of phenylpropane units such as p-coumaryl,

coniferyl and sinapyl alcohol [28]. As lignin is tightly bound to cellulose and

hemicellulose, lignin removal is an effective strategy for pretreatment prior to

enzymatic hydrolysis. This is because lignin can reduce the efficiency of enzymatic

hydrolysis as cellulases can non-specifically adsorb to lignin [31] or lignin can block

cellulose from getting accessed by cellulase [28].

2.2.2 Pretreatment techniques for lignocellulosic biomass

Pretreatment is crucial for effective enzymatic hydrolysis and fermentation of

lignocellulosic biomass. The aims of pretreatment are to remove lignin, hydrolyse

hemicellulose and interrupt the crystalline structure of cellulose [32]. In addition,

pretreatments generally increase the biomass surface area so that more surfaces are

exposed in the lignocellulose matrix for enzymatic hydrolysis. Effective pretreatment

16

processes should have low loss of sugars and low concentration of sugar degradation

products [30]. Sugar degradation products such as acetic acid, furfural and 5-

hydroxymethyl furfural (HMF) have been reported to cause inhibition to microbial

growth [33]. Acetic acid is formed through deacetylation of hemicellulose. Furfural

is the degradation product of pentoses and HMF is generated from the degradation of

hexoses [33].

Pretreatment of lignocellulosic biomass can be categorized into physical,

biological, physicochemical and chemical pretreatments. Physical pretreatments that

have been employed for lignocellulosic biomass includes mechanical size reduction,

microwave oven and irradiation pretreatment [30]. However, physical pretreatments

such as milling are costly and generally result in low effectiveness [34]. Biological

pretreatment techniques involve degradation of the complex lignocellulosic structure

with the use of enzyme-producing fungi such as such as brown-, white- and soft-rot

fungi [35], which therefore does not require high chemical input and energy use [34].

However, there are currently no controllable biological systems that are rapid enough

for the pretreatment process [34].

Physicochemical pretreatment techniques that have been applied for

lignocellulosic biomass are steam explosion, liquid hot water (LHW) and

supercritical CO2 methods. Steam explosion involves heating the biomass with high

pressure steam, approximately at 20 - 50 bar and 160 – 290 °C for a few minutes,

followed by sudden decompression to atmospheric pressure [30, 36]. Rapid

depressurisation of the biomass disrupts the fibre structure, which causes some

disintegration of lignin structure and partially hydrolyse hemicellulose [37]. In the

LHW process, compressed hot liquid water is used to hydrolyse hemicellulose at a

temperature of 170 – 230 °C and pressure above 5 MPa for 20 min [30]. The LHW

process results in high xylose recovery and is chemical-free [30]. However, this

pretreatment requires high inputs of water and energy [34]. Supercritical CO2

pretreatment offers an environmentally friendly pretreatment technique for

lignocellulosic biomass [36]. Despite all the advantages of steam explosion, LHW

and supercritical CO2, the use of high pressures in these techniques may have

negative effects on the economics of the pretreatment process [34].

17

Chemical pretreatment techniques have the potential for effective pretreatment,

which increases operating costs depending on the cost and amount of chemical used

[34]. Chemical pretreatment techniques like dilute acid and alkaline pretreatments

are the most common techniques for pretreating lignocellulosic biomass. Alkaline

pretreatments primarily remove lignin from the lignocellulose matrix, so that

cellulose and hemicellulose are more susceptible to enzymatic hydrolysis. Alkaline

pretreatments work by interrupting the biomass cell wall through hemicellulose,

lignin and silica solubilisation; uronic and acetic esters hydrolysis; and cellulose

swelling [30]. Alkaline pretreatments are carried out at moderate temperatures and

pressures with the use of alkaline agents such as sodium hydroxide (NaOH),

potassium hydroxide (KOH), calcium hydroxide (Ca(OH)2) and aqueous ammonia

(NH3) [30]. However, the high cost of NaOH and KOH are not economical for the

production of fuels [34]. Unlike alkaline pretreatments, dilute acid pretreatments

mainly hydrolyse hemicelluloses by breaking β-glycosidic bond of hemicellulose and

making monomeric C5 sugars available [36]. The most common acidic agent used

for dilute acid pretreatments is sulfuric acid (H2SO4), followed by hydrochloric acid,

nitric acid and phosphoric acid [30]. Dilute acid pretreatments, however, promote

degradation of sugars into inhibitory compounds such as furfural, HMF and acetic

acid [38]. Some ionic liquids (ILs) are reported to be effective in dissolving biomass.

ILs are typically non-flammable, thermally stable and non-volatile [34]. ILs with

anion activity dissolve carbohydrates and lignin simultaneously, where the complex

non-covalent interactions between cellulose, hemicellulos and lignin of the biomass

are effectively disrupted, with minimal production of degradation products [34].

However, the production and recovery costs of ILs limit its commercial application.

Chemical methods that have been tested for the pretreatment of oil palm

biomasses are alkaline-, dilute acid- and IL-based methods. In one study, a glucose

yield of 41.4% was obtained with 21% (w/w) aqueous NH3 pretreatment of EFB

followed by enzymatic hydrolysis [39]. Pretreatment of EFB by dilute H2SO4

increased the cellulose content of the fibre from 41.32% to 62.97% [40]. IL

pretreatment of oil palm frond (OPF) resulted in 100% glucose recovery [41]. EFB

has also been subjected to ammonia fibre expansion (AFEX) pretreatment [30].

AFEX is the combination of the alkaline treatment and steam explosion at moderate

temperature and short periods of time [30]. AFEX pretreatment of EFB resulted in

18

90% sugars recovery after enzymatic hydrolysis [42]. One of the features of AFEX is

that only a very small fraction of hemicellulose is solubilised [30].

Most of the chemical pretreatment methods that have been tested on oil palm

biomass are shown to be effective. However, some of these techniques are not

economical considering the overall cost for the conversion of lignocellulosic biomass

to fuel. Dilute acid pretreatment using H2SO4 is a promising technique for an

effective and economical process for biomass fractionation of EFB. H2SO4 is cheap

and its use in dilute acid pretreatment led to effective results [43]. In addition, the use

of dilute acid pretreatment has been well established on various types of

lignocellulosic biomass [34]. Dilute acid pretreatment also does not require explosive

depression for effective pretreatment [34]. Even though dilute acid pretreatment is

accompanied by the production of sugar degradation products that are potential

growth inhibitors (i.e., acetic acid, furfural and HMF), detoxification can be applied

to pretreatment hydrolysate following dilute acid pretreatment. Overliming is one of

the most common detoxification methods that have been used to remove these

inhibitors. In this process, the pH of the hydrolysate is raised to 9-10 by Ca(OH)2

followed by lowering the pH to 5.5 using H2SO4 [44]. Even though dilute acid

pretreatment does not remove the majority of lignin from the solid residue of the

biomass, the pretreatment disrupts the structure of lignin [34]. Therefore, lignin that

remains in the solid residue may not have the same negative impact on enzymatic

hydrolysis [34].

2.2.3 Enzymatic hydrolysis of lignocellulosic biomass

Depolymerisation of the complex sugars in pretreated lignocellulosic biomass

to sugar monomers can be accomplished through acidic or enzymatic hydrolysis.

Enzymatic hydrolysis is generally the preferred method for hydrolysis due to its high

specificity and low levels of production of compounds that can inhibit microbial

cultivation. Therefore, effective enzymatic hydrolysis requires high availability of

cellulose and xylan in the lignocellulosic matrix, which makes biomass pretreatment

the most critical step in the production of fermentable sugars from lignocellulosic

biomass.

19

Enzymatic hydrolysis of the pretreated lignocellulosic biomass occurs through

the application of cellulase and hemicellulase enzymes for hydrolysing the bonds of

cellulose and hemicellulose respectively. Cellulase enzymes typically consists of

cocktails of β-1,4-endoglucanases, β-1,4-exoglucanases and β-glucosidases. β-1,4-

endoglucanases attack the low crystallinity regions of cellulose to create free chain

ends [30]. Cellobiose units are cleaved from the free chain ends by β-1,4-

exoglucanases and are then hydrolysed into glucose by β-glucosidases [45].

Hemicellulase enzymes are more complex than cellulases as hemicellulose has more

diverse compositions. The key components of hemicellulases are endoxylanases and

β-xylosidase [31]. Endoxylanases hydrolyse the xylan backbone into shorter

oligosaccharides, which are then cleaved into xylose by β-xylosidase [31].

Commercial cellulase and hemicellulase enzymes are typically produced from fungi.

There are various types of fungi that are capable of producing endoglucanases,

exoglucanases, β-glucosidases and endoxylanase such as Trichoderma and

Aspergillus [30].

Temperature, pH and substrate loading are among the key factors that affect

enzymatic hydrolysis. Optimal temperature and pH conditions are required to

maintain the three dimensional shape of the enzyme’s active site, which is critical for

effective enzymatic activity [46].

2.3 Microbial cultivation for oil production from lignocellulosic biomass

2.3.1 Microbial oil cultivation by oleaginous microorganisms

The presence of carbohydrate in the lignocellulosic oil palm biomass provides

an opportunity for the conversion of these fibrous residues into higher value products

through microbial cultivation. However, the oil palm biomass must be first pretreated

and hydrolysed prior to any further microbial application for breaking down the

lignocellulosic structure of the wastes into simple sugars. These simple sugars can be

converted into oil by oleaginous microorganisms. Certain types of microalgae,

bacteria, fungi, and yeasts are capable of accumulating more than 20% lipid in their

intracellular membranes [47]. Lipids accumulated are used by microorganisms as an

energy source and for cell membrane synthesis [48].

20

Microalgae can produce oil through phototrophic and heterotrophic cultivation,

depending on the types of carbon sources as the feedstock for cultivation. Oil

production by bacteria is still not practical, even though bacteria have higher growth

rates compared to other microorganisms, as bacteria only accumulate complex lipids

[49]. Oleaginous yeasts and filamentous fungi have been reported to be able to

accumulate oil [50]. However, there are only a small number of studies for oil

production from fungi and yeasts, in comparison to microalgae [51].

The cultivation of oleaginous microorganisms is carried out under nutrient-

limiting conditions with excess carbon substrate[52]. Lipid can be accumulated

within the cells as discrete oil droplets [50]. Lipid accumulation pathways can be

categorized into two; namely de novo and ex novo. In de novo synthesis, hydrophilic

materials like sugars are consumed as the sole carbon source in nitrogen-limiting

conditions [53, 54]. Conversely, in ex novo synthesis, hydrophobic materials such as

fatty acids, oils or triacylglyceride (TAG) are utilised and accumulated with or

without modification within the cell [54, 55].

Oleaginous microorganisms start to build up oil from excess carbon with the

absence of nutrients as the stress condition. Oil production from glucose in

microorganisms involves glycolysis and tricarboxylic acid (TCA) cycles for glucose

metabolism [50]. Citrate from TCA that has been transported out from mitochondria

to cytosol is then converted to acetyl-coA through ATP-citrate-lyase (ACL) [56],

where acetyl-CoA is the precursor of fatty acid biosynthesis [50]. Non-oleaginous

microorganisms (e. g., Saccharomyces cerevisiae) will not accumulate oil even under

favourable growth conditions for oil production, which Ratledge suggested is due to

the absence of the ACL enzyme [50].

Nitrogen limitation is the most established stress condition for oleaginous

cultivation [50]. In nutrient-limiting conditions, protein and nucleic acid production

will stop when all nitrogen sources have been consumed by microorganisms [52].

However, the excess carbon will continue to be assimilated for oil synthesis.

Therefore, carbon to nitrogen ratio (C/N) is crucial for microbial oil production as

oleaginous microorganisms accumulate oil with excess carbon sources and limited

nitrogen supply [57]. Many studies have demonstrated that yeast extract is the best

nitrogen source for maximum biomass yield and oil accumulation for oleaginous

21

microorganisms [58-61]. This is because yeast extract is not only supplying nitrogen

to the cells, but also contains essential vitamins and metal ions [58, 61].

There are other parameters such as physical conditions, which are also critical

to oleaginous cultivation. Among the physical parameters that are important to

oleaginous cultivation are temperature, pH and oxygen supply. Temperature can also

influence the degree of saturation of lipids, as decreasing temperature will reduce the

degree of saturation of lipids [55]. The compositions of polyunsaturated fatty acids

(PUFAs) of Mortierella alpina cultivated at 12 °C were reported to be higher than

the cultivation at 15 °C, 20 °C and 25 °C [62]. pH is also an essential factor for oil

production from oleaginous microorganisms, as growth and oil accumulation only

occur under certain pH conditions [57]. Mortierella ramanniana cultivated on

dextrose yeast broth was reported to only grow at pH 3.0-10.0 and resulted in the

highest biomass concentration at pH 5.0 [61]. Oxygen supply is vital to oleaginous

microbial cultivation as some oleaginous microorganisms are not able to assimilate

organic carbon under anaerobic condition [26]. For some oleaginous microorganisms

that are not strict aerobic microorganisms, anaerobic conditions that occur during the

cultivation could lead to the formation of ethanol or lactic acid as the by-product

from carbon assimilation, thereby reducing the conversion efficiency of carbon to oil.

However, the effect of temperature will not be investigated further in this study as

there are numerous studies that have been conducted in this area. In addition, the

literature has demonstrated that the influence of temperature in the microbial

cultivation is more significant to the degree of saturation of fatty acids [63].

Therefore, optimum temperature from previous studies will be used for microbial

cultivation in this study.

However, the initial step in microbial cultivation of lignocellulosic

hydrolysates is to select oleaginous microorganisms that are able to grow and

produce oil from lignocellulosic hydrolysates. In this research project, the following

criteria have been formulated in order to evaluate the most suitable oleaginous

microorganisms for oil production from lignocellulosic hydrolysates.

1. Capability to grow on glucose and/or xylose

22

This criterion is essential because lignocellulosic biomass consist of mainly cellulose

and hemicellulose. Hydrolysis of cellulose and hemicelluloses from lignocellulosic

biomass forms monomeric sugars namely, glucose and xylose respectively.

2. High oil concertation and oil content

Microorganisms that are capable of accumulating high level of oil are preferable for

further study of microbial oil production from the oil palm biomass hydrolysates.

3. High oil yield

Oil yield measures the efficiency of converting carbon substrates to oil.

4. High tolerance to inhibitors

Chemical pretreatment of EFB may results in the production of sugar degradation

compounds such as furfural (from pentoses) and 5-hydroxymethylfurfural (HMF)

(from hexoses). Furfural and HMF have been shown to have inhibitory impacts on

yeasts and fungi [64, 65].

An additional important criterion that can be considered is the capability of

the microorganism to assimilate glycerol. Glycerol is the by-product of the biodiesel

production process, and the reapplication of glycerol ensures the sustainability of

biodiesel production from the palm oil industry. Many oleaginous microorganisms

can thrive well with the use of glycerol as the organic carbon substrate.

There are limited studies on microbial oil production from oil palm biomass

hydrolysates. EFB has been used for microbial oil production by Tampitak et al.

through alkaline pretreatment, followed by one-step or two-step acid hydrolysis of

pretreated EFB [66]. EFB used for the production of DHA by microalage

Aurantiochytrium sp. KRS101 was subjected to alkaline pretreatment, followed by

23

enzymatic hydrolysis [67]. This section explores the potential use of heterotrophic

algae, oleaginous yeasts and filamentous fungi for microbial oil production as the

initial step to achieve the first aim of this research.

2.3.2 Heterotrophic cultivation of microalgae

Microalgae cultivation can be categorized into four main types of cultivation

including phototrophic, heterotrophic, mixotrophic and photoheterotrophic [68].

Heterotrophic cultivation is viewed as the most suitable growth environment for

microalgae on lignocellulosic hydrolysate. Microalgae grown in this type of

cultivation condition are capable of metabolising organic carbon in the absence of

light. Heterotrophic cultivation has been reported to be more advantageous than

phototrophic cultivation as it provides cheaper operating costs and better cultivation

process control, as there is no light requirement [69]. Chlorella species grown

heterotrophically have been reported to have higher growth rates compared to

phototrophic cultivation. Heterotrophic cultivation of Chlorella protothecoides on

glucose resulted in four fold increase in oil accumulation compared to growth under

phototrophic condition [70].

Chlorella species have been shown to accumulate more than 25% oil in their

cells [71]. Chlorella vulgaris is the most frequently studied microalgae for oil

production, followed by C. protothecoides and Chlorella sorokiniana, especially for

cultivation on glucose as the carbon substrate. However, there are limited studies on

the cultivation of microalgae on different carbon substrates like xylose which

typically made up the major component of hydrolysate of pretreatment. One study

has reported on the use of xylose by Chlorella species and shown that this

microorganism could not assimilate xylose in the absence of light [72]. The

cultivation of microalgae Aurantiochytrium sp. on enzymatic hydrolysate of EFB

showed that only 2 g/L of xylose was consumed from media containing 18 g/L

xylose [67]. Another study has shown that C. protothecoides could grow on crude

glycerol with high biomass and oil yield [73].

C. protothecoides is viewed as a promising microorganism for microbial oil

production from the organic carbon substrates. C. protothecoides has been reported

to thrive in glucose- and glycerol- containing media [73-77]. In addition, C.

24

protothecoides has been reported to be able to produce oil from various organic

carbon substrates. For instance, feedstock that has been used for growing C.

protothecoides heterotrophically are: acetate, sweet sorghum hydrolysate, corn

powder hydrolysate, Jerusalem artichoke tuber hydrolysate, waste activated sludge

hydrolysate, waste molasses hydrolysate, potato starch hydrolysate and cassava

starch hydrolysate [76, 78-83]. However, these feedstocks primarily consist of

glucose and fructose. There have been no reports on the utilisation of xylose by C.

protothecoides under heterotrophic cultivation conditions.

Another species of Chlorella, C. zofingienesis also has the potential to be used

for microbial oil production from organic carbon sources. C. zofingienesis has been

previously cultivated under heterotrophic condition for carotenoid synthesis but has

not been explored comprehensively for oil production. However, the use of C.

zofingienesis for oil production is promising. One study has demonstrated that higher

oil concentration under heterotrophic cultivation (5.0 g/L) was achieved in

comparison to the growth under photoautotrophic cultivation (0.5 g/L) [84]. There

are no studies exploring whether this microorganism is capable of producing oil from

xylose or glycerol as the carbon substrates.

One of the drawbacks of using heterotrophic microalgae cultivation for oil

production is that heterotrophic cultivation is prone to contamination due to the

presence of high concentration of sugars in the media [68]. Contamination problems

could also be exacerbated by microalgae’s slow growth rates compared to bacteria

and fungi. Therefore, it is important to also explore other types of oleaginous

microorganisms which may be more robust for oil production from EFB hydrolysate.

2.3.3 Oleaginous yeasts

The use of yeast strains such as Saccharomyces cerevisiae in sugar

fermentation has been extensively applied in ethanol production, where its industrial

application has been established for millennia. However, the use of yeasts for

microbial oil production requires more exploration. There are several types of yeasts

that are known to accumulate oils such as Rhodosporidium, Rhodotorula, Lipomyces

and Yarrowia [85]. These yeast strains are capable of accumulation of up to 50% oil

within the cells [85]. Among these yeast strains, Yarrowia lipolytica,

25

Rhodosporidium toruloides, Lipomyces starkeyi, Trichosporon fermentans,

Trichosporon pullulan, Rhodotorula glutinis, Trichosporon capitatum and

Cryptococcus curvatus are the species that have been most frequently studied and

shown high biomass and oil yields [86]. Oleaginous yeasts have been successfully

cultivated on various organic carbon substrates (Table 2-1), including agro-industrial

wastes, organic acids, molasses, food products, glycerol, whey and wastewaters [54,

57].

Table 2-1 Various agro-industrial hydrolysates as the feedstock for oleaginous yeasts cultivation for oil production

Substrate Sugar type Strain ReferenceCassava starch hydrolysate

Glucose Rhodosporidium toruloides [87]

Corn stover hydrolysate

Glucose and xylose

Trichosporon cutaneum [88]

Corncob hydrolysate

Glucose and xylose

Cryptococcus sp., Trichosporon coremiiforme, Trichosporon cutaneum and Trichosporon dermatis

[89-92]

Rice straw hydrolysate

Glucose and xylose

Trichosporon fermentans [93]

Sugarcane bagasse hydrolysate

Glucose and xylose

Trichosporon fermentans and Yarrowia lipolytica Po1g

[94, 95]

Sweet sorghum bagasse hydrolysate

Glucose and xylose

Cryptococcus curvatus

[96]

Wheat straw hydrolysate

Glucose and xylose

Cryptococcus curvatus, Lipomyces starkeyi, Rhodotorula glutinis, Rhodotorula toruloides and Yarrowia lipolytica

[97]

Cryptococcus species have been known to accumulate substantial amounts of

oil, especially C. curvatus, which has been regularly studied for oil accumulation

from various carbon feedstocks [97, 98]. Other Cryptococcus species including

Cryptococcus albidus also shows potential for oil production. However, there have

been no reports in the use of C. albidus for oil production from lignocellulosic

biomass. C. albidus has been cultivated on volatile fatty acids for oil production [99,

100]. The only other studies on oil accumulation of C. albidus date back to the

1980’s by Hansson and Dostálek. These researchers conducted studies on C. albidus

for oil production with various parameters including different types of sugar

26

substrates and nitrogen sources, in batch, fed-batch and continuous cultivation

conditions [101-103]. Since there are only a few studies that have been undertaken

on C. albidus for oil production, there is a considerable knowledge gap relating to

whether C. albidus is capable of assimilating lignocellulosic hydrolysates.

The use of C. albidus for cultivation on lignocellulosic hydrolysates is of

interest as C. albidus was shown to be able to accumulate oil not only from glucose

as feedstock but also from xylose and glycerol under limiting-nitrogen conditions. C.

albidus grown in glycerol-containing media recorded the highest oil yield (43.8%

(w/w)), followed by cultivation on glucose (40.1% (w/w)) and xylose (33% (w/w))

[101]. C. albidus is also beneficial for commercial application as it grows with low

optimum temperature of 25 to 30 and broad optimum pH (pH 5.5 to 7.0) [99,

101]. Another attractive feature of C. albidus is its ability to accumulate oil with or

without nutrient limitation [102]. Therefore, there is a possibility that C. albidus may

accumulate oil even in the early stages of cultivation.

Rhodotorula mucilaginosa has also been shown to be able to produce oil based

on previous studies. However, the extent of these studies is quite limited. In addition,

another species of Rhodotorula, R. glutinis, is well known for its high level of oil

production, and has been successfully grown on lignocellulosic hydrolysates

including hydrolysates of acid-pretreated wheat straw [97]. Marine-derived R.

mucilaginosa was cultivated on hydrolysates of inulin, tubers extract of Jerusalem

artichoke and cassava starch, with oil contents of 47 – 53% (w/w) [86, 104]. In

addition, R. mucilaginosa was also used for oil production from molasses with an oil

content of 69.5% (w/w) [105]. Fatty acids composition found in oils of R.

mucilaginosa are mainly palmitic acid (C16:0), palmitoleic acid (C16:1), stearic acid

(C18:0), oleic acid (C18:1) and linolenic acid (C18:2); which is similar to the

composition of vegetable oils [86].

Oil production through yeast cultivation is beneficial as yeasts can have high

growth rate, high oil accumulation yields and high similarity of fatty acids

compositions to plant oils [104].

27

2.3.4 Oleaginous fungi

Certain filamentous fungi strains like Mortierella isabellina and

Cunninghamella echinulate are reported to accumulate high amounts of oil in their

mycelia [53, 54]. Fungal cultivation of M. isabellina has been extensively studied

due to its capability to thrive and accumulate significant amounts of oil in

lignocellulosic hydrolysates including hydrolysates of corn fibre, corn stover, rice

hulls and wheat straw (Table 2-2). M. isabellina has been shown to grow and

produce oil (18.2% (w/w) of oil) with xylose as the organic substrate [106].

Table 2-2 Various agro-industrial hydrolysates as the feedstock for oleaginous fungi cultivation for oil production

Substrate Sugar types Strain Application ReferenceCorn fibre hydrolysate

Glucose and xylose

Mortierella isabellina Biodiesel feedstock

[107]

Corn starch hydrolysate

Glucose Mortierella alpina Arachidonic acid

[108]

Corn stover hydrolysate

Glucose and xylose

Mortierella isabellina Biodiesel feedstock

[109]

Wheat straw hydrolysate

Glucose and xylose

Mortierella isabellina, Mortierella vinacea, Thermomyces lanuginosus, Aspergillus terreus, Cunninghamella elegans and Rhizopus oryzae

Biodiesel feedstock

[110, 111]

Similar to oils extracted from algae and yeasts, fungal oils can be used as

feedstocks in biodiesel production (Table 2-2). Another major attraction of

oleaginous fungi cultivation is that certain filamentous fungi, such as Mortierella

alpina, have been reported to accumulate high amounts of γ-linolenic acid (GLA)

and arachidonic acid (ARA) [108, 112]. The application of these two polyunsaturated

fatty acids (PUFA) is significant in the health products industry.

Another interesting feature of filamentous fungi is that the morphology of

filamentous fungi which in submerged culture is typically in the form of free

dispersed mycelia or pellets. Many filamentous fungi grow in pellets due to the

aggregation of fungi’s mycelia (Figure 2-6) [113]. The morphology of filamentous

28

fungi enable easy separation during downstream processing, where the biomass can

be easily harvested through a simple filtration technique [113].

Aspergillus oryzae is promising for microbial production from lignocellulosic

hydrolysates. A. oryzae has been used intensively in saccharification studies as

Aspergillus strains are known to be excellent enzymes producers for breaking down

complex carbohydrates [114]. A. oryzae is used for producing cellulases, β-

galactosidase, xylanase and amylase for enzymatic hydrolysis processes [115]. A.

oryzae has been identified as an oleaginous microorganism, however, there are only

a small number of studies that have been conducted on oil production from this

fungus. Cultivation of A. oryzae on glycerol has not been reported. The capability of

A. oryzae to synthesise saccharification enzymes is another added advantage of this

fungus in addition to the ability to accumulate oil. Because of that characteristic, A.

oryzae has been used frequently for oil production from complex sugars of various

lignocellulosic biomasses such as wheat straw, cellulose, starch and potato

processing waste, without any additional enzymes [114, 116, 117]. The main fatty

acids compositions of oil extracted from A. oryzae cultivated on wheat straw are

palmitic acid (C16:0), linolenic acid (C18:2), oleic acid (C18:1) and stearic acid

(C18:0), which is similar to the fatty acid compositions of palm olein [114].

Figure 2-6 A culture that contains filamentous fungi in pellet form.

Mucor plumbeus is another filamentous fungus that has good potential for oil

production from lignocellulosic hydrolysates. A study of microbial oil production by

M. plumbeus from hydrolysate of acid-pretreated wheat straw resulted in an oil

content of 20.6% (w/w) and oil concentration of 0.99 g/L [110]. However, the use of

29

M. plumbeus has only been reported in a few studies. Certain Mucor species are

recognised as excellent poly-unsaturated fatty acids producers, for example, Mucor

indicus for GLA production [118]. Other Mucor species that have been investigated

for oil production are Mucor circinelloides grown on corn-ethanol stillage

supplemented with crude glycerol and Mucor recurvus cultivated on sugarcane

molasses [119, 120]. Like A. oryzae, cultivation of M. plumbeus on glycerol has not

been reported.

2.4 Applications of microbial oils

2.4.1 Introduction

Oil extracted from oleaginous microorganisms is typically rich in

triacylglycerides (TAG) or polyunsaturated fatty acids (PUFAs). Both TAG and

PUFA have significant applications in oleochemical and pharmaceutical industries.

Microbial oil, also known as single cell oil (SCO), has been of research interest due

to the wide range of potential applications. Commercial production of microbial oils

commenced in 1985, but only lasted for six years as the process was not

economically viable at that time [50]. Therefore, further research is required to make

microbial oil production more cost effective. The utilisation of low cost agro-

industrial waste for microbial cultivation can potentially improve the economics of

microbial oil production.

Microbial oil produced from the cultivation of oleaginous microorganisms can

be utilised as a feedstock for the production of biodiesel, essential fatty acids, cocoa

butter substitute and chemicals, depending on the fatty acid profiles of the oil

produced. Microbial oil with high amounts of TAG can be converted into biodiesel.

On the other hand, microbial oil with high level of PUFAs can be applied for the

production of essential fatty acids. Microbial oil has also been studied for the

production of cocoa butter substitutes. Jin et al. have suggested that microbial oil has

the potential to be applied in the synthesis of various chemicals [56].

2.4.2 Energy application of microbial oil

Environmental and sustainability issues associated with the use of fossil fuels

have driven a global quest to find alternative sources of energy. Biomass-derived

30

biofuels create an opportunity to produce sustainable and renewable energy.

Biodiesel has been well researched and provides an alternative to conventional diesel

fuels.

Biodiesel consists of fatty acid methyl esters (FAMEs) which can be derived

from transesterification of TAG with low molecular weight alcohols. The most

common of biodiesel feedstocks are vegetable oils or animal fats. Vegetable oils,

which comprise TAG extracted from plants was first used in diesel engines by the

engine inventor himself, Rudolph Diesel [112]. Biodiesel has been produced from

various plants oils such as rapeseed oil [121]. However, the application of these

edible oils for biodiesel production could lead to increasing food prices due to

growing demand of both fuels and food products [112]. Even though non-edible oils

such as Jatropha oil and waste cooking oil can be transesterified to biodiesel, these

oils have low availability and reduced performance in cold weather [121]. Therefore,

microbial oil has been suggested as an alternative feedstock for biodiesel production.

Oleaginous microorganisms typically accumulate oil with myristic acid

(C14:0), palmitic acid (C16:0), stearic acid (C18:0), oleic acid (C18:1) and linolenic

acid (C18:2), which are analogous to fatty acid compositions of plant oils [49, 109].

Microbial oil is a viable feedstock for biodiesel as oils with high levels of oleic acid

are suitable to be converted into biodiesel [121]. There are several benefits of using

microbial oils as an alternative to plant oils in biodiesel production which are (1) no

competition with food production, (2) less labor intensive, (3) easy scaling up, (4) no

seasonal and climate impacts [122]. Numerous studies have successfully converted

oil extracted from C. protothecoides to biodiesel [70, 76, 83, 123]. There are also

several studies that used yeast oils for biodiesel production, but studies on the

application of fungal oils for producing biodiesel are quite limited [54].

2.4.3 Health applications of microbial oils

Microbial oils with high levels of PUFAs have the potential to be used as

alternative feedstocks in health products manufacturing, and for the production of

essential fatty acids. Among PUFAs that have been extracted from oleaginous

microorganisms are γ-linolenic acid (GLA) (C18:3, n-6), dihommogamma-linolenic

acid (DHGLA) (C20:3, n-6), arachidonic acid (ARA) (C20:4, n-6), docosahexaenoic

31

acid (DHA) (C22:6, n-3) and eicosapentaenoic acid (EPA) (C20:5, n-3), and can be

used as dietary sources of essential fatty acids [54]. Essential fatty acids are fatty

acids that cannot be synthesized by humans or animals, but must be taken in dietary

form for health [121]. Essential fatty acids have been shown to have important health

benefits, in addition to having a crucial role in the development of brain and retinal

function, and preventing cancer [54]. However, the use of commercial sources of

DHA and EPA from marine fish oils has raised several issues such as heavy metals

contamination, limited supply, odour and taste problems, and it has a complicated

purification process [124, 125]. Mucoralean fungi have been investigated for PUFAs

accumulation including Mucor circinelloides for GLA production and Mortierella

alpine for ARA production [47, 126].

2.4.4 Food applications of microbial oils

Microbial oil has the potential to be a feedstock for cocoa butter equivalent

(CBE) production, though this field has not been explored intensively. Cocoa butter

has significant applications in cosmetology and food technology and is one of the

key ingredients in chocolate production [47, 57]. Cocoa butter is mainly comprised

of TAG in the form of P-O-S or S-O-S (P: Palmitic acid, O: Oleic acid, S: Stearic

acid) [57]. Biomass-derived microbial oil may provide a more economical raw

material for cocoa butter production, as existing production involves high cultivation

costs of cocoa [57]. Since cocoa butter consists of palmitic acid, stearic acid and

oleic acid, microorganisms composed of similar fatty acid profiles can be used for

CBE production [47]. A study on the cultivation of Yarrowia lipolytica on glycerol

and glucose, with stearin as a co-substrate in nitrogen-limiting environment, resulted

in the production of oils with similar fatty acid compositions to cocoa butter [127].

The oils of Y. lipolytica consisted of 50-70% stearic acid from the total fatty acids

[127].

2.4.5 Chemicals applications of microbial oils

Fatty acids from microbial oils have the potential to be sustainable and

renewable materials for the production of chemicals. Renewable raw materials in the

chemical industry include the use of animal-derived oils and fats [128]. Research on

the synthesis of chemicals from plant-derived oils is becoming popular as plant oils

32

have the potential to be a renewable and sustainable raw material, as well as an

alternative to petroleum-derived raw materials for the production of chemicals [129].

There are various applications of fatty acids in the synthesis of chemicals such as the

synthesis of 9-decenoic acid from oleic acid through metathesis reaction with

ethylene [128]. Fatty acids from vegetable oils have also been tested for the

production of polyurethanes [129]. Vegetable oil-derived polyurethanes was shown

to be comparable with polyurethanes derived from petrochemical polyols [129].

However, the studies on the use of microbial oil-derived fatty acids for chemical

production are limited.

A microbial oil biorefinery that comprises biodiesel production can potentially

utilise glycerol, the by-product of transesterification of oil, as the feedstock for

microbial cultivation and for the production of chemicals. Glycerol can be used as an

alternative feedstock for the production of many C3 commodity chemicals, where

these chemicals are currently synthesised from propylene in petrochemical processes

[56].

2.5 Research gap and discussion

Studies have shown that there are various groups of oleaginous

microorganisms, including microalgae, yeasts and filamentous fungi, that have the

capacity to accumulate lipids from carbon substrates. Based on the literature,

different groups of oleaginous microorganisms could potentially have different

capacities and challenges in oil production from lignocellulosic hydrolysates.

However, there is limited information on oil production from lignocellulosic

hydrolysates since the literature focusses on cultivation with glucose as the carbon

substrate. Therefore, a systematic selection approach is important in order to select

microorganisms that are not only limited to a specific substrate. Adding to the

complexity of the selection is that there is no direct comparison between different

groups of microorganisms for oil production from the same substrates. Criteria have

been identified in order to facilitate the selection, where the goal of selection is to

evaluate the most suitable oleaginous microorganisms for oil production from

lignocellulosic hydrolysates. However, the selection is still complex as each criterion

has a different degree of importance to the goal of selection. In addition, there is no

systematic criteria-based approach to selection of oleaginous microorganisms for oil

33

production. Based on the literature, six oleaginous microorganisms have been

identified as potential microorganisms for oil production from lignocellulosic

hydrolysates, which are Chlorella protothecoides and Chlorella zofingiensis

(microalgae), Cryptococcus albidus and Rhodotorula mucilaginosa (yeasts), and

Aspergillus oryzae and Mucor plumbeus (fungi). However, these microorganisms

have to be further evaluated through cultivation on glucose, xylose and glycerol,

followed by multi-criteria analysis in order to select the most suitable

microorganisms to be cultivated on lignocellulosic hydrolysates.

As shown in this chapter, there are fewer studies on the use of lignocellulosic

hydrolysates as the feedstock for microbial oil production. There is more complexity

involved with the use of lignocellulosic hydrolysates in comparison to the use of pure

sugars including presence of mixed sugar solutions (i.e., glucose and xylose),

inhibitors (i.e., acetic acid, HMF and furfural) and additional nitrogen sources in the

cultivation media. Therefore, for cultivation on lignocellulosic hydrolysates, more

investigation is required with regard to (1) the sugar consumption profiles of

microorganisms, (2) the impact of inhibitors and the need of detoxification of

hydrolysates and (3) the need for additional nitrogen sources in the cultivation media,

in order to develop the process of oil production from EFB.

A complete evaluation of the oil production process from EFB has to also

include the economic assessment of the process. From the reported studies of

microbial oil production from EFB, none of those studies have evaluated the

economic aspects of microbial oil production from EFB. The techno-economic

assessment of oil is significant in order to evaluate the viability of microbial oil

production from EFB, and whether the process may improve the profitability and

sustainability of the palm oil industry.

Optimising the process for microbial oil production from EFB is significant

in order to achieve the optimal oil yield that can improve the economics of the

process. As discussed previously in this chapter, optimum C/N ratio is critical for oil

accumulation. However, there are no studies that evaluate the impact of C/N ratio on

the microbial oil production from the hydrolysates of EFB. There are other important

conditions of cultivation that may impact the oil yield such as pH and inoculum size.

However, there are limited studies on the optimisation of the cultivation of

34

oleaginous microorganisms on lignocellulosic hydrolysates. There are also no studies

on microbial oil production from EFB in bioreactor systems. The cultivation study in

bioreactor systems is important for evaluating the potential for scaling up the process

for commercial application.

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46

Selecting oleaginous microorganisms for microbial oil production

3.1 A multi-criteria analysis approach for ranking and selection of microorganisms for the production of oils for biodiesel production

F. B. Ahmad, Z. Zhang, W. O. S. Doherty, I. M. O’Hara

Centre for Tropical Crops and Biocommodities, Queensland University of

Technology, Brisbane, Australia

Abstract

Oleaginous microorganisms have potential to be used to produce oils as

alternative feedstock for biodiesel production. Microalgae (Chlorella protothecoides

and Chlorella zofingiensis), yeasts (Cryptococcus albidus and Rhodotorula

mucilaginosa), and fungi (Aspergillus oryzae and Mucor plumbeus) were

investigated for their ability to produce oil from glucose, xylose and glycerol. Multi-

criteria analysis (MCA) using analytic hierarchy process (AHP) and preference

ranking organization method for the enrichment of evaluations (PROMETHEE) with

graphical analysis for interactive aid (GAIA), was used to rank and select the

preferred microorganisms for oil production for biodiesel application. This was based

on a number of criteria viz., oil concentration, content, production rate and yield,

substrate consumption rate, fatty acids composition, biomass harvesting and nutrient

costs. PROMETHEE selected A. oryzae, M. plumbeus and R. mucilaginosa as the

most prospective species for oil production. However, further analysis by GAIA

Webs identified A. oryzae and M. plumbeus as the best performing microorganisms.

Keywords: Microbial oil, Multi-criteria analysis, Glucose, Xylose, Glycerol

47

Statement of Contribution

The authors listed below have certified that:

1. they meet the criteria for authorship in that they have participated in the

conception, execution, or interpretation, of at least that part of the publication in their

field of expertise;

2. they take public responsibility for their part of the publication, except for the

responsible author who accepts overall responsibility for the publication;

3. there are no other authors of the publication according to these criteria;

4. potential conflicts of interest have been disclosed to (a) granting bodies, (b) the

editor or publisher of journals or other publications, and (c) the head of the

responsible academic unit, and

5. they agree to the use of the publication in the student’s thesis and its publication

on the Australasian Research Online database consistent with any limitations set by

publisher requirements.

In the case of this article:

A multi-criteria analysis approach for ranking and selection of microorganisms for

the production of oils for biodiesel production. Bioresource Technology, 190 (2015),

Pages 264-273.

Contributor Statement of contribution

Farah B. Ahmad The author contributed to initial

experimental design; conducted

experiment, analysis and data

interpretation; and wrote the first draft of

manuscript and subsequent revisions of

the manuscripts.

Signature

Date

Zhanying Zhang This author provided valuable assistance

in initial experimental design, supervised

48

the analysis and data interpretation and

edited the drafts of the manuscript.

William O. S. Doherty This author contributed to data

interpretation and edited the drafts of the

manuscript.

Ian M. O’Hara This author supervised overall

experimental design, analysis, data

interpretation, and edited the drafts of the

manuscript

Principal Supervisor Confirmation

I have sighted email or other correspondence from all Co-authors confirming their

certifying authorship.

Name

Ian O’Hara

Signature

Date

49

3.1.1 Introduction

With increasing population and development, global petroleum demand is

predicted to increase by up to 40% by 2025 [1]. In this regard, renewable energy

technologies can contribute to meet a portion of the increase, while addressing some

of the major concerns with greenhouse gas emissions from the continued use of fossil

fuels. Biodiesel, commonly produced from vegetable oils, is a renewable

transportation fuel that has received widespread acceptance and uptake. However,

the use of edible oils for biodiesel production will contribute to increase food prices

because of growing demand for use in both fuels and food products [1].

Microorganisms have the potential to be used to produce oils as alternative feedstock

for biodiesel production and reduce the amount of edible oils used for this purpose.

In addition, microbial oils have the potential to be utilised for the production of other

products depending on the fatty acid profiles of the oil produced. These products

include cocoa butter substitutes and health products such as γ-linolenic acid (GLA),

arachidonic acid (ARA), docosahexaenoic acid (DHA) and eicosapentaenoic acid

(EPA) [2, 3].

Microorganisms from certain species of microalgae, yeasts, fungi and bacteria

are able to accumulate lipids (i.e., oils) at more than 20% dry weight of biomass [3].

Lipid production is typically optimised under nitrogen-limiting conditions with

carbon substrates in excess [4]. Lipid accumulation in oleaginous microorganisms is

due to the presence of ATP-citrate lyase (ATP-CL) [3]. ATP-CL catalyses the

formation of acetyl-CoA, which is then used in fatty acid biosynthesis [3].

Lignocellulosic biomasses, from agricultural crop residues such as sugarcane

bagasse and palm oil empty fruit bunch, are rich in carbohydrates. These

carbohydrates, which can be hydrolysed to fermentable sugars such as glucose and

xylose, provide low cost carbon source for microbial oil production as lignocellulosic

biomasses are renewable and abundant [2]. So, it is of interest to study the

production of oils from lignocellulose hydrolysates using selected microorganisms.

The first step, reported here is on the use of glucose and xylose as model substrates.

Certain species of microalgae have been shown to produce oil through

phototrophic or heterotrophic cultivation [5]. In particular, Chlorella species are

capable of producing oil with high yields such as Chlorella vulgaris and Chlorella

50

protothecoides that have been widely studied for heterotrophic cultivation,

principally with the use of glucose or fructose-based substrates [5, 6]. There are only

limited studies on the growth of Chlorella on pentoses such as xylose probably

because microalgae generally do not use pentoses [7]. In addition, the use of

microalgae for heterotrophic cultivation may be prone to contamination in the

presence of high sugar concentrations in the growth media due to their low growth

rates [5].

Besides microalgae, yeasts and fungi are other microorganisms used for lipid

production from various carbon sources. There are several species of yeasts that are

known for their oil accumulating capability growing on various carbon substrates

such as Yarrowia lipolytica, Rhodosporidium toruloides, Lipomyces starkeyi,

Trichosporon fermentans, Trichosporon pullulan, Rhodotorula glutinis and

Cryptococcus curvatus [8, 9]. Oil production by yeast cultivation is promising as

yeasts often exhibit high growth rates with low nutrient requirements, and certain

species have been shown to have a high oil accumulation capability with fatty acid

composition comparable to plant oils [9-11].

Filamentous fungal species such as Mortierella isabellina and

Cunninghamellae chinulata are reported to accumulate high oil contents from several

carbon substrates [12, 13]. Similar to the oil extracted from microalgae and yeasts,

these fungal oils can also be used as a feedstock for biodiesel production [12, 13].

It is concluded, therefore, that each group and species of microorganisms

exhibits advantages and disadvantages for industrial oil production. In addition, there

are many criteria that influence the commercial potential of a microorganism. Most

studies to date have used oil content and oil concentration as the selection criteria,

and have paid little attention to other significant criteria that contribute to an

economically viable oil production process. Key criteria likely to be important in

microorganisms ranking and selection for oil and biodiesel production include:

1. Oil concentration (g/L);

2. Oil content (g/g microbial biomass);

3. Oil production rate (productivity; g/L/day);

4. Oil yield (oil concentration per unit substrate consumed; g/g consumed substrate);

51

5. Substrate consumption rate (g/L/h);

6. Fatty acids profile (%, w/w);

7. Biomass harvesting cost ($/L); and

8. Nutrient cost ($/L).

It is likely that no single microorganism will exhibit the optimum performance

for each of these criteria and hence selection of prospective microorganisms will

require a compromise decision in order to select the best overall performance. In

lignocellulosic hydrolysates, glucose and xylose are typically the major carbohydrate

monomers. Glycerol is produced in large quantities as by-product from biodiesel

production and represents an additional potential feedstock for microbial oil

production in integrated microbial oil and biodiesel production facilities. The

performance of a microorganism may vary across each of these substrates. Other

factor that affects performance of a microorganism is inhibitory effect of degradation

products from the pretreatment process (e.g., furfural from pentose and 5-

hydroxymethylfurfural from hexose) [14]. This factor however is considered to be

secondary to the key criteria listed, as it depends on type of hydrolysate used. The

inhibitors are generally prevalent in hydrolysates from the liquid fraction of

pretreated lignocellulosic materials, but it is negligible in enzymatic hydrolysates

from washed solid residues. The effects of inhibitors to microbial growth may be

reduced by detoxifying hydrolysates, such as through overliming process [14].

Further complicating the selection decision for lignocellulosic hydrolysates is

that there is no standard lignocellulose or lignocellulosic hydrolysate and

composition varies with biomass type, age of plant, climatic conditions during

growth, pre-processing and pretreatment technology and severity. As a result, most

screening studies using lignocellulosic hydrolysates focus on a specific biomass and

pretreatment technology. It is likely, therefore, that the results of screening studies

will be specific to the factors used in the selection.

At the present time, there is no reported methodology for systematic evaluation

of prospective microorganisms that accounts for the diversity of criteria needed for

an economically viable oil production process. So, it is proposed that multi-criteria

analysis (MCA) methods can be used to provide flexible analytical tools to aid

52

complex decision making in the ranking and selection of alternatives (i.e.,

microorganisms) [15]. Preference Ranking Organization Method for the Enrichment

of Evaluations (PROMETHEE) is a computer-based multi-criteria decision aid

methodology to rank alternative solutions to a complex problem. PROMETHEE uses

outranking techniques for alternatives based on the weightings of selected

preferences to determine positive and negative preference flows [16]. The

PROMETHEE I Partial Ranking consists of positive preference flows (Phi+) which

measures the extent to which an alternative outranks all others; and negative

preference flows (Phi-) which measures the extent to which an alternative is

outranked by others [17]. The PROMETHEE II Complete Ranking (Phi) is a

calculation of the net preference flow that shows the balance between the positive

and negative outranking flows [17]. Graphical Analysis for Interactive Aid (GAIA)

is a visual aid tool used with PROMETHEE that enables visualisation and graphical

representation of the analysis.

In a study assessing algae from nine different species for biodiesel production,

PROMETHEE-GAIA was used as the tool for multi-criteria decision making [18].

PROMETHEE-GAIA was used for systematic analysis and graphical representation

of the most preferred and the least preferred species, based on multiple physical and

chemical properties of fuel (e.g., oil concentration and cetane number) as the

selection criteria. However, in this study, equal weight was applied to each criterion

in PROMETHEE. The assessment from this model is not accurate for any particular

scenario that has fuel properties that are more important than others. The best species

selected should reflect the best quality in the most desired criterion or fuel property,

and a compromise quality in the least desired criterion will not give major effect to

the preference results.

It is essential to use structured technique for determining weights for complex

MCA. This is because there is no guidelines in PROMETHEE II for weight

determination, but decision makers are assumed to be able to assign appropriate

weight to each criterion [19]. An environmental evaluation study of municipal solid

waste options used the combination of Analytic Hierarchy Process (AHP) and

PROMETHEE for MCA [15]. AHP is another complex decision making support

technique that provides a structured process for the identification of hierarchies of

53

goals, criteria and alternatives for evaluation [19]. AHP is widely used for

developing weightings of criteria. The combination of PROMETHEE and AHP for

MCA was proposed by Macharis et al. [19]. In the environmental evaluation study

by Herva and Roca, different assessment approaches by an ecological footprint

calculation and by the combination of AHP and PROMETHEE showed the same

ranking for the options evaluated. However, it was remarked that defining weights

was still influenced by the subjective opinion of the decision makers, even with the

use of AHP [15].

This study has evaluated several different species of microalgae (Chlorella

protothecoides and Chlorella zofingiensis), yeasts (Cryptococcus albidus and

Rhodotorula mucilaginosa), and fungi (Aspergillus oryzae and Mucor plumbeus) for

microbial oil production using MCA. Firstly, microbial oil production by different

strains was conducted with three different substrates (i.e., glucose and xylose, as a

model lignocellulosic hydrolysates, and glycerol). The data collected was used by the

MCA approach to analyse factors and to select high ranking candidates using

PROMETHEE-GAIA. The results from this study have shown that the MCA

approach can be used for the selection of microorganisms for oil production that can

be used as feedstock for biodiesel production.

3.1.2 Materials and Methods

3.1.2.1 Strains and media

Six microorganisms (of different origins) were selected for study based on the

information obtained from the literature that are able to cultivate oil. Two microalgal

strains, Chlorella protothecoides (ATCC 30581) and Chlorella zofingiensis (ATCC

30412) were purchased from ATCC (USA). The composition of the basic medium

used for microalgae strains was (per L): 0.7 g KH2PO4, 0.3 g K2HPO4, 0.3 g

MgSO4·7H2O, 25 mg CaCl2·7H2O, 25 mg NaCl, 3 mg FeSO4·7H2O, 0.01 mg

vitamin B1, and 1 mL A5 trace mineral solution at pH 6.8 [20]. The A5 solution

consisted of (per L) 2.86 g H3BO4, 2.5 g MnSO4·7H2O, 22.2 mg ZnSO4·7H2O, 7.9

mg CuSO4·5H2O and 2.1 mg Na2MoO4·2H2O [20].Two yeast strains, Cryptococcus

albidus (FRR no.: 2412) and Rhodotorula mucilaginosa (FRR no.: 2406) were

purchased from FRR Culture Collection (Australia). The composition of the basic

54

medium used for yeasts strains was (per L): 0.4 g MgSO4·7H2O, 2 g KH2PO4, 3 mg

MnSO4·H2O and 0.1 mg CuSO4·5H2O at pH 5.5 [14]. Two fungal strains,

Aspergillus oryzae (FRR no.: 1677) and Mucor plumbeus (FRR no.: 2412) were

purchased from FRR Culture Collection (Australia). The composition of the basic

medium used for fungal strains was (per L): 1 g KNO3, 2.5 g KH2PO4, 10 mg

ZnSO4·7H2O, 2 mg CuSO4·5H2O, 10 mg MnSO4, 0.5 g MgSO4·7H2O, 20 mg

FeSO4·7H2O and 0.1 g CaCl2 at pH 5.5 [21]. Glucose, xylose and glycerol (30 g/L)

were used as the carbon sources in the media supplemented with 4 g/L yeast extract.

Cultures were conducted in triplicate in 500 mL Erlenmeyer flasks containing 200

mL media placed on orbital shaking incubator (Ratek, Australia). Microalgal and

yeast strains were cultivated with 20% (v/v) inocula from their respective

precultivation medium (4 days), at an orbital rate of 180 rpm with temperature

maintained at 28°C. The cultivation for microalgae strains was carried out in the

dark. Fungal strains were cultivated with inoculum from 24 h of precultivation, at an

orbital rate of 160 rpm with temperature maintained at 30°C [22].

Microalgal and yeasts biomass were harvested by centrifugation at 6805 g for 7

min (Sorvall Biofuge Primo R, USA) [23]. Fungal biomass was harvested by vacuum

filtration (Whatman 54 filter paper). The harvested biomass samples were washed

three times (200 mL/wash) using Millipore water and freeze-dried to a constant

weight.

3.2.1.2 Oil extraction

Oil was extracted from the biomass by Accelerated Solvent Extraction (ASE)

technique using Dionex ASE 350 (Thermo Fisher Scientific Inc., USA). The samples

for extraction were prepared by mixing dry biomass (~0.1 g) with 0.4 g of

diatomaceous earth (Thermo Fisher Scientific, Inc., USA) and loaded into 5 mL

cells. The extraction conditions had been optimised and were as follows (see

Appendix 1): temperature, 130 ; static time, 5 min; rinse volume, 25% of cell

volume; purge time, 60 s; and using 4 static cycles. The solvent used was a mixture

of chloroform:methanol in a ratio of 2:1 (v/v) [24]. The extracted oil was collected in

pre-weighed collection bottles. The solvents were evaporated under a stream of

nitrogen. Unless otherwise specified, all results are reported on a dry weight (DW)

basis.

55

3.2.1.3 Oil analyses

Sugars and glycerol concentrations were analysed using high-performance

liquid chromatography (HPLC) by a Waters HPLC system equipped with a SP810

carbohydrate column (300 mm × 8.0 mm, Shodex, Japan) and a refractive index (RI)

detector (Waters 410, US). The column temperature was 85°C and the mobile phase

was water, with a flow rate of 0.5 mL/min [25].

For the determination of fatty acids composition, fatty acid methyl esters

(FAME) were prepared using the method described by Mulbry et al. (2009).FAME

analysis was performed by gas chromatography-mass spectrometry (GC-MS) by

Shimadzu GCMS-TQ8040 (Shimadzu Corporation, Japan) on a TG-WAXMS

column (30 m long × 0.32 mm I.D.× 1 µm film thickness; Thermo Fisher Scientific,

Inc., USA). The carrier gas was helium at a flow rate of 1.5 mL/min. A 10:1 split

injection was used. The injection temperature was set at 230°C, the MS ion source

temperature at 220°C and the MS interface temperature at 240°C. The GC-MS

method was carried out using the following temperature program: initial temperature

at 40°C, hold for 2 min, followed by 10°C/min ramp to 230°C and hold for 20 min.

Mass spectrometry was performed using Q3 scan with an m/z 20-650 scanning range.

Chromatograms and mass spectra were evaluated using the GCMSsolution software

(Shimadzu Corporation, Japan). The retention times and mass spectra were identified

using FAME mix (F.A.M.E. Mix, C8-C24; Sigma-Aldrich, Australia).

3.1.2.4 Multi-criteria analysis

Establishing criteria hierarchy

AHP and PROMETHEE-GAIA were used for MCA. PROMETHEE-GAIA

was implemented using Visual PROMETHEE 1.4 Academic Edition. The stated goal

of the MCA was to select the most suitable prospective microorganism(s) for oil

production from lignocellulosic hydrolysates’ model compounds, glucose and

xylose. The alternative solutions were selected to be the six microorganisms studied

which were C. protothecoides, C. zofingiensis, C. albidus, R. mucilaginosa, A.

oryzae and M. plumbeus. Figure 3-1 shows the criteria hierarchy that was established

from the key parameters reported in the Introduction section. The quantitative criteria

under Cluster 1 (C1 – C6) were evaluated based on the results of the experimental

56

study on microbial cultivation on glucose, xylose and glycerol substrates. The criteria

under Cluster 2 (C7 and C8) were evaluated qualitatively.

Figure 3-1 Criteria hierarchy for the evaluation of microorganisms for microbial oil production. Cluster 1 criteria were evaluated based on cultivation results on glucose

(G), xylose (X) and glycerol (L).

Establishing criteria weights

AHP techniques were used to determine the relative weightings of each

criterion [15, 19]. This was based on hierarchy, priority setting and logical

consistency [19, 26]. Relative priorities were given to each element through pairwise

comparisons using Saaty’s scale 1-9, whereby 1 indicates equal, 3 moderate, 5

strong, 7 very strong and 9 extreme importance [15, 26]. The scales of 2, 4, 6 and 8

were used for compromise values of importance [26]. The consistency of each

pairwise comparison in this study was calculated, where the consistency falls within

the range of the good consistency ratio (CR) proposed by Saaty (2008). There is the

possibility of random judgement in assessing the priorities, if the consistency ratio is

more than 10% [26]. The pairwise matrices for criteria groups belonging to each

cluster and criteria of Cluster 1 are provided in Table 3-1 and Table 3-2.

As shown in Figure 3-1, Cluster 1 evaluates the relative capability of the

alternative solutions for cultivation on the various carbon sources in order to achieve

the goal. The priorities given to the carbon substrates are based on the capability of

the respective microorganisms to grow and produce oil with the highest priority on

glucose and the lowest priority on glycerol (Glucose (G)> Xylose(X)>Glycerol

57

(L)).Higher priority is given to growth on glucose than xylose as lignocellulosic

biomass generally contains more glucose than xylose. Glycerol was also included in

the criteria as a potential substrate as glycerol is a by-product of biodiesel production

and a potential fermentation substrate in an integrated biodiesel production system.

The capability to grow on glycerol is assigned with a low weight as it only serves to

provide a secondary benefit to the objective compared to the primary benefit

resulting from growth on glucose and xylose.

Table 3-1 Pairwise comparison matrix with respect to goal for criteria groups of Cluster 1 and Cluster 2.

Goal Glucose Xylose Glycerol Harvesting Nutrient Normalised weights (%)

Glucose 1 3 7 6 9 51.05 Xylose 1/3 1 5 4 7 27.12 Glycerol 1/7 1/5 1 1/2 3 7.06 Harvesting 1/6 1/4 2 1 5 11.31 Nutrient 1/9 1/7 1/3 1/5 1 3.47

Table 3-2 Pairwise comparison matrix with respect to goal for criteria of Cluster 1. Goal C1 C2 C3 C4 C5 C6 Normalised weights (%) C1 1 3 4 5 6 7 44.08 C2 1/3 1 2 3 4 5 21.99 C3 1/4 1/2 1 2 3 4 14.51 C4 1/5 1/3 1/2 1 2 3 9.38 C5 1/6 1/4 1/3 1/2 1 2 6.03 C6 1/7 1/5 1/4 1/3 1/2 1 4.02

The criteria assigned under Cluster 1, C1 - C6 were assessed with the priorities

of C1 > C2 > C3 > C4 > C5 > C6. The first two criteria, C1 (oil concentration) and

C2 (oil content) were given the highest priority as they reflect the key economic

advantage resulting from high concentration and yield of the desired product from

each carbon substrate. Substrate consumption rate (C3) reflects the potential

economic benefit of lower capital and operating costs from reduced fermenter

capacity. Oil yield (C4) reflects the efficiency with which the microorganism

converts the substrate (which is an operating cost) to product (which is a revenue).

Fatty acid profile (C5) evaluates the relative value of the oil for use in biodiesel

production, and is calculated as the percentage of saturated and mono-unsaturated

fatty acids in the oil produced. Oils with high levels of saturated and

monounsaturated fatty acids are desirable for biodiesel application [27].

58

Polyunsaturated fatty acids especially those with more than four double bonds are

less preferred for biodiesel production due to the low oxidative stability of the

biodiesel during storage [28]. However, microbial oils with high level of

polyunsaturated fatty acids, such as linoleic acid (C18:2n6) and linolenic acid

(C18:3n3) have the potential to be used in health products manufacturing [2]. Oil

productivity (C6) reflects average oil concentration per day of cultivation.

For the criteria belonging to Cluster 2 (C7 and C8), the alternatives studied

were categorised based on the groups of microorganisms as each alternative in the

same group were assumed to share similar characteristics. For evaluating qualitative

criteria, a 5-point scale was used (very good, good, average, bad, and very bad).

Fungi were classified as very good for C7 (Biomass harvesting cost) because fungal

strains generally grow in pellet form. Pellet form is preferable for harvesting as the

biomass can be harvested by simple sedimentation and filtration, whereas single cell

biomass requires centrifugation or finer filtration techniques. Harvesting by

sedimentation and filtration is a lower cost harvesting technique compared to

harvesting via centrifugation [5]. For criterion C8 (Nutrient cost), yeasts were given

the best ranking as yeast species generally require fewer nutrients in the media

compared to microalgae for oleaginous cultivation[10].

Ranking of alternatives

In PROMETHEE, the preference function converts the deviations between the

evaluation of two alternatives for each criterion into a preference degree ranging

from 0 to 1 [16]. The preference functions used in this study are V-shape functions

for quantitative criteria, and the usual function for qualitative criteria [17]. V-shape

function specifies values of preference threshold, p, which is the smallest deviation

that is considered as sufficient to generate a full preference [17]. The indifference

threshold, q, is the largest deviation that is considered negligible by the decision

maker and is equal to 0 in the V-shape function [17]. The values of p in this study

were determined using the built-in Preference Function Assistant in Visual

PROMETHEE.

GAIA was used to further analyse and visualise the outcomes of the analysis.

The following elements refer to results shown in the GAIA plane [15, 17]: (1) The

criteria are represented by axes. Axes are oriented in approximately the same

59

direction for criteria expressing similar preference and in opposite directions for

conflicting criteria. Axes are oriented orthogonally for unrelated criteria. (2)

Alternatives are represented by shapes. Alternatives with similar profiles are

positioned close to each other. Alternatives with better performance on a given

criterion are located in the direction of the corresponding criterion. (3) The weights

of criteria are represented by the pi vector on the decision axis. The orientation of

this axis shows which criteria are in accordance with PROMETHEE rankings and

which are not.

3.1.3 Results and discussion

3.1.3.1 Biomass concentrations and carbon substrate consumptions on glucose,

xylose and glycerol

Figure 3-2(a) shows the biomass concentrations of the six selected

microorganisms growing on glucose, xylose and glycerol substrates. The yeast strain,

R. mucilaginosa gave the highest biomass concentration of 16.8 (±1.8) g/L on

glucose, while the other microorganisms had similar biomass concentrations on

glucose ranging from 7.9 to 9.8 g/L. One possible reason for the high biomass

concentration of R. mucilaginosa is that the cultivation was not carried out in

complete darkness. Biomass production from other species of Rhodotorula, R.

glutinis was shown to increase when it was cultivated under light irradiation

conditions [29]. For cultivation on xylose, R. mucilaginosa, A. oryzae and M.

plumbeus all resulted in high biomass concentrations of 10.8 (±0.4) g/L, 10.0 (±0.4)

g/L and 9.3 (±0.7) g/L respectively. However, no significant biomass growth resulted

from C. protothecoides and C. zofingiensis cultivation when xylose was used as the

carbon source. These results are in agreement with a previous study that showed

Chlorella species (e.g., C. vulgaris and C. sorokiniana) were not able to assimilate

xylose heterotrophically [7]. Fungal strains M. plumbeus and A. oryzae also showed

the highest biomass concentrations on glycerol (10.2 ±0.4 g/L and 9.5 ±0.8 g/L

respectively). The results showed that both fungal strains, M. plumbeus and A.

oryzae, and both yeasts strains, R. mucilaginosa and C. albidus, were able to grow on

each of the three carbon sources studied. Interestingly, M. plumbeus and A. oryzae

showed relatively consistent biomass concentrations on glucose, xylose and glycerol

substrates.

60

61

(a)

(b)

(c)

Figure 3-2 (a) Biomass concentration, (b) oil content and (c) oil concentrations for growth of six microorganisms on glucose, xylose and glycerol.

0

2

4

6

8

10

12

14

16

18

20

Glucose Xylose GlycerolB

iom

ass

conc

entr

atio

n (g

/L)

C. protothecoides

C. zofingiensis

C. albidus

R. mucilaginosa

A. oryzae

M. plumbeus

0

5

10

15

20

25

30

35

40

Glucose Xylose Glycerol

Oil

con

tent

(%

, w/w

)

C. protothecoidesC. zofingiensisC. albidusR. mucilaginosaA. oryzaeM. plumbeus

0

0.5

1

1.5

2

2.5

3

3.5

4

Glucose Xylose Glycerol

Oil

con

cent

rati

on (

g/L

)

C. protothecoidesC. zofingiensisC. albidusR. mucilaginosaA. oryzaeM. plumbeus

62

The results of substrates consumption by the six microorganisms studied over

168 h of cultivation are shown in Figure 3-3. All six microorganisms were shown to

consume glucose more rapidly than xylose and glycerol. Generally, glucose is more

preferable than xylose as a fermentation substrate as assimilation of xylose requires

specific metabolic pathways [13]. Glucose was shown to be completely consumed by

fungal strains A. oryzae and M. plumbeus within only 48 h to 72 h of cultivation.

Yeast strain R. mucilaginosa and microalgae strain C. protothecoides consumed

glucose completely by the end of the cultivation period. Xylose was completely

consumed in the media by A. oryzae in 96 h, where as it took 144 h for M. plumbeus

and R. mucilaginosa to consume xylose completely. Extremely low consumption of

xylose was evident for either of the microalgae strains. All microorganisms

consumed glycerol at a slower rate than glucose and xylose. Consumption of glycerol

was again the fastest for the fungal species A. oryzae and M. plumbeus.

The two fungal strains, A. oryzae and M. plumbeus, demonstrated the highest

consumption rates on glucose, xylose and glycerol. It is known that upon depletion of

the carbon source, there exists the possibility of lipid turnover, in which storage

lipids are metabolised resulting in a reduction in lipid content [30]. In this study, the

lipid content was not monitored at each time point as the work focused on the

development of MCA method for screening and selection of optimal oil producing

microorganisms. It is noted, however, that the peak oil content for microorganisms

with rapid substrate consumption may have been higher than the results show.

63

(a)

(b)

(c)

Figure 3-3 Consumption of (a) glucose, (b) xylose and (c) glycerol over 168 h of cultivation.

0

20

40

60

80

100

0 24 48 72 96 120 144 168

Glu

cose

con

sum

ptio

n (%

, w

/w)

Cultivation time (h)

C. protothecoidesC. zofingiensisC. albidusR. mucilaginosaA. oryzaeM. plumbeus

0

20

40

60

80

100

0 24 48 72 96 120 144 168

Xyl

ose

cons

umpt

ion

(%,

w/w

)

Cultivation time (h)

C. protothecoidesC. zofingiensisC. albidusR. mucilaginosaA. oryzaeM. plumbeus

0

20

40

60

80

100

0 24 48 72 96 120 144 168

Gly

cero

l con

sum

ptio

n (%

, w

/w)

Cultivation time (h)

C. protothecoidesC. zofingiensisC. albidusR. mucilaginosaA. oryzaeM. plumbeus

64

3.1.3.2 Microbial oil production from different carbon substrates

Figure 3-2(b) shows the results of the oil contents of the strains on glucose,

xylose and glycerol substrates after 168 h cultivation. C. protothecoides cultivation

on glucose showed the highest oil content of 35.4% (w/w), followed by A. oryzae

(26.9%), M. plumbeus (26.2%), C. zofingiensis (24.7%), R. mucilaginosa (21.6%)

and C. albidus (19.5%). It has been demonstrated in previous studies that C.

protothecoides is an excellent oil producer on glucose with up to 58% oil content

obtained from batch cultivation in a 5 L bioreactor for 140 h [23]. The highest oil

content on xylose was achieved by M. plumbeus, which was 23.8%, followed by A.

oryzae, C. albidus and R. mucilaginosa (oil contents of 20.7%, 18.3% and 14.4%

respectively). As there was almost no growth of Chlorella strains on xylose, the oil

content was not measured. The highest oil contents on glycerol were achieved by M.

plumbeus, A. oryzae, and C. albidus, which were all around 26% (27.4%, 25.8% and

26.4% respectively). Lower oil contents on glycerol substrates were shown by R.

mucilaginosa, C. protothecoides and C. zofingiensis.

Figure 3-2(b) also shows that A. oryzae and M. plumbeus had consistent oil

contents with varying carbon sources. Although the two fungal strains had ~8-9%

lower final oil contents than C. protothecoides, these strains grew much faster and

are likely to result in comparable or higher oil productivity. Yeast strain R.

mucilaginosa produced the highest biomass concentration while still producing

similar oil contents to most of the other strains.

Figure 3-2(c) shows oil concentrations for the six microorganisms growing on

glucose, xylose and glycerol. The cultivation of R. mucilaginosa on glucose resulted

in the highest oil concentration of 3.61 (±0.16) g/L primarily as a result of the very

high biomass concentration compared to the other species. C. zofingiensis and the

two fungal strains had similar oil concentrations on glucose. M. plumbeus showed

the highest oil concentration on xylose and glycerol (2.21 ±0.04 g/L and 2.78 ±0.10

g/L respectively), followed by A. oryzae (2.07 ±0.05 g/L and 2.45 ±0.15 g/L

respectively). Figure 3-2(c) also shows the consistency in the oil concentrations

achieved by the two fungal strains across all three carbon sources compared to the

other species which tended to be more variable with varying carbon substrates.

65

3.1.3.3 Fatty acids profiles

The results of the fatty acid compositions of the six microorganisms growing

on glucose, xylose and glycerol are presented in Table 3-3. The major fatty acids

identified were palmitic (C16:0), stearic (C18:0), oleic (C18:1) and linoleic (C18:2).

Oleic acid was the predominant fatty acid in most cases which is in accordance with

previous studies [9]. Variations were observed for the cultivation of C. albidus on

glucose and xylose substrates, with linoleic acid as predominant fatty acid while

palmitic acid was the predominant fatty acid with C. zofingiensis on glycerol. The

reasons for high accumulation of palmitic acid by C. zofingiensis on glycerol are

unknown as this is the first study to cultivate C. zofingiensis on glycerol.

Nevertheless, this C. zofingiensis may have similar pathways to metabolise glycerol

to Chlorella saccharophila reported previously, which produced palmitic acid as

predominant fatty acid on glycerol but oleic acid on glucose [31, 32]. The

composition of oleic acid was decreasing and palmitic acid was increasing with

increasing ratio of glycerol mixed with glucose substrate [32].

3.1.3.4 Preference ranking

Based solely on the oil concentration results above, it could be concluded that,

of the microorganisms assessed, R. mucilaginosa and C. protothecoides were the

most prospective microorganisms for microbial oil production from glucose. On the

other hand, A. oryzae and M. plumbeus appeared to be the most prospective for oil

production from xylose. M. plumbeus had the lowest polyunsaturated fatty acid

content when grown on glucose and hence potentially produced better oil for

biodiesel production but had the highest polyunsaturated fatty acid when grown on

glycerol. Furthermore, these initial conclusions ignore the impact of other aspects

that impact on production cost including harvesting and nutrition costs. Therefore,

PROMETHEE-GAIA was used to systematically assess each alternative based on the

criteria shown above.

66

Table 3-3 Fatty acid compositions of oil extracted from six different microorganisms grown on various carbon substrates.

Microorganisms

Relative abundance of total fatty acids (%, w/w) SFAa MUFAa PUFAa C14:0 C16:0 C16:1 C18:0 C18:1 C18:2 C18:3 C20:0

Glucose medium C. protothecoides 6.3

(±2.0) 23.8 (±1.5)

3.8 (±0.7)

6.1 (±0.7)

42.8 (±2.6)

5.1 (±3.0)

6.8 (±2.4)

- 38.2 49.2 12.6

C. zofingiensis 7.2 (±1.1)

22.4 (±1.9)

7.8 (±2.0)

6.9 (±3.0)

42.2(±2.7)

6.5 (±9.8)

4.0 (±3.8)

- 37.6 51.5 10.8

C. albidus 1.5 (±0.6)

22.7 (±0.1)

1.7 (±0.4)

4.1 (±1.3)

34.1 (±2.5)

35.8 (±2.2)

- - 28.4 35.8 35.8

R. mucilaginosa 2.7 (±0.7)

18.9 (±3.7)

1.7 (±0.3)

6.9 (±2.2)

54.2 (±6.5)

12.6 (±8.4)

2.9 (±0.9)

- 28.6 55.9 15.5

A. oryzae 4.5 (±2.8)

25.5 (±4.4)

3.4 (±0.4)

15.6 (±6.0)

34.9 (±2.9)

9.8 (±8.3)

3.1 (±0.5)

1.1 (±0.7)

47.7 39.1 13.2

M. plumbeus 2.0 (±0.8)

28.8 (±0.8)

2.5 (±0.5)

22.1 (±1.7)

37.4 (±0.6)

2.8 (±2.1)

1.1 (±0.7)

1.6 (±0.3)

55.4 40.6 4.00

Xylose medium C. albidus - 29.5

(±2.0) - 13.4

(±1.8) 23.4 (±2.2)

33.7 (±0.3)

- - 42.9 23.4 33.7

R. mucilaginosa 1.8 (±0.2)

20.3 (±1.7)

1.11 (±0.3)

6.1 (±0.8)

49.2 (±3.1)

20.1 (±5.3)

1.3 (±1.2)

- 28. 3 50.4 21.4

A. oryzae 0.8 (±0.1)

20.5 (±1.9)

1.7 (±0.3)

16.4 (±0.7)

37.5 (±0.9)

21.1 (±3.2)

- 1.5 (±0.1)

39.4 39.4 21.2

M. plumbeus 1.3 (±0.6)

20.5 (±4.0)

1.8 (±0.6)

19.0 (±1.7)

33.8 (±3.1)

21.1 (±9.0)

1.0 (±0.8)

1.5 (±0.3)

42.2 35.7 22.1

Glycerol medium C. protothecoides 10.3

(±1.2) 26.6 (±0.2)

4.4 (±1.5)

6.5 (±0.5)

35.9 (±4.3)

7.0 (±9.4)

2.1 (±1.8)

- 46.8 43.4 9.9

C. zofingiensis 17.7 (±4.2)

56.4 (±3.2)

- 8.2 (±2.0)

10.4 (±6.4)

7.3 (±2.4)

- - 82.2 10.4 7.3

C. albidus 1.5 (±0.1)

24.4 (±1.1)

1.9 (±0.3)

5.5 (±2.2)

42.4 (±2.3)

24.3 (±0.6)

- - 31.4 44.3 24.3

R. mucilaginosa 4.6 (±1.2)

14.7 (±1.3)

1.6 (±0.2)

9.1 (±1.9)

47.6 (±3.6)

6.6 (±2.5)

15.7 (±3.2)

- 28.4 49.3 22.4

A. oryzae 0.9 (±0.5)

14.2 (±0.9)

1.9 (±0.5)

16.9 (±0.8)

34.4 (±1.1)

29.3 (±1.3)

0.5 (±0.0)

1.8 (±0.3)

33.9 36.4 29.8

M. plumbeus 0.5 (±0.7)

14.1 (±0.0)

2.8 (±1.1)

14.3 (±0.2)

30.9 (±2.4)

35.6 (±2.1)

0.5 (±0.2)

1.3 (±0.2)

30.2 33.7 36.1

a SFA means saturated fatty acids, MUFA means monounsaturated fatty acids and PUFA means polyunsaturated fatty acids.

Figure 3-4(a) shows the results of the PROMETHEE I partial rankings for the

six microorganisms studied. In PROMETHEE I, the presence of crossed tie lines

indicate that the alternatives are not comparable using this technique. For instance,

M. plumbeus is not comparable to A. oryzae because M. plumbeus obtained a higher

Phi-(negative preference flow), and a lower Phi+ (positive preference flow)

compared to A. oryzae.

67

(a)

(b)

Figure 3-4 (a) PROMETHEE I partial ranking of alternatives and (b) PROMETHEE II complete ranking where RM denotes R. mucilaginosa, AO A. oryzae, MP M.

plumbeus, CP C. protothecoides, CA C. albidus and CZ C. zofingiensis.

68

Figure 3-4(b) also shows the results of the PROMETHEE II complete rankings

for the six microorganisms studied. The only microorganisms that obtained positive

Phi scores were A. oryzae, M. plumbeus and R. mucilaginosa with the two fungal

species A. oryzae and M. plumbeus being the most preferred options with almost

equivalent Phi scores. As a result, based on the criteria selected and the experimental

results, these three microorganisms (A. oryzae, M. plumbeus and R. mucilaginosa)

were predicted to be more preferred for oil production from the lignocellulosic

hydrolysates model compounds, and glycerol than the other microorganisms.

The GAIA plane from the analysis is shown in Figure 3-5 and has a quality

level of 80.5% which is reliable as it is above 70% quality significance level. The pi

decision axis is aligned in the direction of the fungal strains A. oryzae and M.

plumbeus, which shows that these alternatives are preferred which is in agreement

with the PROMETHEE II ranking.

In the GAIA plane, the criteria vectors that lie in the same direction as the

decision vector reflect the influence that these criteria have on the decision. Figure

3-5 shows that the substrate consumption rate (C3) and fatty acid profiles (C5) for all

of the substrates express a positive preference on the decision.

Sensitivity analysis was carried out on the selected preference function and

criteria weights. By substituting the V-shape preference function with linear function

for all quantitative criteria without changing the preference threshold, (p), the

PROMETHEE II ranking remains the same. The sensitivity of the criteria weights to

the results are analysed based on weight stability intervals (Table 3-4). Weight

stability intervals are the limits where any variation in weight within the intervals

will not change the ranking of PROMETHEE II, given that there is no change to the

relative weights of other criteria [15]. Most of the criteria exhibited broad weight

stability intervals which show that the analysis is robust.

69

(a)

(b)

Figure 3-5 GAIA plane at (a) 100% zoom and (b) 400% zoom without the alternatives. The alternatives are denoted as RM for R. mucilaginosa,

AO for A. oryzae, MP for M. plumbeus, CP for C. protothecoides, CA for C. albidus and CZ for C. zofingiensis. The criteria are denoted as C1-G to C6-G for criteria of Group 1.1 (Glucose), C1-X to C6-X for criteria of Group 1.2 (Xylose) and C1-L to

C6-L for criteria of Group 1.3 (Glycerol). Some criteria are not visible due to overlapping such as C1-X by C1-L, C5-X and C3-X by C3-L, C5-G by C7, C2-X and

C6-X by C2-L.

70

Table 3-4 Weight stability intervals for criteria with relative weight>5%. Criteria Weight

(%) Weight stability intervals

C1-G Oil concentration on glucose 22.50 [2.70-28.02] C2-G Oil content on glucose 11.22 [0-22.15] C3-G Consumption rates on glucose 7.41 [3.40-71.58] C1-X Oil concentration on xylose 11.95 [2.51-34.65] C2-X Oil content on xylose 5.96 [0-19.23]

The three highest ranking alternatives, A. oryzae, M. plumbeus and R.

mucilaginosa were further analysed using GAIA Web to determine the influence of

individual criteria on the preference result (Figure 3-6). GAIA Web shows a

graphical representation of the unicriterion net flow scores for the selected

alternative. The criteria axes in GAIA Web are positioned with the same orientation

as in the GAIA plane, where criteria with similar preferences are located close to

each other. The GAIA Web shows the key criteria with the radial distance indicating

unicriterion net flows with -1 value at the centre of the web and +1 on the outer

circle.

Figure 3-6(a) shows that R. mucilaginosa performed strongly for the criteria of

oil concentration, oil yield and substrate consumption rate on glucose but the criteria

of oil content, fatty acid profile and oil productivity on glycerol were weak. Oil

concentration, oil content, and substrate consumption rate on xylose and glycerol

were all weak. On the other hand, A. oryzae shows very good preference for oil

concentration, oil content, and fatty acid profiles on xylose and glycerol and oil

content and fatty acid profile on glucose. In fact it is noted that A. oryzae showed

good preference results across most criteria with the exception of oil concentration

and oil yield on glucose, and productivity and oil yield on glycerol. The fungal strain

M. plumbeus showed very good preferences for most of the criteria on glucose,

xylose and glycerol with the exception of oil concentration and oil yield on glucose,

and productivity on glycerol.

The incomparability between M. plumbeus with A. oryzae in PROMETHEE I

can be assessed through the GAIA Webs. A comparison of the GAIA Webs between

these two species shows different strengths in preference between these fungal

strains for criteria such as fatty acid profiles but the incomparability is not highly

significant. The GAIA Webs confirmed the results obtained from the GAIA plane

71

reflecting that A. oryzae and M. plumbeus showed good preference for most of the

criteria specified.

72

(a)

(b)

73

(c)

Figure 3-6 GAIA Webs for top three alternatives from PROMETHEE which are (a) R. mucilaginosa, (b) A. oryzae and (c) M. plumbeus. Criterion C2-X is not visible due

to overlapping by C6-X.

The preferred alternatives for oil production for biodiesel production from

highest to lowest were established as follows: (1) A. oryzae; (2) M. plumbeus; (3) R.

mucilaginosa; (4) C. protothecoides; (5) C. albidus and (6) C. zofingiensis. The

microorganisms with positive Phi scores (A. oryzae, M. plumbeus and R.

mucilaginosa) were selected as the most prospective species and further analysed

using unicriterion net flow analysis in GAIA Webs. The variations in positive

preferences across these three microorganisms were confirmed by PROMETHEE I,

the GAIA plane and also the GAIA Webs. Therefore, fungal strains A. oryzae, M.

plumbeus and yeast strain R. mucilaginosa have potential for industrial oil

production for biodiesel applications.

The MCA proposed can be improved for ranking and selecting the best

microorganism for oil production from a specific type of hydrolysates, whereby the

priority for carbon substrates can be adjusted accordingly. MCA for oil production

from hydrolysates of liquid fraction of pretreated lignocellulosic materials may

74

include microorganisms’ tolerance to inhibitors such as furfural and 5-

hydroxymethylfurfural, as one of the criteria for ranking and selecting the best

microorganism.

3.1.4 Conclusion

In this study, a MCA approach was used to evaluate the performance of oil

production with different microorganisms. The MCA technique using AHP and

PROMETHEE-GAIA showed that the only microorganisms with positive Phi scores

were A. oryzae, M. plumbeus and R. mucilaginosa. Further GAIA analyses showed

that the fungal strains A. oryzae and M. plumbeus provided superior performance

across a wide range of criteria including growth on glucose and xylose substrates.

Overall, A. oryzae, M. plumbeus and R. mucilaginosa showed promise for biodiesel

production using the lignocellulose hydrolysates model compounds, glucose and

xylose.

3.1.5 Acknowledgements

The authors acknowledge Ministry of Education Malaysia for the postgraduate

scholarship of Farah B. Ahmad. The authors also thank the QUT Central Analytical

Research Facility for its support on sample analyses.

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79

Evaluating microbial oil production from EFB

4.1 Evaluation of oil production from oil palm empty fruit bunch by oleaginous microorganisms

F. B. Ahmad, Z. Zhang, W. O. S. Doherty, I. M. O’Hara

Centre for Tropical Crops and Biocommodities, Queensland University of

Technology, Brisbane, Australia

Abstract

Oil palm empty fruit bunch (EFB) is a readily available, lignocellulosic

biomass that has the potential to be utilised as carbon substrate for microbial oil

production. In order to evaluate the production of microbial oil from EFB, a technical

study was performed through the cultivation of oleaginous microorganisms

(Rhodotorula mucilaginosa, Aspergillus oryzae and Mucor plumbeus) on EFB

hydrolysates. EFB hydrolysates were prepared through dilute acid pretreatment of

the biomass, where the liquid fraction of pretreatment was detoxified and used as

EFB liquid hydrolysate (EFBLH). The solid residue was enzymatically hydrolysed

prior to be used as EFB enzymatic hydrolysate (EFBEH). The highest oil

concentrations were obtained from M. plumbeus (1.9 g/L oil on EFBLH and 4.7 g/L

oil on EFBEH). In order to evaluate the feasibility of large-scale microbial oil

production, a techno-economic study was performed based on the oil yields of M.

plumbeus per hectare of plantation, followed by the estimation of the feedstock cost

for oil production. Other oil palm biomasses (frond and trunk) were also included in

this study, as it could potentially improve the economics of large-scale microbial oil

production. Microbial oil from oil palm biomasses was estimated to potentially

increase oil production in the palm oil industry by up to 25%, at a cheaper feedstock

cost. The outcome of this study demonstrates the potential integration of microbial

oil production from oil palm biomasses with the existing palm oil industry (biodiesel,

80

food and oleochemicals production), that could potentially enhance sustainability and

profitability of microbial oil production.

Keyword: Biodiesel, Empty fruit bunch, Lignocellulose, Lipid, Microbial oil, Oil

palm, Oleaginous microorganism, Techno-economic

Abbreviations: empty fruit bunch, EFB; empty fruit bunch enzymatic hydrolysate,

EFBEH; empty fruit bunch liquid hydrolysate, EFBLH; fresh fruit bunch, FFB;

mesocarp fibre, MF; oil palm frond, OPF; oil palm trunk, OPT; palm kernel shell,

PKS.

81

Statement of Contribution

The authors listed below have certified that:

1. they meet the criteria for authorship in that they have participated in the

conception, execution, or interpretation, of at least that part of the publication in their

field of expertise;

2. they take public responsibility for their part of the publication, except for the

responsible author who accepts overall responsibility for the publication;

3. there are no other authors of the publication according to these criteria;

4. potential conflicts of interest have been disclosed to (a) granting bodies, (b) the

editor or publisher of journals or other publications, and (c) the head of the

responsible academic unit, and

5. they agree to the use of the publication in the student’s thesis and its publication

on the Australasian Research Online database consistent with any limitations set by

publisher requirements.

In the case of this article:

Evaluation of oil production from oil palm empty fruit bunch by oleaginous

microorganisms. Biofuels, Bioproducts and Biorefining, 10 (2016), Pages 378-392.

Contributor Statement of contribution

Farah B. Ahmad The author contributed to initial

experimental design; conducted

experiment, analysis and data

interpretation; and wrote the first draft of

manuscript and subsequent revisions of

the manuscripts.

Signature

Date

Zhanying Zhang This author provided valuable assistance

in initial experimental design, the

analysis and data interpretation, and

82

edited the manuscript draft.

William O. S. Doherty This author contributed to data

interpretation and provided valuable

input in reviewing the manuscript.

Ian M. O’Hara This author supervised overall

experimental design, analysis, data

interpretation, and edited the manuscript

draft.

Principal Supervisor Confirmation

I have sighted email or other correspondence from all Co-authors confirming their

certifying authorship.

Name

Ian O’Hara

Signature

Date

83

4.1.1 Introduction

The world’s palm oil industry produced 54 million tonnes of palm oil in 2013,

which is a 50% increase compared to 2003 [1]. The expansion of the palm oil

industry has also generated increasing amounts of oil palm biomass waste. It is

estimated that palm oil accounts for only 10% of the whole palm tree mass, with the

remaining 90% consisting of oil palm biomass [2]. The five main solid biomass

components produced from the palm oil sector are oil palm frond (OPF) and oil palm

trunk (OPT) from the oil palm plantation; empty fruit bunch (EFB), palm kernel shell

(PKS) and mesocarp fibre (MF) from palm oil mills [3]. From the palm oil mills,

EFB makes up the highest percentage of wastes where it was estimated that 7 million

tonnes of EFB was produced in 2010 in Malaysia alone [3]. EFB is not effectively

utilised for other application in the mills and is usually disposed of at the mills or

plantations [4].

EFB and other oil palm biomasses are lignocellulosic biomass, and therefore

are potential renewable feedstocks for producing sustainable bioproducts and

biofuels such as microbial oil-derived biodiesel. Pretreatment is essential for

lignocellulosic biomass prior to bioprocessing in order to deconstruct the complex

biomass structure and subsequently produce fermentable sugars by enzymatic- or

acid-hydrolysis. Dilute acid pretreatment is the most commonly used pretreatment

technique due to its relatively low cost [5], where it generally removes the majority

of hemicellulose and makes the cellulose component more accessible to cellulases

[6]. Dilute acid pretreatment results in liquid fraction that mainly consists of pentose

sugars and solid residue that can be used for the production of a glucose-rich solution

by subsequent hydrolysis. However, this type of pretreatment is often accompanied

by sugar degradation products such as furfural and 5-hydroxymethyl furfural (HMF)

[7], which may inhibit the growth of microorganisms. Detoxification methods such

as overliming can be applied in order to reduce the inhibitory effects of furfural and

HMF [8].

Studies have shown that a number of oleaginous yeasts (e. g., Cryptococcus

curvatus, Rhodotorula glutinis, Trichosporon coremiiforme, Trichosporon cutaneum

and Yarrowia lipolytica Po1g) and filamentous fungi (e. g., Mortierella isabellina

and Mortierella vinacea) are able to grow and produce oil on the hydrolysates of

84

pretreated or enzymatic hydrolysed lignocellulosic biomass [9-14]. Liquid fraction

from dilute acid pretreatment of lignocellulosic biomass has been utilised as the

carbon source for microbial oil production. For instance, the cultivation of R. glutinis

on corncob hydrolysate in 5 L bioreactor produced 5.5 g/L oil with a yield of 130

mg/g [5]. A study on the cultivation of M. isabellina on enzymatic hydrolysate of

corn stover resulted in an oil concentration of 5.1 g/L with a yield of 137 mg/g [15].

EFB has been subjected to microbial oil production where the carbon substrates from

EFB were prepared through alkaline and/or acid hydrolysis. In a study of microbial

oil production by Tampitak et al., EFB was first delignified with 10% (wt%) NaOH

followed by one- or two-step acid hydrolysis to produce sugars [16]. The highest oil

concentration of 2.73 g/L, with an oil yield of 140 mg/g substrate by Candida

tropicalis, was achieved from the pulp residue hydrolysate of two-step acid

hydrolysis [16]. The production of microbial oil from enzymatic hydrolysate of EFB

acid-pretreated solid residue, however is yet to be explored. There are also limited

studies on microbial oil production obtained from both liquid fraction and solid

residue of the same pretreated biomass. The utilisation of both hydrolysates could

potentially enhance the total oil yields and improve the economics of microbial oil

from oil palm biomasses. The techno-economic assessment on microbial oil

production from lignocellulosic biomass is also limited as there were only a few

studies focusing on the economic aspect of microbial oil production from

lignocellulosic biomass.

The aim of this study was to assess oil production from EFB by oleaginous

microorganisms that were selected based on our previous study [17], which were

yeast Rhodotorula mucilaginosa, filamentous fungi Aspergillus oryzae and Mucor

plumbeus. In this study, EFB was pretreated by dilute acid, where the liquid fraction

was separated, detoxified and used as liquid hydrolysate (EFBLH) for microbial oil

production. The solid residue was subjected to enzymatic hydrolysis, where the

hydrolysate was used for microbial oil production as enzymatic hydrolysate

(EFBEH). The oil production capacity of these microorganisms on both hydrolysates

(EFBLH and EFBEH) was assessed in terms of microbial oil production, sugar

utilisation efficiency and tolerance to inhibitors. The fuel quality of the microbial oils

was assessed in order to evaluate the viability of the oils to be used as biodiesel. The

utilisation of both hydrolysates is important for cost-effective biorefinery

85

applications, especially for maximising total microbial oil production. The techno-

economic evaluation was performed in order to assess the potential increase of oil

production in the oil palm sector and also the economic viability of microbial oil

production from oil palm biomasses. This is the first study to conduct a techno-

economic evaluation on microbial oil production from oil palm biomasses.

4.1.2 Material and methods

4.1.2.1 Material

Empty Fruit Bunch (EFB)

EFB was provided by Teck Guan Industries Sdn. Bhd., (Sabah, Malaysia).

EFB was air-dried and had a moisture of 7.8% (w/w).

Strains

The yeast strain Rhodotorula mucilaginosa (FRR no.: 2406) and fungal strains

Aspergillus oryzae (FRR no.: 1677) and Mucor plumbeus (FRR no.: 2412) were

purchased from FRR Culture Collection (Australia). The yeast strain was maintained

on yeast dextrose potato (YDP) agar slants at 4 °C [18]. Fungal strains were

maintained on potato dextrose agar (PDA) at 4 °C [12].

The strains used in this study were selected based on a multi-criteria analysis

by Ahmad et al. in determining the most suitable microorganisms for oil production

from model substrates of lignocellulosic hydrolysate [17].

4.1.2.2 Methods

EFB pretreatment

The air-dried raw EFB was pretreated with 0.4 wt% H2SO4 at a solid loading of

1:6 (solid:liquid (w/w)) in 7.5 L Parr reactor (Model 4554, Parr Instrument Company,

USA) at a stirrer speed of 100 rpm, at 170 °C for 15 min [19]. The liquid fraction and

the solid residue were separated by filtration (Figure 4-1) using Whatman filter paper

(Grade 1, Whatman, England). The compositional analysis of raw and pretreated

EFB was performed according to the methods developed by National Renewable

Energy Laboratory [20, 21].

86

Figure 4-1 Flow chart of hydrolysates preparation from EFB for microbial cultivation.

Detoxification of pretreated EFB liquid hydrolysate

A subsample of the liquid fraction was detoxified by overliming technique. The

subsample was heated up to 42 °C while stirring, followed by the addition of

Ca(OH)2 powder to pH 10, where the temperature was then maintained at 50 °C for

30 min using stirring hot plate [10]. The mixture was then filtered using 0.22 µm

membrane (Sartorius, Germany) [10]. The filtrate was cooled to 30 °C and re-

acidified with H2SO4 to pH 5.5, followed by filtration using 0.22 µm membrane [10],

and was used as EFB liquid hydrolysate (EFBLH). Another subsample of the liquid

fraction was not overlimed but its pH was increased to 5.5 by Ca(OH)2, followed by

0.22 µm filtration [10], where the filtrate was used as non-detoxified hydrolysate as

the control for the cultivation.

Enzymatic hydrolysis of solid residue

Enzymatic hydrolysis of washed EFB solid residue was performed at a solid

loading of 10 wt% using Accelerase™ 1500 (Batch no: 4901298419) at 20 FPU/g

Liquid fraction

Washing

Solid residue

EFB Fibre

Dilute acid pretreatment

Filtration

Detoxification by overliming

Enzymatic hydrolysis

Liquid fraction Solid residue

Liquid hydrolysate (EFBLH)

Enzymatic hydrolysate (EFBEH)

Residue

87

glucan, at pH 5.5. The enzymatic hydrolysis was conducted on OM15 orbital shaking

incubator (Ratek, Australia) set at 50 °C and 150 rpm for 72 h. The liquid fraction of

enzymatic hydrolysis was separated by centrifugation at ~6800 g for 20 min. The

supernatant was filtered using a 0.22 µm membrane [10], and was used as EFB

enzymatic hydrolysate (EFBEH). The residue of enzymatic hydrolysis was not

analysed.

Cultivation and microbial oil production

The yeast strain was pre-cultured prior to cultivation. R. mucilaginosa was

grown for 48 h in the pre-cultivation medium with 20 g/L xylose, 10 g/L peptone and

10 g/L yeast extract [22]. For inoculation of the yeast strain into the hydrolysates

cultivation medium, 10% (v/v) inocula from yeast pre-cultivation medium were used.

For inoculation of fungi into the hydrolysates cultivation medium, 0.6 mL spore

suspension containing 1 x 107 spores/mL was used.[12]

The cultivation media (hydrolysates) were prepared by supplementing EFBLH

and EFBEH with 0.4 g/L MgSO4·7H2O, 2 g/L KH2PO4, 3 mg/L MnSO4·H2O and 0.1

mg/L CuSO4·5H2O, and 1.5 g/L yeast extract as the nitrogen source, with pH

adjustment to 5.5 [10]. The cultivation was performed in triplicate with 30 mL

working volume in 150 mL Erlenmeyer flask at 28 °C on OM15 orbital shaking

incubator (Ratek, Australia) for 7 days. Yeast and fungal biomasses were harvested

based on methods described previously, followed by biomass freeze-drying to

constant weight [17].

Oil extraction

Oil was extracted from the biomass by Accelerated Solvent Extraction (ASE)

technique using Dionex ASE 350 (Thermo Fisher Scientific Inc., USA) according to

oil extraction technique described previously [17]. The extraction conditions were as

follows: temperature, 130 ; static time, 7 min; rinse volume, 25% of cell volume;

purge time, 60 s; and using 2 static cycles, using chloroform/methanol in a ratio of

2:1 (v/v). The extracted oil was collected in pre-weighed collection bottles. The

solvents were evaporated under a stream of nitrogen. Unless otherwise specified, all

results are reported on a dry weight (DW) basis.

88

Sugars, organic acids, furans, oil and nitrogen analyses

Sugars concentrations (glucose, xylose, cellobiose and arabinose) were

analysed using high-performance liquid chromatography (HPLC) by a Waters HPLC

system equipped with a SP810 carbohydrate column (300 mm × 8.0 mm, Shodex,

Japan) and a refractive index (RI) detector (Waters 410, US) [23]. The column

temperature was 85 °C and the mobile phase was water, with a flow rate of 0.5

mL/min. Organic acids concentrations (formic acid, acetic acid and levulinic acid)

and furans (furfural and 5-hydroxymethylfurfural (HMF)) were analysed using the

same HPLC system equipped with a Aminex HPX-87H column (300 mm × 8.0 mm,

Bio-Rad, US) and the RI detector [23]. The column temperature was 65 °C and the

mobile phase was 5 mM H2SO4, with a flow rate of 0.6 mL/min.

For the determination of fatty acids composition, fatty acid methyl esters

(FAMEs) were prepared using oil derivatisation method as described by Mulbry et

al. [24]. FAME analysis was performed by gas chromatography-mass spectrometry

(GC-MS) by Shimadzu GCMS-TQ8040 (Shimadzu Corporation, Japan) on an Rtx®-

2330 column (60 m long × 0.25 mm I.D. × 0.2 µm film thickness; Restek, USA).

The carrier gas was helium at a flow rate of 1.5 mL/min. A 10:1 split injection was

used. The injection temperature was set at 250 °C, the MS ion source temperature at

220 °C and the MS interface temperature at 240 °C. The GC-MS method was carried

out using the following temperature program: initial temperature at 90 °C, hold for 2

min, followed by 7.5 °C/min ramp to 210 °C and 20 °C/min ramp to 240 °C, hold for

5 min. Mass spectrometry was performed using Q3 scan with an m/z 20-650

scanning range. Chromatograms and mass spectra were evaluated using the

GCMSsolution software (Shimadzu Corporation, Japan). The retention times and

mass spectra were identified using FAME mix (F.A.M.E. Mix, C8-C24; Sigma-

Aldrich, Australia).

Fuel properties were assessed using cetane number, kinematic viscosity at 40

°C, higher heating value and iodine value. Cetane numbers of FAMEs of microbial

oils were calculated based on the empirical equation proposed by Ramírez-Verduzco

et al. [25], where the cetane number of each fatty acid methyl ester was calculated

using the following equation

∅ 71. 8 0.302 20 (1)

89

From Equation (1), ∅ is the cetane number of the ith FAME, is the molecular

weight of the ith FAME and N is the number of double bonds in a given FAME. The

kinematic viscosity of biodiesel at 40 °C was calculated based on the following

equation

ln 12.503 2.496 ln 0.178 (2)

where is kinematic viscosity at 40 °C (mm2/s) of the ith FAME [25]. Iodine values

of FAME were calculated based on the determination of iodine values of individual

FAME by Krisnangkura [26].

Total nitrogen in EFB hydrolysate was analysed using TOC-VCSH (Shimadzu

Corporation, Japan) with TNM-1 (Total Nitrogen Unit) (Shimadzu Corporation,

Japan). Carbon to nitrogen (C/N) ratio (mass/mass) was calculated using the

following equation:

/ , .

. (3)

where the unit for concentrations of total carbon sources and nitrogen were in g/L,

0.4 was the mass fraction of carbon in the carbon sources (g/g) and 0.8 was mass

fraction of nitrogen in yeast extract (g/g). The oil yield (mg/g) was calculated by

dividing the oil concentration (mg/L) with the total glucose and xylose and acetic

acid consumed (g/L).

Technical and economic assessment of microbial oil production

Microbial cultivation efficiency was estimated based on the theoretical oil

yields of 320 mg/g for glucose and 340 mg/g for xylose [12, 27]. Therefore, % oil

conversion efficiency was calculated according to the following equation,

%

/

/ 100 (4)

where the total oil production from 1 tonne EFB was the summation of predicted oil

production from EFBLH and EFBEH by M. plumbeus. The theoretical oil production

from 1 tonne EFB was calculated using theoretical oil yields on glucose and xylose,

based on the total sugars contents in 1 tonne (dry weight) EFB from EFBLH and

EFBEH.

90

Assuming oil conversion efficiencies of other oil palm biomasses (OPT and

OPF) were the same as those for EFB, the predicted oil production from other oil

palm biomasses of per 1 tonne (dry weight) biomass was calculated as

%

1 10 (5)

Potential microbial oil production per ha (kg/ha) for EFB and other oil palm biomass

(OPT and OPF) was calculated using the following equation

/

1 /

/ (6)

For the economic assessment of large scale microbial oil production, the

relative feedstock cost (US$/kg oil) is calculated by dividing the selling price of

feedstock per tonne biomass (US$/t biomass) by the estimated quantity of microbial

oil produced per 1 tonne biomass (kg/t biomass), as

$/

$/

/ (7)

4.1.3 Results and discussion

4.1.3.1 Chemical composition of feedstock samples

Table 4-1 shows the biomass composition of raw EFB and the solid residue

following pretreatment. Raw EFB consists of 38.8% glucan, 22.4% xylan, 27.2%

lignin. The biomass compositions of EFB solid residues after pretreatment were

45.5% glucan, 6.1% xylan and 40.0% lignin (Table 4-1), with cellulose digestibility

at 43.2%. These results demonstrated that dilute acid pretreatment removed the

majority of hemicellulose (xylan) from the solid biomass as xylan dissolved in the

liquid fraction of hydrolysate [10]. In this study, hydrolysates of liquid fraction and

solid residue from pretreatment were used as substrates for microbial cultivation. The

compositional analyses of EFB hydrolysates are displayed in Table 4-2. EFBLH

91

mainly consists of xylose, whereas the major component of EFBEH is glucose. The

concentration of organic acids (i.e., formic acid, acetic acid and levulinic acid) and

furans (i.e., HMF and furfural) are shown in Table 4-2. Organic acids and furans are

the potential growth inhibitors to microbial cultivation, as reported in numerous

studies [7, 28-30]. HMF and furfural have been shown to reduce yield and inhibit

growth in ethanol production, as well as oil production [28-30]. It has been reported

that furfural concentrations above 1.0 g/L resulted in negative impacts on growth and

oil production of the fungal strain, Mortierella isabellina and the yeast strain

Cryptococcus curvatus [29, 30]. Organic acids or weak acids has been shown to

inhibit cell growth and reduce ethanol yield during the fermentation for ethanol

production [28]. However, the presence of formic, acetic and levulinic acids at a low

concentration in the fermentation for ethanol production has been shown to increase

the yield of ethanol [28]. There are, however, limited studies on the inhibitory effect

of organic acids for microbial oil production.

Table 4-1 Chemical compositions of raw and pretreated EFB. The composition of lignin was based on the composition of acid soluble and acid insoluble lignin. Sample Compositions (%, w/w)

Glucan Xylan Lignin Raw EFB a 38.8 ± 0.0 22.4 ± 0.0 27.2 ± 0.0 Pretreated EFB 45.5 ± 0.5 6.1 ± 0.1 40.0 ± 0.1 a consisted of 5.1% ash, 10.1% water extractives and 3.6% ethanol extractives

In this study, no growth was observed from the cultivation of non-detoxified

EFBLH, most likely due to the presence of high concentrations of furfural in the

hydrolysate. The detoxification step by overliming on the liquid fraction of

pretreatment process was shown to reduce the concentration HMF in the hydrolysate

by approximately two times, and the concentration of furfural was reduced by five

times. Furans present at a low concentration in EFBEH as the solid residue was

washed prior to enzymatic hydrolysis. The washing step is also important as it may

reduce the number of detoxification steps in the hydrolysates preparation process.

The loss of sugars in the detoxified EFBLH was observed at 21.4% for glucose and

7.4% for xylose. Yu et al. also showed 13-29% sugar loss in wheat straw

hydrolysate after detoxification using the overliming process [10]. The concentration

of acetic acid in EFBLH was higher than in the original non-detoxified EFBLH

92

possibly due to water loss from the hydrolysate during the overliming process. This

trend was also seen in the results of the study by Yu et al. where the acetic acid in the

hydrolysate increased from 4.0 g/L to 4.2 g/L after the detoxification process [10].

Table 4-2 Sugars (glucose, xylose and arabinose), organic acids (formic acid, acetic acid and levulinic acid) and furans (5-hydroxymethylfurfural (HMF) and furfural)

compositions of liquid (EFBLH) and enzymatic (solid residue) (EFBEH) hydrolysates of EFB.

Feedstock Non-detoxified EFBLH EFBLH EFBEH

Glucose (g/L) 0.42 0.33 17.42

Xylose (g/L) 5.28 4.89 2.91

Arabinose (g/L) 1.33 1.2 0.61

Formic acid (g/L) 1.07 0.82 0.5

Acetic acid (g/L) 7.06 7.89 2.61

Levulinic acid (g/L) 0.13 0.07 0

HMF (g/L) 0.21 0.08 0.05

Furfural (g/L) 2.89 0.56 0.24

4.1.3.2 Sugars consumption and microbial growth on EFB hydrolysates

In this study, R. mucilaginosa, A. oryzae and M. plumbeus were grown on

liquid hydrolysates and enzymatic hydrolysates resulting from the pretreatment of

EFB. The consumption of sugars by R. mucilaginosa, A. oryzae and M. plumbeus are

shown in Figure 4-2. Complete consumption of glucose was observed for almost all

strains on all hydrolysates. Figure 4-2 also shows lower consumption of xylose

compared to glucose in EFBLH. This is most likely due to the slower consumption

rate of xylose by microorganisms compared to the consumption rate of glucose, as

seen in Ahmad et al. [17]. The amount of xylose consumed in EFBEH was lower

than the xylose consumed in EFBLH. This is probably because xylose consumption

only commenced after glucose was almost depleted in the medium, as shown in

numerous studies [31]. For instance, xylose consumption by Trichosporon cutaneum

ACCC 20271 commenced at 120 h after glucose was almost completely consumed in

enzymatic hydrolysate of corncob residue [13]. Sequential sugars consumption is

common in the microbial cultivation of the mixture of glucose and xylose, due to the

catabolite repression mechanism by glucose or allosteric competition for sugar

93

transporters [32]. A number of studies have been conducted on the simultaneous

consumption of glucose and xylose, as co-consumption of sugars in lignocellulosic

hydrolysates is crucial for comprehensive utilisation for the conversion

lignocellulosic biomass to microbial oil [31]. For the cultivation on EFBEH of all

microorganisms, there were ~40% (w/w) of residual xylose remaining in the media at

the end of cultivation. In this study, M. plumbeus had the lowest consumption of

xylose from EFBLH in comparison to R. mucilaginosa and A. oryzae, possibly due to

its low xylose assimilation capacity. This trend was in agreement with the previous

study by Ahmad et al. [17]. Longer cultivation times may allow more complete

consumption of xylose by these microorganisms in glucose-rich media like EFBEH.

However, prolonged cultivation may not be economical depending on the oil

productivity from the residual sugars.

For cultivation on EFBLH, the biomass concentrations of R. mucilaginosa, A.

oryzae and M. plumbeus were at 5.81 (±0.32), 10.57 (±0.61) and 9.35 (±1.20) and

g/L respectively. The growth on EFBEH showed higher biomass concentrations from

fungal strains, A. oryzae and M. plumbeus at 12.0 and 12.6 g/L respectively, in

comparison to the biomass concentration of R. mucilaginosa at 11.3 g/L. It was also

noted that although fungi strains A. oryzae and M. plumbeus consumed less sugars

from EFBLH than R. mucilaginosa, the biomass concentrations of fungi strains,

however, were higher. The biomass concentrations of fungi strains on EFBLH were

higher even at lower sugars consumption possibly due to the consumption of acetic

acid by the microorganisms. A. oryzae showed acetic acid consumption of 97% and

M. plumbeus of 80% by the end of cultivation. Several studies showed that acetate

was effectively metabolised for oil production by oleaginous microorganisms such as

M. isabellina, C. curvatus and Y. lipolytica Po1g [30].

The biomass concentrations of the fungal strains obtained in this study from

EFBEH are comparable to the results of Ruan et al. on the cultivation of Mortierella

isabellina from enzymatic hydrolysate of corn stover with biomass production at

16.8 g/L [15]. The hydrolysate of corn stover was pretreated with dilute acid and

alkali pretreatments prior to enzymatic hydrolysis, and the hydrolysate consists of

22.2 g/L of glucose and 12 g/L of xylose [15]. Overall, this study shows that all three

selected strains have the capacity to grow on EFBLH and EFBEH and are able to

94

grow in EFB hydrolysates even with the presence of 0.08 g/L of HMF and 0.56 g/L

of furfural.

Figure 4-2 Sugars consumption of R. mucilaginosa, A. oryzae and M. plumbeus on EFB liquid (EFBLH) and enzymatic (EFBEH) hydrolysates.

Glucose consumption is represented by (R. mucilaginosa, RM), (A. oryzae, AO) and (M. plumbeus, MP). Xylose consumption is represented by (R.

mucilaginosa, RM), (A. oryzae, AO) and (M. plumbeus, MP).

4.1.3.3 Microbial oil production from EFB hydrolysates

The oil contents results are presented in Figure 4-3(a). The fungal strain M.

plumbeus showed the highest oil content on EFBLH at 19.8%. For the cultivation on

EFBEH, the highest oil contents recorded were by A. oryzae and M. plumbeus at

~37%. Both fungal strains A. oryzae and M. plumbeus showed higher oil

accumulation on EFBEH than EFBLH. One possible reason for this is that EFBEH

has higher C/N ratio (47.0) than EFBLH (10.2) since EFBEH contains a higher

carbon substrate concentration than EFBLH. The C/N ratio has been identified as the

most important factor affecting lipid accumulation by oleaginous microorganisms

[33]. The presence of HMF and furfural in EFBLH may also be a contributing factor

to lower oil accumulation. Even though numerous studies show that inhibitory

compounds have more damaging effects on growth than oil accumulation, Zhang et

al. argued that inhibitory compounds may have a negative impact on oil

RM RMAO AOMP MPRM

RM

AO

AO

MP

MP

0

10

20

30

40

50

60

70

80

90

100

EFBLH EFBEH

% c

onsu

mpt

ion

95

accumulation as well [7, 34]. This is because any negative effect preventing

microorganisms from reaching the non-growth phase where lipid accumulation

usually occurs, will be detrimental to lipid production as well [34]. Different types of

hydrolysates, however, did not affect oil accumulation by R. mucilaginosa, possibly

because of the lower capacity of R. mucilaginosa to accumulate oil. Ahmad et al.

showed that R. mucilaginosa resulted in a maximum oil content of ~22% on 30 g/L

glucose as well as on glycerol [17].

The oil contents of fungal strains A. oryzae and M. plumbeus obtained in this

study from the cultivation on EFBEH were much higher than the oil contents found

in the cultivation by Ahmad et al., using the pure sugar substrates at higher

concentrations which were 30 g/L glucose (at ~26% of oil) and 30 g/L xylose (~20-

23% of oil) [17]. Higher oil accumulation from cultivation on EFBEH is possibly

due to the lower yeast extract concentration used in this study compared to the study

by Ahmad et al. [17], and therefore resulted in a higher C/N ratio. Based on the total

nitrogen analysis, EFBEH consisted of 0.18 g/L nitrogen, in contrast to 0.36 g/L

nitrogen (based on the use of 4 g/L yeast extract) in the cultivation media in Ahmad

et al. [17]. Therefore, the C/N ratio of EFBEH was 47.0, whereas the C/N ratio of the

cultivation media in Ahmad et al. was 35.4.

Figure 4-3(b) shows oil concentrations from R. mucilaginosa, A. oryzae and M.

plumbeus cultivated on EFB hydrolysates. Fungal strains, M. plumbeus had recorded

the highest oil concentration growing on hydrolysates of EFB (1.85 ±0.33 and 4.69

±0.44 g/L on EFBLH and EFBEH respectively), followed by A. oryzae (1.40 ±0.60

g/L on EFBLH and 4.47 ±0.40 g/L on EFBEH). Microbial oil concentrations of

fungal strains M. plumbeus and A. oryzae on EFBLH obtained in this study compares

well to Tampitak et al. with oil concentration of 1.61 g/L by C. tropicalis on

hemicellulose hydrolysate of EFB [16]. The EFB hemicellulose hydrolysate was

prepared by alkaline and dilute acid pretreatment, was diluted to 20 g/L sugars,

followed by detoxification [16]. The result of oil concentration of M. plumbeus on

EFBEH is comparable to oil production by M. isabellina at 6.9 g/L from corn stover

hydrolysate by Ruan et al. [15].

96

(a)

(b)

Figure 4-3(a) Oil contents (%, w/w) and (b) oil concentrations (g/L) of yeast R. mucilaginosa, and fungi A. oryzae and M. plumbeus cultivated on EFB liquid

(EFBLH) and enzymatic (EFBEH) hydrolysates.

The oil production by M. plumbeus and A. oryzae on EFBEH in this study was

two times higher than C. tropicalis on residual pulp hydrolysate (2.73 g/L of oil) and

holocellulose hydrolysate (1.31 g/L of oil) of EFB, even though these two

hydrolysates and EFBEH have almost similar concentrations of sugar of 20 g/L [16].

The oil concentration of yeast R. mucilaginosa (2.17 g/L of oil) on EFBEH is similar

to the yeast strain used by Tampitak et al. (C. tropicalis) on EFB pulp hydrolysate.

The EFB pulp hydrolysate was pretreated with alkaline and dilute acid, followed by

acid hydrolysis, whereas the EFB holocellulose hydrolysate was prepared through

alkaline pretreatment and acid hydrolysis [16]. Both hydrolysates were then

subjected to dilution and detoxification [16]. Low oil production from EFB

holocellulose hydrolysate by Tampitak et al. in comparison to EFB pulp hydrolysate

0

5

10

15

20

25

30

35

40

45

EFBLH EFBEH

Oil

con

tent

(%

, w/w

)

R. mucilaginosa

A. oryzae

M. plumbeus

0

1

2

3

4

5

6

EFBLH EFBEH

Oil

conc

entr

atio

n (g

/L)

R. mucilaginosa

A. oryzae

M. plumbeus

97

was not discussed, even though both hydrolysates have similar glucose and overall

sugars concentrations. One possible reason for this is that there was a slightly higher

concentration of furfural (0.17 g/L) in EFB holocellulose hydrolysate compared to

EFB pulp hydrolysate (0.13 g/L furfural). Another reason for the variation in oil

production is possibly contributed by the concentration of organic acids in the

hydrolysates, which was not discussed. Overall, both fungal strains M. plumbeus and

A. oryzae showed good potential to produce oil from EFB hydrolysates, with oil

concentrations similar to the widely researched fungal strain M. isabellina.

Table 4-3 shows the results of oil concentrations and oil yields by a number of

oleaginous microorganisms from various agro-industrial wastes. Oil yield is an

important parameter for the cultivation as it measures the efficiency of

microorganisms to convert carbon substrates to oil. In this study, M. plumbeus

produced the highest oil concentrations and oil yields from both EFB hydrolysates in

comparison to A. oryzae and R. mucilaginosa. The cultivation of R. mucilaginosa

resulted in lower oil yields on EFBLH (64 mg/g) and EFBEH (93 mg/g). Lower

conversion efficiency of carbon substrates to oil in R. mucilaginosa was most likely

due to the assimilation of carbon substrates for the production of carotenoids, as

Rhodotorula yeasts are well-known carotenoids producers [35]. The oil yield of M.

plumbeus on EFBLH (185 mg/g) is slightly lower than EFBEH (231 mg/g), possibly

due to the presence of inhibitors in EFBLH. The oil yields of fungal strains on

EFBLH in this study are higher than the oil yield (80 mg/g) of C. tropicalis grown on

hemicellulose hydrolysate (liquid fraction of pretreatment) of EFB [16]. The oil yield

of M. plumbeus on EFBLH is comparable to the oil yield (172 mg/g) of

Trichosporon coremiiforme grown on detoxified corncob hydrolysate (2.9 g/L

glucose and 37.9 g/L xylose, 0.32 g/L HMF and 0.06 g/L furfural) [14], where both

hydrolysates contained a higher proportion of xylose than glucose. Table 4-3 also

shows that oil yields of M. plumbeus on lignocellulosic biomass are comparable to

those of other microorganisms, such as the more widely researched yeast strain C.

curvatus (140 mg/g on corncob liquid hydrolysate) and fungal strain M. isabellina

(147 mg/g on corn stover enzymatic hydrolysate) [10, 15].

98

Table 4-3 Biomass concentrations, oil concentrations and oil yields of different oleaginous yeasts and filamentous fungi from batch fermentation

of various hydrolysates of lignocellulosic agro-industrial wastes. Oil yields are expressed as mg oil produced per g sugars consumed, unless mentioned otherwise.

Feedstock Strains Biomass concentration (g/L)

Oil concentration (g/L)

Oil yield (mg/g)

Lignocellulosic biomass processing

Liquid hydrolysate from pretreatment process Corncob Rhodotorula

glutinis 15.1 5.5 130 * Dilute acid

pretreatment [5]

Corncob Trichosporon coremiiforme

20.4 7.7 172 Dilute acid pretreatment [14]

Wheat straw

Cryptococcus curvatus

17.2 5.8 140 a Dilute acid pretreatment [10]

Wheat straw

Mortierella isabellina

5.9 2.3 123 Dilute acid pretreatment [12]

EFB Candida tropicalis

6.4 6.7 80 Dilute alkaline and dilute acid pretreatment [16]

EFB R. mucilaginosa

5.8 0.8 64 a This study

EFB A. oryzae 10.6 1.4 110 a This study

EFB M. plumbeus 9.4 1.9 185 a This study

Solid residue hydrolysate Corn stover

Mortierella isabellina

18.7 6.9 147 Dilute alkaline and dilute acid pretreatment, then enzymatic hydrolysis of pretreatment slurries [15]

Corncob Trichosporon cutaneum

38.4 12.3 131 Enzymatic hydrolysis of residue, pretreatment was not specified [13]

EFB R. mucilaginosa

11.3 2.2 93 a This study

EFB A. oryzae 12 4.5 199 a This study

EFB M. plumbeus 12.6 4.7 205 a This study

* Data is not provided, complete reducing sugars consumption was assumed a Oil concentration (g/L) per reducing sugars consumed as well as acetic acid consumed

99

4.1.3.4 Fatty acid profiles and potential application of microbial oils produced

from EFB hydrolysates

Microbial oils have the potential to be utilized as alternative feedstocks for

biodiesel production, depending on the fatty acids profile of the microbial oil.

Biodiesel is a renewable fuel, typically made from vegetable oils and their

derivatives, especially methyl esters [36]. Microbial oils with similar fatty acids

compositions to vegetable oils have the potential to be used for biodiesel production.

The fatty acids profiles of transesterified microbial oils produced in this study

are shown in Table 4-4. The results showed that microbial oils have similar fatty

acids composition to vegetable oils, with the major fatty acids identified being

palmitic (C16:0), stearic (C18:0), oleic (C18:1) and linoleic acid (C18:2). For R.

mucilaginosa, oleic acid was the predominant fatty acid produced on EFBLH (52.9

%), which is in agreement with the results of Ahmad et al. in the cultivation of R.

mucilaginosa on glucose and xylose [17]. However, palmitic acid was the

predominant fatty acid of oil extracted from R. mucilaginosa grown on EFBEH (47.2

%). Linoleic acid was the predominant fatty acids for both A. oryzae and M.

plumbeus cultivated on EFBLH (36.9% and 39.4% respectively), followed closely by

oleic acid. For the growth of both A. oryzae and M. plumbeus on EFBEH, oleic acid

was identified as the predominant fatty acid at ~33 - 34%, which is in accordance

with the findings from Ahmad et al. on the cultivation of A. oryzae and M. plumbeus

on glucose and xylose [17].

Fuel properties of microbial oils can be further analysed in order to determine

the suitability of microbial oils to be utilised for the production of biodiesel. Among

the most important physical properties of biodiesel are cetane number, kinematic

viscosity at 40 °C, higher heating value and iodine value. Cetane number is a relative

measure of the ignition quality of fuels, whereby low cetane number fuels have the

tendency to increase gaseous and particulate exhaust emissions due to incomplete

combustion [25, 37]. Methyl esters of microbial oils in this study have estimated

cetane numbers to be greater than 59 (Table 4-4), which is above the required

minimum values of 47 and 51 according to the biodiesel specifications of ASTM

6751-08a and EN14214 respectively [25, 38].

100

The viscosity of biodiesel is important as high viscosity will cause poor

atomisation in the combustion chamber and subsequently lead to engine problems

like nozzle choking and engine deposits [36]. Kinematic viscosities at 40 °C of

microbial oils methyl esters were shown in Table 4-4 and the kinematic viscosity of

all microbial oils were within the limit of EN 14214 (3.5 to 5.0 mm2/s) [39]. The

viscosities of fatty acids ester that has been transesterified is typically lower than the

viscosities of fatty acids [36].

Table 4-4 Fatty acids composition of microbial oils methyl ester of R. mucilaginosa, A. oryzae and M. plumbeus cultivated on EFB liquid (EFBLH) and solid residue

enzymatic (EFBEH) hydrolysates, as well as fuel properties, (cetane number, kinematic viscosity, higher heating value and iodine number) of

transesterified microbial oils. Microorganisms Relative abundance of fatty acid

methyl esters (FAME) (%, w/w) FAME fuel properties

C16:0 C18:0 C18:1 C18:2 Cetane number

Kinematic viscosity at 40 °C (mm2/s)

Iodine number

EFBLH R. mucilaginosa 25.8

(±1.8) 12.1 (±0.7)

52.9 (±2.6)

11.2 (±2.8)

64.3 4.66 64.6

A. oryzae 21.1 (±1.9)

13.1 (±1.1)

29.7 (±1.1)

36.9 (±0.6)

59.9 4.42 89.2

M. plumbeus 23.0 (±2.5)

12.3 (±1.1)

23.6 (±5.5)

39.4 (±1.7)

57.9 4.27 88.3

EFBEH R. mucilaginosa 47.2

(±0.2) 31.8 (±0.5)

17.4 (±1.1)

3.6 (±0.4)

73.3 4.78 21.1

A. oryzae 19.3 (±1.1)

17.9 (±0.6)

34.1 (±0.9)

28.6 (±1.2)

61.8 4.50 78.6

M. plumbeus 18.2 (±0.9)

19.1 (±1.9)

33.8 (±1.0)

28.9 (±1.5)

61.9 4.51 78.8

Polyunsaturated fatty acids, especially those with four or more double bonds,

are not preferable for biodiesel production due to its low oxidative stability [40].

However, biodiesel with higher amounts unsaturated fatty acids has a higher cold

filter plug point (CFPP) [38]. The limit of degree of unsaturation of oil suitable for

biodiesel production can be determined through its iodine value. Iodine value is

defined as the number of centigrams of iodine absorbed per gram samples, in which

fuels with higher iodine values have higher degrees of unsaturation [36]. The

estimated iodine values of each methyl ester (Table 4-4) are below the biodiesel

101

standard maximum limit of 115 (German biodiesel standard DIN V 51606) and 120

(EN14214) [36, 38]. Therefore, this study shows that microbial oils produced are

suitable as biodiesel fuels.

4.1.3.5 Techno-economic evaluation of microbial oil production from oil palm

biomasses

Technical assessment of microbial oil production from oil palm biomasses

In this study, microbial oil had been successfully produced from EFB, the

wastes of palm oil production, through the utilisation of hydrolysates from both

fractions of pretreatment, by yeast R. mucilaginosa and fungi A. oryzae and M.

plumbeus. As the cultivation on M. plumbeus resulted in the highest oil

concentrations and oil yields from all hydrolysates, the data of M. plumbeus was

further used for the techno-economic evaluation of microbial oil production from oil

palm biomass.

The prospect of using M. plumbeus for large-scale microbial oil production can

be evaluated by estimating the amount of oil that could be produced from oil palm

biomasses based on the oil yields [12]. The oil yields of M. plumbeus on EFBEH and

EFBLH in this study, based on consumed sugars, are 205 and 185 mg/g respectively.

The results of sugar yields from the study on optimised dilute acid pretreatment of

EFB by Jung et al. was used for estimating microbial oil production from EFB [41].

For microbial oil production from 1 t dry EFB (249.5 kg glucose and 23.9 kg xylose)

[41], 56 kg microbial oil can be produced from enzymatic hydrolysate of the solid

residue. On the other hand, liquid hydrolysate from 1 t dry EFB (68 kg glucose and

135 kg xylose) [41] can potentially yield 37.6 kg of microbial oil. The total oil

production from 1 t dry EFB is estimated to be 93.6 kg. The estimated microbial oil

produced from 1 t EFB is comparable to 103 kg of estimated microbial oil produced

per tonne wheat straw by fungal strain M. isabellina [12]. The theoretical production

of microbial oil from solid residue hydrolysate is estimated to be 155.6 kg oil per 1 t

dry EFB. Based on the microbial oil production by M. plumbeus from EFB in this

study, 60% oil of the theoretical microbial oil production (i.e., 60% oil conversion

efficiency (Equation 4)) was achieved. However, higher oil yields can likely be

obtained with the use of the bioreactor for cultivating M. plumbeus for large-scale

microbial oil production.

102

As the second largest producer of palm oil in the world, Malaysia produces a

substantial amount of EFB from palm oil mills. It is estimated that 1.38 t EFB (dry

weight) is produced per hectare from oil palm plantations [3]. Therefore, the

potential microbial oil production from palm oil EFB is estimated to be 129 kg/ha.

The quantity is approximately 3.4% of 3.84 t/ha average crude palm oil produced in

Malaysia in 2014 (Table 4-5(a)).

Table 4-5 (a) The summary of technical evaluation of microbial oil production from oil palm biomasses (EFB, trunk (OPT) and frond (OPF)) through the comparison of

potential microbial oil yields per hectare to oil yield of crude palm oil. Biomass availability was based on the Malaysian palm oil sector. (b) The summary

of economic evaluation of oil production from oil palm biomasses through the comparison of the relative feedstock cost of oil production from oil palm biomasses and the feedstock cost of crude palm oil production from fresh fruit bunch (FFB).

(a) Oil palm biomass/ Palm oil

Biomass availability (t/ha)

Sugar content per 1 t biomass (kg/t)

Oil yield per hectare (t/ha)

EFB 1.4 476 0.14

OPT (bagasse) 4.2 435 0.35

OPF (basal) 15.3 164 0.48

Crude palm oil - - 3.84

(b) Feedstock for oil production

Selling price (US$/t)

Oil yield per 1 t biomass (kg/t)

Feedstock cost (US$/kg oil)

EFB 15.80 96.3 0.16

OPT (bagasse) 15.00 83.5 0.17

OPF (basal) 25.00 31.5 0.79

FFB 123.00 206.1 0.60

The total oil production can be increased even further through the use of other

oil palm biomasses, such as oil palm frond (OPF), oil palm trunk (OPT), palm kernel

shell (PKS) and mesocarp fibre (MF), for microbial oil production. It is estimated

that there was 87 million t oil palm solid wastes (dry weight) generated in Malaysia

and these wastes are expected to increase to 100 million t by 2020 [3]. All of these

oil palm biomasses identified are lignocellulosic, and potentially can be used as the

feedstock for microbial oil production. From palm oil processing, MF and PKS were

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produced annually at around 1.42 t/ha and 0.85 t/ha respectively [3]. From oil palm

plantations, there are approximately 14 t/ha OPT and 46 t/ha pruned OPF generated

in Malaysia [3]. OPF and OPT have been tested previously as the carbon substrates

for ethanol fermentation [42, 43]. Therefore, the opportunity exists for utilising the

fermentable sugars from OPF and OPT for microbial oil cultivation. The use of these

biomasses as the additional feedstocks will enhance the total oil yield from a

microbial oil production plant, as well as improve the economics of oil production.

Therefore, in this study, the prospect of microbial oil production from OPF and OPT

were also included in the techno-economic evaluation. However, there was no

sufficient information to perform similar evaluation on MF and PKS. The technical

evaluation for OPF and OPT was completed based on Equation 5 and Equation 6.

OPT can be utilised for microbial oil production from the use of OPT bagasse,

which is the remains of OPT that is squeezed for sugar juice production

(approximately 30% of wet felled OPT) [43]. It is estimated that 4.2 t/ha of dried

OPT bagasse is produced annually in Malaysia. The glucose yield of 435 kg/t OPT

bagasse can be obtained from the enzymatic hydrolysis of cellulose and starch of

OPT bagasse [43]. On the basis of 60% cultivation efficiency, the potential microbial

oil production is estimated to be 0.35 t/ha. On the other hand, OPF also has the

potential to be used for oil production as it contains 164 kg glucose per 1 t OPF (dry

weight) [42]. Assuming that the top two-thirds of OPF with leaflets was re-used as

fertiliser and only the basal (lower third) of OPF was utilised as feedstock of oil

production, there is 15.3 t/ha of OPF available for oil production. Therefore, OPF is

estimated to yield microbial oil up to 0.48 t/ha. Table 4-5(a) showed that oil palm

biomasses have the potential to produce approximately 0.97 t oil per hectare, which

has the potential to increase total oil production by 25% from the same plantation

area.

Economic assessment of microbial oil production from oil palm biomasses

The relative feedstock cost (US$/t) (Equation 7) was used to economically

evaluate the feasibility of microbial oil production from oil palm biomasses. The

feedstock cost of oil production from EFB is estimated based on the selling price of

EFB of $15.80/t [44], where the feedstock cost is $0.17/kg oil. Taking the selling

price of OPF at $25/t from Zahari et al. (based on transportation cost, harvesting and

104

collection cost and pre-processing cost) [45], the feedstock cost of oil production

from OPF is $0.79/kg oil. The selling price of OPT bagasse was estimated to be $15/t

(based on transportation and pre-processing cost from Zahari et al.). Therefore the

feedstock cost of oil production from OPT is $0.18/kg oil. On the other hand, based

on the average 2014 yield of FFB at 18.63 t/ha (selling price of $123/kg) and the

yield of crude palm oil at 3.84 t/ha [46], the feedstock cost of crude oil production

from FFB is estimated to be at $0.60/kg oil. To conclude, the feedstock cost of oil

production from the current palm oil sector can be lowered through the use of

alternative feedstocks for oil production such as oil palm biomasses, especially EFB

and OPT for oil production (Table 4-5(b)).

The feasibility of increasing oil production in the palm oil industry from EFB and other oil palm biomasses

From the technical assessment discussed in preceding subsections, there is

great potential to increase the oil production in the palm oil industry through the

utilisation of processing wastes from the industry. In addition, the economic

assessment demonstrated that the integration of oil palm biomasses with existing

palm oil processing, can potentially provide cheaper feedstock cost for oil

production. The proposed process integration of microbial oil production from oil

palm biomasses is illustrated in Figure 4-4, where the microbial oil production is

incorporated into the existing palm oil industry from plantation harvesting and oil

extraction to products manufacturing.

105

Figure 4-4 Process flow of proposed integration of microbial oil production from oil palm biomasses into the existing palm oil processes.

The flow diagram of palm oil production processes was drawn based on life cycle assessment on crude palm oil production in Malaysia [47] (OPF, oil palm frond;

OPT, oil palm trunk; FFB, fresh fruit bunch).

106

Microbial oil produced from oil palm biomasses can potentially be utilised to

supplement existing palm oil production, either for biodiesel production from non-

food feedstock, as well as manufacturing oleochemicals and food products depending

on the fatty acids composition of microbial oils. Microbial oils with high

compositions of monounsaturated and saturated fatty acids are suitable for biodiesel

production, whereas microbial oils that are rich in palmitic and stearic acid are

compatible to crude palm oil and can be integrated with the palm oil refinery for food

and oleochemicals production. The proposed integration can improve the

sustainability of palm oil processing, where the lignocellulosic by-products from

palm oil processes are recycled back to the industry. The proposed integration also

showed that glycerol, the by-product of transesterification process for biodiesel

production, can be re-utilised for microbial oil production which is significant for the

biorefinery approach. Ahmad et al. demonstrated that M. plumbeus could grow and

produce oil from glycerol [17]. In addition, the proposed integration can enhance the

profitability of palm oil processing, with the potential increase of oil production in

the palm oil industry from cheaper feedstocks, through microbial production from

the lignocellulosic by-products of palm oil processes.

4.1.4 Conclusion

Overall, this study demonstrated the biochemical conversion of pretreated oil

palm EFB to oil through microbial cultivation using R. mucilaginosa, A. oryzae and

M. plumbeus. The hydrolysates from both fractions of pretreatment (liquid fraction

and solid residue) were utilised for the microbial cultivation for maximising the total

microbial oil production from EFB. M. plumbeus showed the highest oil

concentrations and the highest oil yields on both hydrolysates of EFBLH and

EFBEH. The prospect of increasing oil production in the palm oil industry from EFB

and other oil palm biomasses (OPT and OPF) was evaluated technically in terms of

the oil production of M. plumbeus per hectare, and was further assessed

economically through the relative feedstock cost for oil production. The assessments

show that microbial oil production from oil palm biomasses have the potential to

increase existing oil production in the palm oil industry by up to 25% with lower

feedstock cost for oil production. The integration of microbial oil production from oil

107

palm biomasses into the palm oil industry can enhance the sustainability and

profitability of the industry.

4.1.5 Acknowledgements

The authors acknowledge the Ministry of Higher Education Malaysia for the

postgraduate scholarship of Farah B. Ahmad. The authors also thank the QUT

Central Analytical Research Facility for its support on sample analyses, as well as

Vitor Takashi Kawazoe for oil extraction and derivatisation process.

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Optimising microbial oil production from EFB

5.1 Improved microbial oil production from oil palm empty fruit bunch by Mucor plumbeus

F. B. Ahmad1, Z. Zhang1, W. O. S. Doherty1, V. S. J. Te'o2 and I. M. O’Hara1

1Centre for Tropical Crops and Biocommodities, Queensland University of

Technology, Brisbane, Australia

2School of Earth, Environmental and Biological Sciences, Faculty of Science and

Engineering, Queensland University of Technology, Brisbane, Australia

Abstract

This study investigated the effect of cultivation parameters on microbial oil

production from hydrolysate of oil palm empty fruit bunch (EFB) using fungus

Mucor plumbeus. The parameters selected for evaluation were sugar concentration

(30 – 100 g/L), yeast extract concentration (0-13.3%, g yeast extract/g sugar), pH (5-

7) and spore concentration (4.3-6.3, log spore number/mL medium). Response

surface methodology was used to optimise the cultivation conditions which were

based on the oil concentration and oil yield. Sugar concentration was the most

influential parameter that affected microbial oil concentration. However, the

cultivation at high sugar concentration (~100 g/L) also resulted in ethanol

accumulation. The optimum condition for oil yield was found at 30 g/L sugar, 0 g/L

yeast extract and pH 5.0. Cultivation in 1 L bioreactor under optimised conditions

resulted in ~1.8 fold increase in oil yield compared to the shake-flask cultivation.

Microbial oil produced from EFB hydrolysate has the potential to be used as the

feedstock for biodiesel production from non-food feedstock.

Keywords: Biodiesel, Bioreactor, Empty fruit bunch, Fungi, Lignocellulose, Lipid,

Oil palm, Oleaginous

114

Abbreviations: 5-hydroxymethylfurfural, HMF; Carbon-to-nitrogen ratio, C/N;

Dissolved oxygen, DO; Empty fruit bunch, EFB; Enzymatic hydrolysate, EH;

Response surface methodology, RSM

115

Statement of Contribution

The authors listed below have certified that:

1. they meet the criteria for authorship in that they have participated in the

conception, execution, or interpretation, of at least that part of the publication in their

field of expertise;

2. they take public responsibility for their part of the publication, except for the

responsible author who accepts overall responsibility for the publication;

3. there are no other authors of the publication according to these criteria;

4. potential conflicts of interest have been disclosed to (a) granting bodies, (b) the

editor or publisher of journals or other publications, and (c) the head of the

responsible academic unit, and

5. they agree to the use of the publication in the student’s thesis and its publication

on the Australasian Research Online database consistent with any limitations set by

publisher requirements.

In the case of this article:

Improved microbial oil production from oil palm empty fruit bunch by Mucor

plumbeus. Accepted with modification for publication in Fuel.

Contributor Statement of contribution

Farah B. Ahmad The author contributed to initial

experimental design; conducted

experiment, analysis and data

interpretation; and wrote the first draft of

manuscript and subsequent revisions of

the manuscripts.

Signature

Date

Zhanying Zhang This author reviewed the initial

experimental design and edited the drafts

116

of the manuscript.

William O. S. Doherty This author provided assistance in data

interpretation and valuable input in

reviewing the manuscript.

Valentino Setoa Junior Te'o This author provided assistance in

bioreactor experiments and reviewed the

manuscript.

Ian M. O’Hara This author supervised overall

experimental design and analysis, and

edited the drafts of the manuscript

Principal Supervisor Confirmation

I have sighted email or other correspondence from all Co-authors confirming their

certifying authorship.

Name

Ian O’Hara

Signature

Date

117

5.1.1 Introduction

Lignocellulosic biomass is an attractive feedstock for microbial oil production

due to its high availability and low price. Microbial oil, or lipid, can be produced

through biochemical conversion of lignocellulosic biomass, which typically involves

the pretreatment and enzymatic hydrolysis of lignocellulosic biomass for breaking

down polysaccharides to hexoses and pentoses, which can be utilised by oleaginous

microorganisms for microbial oil production. Microbial oils in the form of

triacylglycerides (TAG) can be used as feedstocks for second generation biodiesel

through the transesterification process.

Oleaginous filamentous fungi are promising candidates for microbial oil

production from lignocellulosic biomass due to their capacity to grow on a broad

range of carbon substrates (e.g., glucose, xylose, glycerol, etc.) [1, 2], and their

ability to tolerate low concentrations of growth inhibitors (e.g., furfural and 5-

hydroxymethylfurfural (HMF)) resulting from chemical pretreatment of

lignocellulosic biomass [3]. The morphology of filamentous fungi, either in pellet or

filamentous hyphal form, allows simple filtration technique for down-steam

processing [4, 5].

Cultivation conditions play important roles in microbial oil production.

Carbon-to-nitrogen (C/N) ratio is possibly the most important factor as oleaginous

microorganisms accumulate microbial oil under limiting-nitrogen conditions [6, 7].

In carbon substrates assimilation, citrate is accumulated in the cell’s mitochondrion

during nitrogen exhaustion where citrate is then exported to the cytosol [7]. In the

cytosol, citrate is then cleaved by ACL (ATP-citrate lyase) to acetyl-CoA, which is

the precursor of fatty acid synthesis [7]. A high C/N ratio might inhibit microbial

growth if the ratio is too high leading to nitrogen deprived conditions.

Cultivation pH also has a significant influence on microbial growth as the pH

of the cultivation medium may affect membrane permeability [8]. The pH range of 5

to 7 was reported to be the best for the growth of fungal strains from the order of

Mucorales [9], of which the genus Mucor and Mortierella belong to. However, there

were limited studies that relate the influence of pH to microbial oil production.

118

Inoculum concentration is another factor that affects microbial growth and oil

accumulation. Spore inoculum concentration of fungi was reported to have an effect

on fungal morphology and metabolic activity [10], which subsequently could

influence oil accumulation. Despite the effect of a variety of cultivation conditions

on oil production, studies with a systematic approach to process optimisation of oil

production from filamentous fungi are limited.

Oil palm empty fruit bunch (EFB), is the lignocellulosic by-product of palm oil

processing and makes up the highest percentage of wastes generated in palm oil

mills. In this study, the cultivation of the filamentous fungus, Mucor plumbeus, on

EFB hydrolysates for oil production was optimised. M. plumbeus was shown to be

the best candidate for oil production from EFB [11]. EFB hydrolysate was prepared

through dilute acid pretreatment and enzymatic hydrolysis. Response surface

methodology (RSM) was used to optimise oil production by assessing the impact of

the parameters of cultivation (sugar concentration, yeast extract concentration, spores

concentration, and pH) on the oil concentration (g/L) and oil yield (mg oil per g

sugars consumed). Oil yield is an important response parameter for optimisation as it

measures the efficiency of converting the carbon substrates (i.e., an operating cost) to

product (i.e., a revenue) [1]. Microbial oil production was then performed in a

bioreactor system to investigate the effect of reactor operation on oil production.

Studies of cultivation in bioreactor systems are important for assessing the feasibility

and the economics of progressing to industrial scales (e.g., > 1000 L), however, there

are limited studies on microbial oil production from lignocellulosic hydrolysates in

bioreactor systems.

5.1.2 Material and methods

5.1.2.1 Materials

Oil palm EFB was provided by KKS East Mill, Sime Darby Plantation Sdn.

Bhd, Malaysia. Air-dried EFB consisted of 34.0% glucan, 17.2% xylan, 29.6%

lignin, 7.5% moisture, 6.5% ash, 14.2% water extractive and 6.3% ethanol extractive

based on compositional analysis procedure developed by U.S. National Renewable

Energy Laboratory (NREL) [12, 13].

119

Mucor plumbeus (FRR no.: 2412) strain was purchased from FRR Culture

Collection (Australia). Sporulating mycelium of fungal strain were maintained on

potato dextrose agar (PDA) at 4 °C [14].

5.1.2.2 EFB hydrolysate preparation

EFB was pretreated at 170 °C with 0.8 wt% sulfuric acid and a solid/liquid

ratio of 1:6 in 7.5 L Parr reactor (Model 4554, Parr Instrument Company, USA). The

stirring speed was 100 rpm and the reaction time was 15 min. Following

pretreatment, the liquid fraction and the solid residue were separated by filtration

using Whatman filter paper (Grade 1, Whatman, England). The solid residue was

washed with tap water twice and stored at 4 °C in a sealed container for

compositional analysis and enzymatic hydrolysis.

Enzymatic hydrolysis of the washed EFB solid residue was performed at a

glucan loading of 7% (w/w) with a cellulase dosage of 20 FPU/g glucan

(Accelerase™ 1500, Batch no: 4901298419). The pH of the mixture was adjusted to

5.0 and the mixture was then placed in a shaking incubator (OM15, Ratek, Australia)

for 72 h at 50 °C and 150 rpm. At the end of enzymatic hydrolysis, the liquid fraction

of enzymatic hydrolysis was separated by centrifugation. The supernatant was

labelled as EFB enzymatic hydrolysate (EH). EH was concentrated using a rotary

evaporator (Rotavapor, BUCHI, UK) at 60 °C. The concentrated EH consisted of

118.52 g/L glucose, 9.55 g/L xylose and 1.00 g/L arabinose. EH was used with

nutrient supplementation as the cultivation medium.

5.1.2.3 Optimisation in shake flasks

A response surface methodology (RSM) with face-centred central composite

design (CCD) was applied for optimising oil concentration (g/L) and oil yield (g oil

per g sugar consumed) from the cultivation of M. plumbeus on EFB enzymatic

hydrolysate (EH) by varying the conditions of cultivation. The parameters of

cultivation that were varied (independent variables) in this experiment were:

1. Sugar concentration of EH (g/L) (X1)

2. Relative concentration of yeast extract to sugars in EH (%, g yeast extract/g

sugar in EH) (X2)

3. Spore concentration (log spores number/mL medium) (X3)

120

4. Initial pH (X4)

The response factors (dependant variables) for optimisation were oil concentration

(g/L) (Y1) and oil yield (mg/g) (Y2). The coded and actual values of each variable and

its levels (-1 for low value and 1 for high value) for this experimental design are

shown in Table 5-1. The levels were determined based on the preliminary study

(unpublished data), where the selection of the pH level was on the basis that M.

plumbeus showed no capacity to grow at pH 4 and poor growth at pH 8 and above.

Table 5-1 The coded and actual values of each variable and its levels for the experimental design

Independent variable Unit Symbol Code level

-1 0 1

Sugar concentration Sugar g/L X1 30 65 100

Relative concentration of yeast extract

%YE %, g yeast extract/g sugar

X2 0 6.7 13.3

Spore concentration Spore log spores number/mL medium

X3 4.3 5.3 6.3

Initial pH pH X4 5.0 6.0 7.0

Each response variable was fitted to a quadratic model to correlate the

response variable to the independent variables. The experimental data obtained were

calculated and analysed through an empirical second-order polynomial function:

∑ ∑ ∑ ∑ ε (1)

where Y is the predicted response; β0 the intercept, βi the linear coefficient, βij the

quadratic coefficient, βii is the linear-by-linear interaction between xi and xj

regression coefficients, xi, xj are input variables that influence the response variable

Y, k is the number of factors and ε is the random error [15]. Analysis of variance

(ANOVA) was evaluated through statistical analysis of the model. The statistical

significance of the model terms was assessed using the p-value approach.

121

For cultivation experiments, sugar concentrations, yeast extract and spore

inoculum concentration as well as pH were used according to Table 5-1. The

cultivation media were prepared by supplementing EH with 0.4 g/L MgSO4·7H2O, 2

g/L KH2PO4, 3 mg/L MnSO4·H2O and 0.1 mg/L CuSO4·5H2O [16]. The cultivation

was performed with 30 mL working volume in 250 mL Erlenmeyer flask at 28 °C

and 200 rpm on an OM15 orbital shaking incubator (Ratek, Australia) for seven

days. Fungal biomasses were harvested by vacuum filtration and washing, followed

by biomass freeze-drying to constant weight [1].

A validation experiment was performed using experimental conditions of

optimised parameters cultivation. Control cultivation was performed using the media

preparation based on repeatedly used cultivation methods [14, 16]. The nutrients

supplementation in the control cultivation was the same as the present study. Yeast

extract concentration for the control cultivation was 1.5 g/L and the initial pH was

5.5.

5.1.2.4 Cultivation in bioreactor

The cultivation of M. plumbeus on EH was performed in a 1 L bioreactor (New

Brunswick™ BioFlo®/CelliGen® 115 Fermentor and Bioreactor, Eppendorf AG,

Germany). The cultivation was carried out at 28 °C with an initial agitation speed of

200 rpm and aeration rate of 1 vvm (volume air per working volume per minute). A

cascade control for dissolved oxygen (DO) regulation was applied to keep the DO

level higher than 20% by automated increment of agitation speed and aeration rate,

where the aeration and agitation would return to the initial rate once the DO level

reached 20% (The time-course graph for DO, pH, agitation speed and aeration rate

was shown in Appendix 3). The cultivation in the bioreactor was carried out using

EH at the same concentrations of sugar (30 g/L) and yeast extract (0 g/L), and initial

pH (pH 5.0) of optimised conditions, with a working volume of 600 mL. Samples

from the cultivation medium were observed under an Olympus BX41TF microscope

(Japan) with a Olympus DP11 Microscope Digital Camera system (Japan).

The cultivation media were inoculated with 10% (v/v) preculture media. The

preculture was prepared using EH diluted to ~15 g/L sugars with the addition of 1

g/L yeast extract and spore concentration of 6.3 log spores/mL medium (2 x 106

122

spore/mL). The cultivation of preculture was conducted at 28 °C on an OM15 orbital

shaking incubator (Ratek, Australia) for three days.

5.1.2.5 Oil extraction and analyses

Oil was extracted from the biomass based on the procedure described in

Ahmad et al. [11]. All results for oil content are reported on a dry weight (DW)

basis. For the determination of microbial oils’ fatty acids composition, fatty acid

methyl esters (FAME) analysis was carried out using a gas chromatography-mass

spectrometry (GC-MS) system based on the GC-MS method described in Ahmad et

al. [11].

Sugar concentrations (cellobiose, glucose, xylose and arabinose), organic acids

(formic acid, acetic acid and levulinic acid), furans (furfural and 5-

hydroxymethylfurfural (HMF)) and ethanol were analysed using a high-performance

liquid chromatography (HPLC) systems as described in the previous study [11].

Total nitrogen was analysed based on previous study [11]. Carbon-to-

nitrogen (C/N) ratio (g/g) was calculated using the following equation,

/ .

. (2)

where both units for concentrations of total carbon sources and nitrogen were in g/L,

0.4 (g/g) was mass fraction of carbon in the carbon sources and 0.8 (g/g) was mass

fraction of nitrogen in yeast extract. The microbial oil yield (mg/g) was calculated by

dividing the microbial oil concentration (mg/L) with the total glucose and xylose

consumed (g).

5.1.3 Results and Discussion

5.1.3.1 Optimisation of cultivation conditions by response surface methodology

(RSM)

Chemical compositions of EFB hydrolysate

The concentrations of acetic acid and 5-hydroxymethylfurfural (HMF) of EFB

enzymatic hydrolysate (EH) at different sugar concentrations are shown in Table 5-2.

Acetic acid, HMF and furfural were potential microbial growth inhibitors that

typically present in lignocellulosic hydrolysates. Furfural was not detected in the

123

hydrolysates. HMF was below the detection level in EH having a sugar concentration

of 30 g/L and 65 g/L. Therefore, the concentration of HMF was considered to be too

low to have a negative impact on the growth of M. plumbeus. Mortierella isabellina

was shown to be able to tolerate HMF at a concentration of 2.5 g/L [3]. The

concentrated EH (undiluted) consists of 0.89 g/L of nitrogen. Nitrogen may have

originated from the nitrogen-rich commercial hydrolytic enzymes [17].

Table 5-2 Concentrations of sugars, organic acids and 5-hydroxylmethylfurfural (HMF) in enzymatic hydrolysates (EHs).

Sugar concentration (g/L) of EH

Medium label

Glucose (g/L)

Xylose (g/L)

Formic acid (g/L)

Acetic acid (g/L)

HMF (g/L)

30 EH30 28.90 2.59 n. d. 1.63 n. d.

65 EH65 57.09

5.00

0.39 2.51 n. d.

100 EH100 95.06 8.23 0.51 3.56 0.06

n. d. not detected

Mathematical modelling and statistical analysis of optimisation studies

The optimisation experiment on the cultivation of M. plumbeus on EH was

performed based on the experimental design via RSM by varying four parameters of

cultivation as described in Table 5-1. The optimisation experiment consisted of the

combination of sixteen factorial points, six axial points and a centre points with five

replicates (Table 5-4) for a total twenty-six runs of shake-flask cultivation. Oil

concentration and oil yield were set as the response parameters of the optimisation

experiment.

For evaluating the responses from the experiment designed through RSM, the

suitable approximation for true functional relationship between the response (oil

concentration, Y1 and oil yield, Y2) and the independent variable (X1, X2, X3 and

X4) was determined. The approximation was determined through a mathematical

model that was acquired by fitting the linear regression model to the experimental

data [15]. A second-order model was applied for approximating the relationship

between the response and the independent variables, as shown in Figure 5-1(a). The

analysis of variance (ANOVA) of the model indicated that the model of oil

concentration and oil yield are significant (Figure 5-1(a)). Models are determined to

124

be significant if values of Prob>F value (p-value) are less than 0.0500. F-value is the

ratio of the square of mean to the residual. p-value is the smallest level of

significance that would lead to rejection of the null hypothesis [15]. For oil

concentration, model terms of X1, X2, X4, X1X3, X1X4 and X2X3 are significant

(Table 5-3(a)). For oil yield, model terms of X2, X1X2, X1X3, X1X4, X2X3, X2X4

and X3X3 are significant (Table 5-3(b)). Figure 5-1(a) also displays the value of R2

for each model, where the high values of R2 for both responses demonstrated a

relatively high correlation between the simulated values and experimental values.

The mathematical model was further assessed by plotting the predicted values

against the actual values of oil concentration and oil yield, as shown in Figure 5-1(b

and c). The plot demonstrated a good agreement for the predicted values to the actual

values for both oil concentration and oil yield. The model was also evaluated through

the plot of residuals to fitted values (Figure 5-1(d and e)). The plot revealed that the

residuals do not display any obvious pattern [15]. The undesirable pattern in the plot

is the megaphone or outward-opening funnel form, which is due to the increase of

variance as the magnitude of the predicted values increases [15]. Therefore, this

analysis demonstrated that the mathematical model is reliable and the assumptions

are satisfied [15]. The models are reliable for simulating the oil concentration and oil

yield for the cultivation of M. plumbeus on EFB hydrolysate. The results of the

predicted responses from the simulation using the mathematical models (Figure 5-

1(a)) are shown in Table 5-4. The surface plots simulated from the mathematical

models are shown in Figure 5-2 for oil concentration and Figure 5-3Figure 5-3 for oil

yield. The surface plots are useful for evaluating the influence of interaction of two

different factors to the response, which would further assist in determining the

conditions for optimum response (Section 5.1.3.3 and 5.1.3.4).

125

(a) Response Mathematical model (in terms of coded factor)

F-Value

p-value (Prob > F-value)

R2

Y1 Y1 = 2.39 + 1.66 X1 – 0.50 X2 - 0.31 X3 + 0.96 X4 - 0.39 XI X2 - 0.43 X1 X3 + 1.08 X1 X4 - 0.56 X2 X3 - 0.087 X2 X4 - 0.24 X3 X4 + 0.83 X1 X1 - 0.44 X2 X2 + 0.71 X3 X3 - 0.47 X4 X4

9.91 0.0003 0.9266

Y2 Y2 = 36.43 + 1.77 X1 – 9.53 X2 – 3.20 X3 + 4.37 X4 – 4.42 XI X2 – 6.47 X1 X3 + 10.97 X1 X4 – 7.68 X2 X3 + 4.69 X2 X4 – 2.23 X3 X4 + 7.87 X1 X1 – 6.07 X2 X2 + 12.61 X3 X3 + 1.82 X4 X4

8.32 0.0006 0.9137

(b)

(c)

(d)

(e)

0.00

2.00

4.00

6.00

8.00

0.00 5.00

Pre

dict

ed o

il co

ncen

trat

ion

(g/L

)

Actual oil concentration (g/L)

0

20

40

60

80

100

0 50 100Pre

dict

ed o

il yi

eld

(mg/

g)

Actual oil yield (mg/g)

-3.00-2.00-1.000.001.002.003.00

0.00 5.00 10.00

Inte

rnal

ly s

tude

ntis

ed

resi

dual

s

Predicted oil concentration (g/L)

-3

-2

-1

0

1

2

3

0 50 100

Inte

rnal

ly s

tude

ntis

ed

resi

dual

s

Predicted oil yield (mg/g)

126

Figure 5-1 (a) Mathematical models for oil concentration (Y1) and oil yield (Y2), and the parameters of analysis of variance (ANOVA) of each model. (b-c) Plots of

predicted vs. actual values (experimental data). (d-e) Internally studentised residuals vs actual values.

Table 5-3 Analysis of variance (ANOVA) for the response surface quadratic model of oil concentration (a) and oil yield (b) that had significant terms (Sugar

concentration - X1, Relative concentration of yeast extract - X2, Spore concentration - X3, Initial pH - X4).

(a) Source Sum of

Squares

Degree of freedom

Mean

Square

F

Value

p-value

Prob > F

Oil concentration model

79.75 14 5.70 9.91 0.0003

X1 44.25 1 44.25 77.00 < 0.0001

X2 3.35 1 3.35 5.83 0.0343

X4 10.55 1 10.55 18.36 0.0013

X1X3 2.78 1 2.78 4.84 0.0501

X1X4 16.47 1 16.47 28.67 0.0002

X2X3 4.27 1 4.27 7.44 0.0197

(b) Source Sum of

Squares

Degree of freedom

Mean

Square

F

Value

p-value

Prob > F

Oil yield model 6537.93 14 467.00 8.32 0.0006

X2 1234.40 1 1234.40 21.99 0.0007

X1X2 297.22 1 297.22 5.30 0.0419

X1X3 619.38 1 619.38 11.03 0.0068

X1X4 1688.70 1 1688.70 30.09 0.0002

X2X3 796.37 1 796.37 14.19 0.0031

X2X4 298.17 1 298.17 5.31 0.0417

X3X3 348.12 1 348.12 6.20 0.0300

127

Table 5-4 The predicted responses from the simulation of mathematical models for cultivating M. plumbeus on enzymatic hydrolysates (EHs) at different

concentrations of sugars (X1), yeast extract (X2) and spores (X3), and pH (X4). Run Independent variables Predicted value

Sugar (X1)

%YE (X2)

Spore (X3)

pH (X4) Oil concentration (g/L) (Y1)

Oil yield (mg/g) (Y2)

1 0 -1 0 0 2.01 39 2 -1 -1 -1 -1 0.63 56 3 -1 1 1 -1 1.54 50 4 1 -1 1 -1 3.72 58 5 1 -1 -1 1 7.49 78 6 1 0 0 0 5.05 47 7 0 0 0 0 2.05 36 8 0 0 0 1 2.35 40 9 0 0 1 0 2.55 47 10 1 1 1 -1 0.92 5 11 1 1 -1 -1 3.13 36 12 -1 -1 1 -1 2.60 84 13 0 0 0 0 2.05 36 14 1 -1 1 1 7.60 77 15 -1 1 -1 1 1.77 50 16 -1 1 1 1 0.38 37 17 -1 -1 -1 1 1.09 36 18 -1 0 0 0 1.57 42 19 -1 -1 1 1 1.91 53 20 0 0 0 0 2.05 36 21 1 -1 -1 -1 3.68 59 22 1 1 1 1 4.14 41 23 -1 1 -1 -1 1.82 53 24 0 0 0 0 2.05 36 25 0 0 0 0 2.05 36 26 0 0 -1 0 2.96 51 5.1.3.2 Effects of sugar concentration, yeast extract concentration, spore

concentration and pH on microbial oil production

Sugar concentration was selected as one of the parameters for optimisation in

order to assess the influence of carbon concentration on microbial oil production as

C/N ratio is one of the key factors affecting oil production. The surface analysis

indicated that sugar concentration (X1) was significant (p-value < 0.0001) to oil

128

concentration (Figure 5-2(a)). Therefore, increasing carbon (sugars) concentration

would increase the oil concentration. Higher sugar concentration leads to a higher

C/N ratio of the cultivation media, where higher a C/N ratio enhances oil

accumulation by oleaginous microorganisms [6]. The synergy of sugar concentration

with yeast extract concentration (X1X2) was significant to oil yield (p-value =

0.0419) (Figure 5-2(b)). From the surface plots of oil yield, lowering the yeast

extract concentration supplemented to the media would lead to higher oil yield at any

concentration of sugars (Figure 5-3(a)).

The yeast extract concentration was shown to be significant to both oil

concentration and oil yield (p-value = 0.0343 and p-value = 0.0007 respectively).

Lowering yeast extract concentration supplied to the cultivation media promotes the

oil production. This study revealed that fungi could grow even without yeast extract

for optimum oil production. The binary interaction of yeast extract and spore

concentration (X2X3) was significant to the oil concentration and oil yield (p-value =

0.0197 and p-value = 0.0031 respectively) (Table 5-3). The surface plots (Figure 5-

2(d) and Figure 5-3(c)) showed that at the maximum yeast extract concentration,

increasing spores inoculum concentration decreases the oil production. This is

possibly because higher yeast extract concentration provides surplus-nitrogen

condition, where this condition was known to stimulate cell proliferation [18] and

subsequently fungal biomass formation. Therefore, a higher spore inoculation to

surplus-nitrogen medium may have caused a rapid formation of biomass in the

culture, which could lead to poor oxygen-mass transfer and subsequently low oil

concentration (Figure 5-2(a, d and e)).

From the response surface analysis, pH (X4) was shown to be significant to oil

concentration (p-value = 0.0013), as well as binary interaction of pH and sugar

concentration (X1X4) (p-value = 0.0002) (Table 5-3(a)). Based on the surface plots

of the interaction between pH and sugar concentration for both oil concentration

(Figure 5-2(c)) and oil yield (Figure 5-3(b)), it can be concluded that the impact of

pH on oil concentration or oil yield varied according to the level of sugar

concentration. From Figure 5-3(b), at the minimal sugar concentration (30 g/L), a

higher oil yield could be achieved by decreasing the value of pH. However, a total

129

opposite correlation applied at maximum sugar concentration of 100 g/L, where

decreasing pH values would decrease the oil yield.

(a) (b)

(c) (d)

(e)

Figure 5-2 (a-e) Three-dimensional surface plots of binary interaction between different variables to the oil concentration. Sugar is sugar concentration, %YE is

relative concentration of yeast extract, Spore is spore concentration and pH is initial pH.

130

(a) (b)

(c) (d)

Figure 5-3 (a-d) Three-dimensional surface plots of binary interaction between different variables to the oil yield. Sugar is sugar concentration, %YE is relative concentration of yeast extract, Spore is spore concentration and pH is initial pH.

The correlation between pH and sugar concentration might be influenced by

acetic acid concentration. EH diluted to 100 g/L sugars (EH100) contains 3.56 g/L

acetic acid, three times more than that in EH30. The pKa value of acetic acid is 4.75,

which means that at pH 4.75, the concentration of the un-dissociated and dissociated

forms of acetic acid in the cultivation media were equal [19]. Acetic acid in un-

dissociated form was found to be inhibitory to microbial growth [20]. When the

medium was adjusted to pH 7.0, there would be 99% of acetic acid dissociated into

acetate anions [20], which reduces the inhibitory effect of acetic acid on

microorganisms. Therefore, pH 7.0 was more favourable for oil production on

EH100.

131

The surface analysis showed that the spore concentration (X3) did not have

significant influence on the oil concentration and oil yield (p-value = 0.1390 and p-

value = 0.1477 respectively).

5.1.3.3 Substrates consumption, microbial oil fatty acids composition and other

metabolites accumulation

The impact of different cultivation parameters on microbial growth was

analysed through the sugar consumption behaviour of M. plumbeus on EFB

enzymatic hydrolysates (EHs) (Figure 5-4). From the experimental run performed on

EH30 and EH100 (Figure 5-4(a and e)), the cultivations with the maximum yeast

extract and spore concentration resulted in complete consumption of glucose within

48 h (EH30) and 74 h (EH100), regardless of the initial pH of the media. The

cultivation with yeast extract concentration had a faster consumption rate of sugars in

comparison to the cultivation with no yeast extract supplementation for the

cultivation on EH30 and EH65 (Figure 5-4(a and c)).

The trend of sugar consumption was shown to be correlated to the

concentration of yeast extract (nitrogen concentration). The cultivation with

maximum yeast extract concentration had the fastest consumption of glucose and

xylose. As nutrient (e.g., nitrogen) depletion was shown to negatively impact cell

proliferation and carbon substrates uptake rates [21], the opposite may promote

carbon substrates consumption. Even though the cultivation with maximal yeast

extract supplementation could potentially reduce the number of days of cultivation

due to fast sugar consumption, the oil yields were low in comparison to the

cultivation with no additional yeast extract (Figure 5-3(a, b and d)).

The overall rate of glucose consumption of all cultivation runs was higher

than the consumption rate for xylose. In this study, for all cultivations, M. plumbeus

exhibited sequential sugar assimilation where xylose consumption began after the

majority of glucose was consumed in the media. The ratio of the amount of glucose

to xylose in the media was 12:1. The sequential sugar assimilation was common for

media that contained a higher proportion of glucose than xylose, where the

assimilation pattern could be due to catabolite repression by glucose or allosteric

competition for sugar transporters [22].

132

(a)

(b)

(c)

0

5

10

15

20

25

30

35

0 24 48 72 96 120 144 168

Glu

cose

con

cen

trat

ion

(g/

L)

Time (hour)

min YE, minspore, pH5max YE, minspore, pH5min YE, maxspore, pH5max YE, maxspore, pH5min YE, minspore, pH6max YE, minspore, pH7min YE, maxspore, pH7max YE, maxspore, pH7mean YE, meanspore, pH6

0

0.5

1

1.5

2

2.5

3

0 24 48 72 96 120 144 168

Xyl

ose

con

cen

trat

ion

(g/L

)

Time (h)

min YE, minspore, pH5max YE, minspore, pH5min YE, maxspore, pH5max YE, maxspore, pH5mean YE, meanspore, pH6min YE, minspore, pH6max YE, minspore, pH7min YE, maxspore, pH7max YE, maxspore, pH7

0

10

20

30

40

50

60

70

0 24 48 72 96 120 144 168

Glu

cose

con

cen

trat

ion

(g/L

)

Time (hour)

min YE,mean spore,pH5mean YE,min spore,pH5mean YE,max spore,pH6mean YE,mean spore,pH7mean YE,mean spore,pH6

133

(d)

(e)

(f)

Figure 5-4 The consumption of glucose (a) and xylose (b) for the experimental run on EH30. The consumption of glucose (c) and xylose (d) for the experimental run on

EH65. The consumption of glucose (e) and xylose (d) for the experimental run on EH100.

0

1

2

3

4

5

6

0 24 48 72 96 120 144 168

Xyl

ose

con

cen

trat

ion

(g/

L)

Time (hour)

min YE,mean spore,pH5mean YE,max spore,pH6mean YE,mean spore,pH7mean YE,mean spore,pH6mean YE,min spore,pH5

0

1

2

3

4

5

6

7

8

9

10

0 24 48 72 96 120 144 168

Xyl

ose

con

cen

trat

ion

(g/L

)

Time (h)

min YE, minspore, pH5max YE, minspore, pH5min YE, maxspore, pH5max YE, maxspore, pH5min YE, minspore, pH7min YE, maxspore, pH7max YE, maxspore, pH7mean YE, meanspore, pH6

0

1

2

3

4

5

6

7

8

9

10

0 24 48 72 96 120 144 168

Xyl

ose

con

cen

trat

ion

(g/L

)

Time (h)

min YE, minspore, pH5max YE, minspore, pH5min YE, maxspore, pH5max YE, maxspore, pH5min YE, minspore, pH7min YE, maxspore, pH7max YE, maxspore, pH7mean YE, meanspore, pH6

134

The analysis of fatty acids composition showed that the microbial oils consist

of palmitic (C16:0), stearic (C18:0), oleic (C18:1) and linoleic (C18:2) acid, which

was similar to fatty acid compositions reported for the cultivation of other oleaginous

microorganisms [11, 14, 23].

Ethanol was detected in some of the cultivation runs (Table 5-5). Ethanol

accumulation in the cultivation with higher sugar concentrations showed that M.

plumbeus did not possess strict aerobic metabolism. Some Mucor species (e.g.,

Mucor indicus) were utilised for ethanol production from acid hydrolysates of rice

straw and spruce forest residues [24]. In this study, ethanol accumulation was

prevalent in the cultivation with high sugar concentration (~100 g/L). High carbon

substrates loading caused a rapid growth of biomass that could lead to an increase in

the viscosity of the culture and further reduce the efficiency of oxygen-mass transfer

inside the fungal biomass. This phenomenon could result in carbon assimilation

under limiting-oxygen conditions which then led to the production of ethanol.

Ethanol was accumulated most likely at the expense of carbon-to-oil conversion

efficiency, where cultivation with ethanol accumulation of more than 20 g/L

obtained low oil yields (5 mg/g for Run #10 and 36 mg/g for Run #11) (Table 5-5).

The cultivation on EH100 also resulted in higher ethanol yields than oil yields (Table

5-5). Even though ethanol is a valuable co-product, the ethanol yields were too low

in comparison to the theoretical ethanol yield (514 mg/g glucose), where the process

of ethanol recovery could lead to unfavourable economics for the overall cost of

production.

135

Table 5-5 The concentration of ethanol accumulated at the end of the cultivation and ethanol yields per sugars consumed for various enzymatic hydrolysates (EH30,

EH at 30 g/L sugars; EH65, EH at 65 g/L sugars; EH100, EH at 100 g/L sugars). Hydrolysate Run Condition Ethanol

concentra-tion (g/L)

Ethanol yield (mg/g)

Oil yield (mg/g)

EH30 2 Min YE, min spore, pH5 2.99 150 56

23 Max YE, min spore, pH5 0.86 34 53

12 Min YE, max spore, pH5 1.41 62 84

3 Max YE, max spore, pH5 0 0 50

17 Min YE, min spore, pH7 2 67 36

15 Max YE, min spore, pH7 0 0 50

19 Min YE, mean spore, pH7

1.02 35 53

16 Max YE, max spore, pH7 0 0 37

18 Mean YE, mean spore, pH6

1.36 44 42

EH65 1 Min YE, mean spore, pH6

6.66 132 39

26 Mean YE, min spore, pH6

7.88 139 51

9 Mean YE, max spore, pH6

1.92 35 47

8 Mean YE, mean spore, pH7

6.65 115 40

Centre points

Mean YE, mean spore, pH6

8.33 169 36

EH100 21 Min YE, min spore, pH5 11.23 237 59

11 Max YE, min spore, pH5 27.66 268 36

4 Min YE, max spore, pH5 5.28 73 58

10 Max YE, max spore, pH5 25.84 250 5

5 Min YE, min spore, pH7 12.55 131 78

14 Min YE, max spore, pH7 13.83 135 77

22 Max YE, max spore, pH7 6.17 62 41

6 Mean YE, mean spore, pH6

13.04 129 47

136

5.1.3.4 Validating optimisation parameters for oil production from EFB

hydrolysates (EH) by M. plumbeus

The main criteria for finding optimum parameters for oil production are high

oil yield and high oil concentration. The cultivation with maximum sugars (100 g/L)

at pH 7.0 with no additional yeast extract was predicted to give the highest oil

concentrations (7.6 g/L), with predicted oil yield at ~77 mg/g (Table 5-4, Run #14).

The cultivation with minimum sugar concentration and maximum spore

concentration at pH 5.0 without additional yeast extract was predicted to result in the

highest oil yield at 84 mg/g (Table 5-4, Run #12). However, the cultivation run at the

maximum sugar concentration led to the accumulation of more than 5 g/L ethanol

with ethanol yields of more than 50 mg per g sugars consumed (Table 5-5). The

cultivation at 100 g/L also resulted in rapid formation of biomass in high volume

which was a potential challenge for cultivation in the bioreactor. Therefore, the

parameters for optimisation were selected at 30 g/L sugar concentration, pH 5.0 with

spore concentration at 6.3 log spores number/mL medium, without additional yeast

extract. The optimised parameters were predicted to result in an oil concentration of

2.60 g/L and 84 mg/g of oil yield.

The validation experiment resulted in the production of 11.6 g/L biomass and

2.67 g/L oil (oil content of 23.1%), with an oil yield of 94 mg/g. The relative

amounts of sugars consumed from EH after seven days cultivation were 86% of

glucose and 38% of xylose, respectively. The analysis on the fatty acids of microbial

oil from the optimised cultivation revealed that the microbial oil consists of 18.9%

palmitic, 31.0% stearic, 34.7% oleic and 15.5% linoleic acids, which is similar to

fatty acid compositions of M. plumbeus grown in EFB hydrolysates in our previous

study [11]. The predominant fatty acids found in the microbial oil were also similar

to the fatty acid compositions of vegetable oils that has potential for biodiesel

production [25].

137

The cultivation of the control, performed on EH at optimised sugar

concentration (30 g/L), resulted in the production of 13.2 g/L biomass and 2.13 g/L

oil with 16.2% oil content and 52 mg/g oil yield. The resulting oil concentration and

oil yield from the control were lower than those of the optimised cultivation.

However, both glucose and xylose in the cultivation medium of control were

consumed completely by the end of cultivation. The cultivation medium of control

contains a higher nitrogen content and lower C/N ratio than the optimised culture.

The higher nitrogen content may have contributed to a better consumption of the

carbon sources in the comparison study, as sufficient nitrogen supply promotes cell

proliferation. Even with high sugar consumption rates in the comparative study, the

efficiency of carbon substrates conversion into oil was lower than the optimised

cultivation. It is noted that higher sugar consumption rates did not necessarily lead to

a higher oil yield, which provided further evidence on the impact of nitrogen

concentration on oil production as discussed in Section 5.1.3.3.

5.1.3.5 Microbial oil production in bioreactor

The cultivation of M. plumbeus on EH was subsequently performed in a

bioreactor, based on the optimised conditions, to investigate the impact of the

bioreactor system on microbial oil production as well as the prospective of process

scale-up. Figure 5-5(a) shows gradual consumption of sugars throughout the

cultivation. The pH increased slightly at the beginning of the cultivation, but dropped

gradually after 24 h, and reached pH 5.0 at the end of the cultivation. The DO level

was reduced sharply within the first 24 hours as glucose was consumed rapidly at

this phase of the cultivation (Figure 5-5(b)). Due to DO control in the bioreactor

system, the DO level was maintained at 20% by increasing the agitation speed from

its initial speed at 200 rpm (minimum setpoint) to 335 rpm (maximum setpoint) by

41 h. The agitation speed was reduced afterward to the original speed at 200 rpm,

corresponding to the raising DO level, and remained at 200 rpm until the end of

cultivation.

For the first two days of the cultivation, fungal biomass only grew in pellets.

The transition in fungal morphology in the bioreactor became apparent after three

days of cultivation with the appearance of dispersed mycelia mixed with fungal

pellets (Figure 5-6). The transition in morphology, from pellet-only biomass to

138

mixture of pellet and dispersed mycelia, was most likely attributed to the high

agitation speed. Filamentous fungus Mortierella isabellina in dispersed mycelial

form was reported to obtain a higher oil yield and oil content in comparison to fungi

in pellet form [5]. This is because mycelia aggregates possibly had better oxygen and

nutrient intake due to lower biomass density and smaller radius [5]. One of the

challenges of scaling up fungal cultivation is the tendency of fungal biomass in

bioreactor to aggregates and grow on the wall (Figure 5-6(d)) and the sensor probes

of bioreactor [24].

(a)

(b)

Figure 5-5 (a) The consumption of glucose and xylose for bioreactor cultivation on actual enzymatic hydrolysate (EH) of EFB, in comparison to the shake flask

validation run. (b) The trends of dissolved oxygen (DO) and pH level throughout the cultivation, as well as percentage of sugar consumption for the bioreactor cultivation.

In comparison to the shake-flask cultivation, the growth of M. plumbeus on EH

in a bioreactor showed an improvement in the oil concentration and the oil yield

(Table 5-6). Even at a similar C/N ratio, the cultivation in the bioreactor resulted in

0

5

10

15

20

25

30

35

40

0 24 48 72 96 120 144 168

Con

cen

trat

ion

(g/

L)

Time (h)

GlucoseXyloseGlucose in validation runXylose in validation run

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

0

20

40

60

80

100

120

0 24 48 72 96 120 144 168

pH

Rel

ativ

e C

once

ntr

atio

n (

%)

Time (h)

% SugarconsumedDO

pH

Cascade control applied from beginning

139

much higher oil concentration and oil yield. The enhanced oil production was

possibly attributed to enhanced oxygen supply because of better agitation and

aeration in the culture relative to the cultivation in the shake flask. The transition in

fungal morphology was one of the possible factors of the increased oil production.

The sugar consumption of the cultivation in the bioreactor was similar to the shake-

flask cultivation under a similar C/N ratio, as discussed previously, that the nitrogen

content of media might play role in sugar consumption.

Figure 5-6 Fungal

morphology from the bioreactor cultivation on actual enzymatic hydrolysate (EH). (a, c and e) Microscopic images

(fluorescence) at magnification of 100x. (b and f) Microscopic images (bright field) at magnification of 200x. (d) Bioreactor at 41 h of cultivation.

Table 5-6 showed the comparison between the bioreactor cultivation of M.

plumbeus on EH to other bioreactor cultivation of oleaginous yeasts and fungi on

various lignocellulosic hydrolysates. The oil concentration (5.3 g/L) and oil yield

(168 mg/g) from the bioreactor cultivation on EH were comparable to the results of

bioreactor cultivations from other studies such as oil production from corn stover by

0 h

(a) (b)

41 h

(c) (d)

94 h

(e) (f)

140

M. isabellina (6.9 g/L oil) and from rice straw by Rhodotorula glutinis (6.9 g/L oil)

[23, 26]. The results of oil concentration produced from corn stover by Rhodotorula

graminis was much higher than the oil concertation obtained in this study, possibly

due to higher sugar concentration in corn stover hydrolysate [27]. However, the oil

yield in this study was higher than that obtained from the cultivation on corn stover

hydrolysate (89 mg/g). The study of cultivation of Rhodotorula glutinis on rice straw

hydrolysates in an airlift bioreactor by Yen et al. obtained higher oil concentration

than the present study at 6.9 g/L, possibly due to the higher C/N ratio as the oil

concentration was similar to the results of the cultivation M. isabellina at C/N ratio

of 91 [23]. Even though the oil concentration was higher in Yen et al., the oil yield

was comparable to this study.

The outcome of the bioreactor cultivation study demonstrated the potential of

scaling-up of M. plumbeus for large-scale microbial oil production from EFB

hydrolysates without the addition of a nitrogen source such as yeast extract. The

improved yield of microbial oil converted from palm oil processing wastes (i.e.,

EFB) through bioreactor cultivation, without an additional nitrogen source could

potentially improve the economics of large-scale microbial oil production. Therefore,

the microbial oil production process from EFB was promising for commercialisation

of biodiesel production.

Table 5-6 Results of different cultivation performed in this study and the comparison with other batch cultivation of oleaginous yeasts and fungi from

the literature. Feedstock (hydro-lysate)

Reactor type

Strains Glucose (g/L)

Xylose (g/L)

C/N ratio

Oil (g/L)

Oil yield (mg/g)

Refe-rence

EFB residue

Shake-flask

Mucor plumbeus

31.2 3.7 62 2.7 94 This study

EFB residue

Stirred-tank bioreactor

Mucor plumbeus

33.6 2.8 65 5.3 168 This study

Corn stover residue

Stirred-tank bioreactor

Mortierella isabellina

28.6 16.1 91 6.9 147 [23]

Corncob stover

Stirred-tank bioreactor

Rhodotorula graminis

126.0 87.1 n/n 16.3 89 a [27]

Rice straw Airlift bioreactor

Rhodotorula glutinis

23.9 6.1 n/a 6.9 170 [26]

n/a Not available a Data was not provided

141

5.1.3.6 Biodiesel production from EFB

The fatty acids composition of oil from the bioreactor cultivation on EFB

hydrolysate were 15.6% palmitic, 15.9% stearic, 21.1% oleic and 47.4% linoleic

acid, which was different to the oil produced from the shake-flask cultivation. The

higher composition of unsaturated fatty acids in the bioreactor cultivation could be

due to higher oxygen availability in the bioreactor that led to the formation of

unsaturated fatty acids through the aerobic desaturase/elongase pathway [28].

The fatty acids compositions were further used to evaluate the fuel properties

of microbial oil via empirical calculation. The fuel properties were analysed based on

the assessment of fatty acid methyl ester (FAME) as described in Ahmad et al. [29].

The results showed that the oil has a cetane number of 57.11, iodine value of 99.95

and kinematic viscosity of 4.34 mm2/s which is within the limit set by the European

standard for FAME of EN 14214 (>51 for cetane number, <120 for iodine value and

3.5 to 5.0 mm2/s for kinematic viscosity). Therefore, microbial oil from EFB was a

promising source for good quality biodiesel production.

The production cost of biodiesel production from EFB was calculated based on

Koutinas et al. for biodiesel production from pure glucose through microbial

cultivation, oil extraction and transesterification (Table 5-7) [30]. For the production

of 10,000 t biodiesel from EFB, based on the oil yield of 0.168 g/g sugars and the

conversion rate of oil to biodiesel of 90%, it was estimated that 66138 t of sugars

from EFB was required. The cost of sugars production from EFB was estimated to be

at $256/t based on the selling price of diluted sugars from lignocellulosic biomass

[14, 31].

142

Table 5-7 The comparison of raw materials cost (RMC) (a), production cost (b) and cost of biodiesel (c) for the production of biodiesel from EFB and glucose based on Koutinas et al. for the production of 10,000 t/year biodiesel [30].

(a) Process Raw material Quantity

(t/y)

Unit cost

($/t)

Total cost

($ million/y)

Cultivation RMC on

pure glucose

Glucose 42081 400 16.833

Yeast extract 4370 800 3.495

Total 20.328

Cultivation RMC on

EFB

EFB sugar 66138 256 16.931

Yeast extract 0 0 0

Total 16.931

Extraction & transesterification RMC (hexane, methanol, NaOH and HCl) 0.905

RMC for glucose a 21.233

RMC for EFB a 17.836

(b) Cost item Total cost

($ million/y)

Fixed capital investment (FCI) 73.65

Operating labour cost (OLC) 1.005

Utility cost (UC) 7.563

Production cost for glucose bc 58.895

Production cost for EFB bc 53.604

143

(c) Feedstock Cost of biodiesel

($/t)

Glucose 5900

EFB 5360

Theoretical EFB (at theoretical oil yield) d 4483

a RMC = Cultivation RMC + Extraction & transesterification RMC

b Assuming Wastewater treatment cost (WTC) = 0

c Operating cost = 0.28FCI + 2.73OLC + 1.23 (RMC + UC + WTC)

d Theoretical FB sugars = 34722 t/year, oil yield = 0.32 g/g glucose

The raw material cost (RMC) for biodiesel production was calculated as the

total cost for cultivation (carbon substrates and yeast extract), extraction and

transesterification (Table 5-7(a)). RMC for EFB from glucose, for the production of

10,000 t/year biodiesel, was evaluated to be at $21.23 million [30]. RMC for EFB

biodiesel was estimated to be lower at $17.84 million, due to the use of cheaper

lignocellulosic sugars and no additional yeast extract in the cultivation. Table 5-7(b)

presents the components of production cost based on the calculation of cost of

manufacturing for glucose biodiesel [30]. Assuming that the utilities cost and

operating labour cost for the cultivation of EFB sugars for the production of

microbial oil were similar to the production of microbial oil from glucose, the cost of

EFB biodiesel production was estimated to be $5360/t biodiesel. The cost of

production for EFB biodiesel was estimated to be 9% lower than that for glucose

biodiesel. The cost of production could be reduced with an improved oil yield

through optimising cultivation in the bioreactor, as shown in Table 5-7(c), where the

cost for EFB biodiesel at the theoretical oil yield (0.32 g/g glucose [6]) (theoretical

EFB feedstock) was 24% lower than glucose biodiesel. The cost of biodiesel

production from microbial oil is still higher than vegetable oil-derived biodiesel at

$1318/t [30]. However, the production of first generation biodiesel from vegetable

oils can cause an adverse impact on global food security. The global food price from

2010 was forecasted to climb up by 47 % in 2040, based on annual growth rate of

first-generation biofuels production at 2.7% (as predicted by U.S. EIA) [32]. The

analysis of 2013 global first-generation biodiesel consumption revealed that the

calorie content from the oil crop could be equivalent to the calorie requirement to

144

feed 70 million people [33]. In addition, there is limited global agricultural land to

support the current demand from food and fuel markets [33]. The production of

microbial oil-derived biodiesel could be economically viable through implementation

of an energy policy which limits the use of food-based feedstock, technology

advancement for reducing the cost of microbial cultivation (e.g., consolidated

bioprocessing) and biorefinery integration.

5.1.4 Conclusion

The optimisation of oil production from EFB hydrolysate by Mucor plumbeus

was performed using response surface methodology by evaluating the impact of

cultivation parameters on oil concentration and oil yield. The analysis showed that

increasing sugar concentration resulted in an increased oil concentration and

decreasing yeast extract concentration led to an increased oil yield. However, the

cultivation at high sugar concentration (~100 g/L) resulted in ethanol production,

which subsequently led to lower oil yields. The optimum conditions were identified

and utilised for the cultivation in 1 L bioreactor, which resulted in an increase of the

oil yield in comparison to shake-flask cultivation. The microbial oils produced have

potential to be used for biodiesel production.

5.1.5 Acknowledgement

The authors acknowledge Ministry of Higher Education Malaysia for the

postgraduate scholarship of Farah B. Ahmad. The authors thank Mr Mohan

Sivasubramaniam from KKS East Mill for the supply of EFB. The authors also thank

the QUT Banyo Pilot Plant and the QUT Central Analytical Research Facility for its

support on sample preparation and analyses.

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Conclusion

6.1 Discussion

This chapter reviews the key findings and outcomes of the research. The

overall objective of this research project was to develop and optimise a process for

microbial oil production from EFB. In order to achieve the research aims, the work

was undertaken in three phases including the selection of microorganisms (Phase 1),

evaluation of microbial oil production from hydrolysates of EFB (Phase 2) and

optimisation of microbial oil production from EFB hydrolysate (Phase 3). The key

outcomes for each research aim are shown in the following sections.

Research aim 1: To develop a method for identifying high potential strains through

cultivation on pure sugar substrates and multi-criteria analysis.

In Phase 1, six potential microorganisms from different groups (i.e.,

microalgae, yeasts and fungi) were evaluated for microbial oil production. To

develop and demonstrate a new criteria-based selection approach, these

microorganisms were cultivated on glucose, xylose and glycerol. The development

of a robust selection method is important as the majority of previous studies only

focused on the use of glucose as the carbon substrate. The criteria for evaluating the

microorganisms were oil concentration, content and yield, substrate consumption

rate, fatty acids composition, biomass harvesting and nutrient costs. Glycerol served

as an indicator of the opportunity of biorefinery application in oil production from

EFB as glycerol is the primary by-product of biodiesel production, but it had a lower

degree of significance to the selection criteria. As the selection criteria were dynamic

and complex, an MCA approach using AHP and PROMETHEE-GAIA was applied

in order to rank and select the most suitable microorganisms for oil production from

lignocellulosic hydrolysates. The microorganisms ranking based on PROMETHEE

were (1) A. oryzae, (2) M. plumbeus, (3) R. mucilaginosa, (4) C. protothecoides, (5)

C. albidus and (6) C. zofingiensis. This method allowed the direct comparison of

different groups of microorganisms for oil production. The outcome of this study

demonstrates the variation in performance and limitations of microorganism to

produce oil from lignocellulosic hydrolysates. The six potential microorganisms

150

were down-selected based on the MCA ranking. The top three highest ranking

microorganisms were then used in the next phase of the study.

Research aim 2: To screen high ranking strains through cultivation on EFB

hydrolysates and select a prospective candidate for oil production from EFB

hydrolysates.

In Phase 2, EFB hydrolysates from dilute acid pretreatment (EFBLH) and

from enzymatic hydrolysis of the solid residue (EFBEH) were used as feedstocks for

oil production. Evaluation of oil production from EFB was performed using fungi A.

oryzae and M. plumbeus, and yeast R. mucilaginosa. This study is significant as it

evaluated microbial oil production from EFB hydrolysates of dilute acid pretreatment

and enzymatic hydrolysis of solid residue. This study reveals the challenges and

potential advantages of using EFBLH, due to the presence of inhibitory compounds

which include acetic acid, HMF and furfural. However, A. oryzae and M. plumbeus

were shown to be able to assimilate acetic acid for growth. The consumption profiles

revealed sequential-sugar consumption in hydrolysates, as glucose in EFBEH and

EFBLH were completely consumed by the end of cultivation but there was a small

amount of residual xylose. The fuel properties assessment of the oils demonstrates

that TAG from these microbial oils were suitable for the production of biodiesel.

This study resulted in M. plumbeus having the highest oil concentrations and oil

yields on both EFB hydrolysates. Therefore M. plumbeus was selected as the

prospective microorganism for oil production from EFB hydrolysates.

Research aim 3: To assess the potential viability of microbial oil production from

EFB through techno-economic evaluation.

The data from the cultivation of M. plumbeus on EFB hydrolysates was used

for the techno-economic evaluation of oil production from EFB and oil palm

biomasses (trunk (OPT) and frond (OPF)). This evaluation is important as there are

no reported techno-economic assessments on the production of microbial oil from oil

palm biomass. The techno-economic evaluation estimated that EFB, OPT and OPF

could potentially increase oil production in the palm oil industry by 25%. EFB and

OPT were estimated to provide lower feedstock cost for oil production in comparison

to the feedstock cost for crude palm oil production. This study developed a concept

151

for the proposed integration of microbial oil from oil palm biomass with existing

palm oil processing facilities.

Research aim 4: To optimise cultivation conditions on EFB hydrolysates and explore

the potential for bioreactor scale up.

The microbial oil production from EFB hydrolysate by M. plumbeus was

further optimised through evaluating the impact of different cultivation factors (i.e.,

carbon concentration, nitrogen concentration, spore concentration and pH) on oil

concentration and oil yield. The optimisation study, designed by response surface

methodology, revealed that a high sugar concentration (carbon sources) in the

hydrolysates promoted higher oil concentration, and lower yeast extract

concentration (nitrogen source) led to a higher oil yield. However, it had been

discovered that hydrolysate with a high sugar concentration (~100 g/L) also resulted

in the accumulation of ethanol. The ethanol accumulation problem was most likely

caused by the rapid formation of biomass that might lead to oxygen-limiting

condition in the culture. The optimum pH was found to be dependent on the sugar

concentration of the hydrolysates, which could be due to the different level of acetic

acid in the hydrolysates. It was found that no additional yeast extract was required in

the optimised cultivation conditions, which potentially could reduce the operating

cost of the microbial oil production. The optimised condition was then applied for

the cultivation on EFB hydrolysate in 1 L bioreactor. The cultivation in bioreactor is

important as the preliminary steps for large scale microbial oil production. The

cultivation in the bioreactor resulted in an improved oil yield, possibly due to better

mixing that subsequently enhanced the mass-oxygen transfer. The morphology

development of fungi in the bioreactor (from pellets to a mixture of pellets and free

disperse mycelia) could be one of the factors for the improved oil yield.

6.2 Future work

The outcome of this research has the potential to be further developed in the

following areas:

1. Cultivation of M. plumbeus on EFB hydrolysates in larger-scale bioreactor

for potential of scaling up microbial oil production from EFB. Further

investigation is necessary in optimising physical parameters in bioreactor

152

systems and the morphology control at larger-scale cultivation, prior to

scaling up.

2. Microbial oil production from OPT and OPF by M. plumbeus, to the

demonstrate potential of increasing the oil yield for microbial oil production

within the palm oil industry and to develop a value-adding process to oil palm

biomasses.

3. Detailed techno-economic assessment of the production process of microbial

oil from EFB to demonstrate the viability of the microbial oil production at

scale. The method used in the techno-economic evaluation performed in this

research can be used for further assessment on the economic analysis of the

process.

4. Cultivation of M. plumbeus on crude glycerol in the bioreactor, to assess

potential for reutilising by-products of biodiesel, derived from microbial oil,

in biorefinery approach.

5. Cultivation of M. plumbeus on hydrolysates of sugarcane bagasse or other

lignocellulosic biomass in bioreactor, to assess potential large-scale microbial

oil production from other agro-industrial wastes.

6. Application of microbial oil for chemicals applications such as polyurethane

production, that may contribute to biorefinery development in microbial oil

production.

7. Application of fungal biomass after extraction of oil in the following

applications: chitin, animal feed, biogas. The development of reutilisation of

processed fungal biomass may also contribute to biorefinery development in

microbial oil production.

6.3 Conclusion

Overall, this study demonstrated that EFB is a promising feedstock for

microbial oil production. The oil produced from EFB can be utilised for biodiesel

153

production. The integration of microbial oil production from oil palm biomass to the

existing palm oil processing facilities could improve the profitability and

sustainability of palm oil industry.

Appendices

II

III

Appendix 1: Optimising microbial oil extraction by Accelerated Solvent Extraction

Optimising extraction of microalgal oil using Accelerated Solvent

Extraction by response surface methodology

Farah B. Ahmad*, Zhanying Zhang, William O. S. Doherty, Ian M. O’Hara

Centre for Tropical Crops and Biocommodities, Queensland University of

Technology, Brisbane, Australia

*Corresponding Author: farah.ahmad@hdr.qut.edu.au

Abstract

The extraction of oil from biomass is one of the most important aspects in the

harvesting of microalgae for the production of oil. Efficient extraction technique is

important for the quantification of oil content in biomass. Solvent extraction is

typically employed for the extraction of oil. Accelerated Solvent Extraction (ASE) is

an automated pressurised liquid extraction technique that provides rapid and

effective extraction process. There are limited studies on the effects of extraction

conditions using the ASE technique to achieve optimum oil yield. The aim of this

study was to optimise the extraction of oil using the ASE technique by response

surface methodology. A face-centred central composite design (CCD) was used to

evaluate the effects of static cycle (1 to 6 cycles), static time (2 to 10 min) and

temperature (100 to 160 °C) on oil extraction. The optimum condition was found to

be at 4 static cycles, static time of 6 min and temperature of 160 °C, with an oil yield

of 34.9%. From the ANOVA results, R2 of the mathematical model is 0.9970. This

study showed an improvement in the oil yield using the optimum condition for ASE,

where the optimum condition resulted in 1.34 fold increases in oil yield from the

control run.

Keywords: Accelerated Solvent Extraction (ASE), Microalgae, Oil, Lipid, Response

Surface Methodology

IV

V

Statement of Contribution

The authors listed below have certified that:

1. they meet the criteria for authorship in that they have participated in the

conception, execution, or interpretation, of at least that part of the publication in their

field of expertise;

2. they take public responsibility for their part of the publication, except for the

responsible author who accepts overall responsibility for the publication;

3. there are no other authors of the publication according to these criteria;

4. potential conflicts of interest have been disclosed to (a) granting bodies, (b) the

editor or publisher of journals or other publications, and (c) the head of the

responsible academic unit, and

5. they agree to the use of the publication in the student’s thesis and its publication

on the Australasian Research Online database consistent with any limitations set by

publisher requirements.

In the case of this article:

Optimising extraction of microalgal oil using Accelerated Solvent Extraction by

response surface methodology. Accepted with modification for publication in Journal

of Engineering Science and Technology.

Contributor Statement of contribution

Farah B. Ahmad The author contributed to initial

experimental design; conducted

experiment, analysis and data

interpretation; and wrote the first draft of

manuscript and subsequent revisions of

the manuscripts.

Signature

Date

08/06/2016

Zhanying Zhang This author provided valuable assistance

in data interpretation and reviewed the

VI

manuscript.

William O. S. Doherty This author contributed to data

interpretation and provided valuable

input in reviewing the manuscript.

Ian M. O’Hara This author supervised overall

experimental design, analysis, data

interpretation, and edited the manuscript

draft.

Principal Supervisor Confirmation

I have sighted email or other correspondence from all Co-authors confirming their

certifying authorship.

Name

Ian O’Hara

Signature

Date

Nomenclatures v/v Volume per volume w/w Weight per weight (g/g) X1 ASE static cycles X2 ASE static time (min) X3 ASE operating temperature ( ) Y Response variable of quadratic model xi Input variable of quadratic model xj Input variable of quadratic model k Number of factors of quadratic model Greek Symbols β0 Intercept of quadratic model βi Linear coefficient of quadratic model βij Quadratic coefficient of quadratic model

VII

βii Linear-by-linear interaction between xi and xj regression coefficients of quadratic model

ε Random error of quadratic model Abbreviations ASE Accelerated Solvent Extraction CCD Central composite design DE Diatomaceous earth FAME Fatty acid methyl ester PLE Pressurised liquid extraction RSM Response Surface Methodology

1 Introduction

Lipid or microbial oil shows great promise for second generation biodiesel

production. Microbial oil is an alternative to the conventional feedstock used for

biodiesel production, which are plant oils such as soybean oil (edible oil) or Jatropha

oil (inedible oil). It is more advantageous to use microbial oil than plant oils for

biodiesel production due to several factors such as less labour intensive to cultivate,

has short life cycle, is easy to scale up and has no seasonal and climate requirement

[1]. Oleaginous microorganisms are microorganisms (eg., microalgae, yeasts and

fungi) that are able to accumulate more than 20% lipids within the cells [2].

Oleaginous microalgae, yeasts and fungi have been reported to be able to produce oil

from the cultivation on various carbon sources, including industrial and agricultural

wastes [3].

The extraction process is a crucial step in harvesting microalgae from the

culture for oil production in order to ensure maximum yield of desired product from

microalgae biomass. Solvent extraction is the conventional technique for the

extraction of oil or lipid from biomass. The three most commonly used solvent

extraction techniques for extracting oil from microbial biomass are the Bligh-Dyer,

Folch and Soxhlet extraction techniques [4-6]. However, these extraction methods

are usually multi-step procedures and use large amount of solvents for extended

periods of time [7, 8]. For instance, Soxhlet extraction requires longer extraction time

(8 h) [4], due to slow diffusion and desorption of desired extracts from the sample

matrix to the extraction solvents [9]. Folch technique involves two-steps extraction

method, which is extraction followed by purification using water [6].

Pressurised liquid extraction (PLE), or known as Accelerated Solvent

Extraction (ASE) is an alternative solvent extraction technique which involves

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extraction at elevated temperatures under high pressures. ASE is an automated

technique consists of stainless-steel cells that hold the samples for liquid extraction at

the set up temperature [8]. Temperature, pressure and solvent delivery were

electronically controlled by heaters and pumps [8]. In ASE, the high pressure can be

used in order to keep the solvents in liquid state at temperatures above their boiling

points [10]. The application of higher pressures improves extraction efficiency as the

pressure helps diffuse the solvents into desired extracts trapped within the matrix

pores of the biomass [10]. Therefore, the mechanical pretreatment may not be

necessary prior to the extraction by ASE, unlike the conventional extraction

techniques.

In addition, ASE is more advantageous than conventional extraction

techniques as it allows higher number of samples loading and uses less amount of

solvent with shorter extraction time [5-7]. It has been reported that extraction of

persistent organic pollutants (POPs) from soils and sediments using PLE required

only 20 min of extraction time and 10 times less solvent than Soxhlet extraction [8].

ASE also has health and safety benefits, as it reduces the potential for contact with

chemical solvents. Studies showed that the extraction using ASE resulted either in

increased or comparable amounts of oil in comparison to conventional extraction

techniques [11, 12]. A study on oil extraction from algae biomass showed that a

higher amount of oil was obtained using ASE technique than the Folch method,

where the solvents used for both methods were chloroform/methanol (2:1, v/v) [11].

Higher total fatty acids yields were achieved from the extraction of cereal, egg yolk

and chicken breast muscle samples using ASE than a modified Folch method with

the use of isopropanol/hexane (2:3, v/v) for both methods [12].

Previous studies have shown that solvent types and temperature affected oil

yields in ASE [11-13]. The extraction of oil from the algae biomass showed higher

fatty acid yields were obtained with the use of chloroform/methanol (2:1, v/v)

compared to the use of isopropanol/hexane (2:3, v/v) and hexane [11]. The

combination of non-polar and polar solvent (such as chloroform/methanol) was

shown to be more effective for extracting neutral lipid (i. e., microbial oil) from

microbial biomass, in comparison to the use of non-polar solvent (such as hexane)

alone [14]. Another extraction study on dry microalgae biomass using ASE reported

on the effect of temperature to the oil yield where the study demonstrated that

IX

slightly higher amounts of total fatty acid methyl esters (FAMEs) were obtained at

120 °C compared to 110 °C, and significantly higher FAMEs at 120 °C compared to

temperatures below 100 °C [15]. Despite these reports, there is no systematic study

on optimisation of ASE from microbial biomass that correlates the important

extraction parameters such as temperature, the number of process cycles and the

process time to the oil yields.

The aim of this study was to optimise the extraction of microbial oil from

microalgae Chlorella protothecoides using ASE technique by response surface

methodology (RSM). The parameters for determining optimum oil yield were the

number of static cycles, static time (min) and temperature (°C), with oil yield (%,

w/w) as the response parameter. The optimisation study was conducted through the

experimental design, experimental run using microalgal biomass and experimental

data analysis for the development of a mathematical model.

2 Experimental Procedures

2.1 Microbial biomass preparation

Chlorella protothecoides ATCC® 30581 (ATCC, USA) was used in this study.

Microalgae was maintained in a growth chamber with light intensity from 38 - 47

μmol/m2/s at 25 °C under a 14 hour light/10 hour dark cycle. Microalgae were

subcultured in modified Medium 847 as described in the Product Information Sheet

for ATCC® 30581™. The cultivation conditions were similar to inoculum

preparation and microalgae cultivation described previously [16], with 10% (v/v)

inoculum was used. Microbial biomass was harvested by centrifugation at 6805 X g

for 7 min followed by freeze-drying [16].

2.2 Extraction of oil from microalgal biomass using ASE

Dionex ASE 350 (Thermo Fisher Scientific Inc., USA) was used for extraction

of oil from microalgal biomass. The biomass samples were prepared by mixing dry

microalgal biomass (0.25 g) with 4 g of ASE Prep DE (diatomaceous earth) (Thermo

Fisher Scientific Inc., USA) before being loaded into 33 mL cells [11]. The detailed

extraction process in Dionex ASE 350 is illustrated in Figure 1. A static extraction in

the cell commences after solvent filling followed by cell heating, up until before the

X

cell is rinsed with fresh solvents. Static time is the period where static extraction

occurs, and static cycle is the number of times where static extraction occurs.

The extraction conditions were as follows for the control run and RSM

experimental run: rinse volume, 50% of cell volume; purge time, 60 s; with varying

static cycles, temperature and static time using chloroform/methanol (2:1, v/v) as the

extraction solvents. The control run was performed based on the optimised condition

reported in previous study (ASE with 4 static cycles, static time of 120 and

temperature of 5 min) [11]. The extracted oil was collected in pre-weighed collection

bottles. Solvent was later evaporated under a stream of nitrogen. Oil yield (%, w/w)

was calculated as follows,

Oilyield %, /

x100% (1)

2.3 Design of experiment by response surface methodology (RSM)

A response surface methodology (RSM) with face-centred central composite

design (CCD) was applied for designing the experiments of optimising oil yield from

the extraction of microalgae biomass by ASE. The parameters (independent

variables) selected for optimising the oil yield by ASE are static cycles, static time

and temperature. Design of experiments, mathematical modelling and optimisation of

process parameters were performed using the Design Expert 7 Trial version software

package (Stat-Ease Inc., USA). The independent parameters used in this study were

static cycles (X1), static time (min) (X2) and temperature (°C) (X3). The response

factor (dependant variable) for optimisation was oil yield (%) (Y). The coded levels

for parameters, -1 and 1, indicate the limits of each factor, where the actual values of

each factor and its levels for this experimental design are shown in Table 1. The

range of the factor was based on the preliminary study performed previously [17]. A

total of 12 experimental runs were conducted in random with 4 factorial points, 6

axial points and a centre point (in duplicate for experimental error calculation).

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Fig. 1 Flow diagram of Dionex ASE 350 extraction process. X1 is the number of

static cycles, X2 is static time (min) and X3 is operating temperature (°C). Cell is the

stainless steel sample holder where the extraction process occurs.

Table 1 Coded and actual values of the parameters in the experimental design

Factor Notation Units Coded levels of parameters -1 0 1

Static cycles X1 1 4 6

X1

Sample preparation: Mix biomass with DE

Cell is loaded into the oven

Cell is filled with solvent and heated for a fixed time to ensures thermal equilibrium of samples

Cell heating and static extraction (at set up X2 and X3)

Cell is rinsed with fresh solvent

Remaining solvent is purged with N2 gas

Residual pressure is released from the cell

Cell is unloaded from the oven

Solvent + Extract (Oil)

XII

Static time X2 min 2 6 10 Temperature X3 °C 100 130 160

2.4 Statistical analysis and modelling

From the experiments that have been performed based on the design by RSM,

the oil yield (response variable, Y) was fitted by a quadratic model to correlate the

response variable to the independent variables. The experimental data obtained were

calculated and analysed through an empirical second-order polynomial function:

∑ ∑ ∑ ∑ ε (2)

where Y is the predicted response; β0 the intercept, βi the linear coefficient, βij the

quadratic coefficient, βii is the linear-by-linear interaction between xi and xj

regression coefficients, xi, xj are input variables that influence the response variable

Y, k is the number of factors and ε is the random error [18]. Analysis of variance

(ANOVA) was evaluated through statistical analysis of the model. The statistical

significance of the model terms was assessed using P-value approach.

3 RESULTS AND DISCUSSION

3.1. Mathematical modelling of the experimental data

The second-order model was employed for approximating the relationship

between the oil yield and the independent variables, as shown below

Y = - 44.52 + 11.40X1 + 5.20X2 + 0.23X3 + 0.0043X1X2 - 0.043X1X3

- 0.014X2X3 - 0.56X1X1 - 0.25X2X2 + 0.00096X3X3 (3)

where Y is the predicted oil yield and X1, X2 and X3 are static cycles, static time

(min), and temperature (°C) respectively. Table 2 shows the experimental designs,

the actual oil yield and the predicted oil yield. The actual oil yield was the values

from the experimental run, whereas the predicted oil yield was the fitted values of the

mathematical model. The mathematical model demonstrates good estimation of the

predicted oil yield as standard deviations between the actual and predicted oil values

are low.

Table 2 The experimental results and the predicted values of the oil yield.

Run Static cycle (X1)

Static time

Temperature (°C) (X3)

Oil yield (%) (Y) Actual Predicted Standard

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(min) (X2) deviation 1 1 6 130 18.32 18.35 0.02 2 4 6 130 26.01 26.97 0.68 3 6 6 130 27.84 27.87 0.02 4 4 10 130 24.19 24.22 0.02 5 4 6 160 34.89 34.92 0.02 6 4 6 130 28.06 26.97 0.77 7 4 6 100 20.04 20.07 0.02 8 4 2 130 21.10 21.13 0.02 9 1 10 160 25.88 25.86 0.01 10 1 2 100 1.59 1.57 0.01 11 6 10 100 24.07 24.05 0.01 12 6 2 160 25.85 25.83 0.01

The analysis of variance (ANOVA) of the model is presented in Table 3(A). F-

value is the ratio of the square of mean to the residual. P-value is the smallest level of

significant that would lead to rejection of the null hypothesis [18]. F-value and P-

value were used to determine the significance of each independent variable and their

interactions to the extraction of oil. Values of Prob>F (P-value) less than 0.05

indicate model terms are significant. The Model F-value (74.46) implies the model is

significant (P-value < 0.0500). Model terms of X1, X3, X1X3, X1X1 and X2X2 are

significant. There is only a 1.33% chance that Model F-Value could occur due to

noise. The lack of fit F-value of 0.01 implies the lack of fit is not significant, as there

is 94.85% chance that the lack of fit F-value occurs due to noise. Noise could be

attributed to the properties of samples that could vary due to the duration of storage

prior to the extraction process.

Table 3(B) shows the value of R2 for this model. Montgomery defined R2 as the

variability in the data explained by the model, where larger values of R2 (0 ≤ R2 ≤ 1)

is more desirable [18]. R2 value of the model (0.9970) indicates that the total

variation of 99.7% for the oil yield was attributed to the independent variables and

only about 0.3% of the total variation could not be explained by the model [19].

Predicted R2 is a measure of predictive capacity of the model, whereas Adjusted R2

measures the amount of variation about the mean explained by the model adjusted

for the number of parameters in the model [20]. The model shows that the Predicted

R2 (0.9885) is in good agreement with the Adjusted R2 (0.9836). From Predicted R2,

98.85% of the variability of new data attributed to the independent variables, where

only 1.15% of the total variation of the new data cannot be explained by the model.

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Table 3 (A) ANOVA results for the response surface analysis of the quadratic model

of the extraction of oil using ASE technique. (B) Standard deviation, mean,

coefficient of variance, adequate precision and R2 from ANOVA of the model

A Source Sum of squares

Degrees of freedom

Mean square

F-value

P-value (Prob>F)

Significance

Model 708.70 9 78.74 74.46 0.0133 Significant X1 45.32 1 45.32 42.85 0.0226 Significant X3 120.09 1 120.09 113.55 0.0087 Significant X1X3 23.31 1 23.31 22.04 0.0425 Significant X1X1 20.19 1 20.19 19.09 0.0486 Significant X2X2 46.20 1 46.20 43.69 0.0221 Significant Residual 2.12 2 1.06 Lack of fit 0.01 1 0.01 0.01 0.9485 Pure error 2.10 1 2.10 Corrected

Total Sum of Squares

710.82 11

B Value Standard deviation 1.03 Mean 23.15 Coefficient of variance (%) 4.44 PRESS 8.14 R2 0.9970 Adjusted R2 0.9836 Predicted R2 0.9885

The mathematical model was further evaluated by plotting the predicted oil

yield against the actual oil yield as shown in Figure 2(A). The plot demonstrated a

good agreement of the predicted oil yield to the actual oil yield. The model was also

evaluated through the plot of residuals versus fitted values (Figure 2(B)). The plot

showed that the residuals are structureless and do not display any obvious pattern

[18]. The undesirable pattern in the plot can appear in the form of megaphone or

outward-opening funnel due to the increase of variance, as the magnitude of the

predicted values increases [18]. Therefore, this analysis demonstrated that the

mathematical model is correct and the assumptions are satisfied [18]. The model is

reliable for predicting the extraction of oil microalgae biomass using ASE technique.

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Fig. 2. (A) Predicted versus actual plot of oil yield. (B) Internally studentised

residuals versus predicted plot of oil yield.

3.2 Evaluating the interaction among factors that influences extraction of oil

from microbial biomass

From the ANOVA results, it shows that the interaction between static cycles

and temperature is significant (P-value < 0.0500). While the interactions between

static time and static cycles, and static time and temperature are not significant. Low

significant effect of static time to the extraction in this study was in agreement with

the study of extraction of oil from a wet microalgae that showed no considerable

different on total FAMEs at 5 min, 10 min and 15 min [15]. Similar profiles were

also observed on fatty acids extraction from cereal lipids study as increasing static

time from 5 min to 10 min and 15 min had no effect on lipids’ fatty acids yield [12].

A significant impact of temperature on the extraction is possibly because higher

temperatures can improves solubility and mass transfer of liquid solvents into

samples matrix [21]. Higher temperature can also enhance the disruption of the

strong solute-matrix interactions, due to Van Der Waals forces, hydrogen bonding

and dipole attractions between the solutes molecules and actives sites on the matrix

[10]. Static cycle showed significant effect to the oil yield possibly due to the

addition of fresh solvent (i.e., methanol and chloroform) for each static extraction.

The addition of fresh solvent may increase the concentration gradient between the

solution inside the cell and the surface of sample matrix. The increase of

A

B

XVI

concentration gradient promotes faster mass transfer rate according to Fick’s first law

of diffusion [10].

A significant impact of temperature on the extraction is possibly because

higher temperatures can improves solubility and mass transfer of liquid solvents into

samples matrix [10]. Higher temperature can also enhance the disruption of the

strong solute-matrix interactions, due to Van Der Waals forces, hydrogen bonding

and dipole attractions between the solutes molecules and actives sites on the matrix

[10]. In addition, increasing temperature reduces viscosity of liquid solvents which

facilitates diffusion into matrix particles [10].

Static cycle showed significant effect to the oil yield possibly due to the

addition of fresh solvent for each static extraction that may increase the

concentration gradient between the solution inside the cell and the surface of sample

matrix [10]. This is because higher concentration gradient promotes faster mass

transfer rate according to Fick’s first law of diffusion [10].

3.3 Optimising the parameters of the extraction of oil from microbial biomass

The response surface analysis through 3-dimensional response surface plot

(Figure 3) was performed for optimising the yield of oil from microbial biomass

using ASE. Fig. 3(A) shows that at 130 and 6 min static time, the amount of oil

extracted increased with increasing static cycles, up until approximately 4-5 static

cycles. This result showed that oil could be extracted from even after 4 static cycles,

which is in accordance to other study on oil extraction from macroalgae biomass

(Rhizoclonium hieroglyphicum) using ASE [11]. From Fig. 3(B), oil yield

significantly increased with increasing temperature. The impact of static cycle on the

oil yield was more apparent at lower temperature than higher temperature. Fig. 3(C)

shows that at 4 static cycles for all extraction temperatures, the oil yields increased

with increasing static time up until an optimum time at approximately 6 min. The

extraction at 4 static cycles in Fig. 3(C) demonstrated that at a very high extraction

temperature such as at 160 °C, the oil yield was gradually decreasing when the static

time was more than 6 min. This is because that there is the possibility for the

samples to degrade during prolonged extraction process at a very high temperature.

High extraction temperature has been suspected to cause thermal degradation of

XVII

lipids [13]. Even though there was a small decrease in oil yield at lower temperature

(100 °C) for the extraction at more than 6 min, the drop in oil yield was too low.

Fig. 3 Dimensional surface plots of binary interaction between different variables to

the oil yield: (A) static cycles and static time at 130 °C, (B) static cycles and

temperature at 6 min and (C) static time and temperature at 4 static cycles. The

figures were generated from Design-Expert software.

A

B

C

XVIII

The parameters of optimisation of extraction of oil by ASE were determined

based the numerical optimisation according to the criteria showed in Table 4.

Numerical optimisation was performed based on an objective function called

desirability [20]. At desirability (0 to 1) of 1 from the numerical optimisation (Figure

4), the parameters of optimum oil yield selected were 4 static cycles, 6 min and 130

for the extraction using ASE, with the maximum oil yield of 34.9% (w/w).

Table 4 Criteria for numerical optimisation of maximum oil yield

Criteria Goal Lower limit Upper limitStatic cycles In range 1 6 Static time (min) In range 2 10 Temperature (°C) In range 100 160 Oil yield Maximise 1.59 34.89

In this study, the control run on microalgal biomass resulted in an oil yield of

26.0% (w/w), which is lower than the maximum oil yield obtained in this study.

Therefore, the extraction using optimised conditions in this study showed 1.34 fold

increases in oil yield from the control run. The optimised ASE conditions in this

study demonstrated an improvement in extraction technique for quantifying the

amount of oil in the biomass.

Fig. 4 3-Dimensional surface plot of the binary interaction at 160 °C between static

time and static cycle to the desirability value. The figure was generated from Design-

Expert software.

XIX

Conclusions

The RSM was utilised for optimising the oil yield from the extraction on

microalgal biomass using ASE technique. The mathematical model developed from

the response surface analysis was reliable to predict the oil yield. The results showed

a good agreement of the predicted oil yield to the actual oil yield from the

experimental run. Based on the surface response analysis, the optimised ASE

conditions determined were 4 static cycles, static time of 6 min and temperature of

160 , with the maximum oil yield of 34.9% (w/w). The optimised oil yield also

resulted in significant improvement of oil yield in comparison to the oil yield from

the control run, with 1.34 fold increases in oil yield.

Acknowledgements

The authors acknowledge Ministry of Education Malaysia for the postgraduate

scholarship of the first author. The authors also acknowledge the QUT Central

Analytical Research Facility for its support for sample analyses.

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[16] Ahmad, F.B., Zhang, Z., Doherty, W.O.S., and O’Hara, I.M., A multi-criteria

analysis approach for ranking and selection of microorganisms for the production of

oils for biodiesel production. Bioresource Technology, 2015; 190: 264-273.

[17] Ahmad, F., O’Hara, I., and Zhang, Z. Oil extraction from heterotrophic

microalgae biomass: A preliminary study. in Third Malaysia Postgarduate

Conference (MPC) 2013. 2013. Sydney.

[18] Montgomery, D.C., Design and analysis of experiments. 2005, Hoboken, NJ:

John Wiley & Sons.

XXI

[19] Mohajeri, L., Aziz, H.A., Isa, M.H., and Zahed, M.A., A statistical experiment

design approach for optimizing biodegradation of weathered crude oil in coastal

sediments. Bioresource Technology, 2010; 101: 893-900.

[20] Version 6 User’s Guide Design-Expert Software. 2000, Stat-Ease, Inc.

[21] Dionex ASE 350 Accelerated Solvent Extractor Operator's Manual, in

Document No. 065220. 2011, Thermo Fisher Scientific Inc.

XXII

Appendix 2: Microbial oil production from sugarcane bagasse hydrolysates by oleaginous yeast and filamentous fungi

F. B. Ahmad, Z. Zhang, W. O. S. Doherty, I. M. O’Hara

Centre for Tropical Crops and Biocommodities, Queensland University of

Technology, Brisbane, Australia

Abstract

This study investigated the potential use of sugarcane bagasse as a feedstock for oil

production through microbial cultivation. Bagasse was subjected to dilute acid

pretreatment with 0.4 wt% H2SO4 (in liquid) at a solid/liquid ratio of 1:6 (wt/wt) at

170 °C for 15 min, followed by enzymatic hydrolysis of solid residue. The liquid

fractions of the pretreatment process and the enzymatic hydrolysis process were

detoxified and used as liquid hydrolysate (SCBLH) and enzymatic hydrolysate

(SCBEH) for the microbial oil production by oleaginous yeast (Rhodotorula

mucilaginosa) and filamentous fungi (Aspergillus oryzae and Mucor plumbeus). The

results showed that all strains were able to grow and produce oil from bagasse

hydrolysates. The highest oil concentrations produced from bagasse hydrolysates

were by M. plumbeus at 1.59 g/L (SCBLH) and 4.74 g/L (SCBEH). The microbial

oils obtained have similar fatty acid compositions to vegetable oils, indicating that

the oil can be used for the production of second generation biodiesel. On the basis of

oil yields obtained by M. plumbeus, from 10 million t (wet weight) of bagasse

generated annually from sugar mills in Australia, it is estimated that the total

biodiesel that could be produced would be equivalent to about 9% of Queensland’s

diesel consumption.

Keywords: Sugarcane, Bagasse, Oil, Biodiesel, Yeast, Fungi

Abbreviations: 5-hydroxymethylfurfural, HMF; Sugarcane bagasse, SCB; SCBEH,

Sugarcane bagasse enzymatic hydrolysate; SCBLH, Sugarcane bagasse liquid

hydrolysate

XXIII

Statement of Contribution

The authors listed below have certified that:

1. they meet the criteria for authorship in that they have participated in the

conception, execution, or interpretation, of at least that part of the publication in their

field of expertise;

2. they take public responsibility for their part of the publication, except for the

responsible author who accepts overall responsibility for the publication;

3. there are no other authors of the publication according to these criteria;

4. potential conflicts of interest have been disclosed to (a) granting bodies, (b) the

editor or publisher of journals or other publications, and (c) the head of the

responsible academic unit, and

5. they agree to the use of the publication in the student’s thesis and its publication

on the Australasian Research Online database consistent with any limitations set by

publisher requirements.

In the case of this article:

Microbial oil production from sugarcane bagasse hydrolysates by oleaginous yeast

and filamentous fungi. Proceedings of the Australian Society of Sugar Cane

Technologists, 38 (2016).

Contributor Statement of contribution

Farah B. Ahmad The author contributed to initial

experimental design; conducted

experiment, analysis and data

interpretation; and wrote the first draft of

manuscript and subsequent revisions of

the manuscripts.

Signature

Date

Zhanying Zhang This author provided valuable assistance

XXIV

in initial experimental design, the

analysis and data interpretation, and

reviewed the manuscript.

William O. S. Doherty This author contributed to data

interpretation and provided valuable

input in reviewing the manuscript.

Ian M. O’Hara This author supervised overall

experimental design, analysis, data

interpretation, and edited the manuscript

draft.

Principal Supervisor Confirmation

I have sighted email or other correspondence from all Co-authors confirming their

certifying authorship.

Name

Ian O’Hara

Signature

Date

XXV

1 Introduction

Biodiesel, a renewable fuel, shows great promise as an alternative to fossil-

based diesel. Biodiesel is typically produced from plant oils such as soybean oil,

palm oil and Jatropha oil. An increasing amount of research is investigating biodiesel

production from microbial oil, in order to find alternatives for biodiesel production

from edible plant oils. Other benefits of producing biodiesel from microbial oils

compared to plant oils are shorter production life cycles, lower labour intensity,

easier scaling up and reduced seasonal and climate impacts [1].

There are several studies on the production of microbial oils from various

groups of microorganisms especially microalgae, yeasts and fungi, where the

microorganisms that are able to produce oil are termed as oleaginous. Microbial oils

are produced through the cultivation of oleaginous microorganisms on carbon

substrates usually when the stress condition was applied, such as through limited

nitrogen sources [2]. Most microbial oil production studies focus on the use of

simple sugars, especially glucose, as the carbon substrate. However, large-scale

production of microbial oils from pure sugars is not economical. The opportunity

exists to reduce the cost for microbial oil production with the use of cheaper

feedstock such as lignocellulosic agro-industrial wastes.

Sugarcane bagasse, a highly available lignocellulosic biomass, has the potential

to be utilised as an alternative feedstock for microbial oil production. However, the

lignocellulosic structure of bagasse presents one of the challenges of utilising

bagasse for fermentation or microbial cultivation. It is necessary to disrupt the

complex arrangement of cellulose, hemicelluloses and lignin of lignocellulosic

biomass so that cellulose will be accessible for enzyme bioprocessing or biological

degradation [3]. Therefore, a pretreatment step for bagasse is crucial. One of the

most common pretreatment processes is dilute acid pretreatment, which is an

effective process for removing the majority of hemicellulose [4]. Another challenge

of utilising bagasse for oil production is that chemical pretreatment usually generates

sugar degradation products that may inhibit the growth of oleaginous

microorganisms. The most common growth inhibitors are furfural (from pentoses)

and 5-hydroxymethyl furfural (HMF) (from hexoses) [5].

Studies on oil production from bagasse hydrolysates have been conducted

using microalgae strain Chlorella protothecoides and yeast strains Rhodotorula sp.

XXVI

IIP-33 and Yarrowia lipolytica Po1g [6-8]. However, Ahmad et al. showed that yeast

and filamentous fungi are more suitable at utilising a variety of carbon sources

(glucose, xylose and glycerol) for oil production than microalgae [9]. Therefore, in

this study, strains of oleaginous yeast and filamentous fungi (Rhodotorula

mucilaginosa, Aspergillus oryzae and Mucor plumbeus) were grown on bagasse

hydrolysates for oil production.

The aim of this research was to investigate the microbial growth and oil

production from the hydrolysates of dilute acid pretreatment and enzymatic

hydrolysis of bagasse. This is the first study to utilise hydrolysates from both liquid

and solid residue streams from the pretreatment of bagasse for microbial oil

production. The application of hydrolysates from both streams of pretreatment

process can potentially maximise the total microbial oil production. Therefore, the

outcome of this study will contribute to sustainable and profitable production process

for large-scale oil production from bagasse.

2 Materials and Methods

2.1 Dilute acid pretreatment of bagasse and enzymatic hydrolysis of the solid

residue

Sugarcane bagasse used in this study consisted of 37.0% glucan, 18.0% xylan,

30.0% lignin, 4.12% water extractives and 1.6% ethanol extractives, based on the

compositional analysis using procedures from National Renewable Energy

Laboratory (NREL) [10, 11]. The air-dried raw bagasse (500 g dry mass) was

pretreated with 0.4 wt% H2SO4 (in liquid) at a solid/liquid ratio of 1:6 (wt/wt) in 7.5

L Parr reactor at 170 °C for 15 min at 100 rpm. The solid residue and the liquid

fraction from the pretreatment process were separated by filtration (Figure 1).

Enzymatic hydrolysis of bagasse solid residue was performed at pH 5.5 and a solid

loading of 10 wt% using Accelerase™ 1500 (Batch no: 4901298419) at 20 FPU/g

glucan. The enzymatic hydrolysis was conducted for 72 h on OM15 orbital shaking

incubator (Ratek, Australia) set at 50 °C and 150 rpm. The liquid fraction of

enzymatic hydrolysate was separated by centrifugation (Figure 1). The liquid

fractions from the bagasse pretreatment process as well as from enzymatic hydrolysis

were detoxified and were used with nutrient supplementation as bagasse liquid

hydrolysate (SCBLH) and as enzymatic hydrolysate (SCBEH) respectively.

XXVII

Figure 1 Overview of hydrolysates preparation from bagasse for the microbial cultivation

2.2 Detoxification of pretreated bagasse liquid fraction

Non-detoxified hydrolysates were prepared by adjusting the pH of the liquid

fraction to pH 5.5 using Ca(OH)2, followed by 0.22 µm filtration [12]. Detoxification

was conducted by overliming technique at 50 °C by increasing the pH to 10 by the

addition of Ca(OH)2, followed by filtration using 0.22 µm membrane (Sartorius,

Germany) [12]. The mixture filtrate was cooled to 30 °C and re-acidified with H2SO4

to pH 5.5, and filtered using 0.22 µm membrane [12].

2.3 Microbial cultivation and oil production

The yeast strain Rhodotorula mucilaginosa (FRR no. 2406) and the fungi

strains Aspergillus oryzae (FRR no.: 1677) and Mucor plumbeus (FRR no. 2412)

were purchased from FRR Culture Collection (Australia). R. mucilaginosa was pre-

cultured prior to cultivation for 48 h [13]. For inoculation of the yeast into the

cultivation media, 10% (v/v) inocula from the pre-cultivation medium were used. For

inoculation of fungi into the cultivation media, 0.6 mL spore suspension containing 1

x 107 spores/mL was used [14]. The cultivation media (hydrolysates) were prepared

by supplementing with 0.4 g MgSO4.7H2O, 2 g KH2PO4, 3 mg MnSO4.H2O and 0.1

mg CuSO4.5H2O, and 1.5 g/L yeast extract as the nitrogen source [12]. The

Enzymatic hydrolysis

Sugarcane bagasse

Dilute acid pretreatment

Filtration

Detoxification by overliming

Detoxification by overliming

Liquid fraction Solid residue

Liquid hydrolysate (SCBLH) Enzymatic hydrolysate (SCBEH)

XXVIII

cultivation was performed in triplicate with 30 mL working volume in 150 mL

Erlenmeyer flask at 28 °C on an OM15 orbital shaking incubator (Ratek, Australia)

for 7 days. The biomass was harvested and freeze-dried to constant weight [9].

2.4 Oil extraction

Oil was extracted from the biomass by Accelerated Solvent Extraction (ASE)

technique using Dionex ASE 350 (Thermo Fisher Scientific Inc., USA) [9]. The

extraction conditions were as follows: temperature, 130 ; static time, 7 min; rinse

volume, 25% of cell volume; and using two static cycles, using chloroform/methanol

in a ratio of 2:1 (v/v). The results are reported on a dry weight (DW) basis unless

otherwise specified.

2.5 Sugars, organic acid, furans and oil analyses

Sugar, organic acid and furan concentrations were measured using high-

performance liquid chromatography (HPLC) as described in previous studies [9, 15].

For the determination of fatty acids composition, fatty acid methyl esters (FAME)

were prepared and analysed using gas chromatography-mass spectrometry (GC-MS)

based on Ahmad et al. (2015). The following GC-MS method was used: injection

temperature at 250 °C, initial temperature at 90 °C, hold for 2 min, followed by 7.5

°C/min ramp to 210 °C and 20 °C/min ramp to 240 °C, hold for 5 min.

Results and discussion

3.1 Composition of sugarcane bagasse hydrolysates

In this study, hydrolysates from both streams of the dilute acid pretreatment of

bagasse (Figure 1) were used as the cultivation media for oil production. The liquid

fraction of dilute acid pretreatment typically contains readily fermentable soluble

sugars. The solid residue of pretreated biomass primarily consists of cellulose and

therefore, requires enzymatic hydrolysis for breaking down cellulose and other

complex sugars to fermentable sugars. The fermentable sugars (i.e. glucose and

xylose) from hydrolysates of pretreated bagasse (Table 1) were utilised as carbon

substrates for microbial oil production.

The detoxification step was necessary for bagasse hydrolysates in this study as

it contains considerable concentrations of potential growth inhibitors (e.g. furfural

and HMF). Furfural had been reported to inhibit the growth of oleaginous yeast

XXIX

Cryptococcus curvatus at the concentration of 1.0 g/L [16]. HMF however, has been

shown to have a less inhibiting impact on growth [5, 16, 17]. No growth was

observed in this study from the cultivation on non-detoxified bagasse hydrolysates.

In this study, the detoxification technique of overliming was applied and the

detoxification had reduced the concentrations of potential inhibitors. It is often

recommended to include a washing step on pretreated solid residue prior to

enzymatic hydrolysis, in order to avoid the presence of potential inhibitors in the

enzymatic hydrolysate. In addition, the washing step may also reduce detoxification

requirements.

Table 1 Selected sugars (glucose and xylose), acetic acid, HMF and furfural compositions of sugarcane bagasse hydrolysates.

Pretreatment stream

Feedstock Glucose (g/L)

Xylose (g/L)

Acetic acid (g/L)

HMF (g/L)

Furfural (g/L)

Liquid fraction

Non-detoxified SCBLH

7.76 8.32 5.85 0.91 3.90

SCBLH 6.11 6.00 6.60 0.04 0

Solid residue Non-detoxified SCBEH

29.96 3.46 2.36 0.38 3.39

SCBEH 31.34 1.21 2.53 0 0.17

3.2 Biomass concentration and sugars consumption from the cultivation on

bagasse hydrolysates

The oleaginous microorganisms used in this study for oil production from

bagasse hydrolysates were Rhodotorula mucilaginosa, Aspergillus oryzae and Mucor

plumbeus. These microorganisms were the highest ranking microorganisms from a

multi-criteria analysis by Ahmad et al. (2015) that had been conducted to select

preferred oleaginous microorganisms for oil production [9].

All microorganisms used in this study were able to grow on bagasse

hydrolysates. As shown in Figure 2, fungi M. plumbeus and A. oryzae had the highest

biomass concentrations on SCBLH at 9.8 and 9.2 g/L respectively, followed by R.

mucilaginosa. The results of the biomass concentrations on SCBLH compare well to

XXX

the growth of Yarrowia lipolytica Po1g on the detoxified liquid hydrolysate of

bagasse (13.51 g/L of xylose and 3.93 g/L of glucose) with biomass concentration of

11.42 g/L [6].

For the cultivation on SCBEH, M. plumbeus had the highest biomass

concentration at 19.9 g/L followed closely by A. oryzae Figure 2. The higher biomass

concentrations from the growth on SCBEH than SCBLH correspond to higher sugars

concentration of the SCBEH. The biomass concentrations of the fungi obtained from

SCBEH are comparable to the cultivation of fungus Mortierella isabellina with

biomass concentrations at 16.8 g/L on enzymatic hydrolysate of corn stover (22.2

g/L of glucose and 12 g/L of xylose) [18].

Figure 2 Microbial biomass concentrations (g/L) from bagasse hydrolysates.

The cultivation on SCBLH showed poorer consumptions of glucose by

microorganisms in comparison to the cultivation on SCBEH (Figure 3), possibly due

to the presence of HMF in the cultivation media. HMF may have caused a slower

growth rate and subsequently low consumption of carbon substrates. This is because

microorganisms that metabolise HMF may have a longer lag phase for growth [5]. In

the cultivation on SCBEH, the consumption of xylose in is much lower than the

consumption of glucose (Figure 3). Lower consumptions on xylose by

microorganisms were possibly because xylose consumption began only after there

was almost no glucose left in the medium, as reported in numerous studies [19].

0

5

10

15

20

25

SCBLH SCBEH

Bio

mas

s co

ncen

trat

ion

(g/L

) R. mucilaginosa

A. oryzae

M.plumbeus

XXXI

Figure 3 Sugars consumption (glucose and xylose) by microorganisms on bagasse hydrolysates.

3.3 Microbial oils production from bagasse hydrolysates

The oil content results (Figure 4(a)) showed that M. plumbeus had the highest

oil contents on both SCBLH (14.9%) and SCBEH (23.8%). The oil content of A.

oryzae is 9.0% on SCBLH and 19.6% on SCBEH. For R. mucilaginosa, the oil

contents on both hydrolysates are very similar (~11%).

The oil concentrations (Figure 4(b)) showed that M. plumbeus had the highest

oil concentrations on SCBLH and SCBEH at 1.6 g/L and 4.7 g/L respectively,

followed by A. oryzae. The oil concentration of M. plumbeus on SCBEH compares

well to oil concentration of 6.68 g/L by Y. lipolytica Po1g from bagasse hydrolysate.

Overall, this study showed that the use of M. plumbeus resulted in the best biomass

and oil production growing on both SCBLH and SCBEH in comparison to A. oryzae

and R. mucilaginosa.

0

10

20

30

40

50

60

70

80

90

100

Glucose Xylose Glucose Xylose

% s

ugar

s co

nsum

ptio

n (w

/w)

R. mucilaginosa

A. oryzae

M. plumbeus

SCBLH SCBEH

XXXII

(a)

(b)

Figure 4 (a) Oil content (%, w/w) and (b) oil concentration (g/L) of microbial biomass from the cultivation on bagasse hydrolysates.

3.4 Evaluation of potential biodiesel application of microbial oils

Microbial oils with fatty acid compositions similar to vegetable oils have the

potential to be used as feedstock for biodiesel production. In this study, the majority

of fatty acids identified were palmitic (C16:0), stearic (C18:0), oleic (C18:1) and

linoleic acid (C18:2) (Table 2), which is similar to the fatty acid composition of

vegetable oils. For R. mucilaginosa, oleic acid was the predominant fatty acid

growing on both hydrolysates, which is analogous to the results of the cultivation of

R. mucilaginosa on glucose and xylose [9]. Linoleic acid was found to be the

predominant fatty acid for both fungi strains on SCBLH, and oleic acid was the

predominant fatty acid on SCBEH.

Fuel properties of microbial oils were evaluated using cetane number and

iodine value (Table 2). Cetane number is an indicator to the ignition quality of fuels

0

5

10

15

20

25

30

SCBLH SCBEH

Oil

con

tent

(%

, w/w

)

R. mucilaginosa

A. oryzae

M.plumbeus

0

1

2

3

4

5

6

SCBLH SCBEH

Oil

con

cnet

ratio

n (g

/L)

R. mucilaginosa

A. oryzae

M.plumbeus

XXXIII

[20]. Iodine value measures the degree of saturation of fuels. The fatty acid methyl

ester (FAME) of microbial oils in this study were within the limit of the European

biodiesel specification since the European Standard for FAME (EN14214) specifies

cetane number of biodiesel has to be above 51 and iodine number below 120 [21].

Therefore, this study shows that the microbial oils produced are suitable for second

generation biodiesel production from bagasse.

Table 2 Fatty acids composition of microbial oils methyl esters from the cultivation on bagasse hydrolysates, as well as cetane number [20] and iodine number [22] of

the transesterified microbial oils. Feedstock Microorganisms Relative abundance of fatty acid

methyl esters (FAME) (%, w/w) FAME fuel properties

C16:0 C18:0 C18:1 C18:2 Cetane number

Iodine number

SCBLH R. mucilaginosa 33.0 (±2.0)

21.4 (±2.1)

45.7 (±0.6)

- 70.2 39.1

A. oryzae 18.7 (±1.2)

15.7 (±1.3)

32.0 (±1.4)

37.0 (±0.8)

61.7 91.3

M. plumbeus 18.5 (±0.9)

20.5 (±1.0)

27.6 (±4.3)

36.1 (±1.5)

62.4 86.0

SCBEH R. mucilaginosa 35.6 (±2.0)

11.8 (±2.3)

48.8 (±0.6)

7.0 (±0.4)

69.0 53.8

A. oryzae 18.1 (±0.7)

17.6 (±0.9)

34.3 (±1.6)

28.4 (±1.4)

60.7 78.4

M. plumbeus 18.8 (±0.9)

18.1 (±1.7)

35.3 (±1.2)

26.3 (±1.4)

61.4 75.6

3.5 Prospects for large-scale microbial oil production from bagasse hydrolysates

by M. plumbeus

M. plumbeus has great potential for oil production from bagasse as it had the

highest biomass and oil concentration on both bagasse hydrolysates. Large-scale

microbial oil production from bagasse can be assessed through the yields of oil. The

oil yields (mg oil per g carbon substrates consumed including glucose, xylose and

acetic acid) of M. plumbeus were 167 mg/g on SBCLH and 142 mg/g on SCBEH.

The oil production was calculated by multiplying the oil yields with the sugar yields

from 1 t (DW) bagasse. A study on optimised dilute acid pretreatment and enzymatic

hydrolysis of bagasse reported that the sugars yield from 1 t bagasse (DW) contained

29 kg of glucose and 198 kg of xylose from liquid hydrolysate, and 360 kg of

glucose and 15 kg of xylose from enzymatic hydrolysate [23]. By combining the oil

production from both hydrolysates, it is estimated that up to 91 kg of microbial oil

XXXIV

can be produced from 1 t dry bagasse by M. plumbeus. The utilisation of both

hydrolysates maximises the total oil production from bagasse. The total oil

production from bagasse by M. plumbeus is comparable to the oil production by M.

isabellina with 103 kg oil from 1 t (DW) of wheat straw [14]. Table 3(a) shows the

comparison of the feedstock cost for oil production from bagasse and pure glucose,

where bagasse provides nine times lower feedstock cost compared to the use of pure

glucose. The oil yield and the price of pure glucose were based on previous studies

[9, 24].

Table 3 (a) The comparison of estimated feedstock cost for oil production from bagasse and pure glucose. (b) The estimated yield of biodiesel per 1 t (dry weight)

bagasse based on the oil yields of M. plumbeus (a) Microbial oil

feedstock Price (US$/t feedstock)

Oil yield (kg/t feedstock)

Feedstock cost (US$/kg oil)

Sugarcane bagasse 50 91 0.55 Pure glucose 400 80 5.00 (b) Yield (L/t dry bagasse) Biodiesel from SCBLH

(FAME density of 874.2 g/L) 37

Biodiesel from SCBEH (FAME density of 860.5 g/L)

56

Biodiesel from bagasse 93

Biodiesel yields in Table 3 were calculated based on 91% (w/w) microbial oil

conversion [14, 25] and estimated FAME densities [20]. From the 10 million wet t of

bagasse (with 50% moisture content) generated annually from sugar mills in

Australia, a maximum of around 465 million L biodiesel could potentially be

produced if all of the bagasse was used for microbial oil production. Based on diesel

consumption of 5200 million L in Queensland [26], this would be equivalent to about

9% of Queensland’s diesel consumption. A greater proportion is potentially able to

be produced through the use of trash and future production of high fibre sugarcanes.

While wide scale application of microbial oils from bagasse for biodiesel production

would only replace a small fraction of total Queensland diesel consumption, local

and regional opportunities may exist in some areas such as for replacement of diesel

use in sugarcane harvesting and transport.

XXXV

Conclusion

Rhodotorula mucilaginosa, Aspergillus oryzae and Mucor plumbeus showed

the capacity to produce oil from hydrolysates of bagasse. The fungus M. plumbeus

showed the highest oil concentrations on both hydrolysates, therefore, the oil yields

of M. plumbeus were further used to estimate large-scale microbial oil production

from bagasse. From the estimated total oil production, this study shows the potential

to reduce the feedstock cost for microbial oil production through the use of bagasse.

Therefore, bagasse shows a great promise as the feedstock for biodiesel production

that may supplement diesel use for local consumption. The utilisation of both

bagasse hydrolysates (SCBLH and SCBEH) may create sustainable and profitable

microbial oil production.

Acknowledgements

The authors acknowledge Ministry of Education Malaysia for the postgraduate

scholarship of the first author. The authors also acknowledge the QUT Central

Analytical Research Facility for its support on sample analyses, as well as Vitor

Takashi Kawazoe for oil extraction and derivatisation process.

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XXXVIII

Appendix 3: Time-course graph for DO, pH, agitation speed and aeration rate for bioreactor cultivation

Figure A3-1 Online data from bioreactor cultivation where DO is represented by red

line, pH by blue line, agitation speed (rpm) by magenta line and aeration rate (vvm)

by green line. The horizontal axis represents time (h).