aqueous enzymatic extraction of

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AQUEOUS ENZYMATIC EXTRACTION OF WHEAT GERM OIL By MEIZHEN XIE Bachelor of Science in Food Science China Agricultural University Beijing, China 2004 Submitted to the Faculty of the Graduate College of the Oklahoma State University in partial fulfillment of the requirements for the Degree of MASTER OF SCIENCE December, 2009

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AQUEOUS ENZYMATIC EXTRACTION OF

WHEAT GERM OIL

By

MEIZHEN XIE

Bachelor of Science in Food Science

China Agricultural University

Beijing, China

2004

Submitted to the Faculty of the Graduate College of the

Oklahoma State University in partial fulfillment of

the requirements for the Degree of

MASTER OF SCIENCE December, 2009

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AQUEOUS ENZYMATIC EXTRACTION OF

WHEAT GERM OIL

Thesis Approved:

Nurhan T. Dunford

Thesis Adviser

Carla Goad

Mark Wilkins

A. Gordon Emslie

Dean of the Graduate College

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ACKNOWLEDGMENTS

I want to thank my advisor Dr. Nurhan Dunford, for providing me with valuable

guidance, suggestions, encouragement and patience, which helped the completion of this

study.

Special gratitude is given to Dr. Goad whose valuable input is indispensible for

this study. I would like to thank Dr. Wilkins for being my committee member.

I also want to thank Oklahoma State University and the Robert M. Kerr Food &

Agricultural Product Center for providing a good learning atmosphere and excellent

research facilities.

Last but not least, I want to thank my family, friends and people in my research

laboratory for all the help, support, and encouragements.

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TABLE OF CONTENTS

Chapter Page I. INTRODUCTION ..................................................................................................... 1

1.1 Statement of problem ........................................................................................ 1 1.2 Hypothesis ......................................................................................................... 2 1.3 Objective ........................................................................................................... 2 II. LITERATURE REVIEW ......................................................................................... 3 2.1 Wheat germ ....................................................................................................... 3 2.1.1 Wheat germ structure ....................................................................... 3 2.1.2 Wheat germ composition ................................................................. 4 2.2 Extraction of wheat germ oil ............................................................................. 5 2.3 Aqueous enzymatic oil extraction ..................................................................... 5 2.3.1 Extraction process .............................................................................. 5 2.3.2 Forms of oil obtained by AEOE ........................................................ 6 2.3.3 Factors affecting AEOE yields .......................................................... 7 2.3.3.1 Enzyme type .......................................................................... 7 2.3.3.2 Particle size ........................................................................... 9 2.3.3.3 pH and temperature ............................................................. 10 2.3.3.4 Liquid: solid ratio ................................................................ 11

2.3.3.5 Enzyme concentration ......................................................... 11 2.3.3.6 Extraction time .................................................................... 12 III. MATERIALS AND METHODS .......................................................................... 13 3.1 Source and preparation of wheat germ ........................................................... 13 3.2 Enzyme selection ............................................................................................ 13 3.2.1 Viscozyme L ...................................................................................... 13 3.2.2 Multifect CX GC ................................................................................ 13

3.2.3 Multifect CX 13L ............................................................................... 14 3.2.4 Alcalase 2.4L FG ............................................................................... 14

3.3 Enzyme screening tests ................................................................................... 14 3.4 Optimization by Response Surface Methodology .......................................... 15 3.5 Analytical methods ......................................................................................... 16

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3.5.1 Moisture content ................................................................................ 16 3.5.2 Ash content ........................................................................................ 17 3.5.3 Oil content .......................................................................................... 17 3.5.4 Protein content ................................................................................... 17 3.5.5 Starch content ..................................................................................... 17

3.5.6 Enzyme activity test ........................................................................... 18 3.5.6.1 Viscozyme L ....................................................................... 18

3.5.6.2 Multifect CX GC ................................................................. 18 3.5.6.3 Multifect CX 13L ................................................................ 18

3.5.6.4 Alcalase 2.4L FG ................................................................ 18 3.6 Statistical analysis ........................................................................................... 19

IV. RESULTS AND DISCUSSION ........................................................................... 20 4.1 Characterization of wheat germ ...................................................................... 20 4.2 Effects of enzyme type on oil extraction yield ............................................... 21 4.3 Optimization of aqueous extraction process ................................................... 23 V. CONCLUSION ...................................................................................................... 29 FUTURE RESEARCH ............................................................................................... 31 REFERENCES ........................................................................................................... 32 TABLES ..................................................................................................................... 39 FIGURES .................................................................................................................... 51

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LIST OF TABLES

Table Page 1. Coded and actual levels of independent variables .............................................. 38 2. Experimental design for non-enzymatic processes by Response Surface Methodology ......................................................................... 39 3. Experimental design for enzymatic processes by Response Surface Methodology ......................................................................... 40 4. Proximate composition of wheat germ ............................................................... 41 5. Particle size distribution of ground wheat germ ................................................. 42 6. Enzymes used in this study and their activities .................................................. 43

7. Observed and predicted oil extraction yield (%) for non-enzymatic processes ............................................................................... 44 8. Observed and predicted oil extraction yield (%)

for enzymatic processes ...................................................................................... 45 9. Analysis of variance for response surface quadratic models for non-enzymatic processes .................................................................. 46 10. Analysis of variance for response surface quadratic

models for enzymatic processes ........................................................................ 47 11. Estimated coefficients of the quadratic

models for non-enzymatic processes .................................................................. 48 12. Estimated coefficients of the quadratic

models for enzymatic processes .......................................................................... 49

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LIST OF FIGURES

Figure Page 1. Structure of wheat grain ...................................................................................... 51 2. Structure of oil body ........................................................................................... 52 3. Aqueous enzymatic oil extraction process .......................................................... 53 4. A schematic of aqueous enzymatic oil extraction procedure employed in this study ........................................................................................ 54 5. Oil extraction yields by different enzymes ......................................................... 55 6. Change in activity of Alcalase 2.4L FG during experimental period ................. 56 7. Change in activity of Multifect CX GC during experimental period ................. 57 8. Response surface for oil extraction yield by non-enzymatic process in boric acid-NaOH buffer at pH 8.0 ..................................................... 58 9. Response surface contour for oil extraction yield by non-enzymatic process in boric acid-NaOH buffer at pH 8.0 ............................ 59 10. Response surface for oil extraction yield by non-enzymatic

process in Tris-HCl buffer at pH 8.0 .................................................................. 60 11. Response surface contour for oil extraction yield by non-enzymatic process in Tris-HCl buffer at pH 8.0 .................................................................. 61 12.Response surface for oil extraction yield by non-enzymatic

process in citric-phosphate buffer at pH 5.0 ....................................................... 62 13. Response surface contour for oil extraction yield by

non-enzymatic process in citric-phosphate buffer at pH 5.0 .............................. 63 14.Response surface for oil extraction yield by enzymatic

process with Alcalase-B, at enzyme concentration of 0.1% ............................... 64 15. Response surface contour for oil extraction yield by enzymatic

process with Alcalase-B, at enzyme concentration of 0.1% ............................... 65 16. Response surface for oil extraction yield by enzymatic

process with Alcalase-B at enzyme concentration of 2.5% ................................ 66 17. Response surface contour for oil extraction yield by enzymatic

process with Alcalase-B at enzyme concentration of 2.5% ............................. 67 18. Response surface for oil extraction yield by enzymatic

process with Alcalase-B at enzyme concentration of 5% ................................... 68 19. Response surface contour for oil extraction yield by enzymatic

process with Alcalase-B at enzyme concentration of 5% ................................... 69 20. Response surface for oil extraction yield by enzymatic

process with Multifect CX GC at enzyme concentration of 0.1% ...................... 70

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21. Response surface contour for oil extraction yield by enzymatic process with Multifect CX GC at enzyme concentration of 0.1% ...................... 71

22. Response surface for oil extraction yield by enzymatic process with Multifect CX GC at enzyme concentration of 2.5% ...................... 72 23. Response surface contour for oil extraction yield by enzymatic

process with Multifect CX GC at enzyme concentration of 2.5% ...................... 73 24. Response surface for oil extraction yield by enzymatic

process with Multifect CX GC at enzyme concentration of 5% ......................... 74 25. Response surface contour for oil extraction yield by enzymatic

process with Multifect CX GC at enzyme concentration of 5% ......................... 75 26. Response surface for oil extraction yield by enzymatic

process with Alcalase-T at enzyme concentration of 0.1% ................................ 76 27. Response surface contour for oil extraction yield by enzymatic

process with Alcalase-T at enzyme concentration of .01% ................................ 77 28. Response surface for oil extraction yield by enzymatic

process with Alcalase-T at enzyme concentration of 2.5% ................................ 78 29. Response surface contour for oil extraction yield by enzymatic

process with Alcalase-T at enzyme concentration of 5% ................................... 79 30. Response surface for oil extraction yield by enzymatic

process with Alcalase-T at enzyme concentration of 5% ................................... 80 31. Response surface contour for oil extraction yield by enzymatic

process with Alcalase-T at enzyme concentration of 5% ................................... 81

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NOMENCLATURE

ANOVA Analysis of variance

v/w Volume to weight

w/w Weight to weight

rpm Rotation per minute

% Percentage

oC Degree centigrade

g Gram

h Hour

ml Milliliter

min Minute

µm Micrometer

mm Millimeter

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CHAPTER I

INTRODUCTION

1.1 PROBLEM STATEMENT

Wheat germ is a byproduct of the grain milling industry. It contains about 10% oil.

The conventional wheat germ oil extraction method utilizes n-hexane as a solvent. This

method is very effective, with an oil yield of higher than 95%. However, n-hexane has

been proven to be an environmental pollutant. Hexane is a flammable solvent. Hence, it

can create an unsafe environment for the people working in the plants. In addition, health

conscious consumers may have concerns about potential solvent residue in hexane

extracted oil. Other alternatives to the hexane based extraction are mechanical pressing

and supercritical fluid extraction. Mechanical pressing completely avoids the use of

organic solvents. Thus the final product can be considered natural. However, the

efficiency of this method can be 50% or lower, depending on the germ pretreatment and

type of press used for extraction. Supercritical fluid extraction using non-toxic and

non-explosive carbon dioxide as a solvent produces a chemical-free final product. Carbon

dioxide is recycled to the system after oil separation. Hence supercritical carbon dioxide

extraction is environmentally benign and does not leave solvent residue in the oil.

However, the capital cost required for the supercritical fluid system set up is quite high.

New technologies need to be developed to overcome the disadvantages of the existing

extraction methods.

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1.2 HYPOTHESIS

Aqueous enzymatic extraction, which utilizes water as the solvent and is performed

under mild conditions with the aid of enzymes, is a viable alternative technology for oil

extraction from wheat germ.

1.3 OBJECTIVE

The main objective of this study is to evaluate the efficiency of aqueous enzymatic

extraction of oil from wheat germ. The specific objectives are as follows:

i. To screen various enzymes for their suitability for oil recovery.

ii. To study the effects of processing parameters on oil extraction yield.

iii. To optimize oil extraction yield by response surface methodology.

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CHAPTER II

LIETRATURE REVIEW

2.1 WHEAT GERM

2.1.1 Wheat Germ Structure

Together with bran and starchy endosperm, wheat germ (WG) makes up the basic

structure of wheat grain (Figure 1) (Fennema 1985). WG is partly embedded in the

endosperm at the base of the wheat grain, and can be separated from bran and endosperm

by milling. Whole wheat grain moisture content is adjusted to 13-15% by tempering prior

to milling. This process softens the grain and toughens the bran making it easier to

separate it from the endosperm and germ (Atwell 2001). Also, tempering softens the

endosperm, which breaks apart with less force.

WG accounts for about 2-3% by weight of the grain (Atwell 2001), and consists of

embryo (or embryonic axis) and scutellum (Posner and Hibbs 1997). The embryo is about

1.2% by weight of the grain, and is the part that eventually develops into the first roots

and shoot of the new plant. The scutellum, which is located between the embryo and the

endosperm and accounts for about 1.5% by weight of the grain, is the part that transports

sugars hydrolyzed from endosperm to the embryo during germination (Barnes 1982).

In WG, oil is stored in a subcellular organelle called the oleosome, oil body or

spherosome, whose structure is presented in Figure 2 (Waltermann and Steinbuchel 2005).

As the main form of oil in plants, triacylglycerols (TAG) coalesce in the centre of the oil

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bodies which are covered by a membrane made up of phospholipids (PLs). Unlike the

membranes of the other organelles in cells which possess a bi-layer structure of PLs, the

membrane of the oil body is a single-layer formed by PLs with protein embedded in it.

The hydrophobic end of the PLs is oriented toward the TAG matrix. The hydrophilic end

of PLs extends toward the aqueous cytoplasm. The proteins in the membrane of the oil

body are called oleosin (Huang 1992). The structure of the oil body serves two purposes:

maintaining lipids in the aqueous cytoplasm of the cell, and providing a large surface to

facilitate the action of lipases to break down lipids to produce energy during germination.

Plant oil bodies usually contain 94–98% (w/w) neutral lipids, 0.5–2% PLs and 0.5–3.5%

proteins (Huang 1992). In WG, oil is present in both scutellum and embryo. Oil bodies in

the cells of the epithelium and parenchyma in scutellum accumulate around protein

bodies and periphery of the cells (Morrson and others 1975; Murphy and others 1993).

The arrangement of oil bodies in the embryo is not well known.

2.1.2 Wheat Germ Composition

Wheat germ is rich in protein and lipid, but not in starch. The composition of WG

depends on the method used to separate it from the endosperm. In commercial WG, a

typical gross composition is as follows: moisture (6%), protein (26%), oil (10%), ash

(4%), starch (20%), crude fiber (3%) and other substances (15%) (Barnes 1982). The

occurrence of starch in commercial WG is mainly due to endosperm carry over during the

milling process. The oil content has been reported to be 25-30% in dissected WG which is

not contaminated by the bran and endosperm (Hargin and Morrison 1980). Linoleic acid

(18:2) is the predominant fatty acid (FA), which makes up 60% of the total FA in wheat

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germ oil (WGO). Other important FAs present include palmitic acid (16:0) (15%), oleic

acid (18:1) (15%), and linolenic acid (18:3) (10%) (Barnes 1982).

2.2 EXTRACTION OF WHEAT GERM OIL

After separated from bran and endosperm, WG, which appears as yellow flake, is

subjected to an oil extraction process. Three methods are currently being used to produce

commercial WGO: organic solvent based extraction, mechanical pressing and

supercritical fluid extraction. In organic solvent based extraction, oil is extracted from

WG into hexane, and crude oil is obtained after the evaporation of the solvent (Barnes

and Taylor 1980). In mechanical pressing, oil is extruded out of WG by mechanical

pressure. Since the oil extraction yield is low, mechanical pressing is recommended when

WG is free of contaminations from endosperm and bran (Dunford 2009). Utilization of

supercritical fluid technology for WGO recovery eliminates the potential solvent residues

in the final product because solvent is completely removed from the product by reducing

the pressure of the system at a point that fluid returns back to gas phase (Eisenmenger and

others 2006).

2.3 AQUEOUS ENZYMATIC OIL EXTRACTION

2.3.1 Extraction Process

The steps involved in aqueous enzymatic oil extraction (AEOE) usually include

grinding (wet or dry) of the oil-bearing materials, mixing of the comminuted material

with aqueous solution, incubation with enzyme, separation of liquid and solid phases by

centrifugation or filtration and recovery of oil from liquid phase. Figure 3 provides a

flowchart of this process. Apart from the steps described above, other unit operations can

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be employed depending on the chemical composition of the specific oil-bearing material.

For example, during corn germ oil extraction, before the incubation with enzyme, a

hydrothermal treatment step is applied to inactivate the intrinsic lipase and increase the

quality of oil obtained (Bocevska and others 1993; Dominguez and others 1994; Moreau

and others 2004; Dickey and others 2008). In the case of rapeseed or canola, seeds are

cooked prior to enzyme incubation with the objective of inactivating native enzyme

myrosinase which can produce some toxic compounds such as nitriles and isothiocyanate

during the extraction process (Rask and others 2000; Zhang and others 2007; Latif and

others 2008).

2.3.2 Forms of Oil Obtained by AEOE

Unlike in the organic solvent extraction process where oil is recovered as free oil,

AEOE produces oil in three forms: free oil, emulsified oil and oil in skim. In soybean,

presence of all three forms of oil has been reported by Rosenthal and others (2001). Both

emulsified and free oil were obtained from corn germ (Moreau and others 2004), rapeseed

(Zhang and others 2007), and coconut (Chen Man and others 1996; Sant’Anna and others

2003). Dominguez and others (1995) and Abdulkarim and others (2006) observed only

the emulsified form of oil from sunflower seeds and Moringa oleifera seed, respectively.

The forms of oil obtained from AEOE are dependent upon the compositions of the

oil-bearing materials as well as the processing parameters such as particle size of the

comminuted material, liquid to solid ratio, enzyme concentration, incubation time, and

shaking speed (Sharma and others 2002).

Since oil extracted by the aqueous enzymatic process is present in multiple forms that

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are usually difficult to separate, it is impossible to calculate the exact oil yield in one

particular form. As a result, oil extraction yield is usually calculated based on the total

amount of oil extracted into the liquid phase, which is the difference between the amount

of oil in the starting material and that in the solid residue after extraction (Bocevska and

others 1993; Rosenthal and others 1998; Sineiro and others 1998; Rosenthal and others

2001; Hanmoungjiai and others 2002; Lamsal and others 2006).

2.3.3 Factors Affecting AEOE Yields

AEOE yields are influenced by both the types of enzymes used and the processing

parameters employed.

2.3.3.1 Enzyme Type

The role of enzymes in AEOE from oil-bearing materials is to hydrolyze the

structural components of plant cells and facilitate the release of oil. Therefore, the

selection of enzymes is dependent on the composition of the cell wall and membrane that

form the boundary for oil bodies, and the cytoplasmic network where oil bodies are

imbedded. Plant cell wall is mainly comprised of cellulose, hemicelluloses and pectin

which all together account for 80-90% of the polysaccharides present (Dominguez and

others 1994). Protein as a dispensable structural component and other components are

present only at very low levels in cell wall (Keegstra and others 1973; Dominguez and

others 1994). Enzymes that are effective in breaking up the cell structure include but are

not limited to carbohydrases such as cellulase, hemicellulase and pectinase, and protease.

Commercial enzyme preparations including cellulase, hemicellulase, pectinase,

β-glucanase, α-amylase, and protease, have been utilized in AEOE. The individual or

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combined effects of these enzymes on various oil-bearing materials have been studied.

These studies have shown that enzymes have a significant effect on enhancing the oil

extraction yield when compared to the control which is carried out without enzymes

(Barrios and others 1990; Sinerio and others 1998; Moreau and others 2004; Abdulkarim

and others 2006; Lamsal and others 2006; Latif and others 2008; Womeni and others

2008). For example, the use of α-amylase for AEOE resulted in higher oil extraction yield

from avocado when compared to pectinase, protease, cellulase and different combinations

of these four enzymes (Buenrostro and Lopez-Munguia, 1986). Tano-Debrah and Ohta

(1994) reported that the highest increase in oil extraction yield from shea tree kernels was

achieved by a combination of protease and an enzyme with cellulase and hemicellulase

activities. Chen Man and others (1996) observed that in coconut oil extraction, a mixture

of cellulase, polygalacturonase, protease and α-amylase was more effective than when

these enzymes were used individually. According to Womeni and others (2008) the

highest oil extraction yield from Irvinia gabonensis seeds (68%) was obtained with a

mixture of carbohydrases (cellulase, arabanase, β-glucanase, hemicellulase and xylanase)

rather than protease or pectinase used individually. Protease was found to be superior to

α-amylase, pectinase and cellulase in extracting oil from Moringa oleifera seeds, but a

mixture of these four enzymes was even more effective (Abdulkarim and others 2006).

For rice bran oil extraction, protease was found to give higher oil extraction yield when

compared to cellulase, hemicellulase, pectinase and a mixture of cell wall-degrading

enzymes (cellulase, arabanase, β-glucanase, hemicellulase and xylanase) (Hanmoungjai

and others 2002). In rapeseed oil extraction pectinase, when used alone, was more

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effective than cellulase, β-glucanase and xylanase, but was less effective than the

combination of these 4 enzymes (Zhang and others 2007). A similar trend was observed

when Latif and others (2008) compared the effects of protease, pectinase, and mixtures of

cell wall-degrading enzymes on oil extraction yield from canola seeds. It was reported

that the use of protease for soybean (Lamsal and others 2006) and rice bran (Hanmougjai

and others 2002) oil extraction resulted in higher yields than those obtained from cell

wall-degrading enzymes. However, in corn germ oil extraction, protease resulted in lower

oil yield than that obtained by cell wall-degrading enzymes, especially cellulase (Moreau

and others 2004).

Not only do the types of enzymes, but also the specificity for pH and sources of the

same type of enzyme have different impacts on oil extraction yield. The order of

effectiveness of protease in improving oil extraction yield was found to be as follows:

alkaline protease > neutral protease > acid protease (de Moura and others 2008; Wu and

others 2009). It was also reported that fungal protease was superior to that extracted from

papaya (papain) (Hanmoungjai and others 2002). Cellulase secreted by Trichoderma

reesei showed higher efficacy in extracting oil than those produced by Trichoderma viride

and Aspergillus niger (Moreau and others 2004).

2.3.3.2 Particle Size

The particle size of the ground material is an important parameter for AEOE

efficiency. Smaller particle size indicates an efficient grinding which mechanically breaks

apart the cell structure of materials (Rosenthal and others 1996). In addition, smaller

particle size results in larger surface area which allows better contact between oil bearing

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material and solvent and reduces resistance to the diffusion of oil, as well as other

components, from the solid matrix to the aqueous medium. The rate of enzyme diffusion

into the solid substrate is also improved with smaller particle size (Rosenthal and others

1996). Although the importance of smaller particle size has been well recognized, only a

few studies have been carried out to investigate its effect on oil extraction yield. A study

by Rosenthal and others (2001) on soybean oil extraction yield showed that the oil

extraction yield increased with a decrease in particle size from 1200 µm to less than 200

µm. Santamaria and others (2003) found that the oil extraction yield of Chilean hazelnut

was enhanced when the particle size of the material was reduced from 1.6 mm to 0.4 mm.

2.3.3.3 pH and Temperature

The pH and temperature of water employed in AEOE are usually dictated by the

enzymes used, so the effect of these two factors on oil extraction efficacy can be

considered as their impacts on enzyme activities. The pH of solvent could actually change

the solubility of some cell components, especially that of protein. In AEOE, protein

solubility is closely associated with oil extraction yield. In general a high oil extraction

yield is obtained when the solubility or extraction yield of protein is high, which happens

when the pH is away from its isoelectric point (pI) (Rosenthal and others 1996; Rosenthal

and others 1998; Hanmoungjai and others 2002). The pI of protein usually varies

depending on the source. For example, the pI for soybean protein is around 4.5, while that

for sunflower protein is 4.0 (Rosenthal and others 1996). Therefore, it is important that

the pH employed in AEOE is away from the pI of the protein for a given material, in

order to obtain high oil extraction yield.

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2.3.3.4 Liquid: Solid Ratio

In general, the amount of solvent used for recovery of target substances is an

important parameter that must be optimized to achieve high extraction yields, so is the

case in AEOE. de Moura and others (2009) observed that the extraction yield of soybean

oil was enhanced as the liquid to solid ratio (LSR) increased from 5:1 to 10:1.

Hanmoungjai and others (2002) found an increase in rice bran oil extraction yield when

the liquid to solid ratio was increased from 4:1 to 5:1, but no more yield enhancement

was observed when this ratio was further increased to 10:1. For Chilean hazelnut oil

extraction, the increase in LSR from 3:1 to 5:1 improved the oil yield. However, a ratio of

6:1 resulted in decreased oil yield (Santamaria and others 2003). These observations

demonstrate that it is important to determine the minimum water: solid ratio resulting in

the highest oil yield, in order to minimize water use which leads to less energy

consumption in the extraction process, residual meal drying and waste processing.

2.3.3.5 Enzyme Concentration

In AEOE, the concentration of enzyme greatly affects the enzymatic reaction rate,

and thus influences the oil extraction yield for a given period of time. In plum kernel oil

extraction, the oil yield increased from 49 to 70% with an increase in enzyme

concentration (EC) from 0.05 to 1% (w/w) (Picuric-Jovanovic and others 1997). For

coconut oil extraction, the improvement in oil yield from 41 to 69% was achieved when

EC was increased from 0.1 to 1% (w/w) (Chen Man and others 1996). Zhang and others

(2007) reported an increment in the extraction yield of rapeseed oil when EC was

increased from 0.2 to 2.5% (v/w), but further increase in EC up to 5% did not bring

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additional improvement in extraction yield. In the extraction of Moringa oleifera seed oil,

Abdulkarim and others (2006) observed that the oil extraction yield was improved with

an increase in EC from 0.5 to 2.0% (v/w), and then decreased slightly at the concentration

of 2.5%. It is clear from above mentioned studies that there is an optimum EC that results

in maximum oil yield. However, economic feasibility of an AEOE process needs to be

determined by an optimization study that will balance EC, oil extraction yield and the

cost of enzyme (Zhang and others 2007).

2.3.3.6 Extraction Time

Action of enzyme on oil-bearing materials and mass transfer between the aqueous

medium and the material are time dependent processes. In most cases an increase in

extraction time (ET) results in an improvement in the oil extraction yield, but the

improvement slows down and eventually stops as time prolongs (Dominguez and others

1994; Sharma and others 2001; Sharma and others 2002; Abdulkarim and others 2006;

Zhang and others 2007). Hence time is a variable that needs to be included in process

optimization studies.

Several studies have reported the presence of significant interactions among ET, EC

and LSR indicating that these are not independent factors (Hanmoungjai and others 2001;

Zhang and others 2007; Womeni and others 2008). The optimum combination of these

factors needs to be investigated by employing an appropriate experimental design such as

factorial design or response surface methodology (RSM) in order to achieve the

maximum oil extraction yield.

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CHAPTER III

MATERIALS AND METHODS

3.1 SOURCE AND PREPARATION OF WHEAT GERM

Full-fat WG used in this study was obtained from ADM Milling Co. (Enid, OK,

U.S.A.). The sample was ground using a laboratory mill (Model 3600, Perten Instruments,

Sweden) and kept in an airtight plastic container at -20 oC until further use for proximate

composition analysis and extraction tests.

3.2 ENZYME SELECTION

Initial enzyme screening tests were carried out by using 3 carbohydrases (Viscozyme

L, Multifect CX GC and Multifect CX 13L) and 1 protease (Alcalase 2.4L FG). Selection

of these enzymes was based on the chemical composition of wheat germ.

3.2.1 Viscozyme L

This enzyme was kindly provided by Novozymes (Bagsvaerd, Denmark). Viscozyme

L is produced from a selected group of Aspergillus strains. The enzyme contains a variety

of carbohydrases (arabanase, cellulase, β-glucanase, hemicellulase and xylanase), and has

a declared activity of 100 FBG/g. One FBG is the amount of enzyme which releases

glucose or reducing sugar equivalent to 1 µmol glucose from β-glucans at pH 5.0 and 30

oC in one minute. The optimum conditions for the activity of this enzyme are pH 3.3-5.5

and a temperature of 40-50 oC.

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3.2.2 Multifect CX GC

Multifect CX GC, an enzyme with cellulase activity, is provided by Genencor

(Rochester, NY, U.S.A). This enzyme is derived from a selected strain of Trichoderma

reesei, and has side activities including hemicellulase, xylanase, and β-glucanase. The

declared activity is 3200 CMC/g. One CMC unit is defined as the amount of enzyme

which produces 1 µmol glucose equivalent from carboxymethyl cellulose at pH 5.0 and

50 oC in one minute. This enzyme is effective at a pH of 2.7-5.7 and temperature of 35-70

oC.

3.2.3 Multifect CX 13L

Multifect CX 13L, a mixture of several enzymes, was also provided by Genencor

(Rochester, NY, U.S.A). It is produced from selected strains of Trichoderma reesei and

Penicillium funiculosum. The enzyme, with a specified activity of 3900 CMC/g, exhibits

significant activity towards cellulose, hemicelluloses, β-glucans and arabinoxylans. This

enzyme mixture is active over the pH range of 3.5-6.0 and temperatures between 40 and

75 oC.

3.2.4 Alcalase 2.4L FG

This enzyme was obtained from Novozymes (Bagsvaerd, Denmark). It is an alkaline

endoproteinase produced from a selected strain of Bacillus licheniformis and has a

declared activity of 2.4 AU/g. The definition for AU is given in the article by Zhao and

others (2003). The enzyme has an optimum activity at temperatures between 50 and 55 oC

and pH of 7.5-8.5.

3.3 ENZYME SCREENING TESTS

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Ground WG (15 g) was mixed with 180 ml buffer in a 500 ml flask, to achieve a LSR

of 12: 1 (v/w). For Viscozyme L, Multifect CX GC and Multifect CX 13L 0.15M

citric-phosphate buffer at pH 5.0 was used. Two different buffers, 0.12M boric

acid-NaOH and 0.1M Tris-HCl, at pH 8.0 were used for Alcalase 2.4L FG. The mixture of

WG and buffer was placed in a water bath shaker (Model C76, New Brunswick Science,

Edison, NJ, USA), and heated to 50 oC with constant shaking at 200 rpm. Enzymes were

added at a concentration of 5% (w/w) based on the weight of the WG. Then the mixture

was incubated for 4 h. After the incubation, the mixture was centrifuged in a bench top

centrifuge (Sorvall RC 5C, Termo, Ashwville, NC, USA) at 13,000 rpm and 25 oC for 15

min. The liquid phase was drained off, and 180 ml deionized water was added to the

centrifuge tube containing wet residual solids to wash away the oil which may remain on

the wall of the centrifuge tube and in the solid matrix. The wet residue was well mixed

with the deionized water, and subjected to a second centrifugation under the same

conditions used before. The liquid phase was drained off once again. The wet residue was

dried in a forced-air oven (VWR Science, model 1370 FM, Bristol, CT) at 85 oC for 16 h.

The dried residue was weighed and analyzed for oil content. The oil extraction yield is

calculated by the following formula:

Oil extraction yield (%) = Total oil in wheat germ - oil in residue

* 100% (1) Total oil in wheat germ

Four different oil extraction runs without enzyme were conducted as controls. The

first control was carried out with deionized water (pH 6.6) as the aqueous solvent.

Citric-phosphate buffer at pH 5.0, boric acid-NaOH buffer at pH 8.0, and Tris-HCl buffer

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at pH 8.0 were the other controls. Other processing parameters were kept the same as

those for the enzymatic process during the control experiments. A schematic flow

diagram of the extraction process is shown in Figure 4.

3.4 OPTIMIZATION BY RESPONSE SURFACE METHODOLOGY

Based on the results of the experiments described above, Alcalase 2.4L FG and

Multifect CX GC were chosen for the optimization experiments. In the case of Alcalase,

both boric acid-NaOH and Tris-HCl buffers were used to investigate the effect of

processing parameters on oil extraction yield under different buffer systems. Response

Surface Methodology (RSM) with central composite design was employed. Three

processing parameters, LSR, ET, and EC at 5 levels each were investigated as the

independent variables to estimate the oil extraction yield in the enzymatic process. The

actual and coded levels of the three independent variables are shown in Table 1. Control

experiments were also carried out for each enzyme. The levels of LSR and ET for the

control experiments were the same as those used in the enzymatic process. The

experimental designs for the non-enzymatic and enzymatic processes are presented in

Table 2 and 3, respectively. The extraction procedure and the other processing parameters

used in these optimization experiments were kept the same as those employed in the

experiments described in section 3.3.

3.5 ANALYTICAL METHODS

3.5.1 Moisture Content

The moisture content of the ground WG was determined according to AACC method

44-15A (AACC, 1995). The ground WG was brought to room temperature before use.

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Aluminum moisture dishes were pre-dried in a forced-air oven (VWR Science, model

1370 FM, Bristol, CT) at 130 oC for 1 h prior to analysis, and then cooled in a desiccator

to room temperature. About 2 g of sample were weighed in the pre-dried aluminum dish,

and dried in the oven at 130 oC for 1 h. The moisture content of the sample was reported

as the loss in sample weight as percentage of the initial sample weight.

3.5.2 Ash Content

The ash content of the ground WG was measured by AOAC method 923.03 (AOAC,

1995). The ground WG was taken out of the freezer and cooled to room temperature prior

to use. Crucibles were pre-dried in a furnace (Fisher Science, Model 58 Isotemp® Muffle

Furnace 600 Series, Fair Lawn, NJ) at 525 oC for 5 h, and then cooled down to room

temperature in a desiccator. Approximately 2 g of the ground wheat germ were weighed

into the pre-dried crucible and ashed at 525 oC for 5 h. The percentage residual weight

was reported as the ash content of the sample.

3.5.3 Oil Content

The oil contents of the ground WG and the dried residue after extraction were

measured according to AOAC method 2003.05 (AOAC, 2005). Samples were brought to

room temperature before analysis. About 1 g of sample was weighed in a cellulose

thimble, and extracted in a Soxtect extraction unit (Tecator, Model 1043 Extract Unit,

Sweden) with 40 ml of petroleum ether (Mallinckrodt, Paris, KE) for 1 hour. The amount

of oil extracted as the percentage of initial sample weight was reported as the oil content

in the sample.

3.5.4 Protein Content

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The amount of protein in the ground WG was determined by the method of Forage

Analyses Procedures (1993). Protein was analyzed as nitrogen on a Leco Truspec

carbon-nitrogen analyzer (Truspec CN, Leco USA, St. Joseoh, MI). A factor of 5.7 was

used to convert the amount of nitrogen to the amount of protein in the sample.

3.5.5 Starch Content

Starch content of the ground wheat germ was determined according to AOAC

method 996.11 (AOAC, 2005), which is based on the use of thermostable α-amylase and

amyloglucosidase.

3.5.6 Enzyme Activity Test

3.5.6.1 Viscozyme L

The activity of Viscozyme L was determined using the Somogyi-Nelson method

provided by the Joint Food and Agriculture Organization of the United Nations

(FAO)/World Health Organization (WHO) Expert Committee on Food Additives (JECFA),

and expressed in fungal beta-glucanase unit per gram (FBG/g) (JECFA 2000).

3.5.6.2 Multifect CX GC

The activity of this enzyme was measured in CMC/g according to the method

provided by JECFA (2003).

3.5.6.3 Multifect CX 13L

The method used to determine the activity of Multifect CX 13L was the same as that

for Multifect CX GC.

3.5.6.4 Alcalase 2.4L FG

The activity of Alcalase 2.4L FG was determined according to the method provided

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by Megazyme (Wicklow, Ireland), and expressed as Unit/g (Megazyme 2006). One Unit

is defined as the amount of enzyme that produces the equivalent of 1 µmol tyrosine per

minute from soluble casein at pH 8.0 and 40 oC.

3.6 STATISTICAL ANALYSIS

All analytical tests and extraction experiments were carried out at least in duplicate

and in randomized order with the mean values being reported. Analysis of variance

(ANOVA) of the results from enzyme screening and the analysis of RSM experiments

were performed using SAS 9.1 (SAS Institute Inc., 2003).

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CHAPTER IV

RESULTS AND DISCUSSION

4.1 CHARACTERIZATION OF WHEAT GERM

The proximate composition of the ground WG used for the optimization tests is

shown in Table 4. The moisture content of the sample was about 11%. The high moisture

content of WG is due to the fact that whole wheat grain moisture content is adjusted to

about 13 to 15% prior to milling. The reasons for the moisture adjustment were discussed

earlier in section 2.1.1 of this thesis. The oil content of the WG extracted by petroleum

ether was about 11% (w/w, as is basis) (Table 4). This result is in agreement with the data

reported in the literature for commercial WG (Barnes 1982; Dunford and Zhang 2003;

Zhu and others 2006), but is much lower than that obtained from dissected WG, 25-30%

(Hargin and Morrison 1980). The lower oil content in commercial WG is because of the

contamination from bran which usually contains less than 5% oil and significant amount

of starchy endosperm (Barnes 1982). Indeed, about 9% starch was detected in our

samples (Table 4). This is much lower than that reported by Barnes (1982), 20%. WG is

well known as a rich source of plant protein. According to the literature, WG contains 26

to 36% protein (Barnes 1982; Ge and others 2000; Claver and Zhou 2005; Zhu and others

2006). WG used in this study had about 34% protein (Table 4) which is within the range

reported in literature. The level of ash in WG was similar to that reported in literature

(Barnes 1982; Zhu and others 2006). Other components, which account for about 30% of

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WG, may comprise mainly non-starch carbohydrates including free sugars such as

sucrose and raffinose, fiber and pentosans (Dubois and others 1960; Amado and Arrigoni

1992).

The particle size distribution of the ground WG used in this study is presented in

Table 5. About 89% of the ground WG had a particle size between 150 and 500 µm. The

size of the ground WG is much smaller than those reported in literature, 1 mm or larger

(Dominguez and others 1995; Sengupta and Bhattacharyya 1996; Hanmoungjai and

others 2001; Santamaria and others 2003), indicating a sufficient grounding of the WG.

4.2 EFFECT OF ENZYME TYPE ON OIL EXTRACTION YIELD

The activities of the enzymes measured prior to screening tests as well as their

declared activities by the suppliers are presented in Table 6. There were discrepancies

between measured and the declared activities for Viscozyme L, Multifect CX 13L and

Multifect CX GC. This is because of the slight variations in analytical protocols used for

the activity measurements.

The oil extraction yields obtained from aqueous extraction processes with and

without enzymes (the controls) are shown in Figure 5. It was found that the control tests

carried out at pH 8.0 (controls 3 and 4) resulted in significantly higher oil yields than

those conducted at pH 6.6 and 5.0 (controls 1 and 2). The effect of pH on oil extraction

yield may be due to their influence on the solubility of proteins. The pI of WG protein is

around 4.0 (Ge and others 2000). Although pH 5.0 and 6.6 are higher than pI of WG, it

appears that most proteins still remain insoluble at these pH values. Indeed, a preliminary

protein analysis on the residual WG after extraction indicated that at low pH protein

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extraction yields were lower than those at pH 8 (unpublished data). At pH 8.0, which is

far away from the pI 4.0, the solubility of WG protein is enhanced greatly. Since oil

bodies are embedded in the matrix of proteins in the cytoplasmic network of the cell, the

increased solubilization of protein into the aqueous medium consequently results in the

increased oil release from the WG. As can be seen from Figure 5, oil extraction yield

obtained with boric acid-NaOH buffer at pH 8.0 (control 3) was significantly lower (p <

0.05) than that obtained with Tris-HCl buffer at pH 8.0. This might be due to the

interaction of buffer components with proteins. A comparison of the oil extraction yields

with the four controls indicates that both pH and buffer system play an important role in

the aqueous extraction of WGO.

This study demonstrated that Alcalase 2.4L FG gave significantly higher oil yield

than Viscozyme L, Multifect CX 13L and Multifect CX GC (Figure 5). This finding is

consistent with the results obtained with rice bran (Hanmoungjai and others 2002),

coconut (Chen Man and others 1996), Moriga oleifera seed (Abdulkarim and others

2006), and soybean (Rosenthal and others 2001), where proteases and carbohydrases

were compared for their effects on oil extraction yield. No significant difference was

observed among the oil extraction yields obtained by Viscozyme L, Multifect CX 13L and

Multifect CX GC.

The effects of Alcalase 2.4L FG in two different buffer systems were also

investigated (Figure 5). The experimental results showed that Alcalase 2.4L FG produced

a significantly higher oil yield in Tris-HCl buffer than that in boric acid-NaOH buffer. As

mentioned in the first paragraph of this section, a similar trend was observed during

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non-enzymatic extraction tests.

Oil yields from control (control 4) and Alcalase 2.4L FG treated samples were not

significantly different (p > 0.05) when extraction was conducted in Tris-HCl buffer

system. However, Alcalase 2.4L FG produced a significantly lower oil yield than the

control (Control 3) when boric acid-NaOH buffer was used. This result is in contrast with

most of the studies that reported an increased oil yield when extraction is carried out with

an enzyme (protease) (Chen Man and others 1996; Rosenthal and others 2001;

Hanmoungjai and others 2002; Abdulkarim and other 2006). Viscozyme L, Multifect CX

13L and Multifect CX GC did not improve the oil yield when compared to the control

(control 2). Further investigation of the effect of Alcalase 2.4L FG on WGO extraction

was performed by RSM that will be discussed in the next section. Among the three

carbohydrases, Multifect CX GC was further investigated for its efficacy on WGO

extraction by RSM in this study. Commercial availability of this enzyme and its reported

efficacy in extracting oil from corn germ (Moreau and others 2004) were the main

reasons for selection of this enzyme for further investigation.

4.3 OPTIMIZATION OF AQUEOUS EXTRACTION PROCESS

Optimization tests were carried out using two enzymes, one protease and one

carbohydrase, Alcalase 2.4L FG and Multifect CX GC, respectively. The stability of these

enzymes was monitored by weekly activity measurements throughout the study. Figures 6

and 7 indicate that the activities of the enzymes did not change significantly during the

experimental period. Non-enzymatic aqueous extraction of WGO was also evaluated by

RSM.

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The experimental data obtained from the RSM design for processes with and without

enzymes are shown in Tables 7 and 8, respectively. For the non-enzymatic process in

boric acid-NaOH buffer at pH 8.0, the oil extraction yields ranged from 15.62 to 47.7%,

both of which were obtained at ET of 0.5 h, and LSRs of 4 and 20, respectively (Table 7).

The range of the oil yield was broader when Tris-HCl buffer at pH 8.0 was used for WGO

extraction, 3.97 - 48.07%. The lowest and highest yields were observed at LSR of 12, and

ETs of 24 and 0.5 h, respectively. In citric-phosphate buffer at pH 5.0, the non-enzymatic

process resulted in oil yields ranging from 2.07 to 17.07%, which were at LSR of 20 and

ET of 0.5 h, and LSR of 4 and ET of 12.25 h, respectively.

For the enzymatic process with Alcalase 2.4L FG in boric acid-NaOH buffer at pH

8.0 (Alcalase-B), the lowest oil yield of 2.79% was obtained at LSR, EC and ET of 4,

2.55% and 12.25 h, respectively. The highest oil yield of 36.32% was at LSR, EC and ET

of 16.5, 4% and 5.25 h, respectively (Table 8). In Tris-HCl buffer at pH 8.0, the oil

extraction yields obtained by Alcalase 2.4L FG ranged from 10.63 to 66.45%. The

extraction conditions which resulted in the lowest and highest oil yields were the same in

both buffer systems. It appears that Tris-HCl buffer is a better choice for WGO extraction

than boric acid-NaOH. As mentioned earlier in this thesis, the effect of buffer on

extraction yield might be due to difference in interaction of buffer components with WG

proteins.

The oil yields varied between 2.57 and 22.99% when Multifect CX GC was used for

WGO extraction (Table 8). The lowest value was observed at LSR of 16.5, EC of 4 and

ET of 5.25. The highest value was obtained at LSR of 4, EC of 2.55%, and ET of 12.25 h.

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In summary, the non-enzymatic processes resulted in higher oil yield at pH 8.0 than at pH

5.0. The enzymatic process with Alcalase 2.4L FG in Tris-HCl (Alcalase-T) buffer gave

the highest oil yield.

The following quadratic models were developed to explain the relationship between

the oil extraction yield and processing parameters in the six extraction processes.

YB (%) = 12.02 + 0.1R + 0.14R2 + 0.22T + 0.035T2 – 0.13R*T (2)

YT (%) = 76.01 – 4.58R + 0.22R2 – 4.88T + 0.14T2 – 0.04R*T (3)

YC (%) = 12.72 – 1.11R + 0.022R2 + 0.94T – 0.012T2 – 0.021R*T (4)

YAlcalase-B (%) = –13.11 + 0.75R + 0.02R2 + 7.88C – 0.21C2

+ 1.03T – 0.016T2 + 0.027R*T – 0.0044R*C – 0.49C*T (5)

Y Alcalase-T (%) = 20.7 – 3.15R + 0.28R2 + 13.19C + 2.06C2

- 1.41T + 0.11T2 + 0.049R*T – 0.88R*C – 0.95C*T (6)

Y Multifect (%) = 21.36 – 2.26R + 0.064R2 + 0.85C – 0.2C2

+ 0.57T – 0.013T2 – 0.0035R*T – 0.052R*C + 0.046C*T (7)

YB, YT, and YC represent the estimated oil extraction yields for the non-enzymatic

processes in boric acid-NaOH at pH 8.0, Tris-HCl at pH 8.0 and citric-phosphate buffer at

pH 5.0, respectively. Y Alcalase-B, Y Alcalase-T, and YMultifect represent the estimated oil

extraction yields in the enzymatic processes with Alcalase-B, Alcalase-T, and Multifect

CX GC, respectively. R, C and T are the processing parameters LSR, EC and ET,

respectively.

All the response surface models shown above were significant (p < 0.05) (Tables 9

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and 10). The models developed for the non-enzymatic processes (Equations 2-4)

satisfactorily explain the oil extraction yield in relation to the processing parameters,

which is evident from the high coefficients of determination (R2 > 0.94) (Table 9). For the

enzymatic processes, the models established for oil yield from Multifect CX GC and

Alcalase-T treated WG had the highest and lowest R2 (0.9267 and 0.49), respectively

(Table 10). A significant lack of fit is detected for all the models. However, the residual

analysis showed that for each model, there are only one or two outliers contributing to the

significant lack of fit. Although there is a significant lack of fit, the high R2 values for

most of the models, except for the one for Alcalase-T, support the adoption choice of the

models. In these cases, the information about the effects of the processing parameters can

still be investigated from the analysis.

The variables that had significant effects on oil extraction yield in boric acid-NaOH

buffer were the quadratic terms of LSR and ET, and the interaction term of these two

parameters (Table 11). In the case of Tris-HCl buffer, the variables with significance were

the linear and quadratic terms of LSR, and EC. The interaction term for LSR/ET was not

significant. For the citric-phosphate buffer system, the linear terms of LSR and ET were

significant. No interaction was observed between LSR and ET.

The estimated coefficients of the quadratic models for enzymatic processes are

shown in Table 12. The terms for linear EC, and EC/ET interaction for WG treated with

Alcalase-B were significant (Table 12). When Alcalase-T system was used for WGO

extraction, the EC/ET interaction term was the only variable that showed significance.

The linear and quadratic terms of LSR and the linear term of ET were significant for

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Multifect CX GC. No interactions between LSR, EC and ET were observed in this

process.

Figure 8 shows the response surface for the predicted oil extraction yield by the

non-enzymatic process in boric acid-NaOH buffer, as a function of LSR and ET. The

corresponding contour is presented in Figure 9. An increase in LSR improved the oil

extraction yield. At low LSR, the oil yield increased slightly with increasing ET. At high

LSR oil yield decreased with increasing ET. This is due to the interaction between these

two parameters. In Tris-HCl buffer, an increase in LSR caused an enhancement in the oil

extraction yield at short ET. When the ET was increased, the oil yield decreased

drastically (Figures 10 and 11). For the non-enzymatic process in citric-phosphate buffer,

an increase in LSR resulted in a decrease in the oil extraction yield. Higher ET lead to an

enhancement in the oil yield (Figures 12 and 13). It is clear that LSR and ET influence the

oil extraction yield in completely opposite ways in the non-enzymatic processes at pH 8.0

and 5.0, indicating the important role of pH in aqueous oil extraction. The buffer system

also has a significant impact on oil yield which was evident from the different shapes of

the response surfaces for oil yield in Tris-HCl and boric acid-NaOH buffers (Figures 8

and 10). The oil yield obtained at pH 5.0 was generally lower than those obtained at pH

8.0. The highest oil extraction yield by the non-enzymatic process, 70%, was predicted at

LSR of 20 and ET of 0.5 h for both boric acid-NaOH and Tris-HCl buffers.

Figures 14 - 19 show the response surfaces and the contours for oil extraction yield

with Alcalase-B, as a function of LSR, ET at EC of 0.1, 2.5 and 5%. An increase in EC

from 0.1 to 5% did not increase the overall oil yield, but it did alter the shape of the

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response surface. The change in the shape is due to the interaction between EC and ET. At

low EC an increase in ET resulted in an enhancement in oil yield (Figures 14 and 15). At

medium EC,an increase in ET did not have a significant effect on oil yield (Figures 16

and 17). A decrease in oil yield with the increase in ET was observed at high EC (Figures

18 and 19). The increase in LSR lead to an improvement in the oil yield regardless of the

EC, which means there is no interaction between LSR and EC. In the Alcalase-B process

at low EC (0.1%) high oil extraction yields were obtained at high ET (Figures 14 and 15).

However at high EC (5%) high oil yield was obtained at low ET (Figures 18 and 19).

Figures 20-25 are the response surfaces and the contours for oil yield obtained with

Multifect CX GC as a function of LSR and ET at EC of 0.1, 2.5 and 5%. An increase in

EC did not improve the oil yield, nor did it change the shape of the response surface,

indicating no interaction between EC, LSR and ET. The oil extraction yield increased

with the increasing ET and decreased with increasing LSR. This trend is similar to that

observed with the corresponding non-enzymatic process.

The response surfaces and contours for oil yield obtained with Alcalase-T, as a

function of LSR and ET at EC of 0.1, 2.5 and 5%, are presented in Figures 26-31.

However, the relationship between the oil yield and LSR, ET and EC in this process is not

discussed in this thesis because of the low R2 (0.49) of the model developed and lack of

fit. It is obvious that within the experimental range, the processing parameters interact

with each other in a more complex manner in Alcalase-T process than in other processes

investigated. For Alcase-B the highest predicted oil yield was about 40%. In general oil

yield from Multifect CX GC was lower than the other two enzyme systems examined in

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this thesis.

Although the highest predicted oil yield for Alcalase-B was about 40%, this value is

much lower than that for the corresponding non-enzymatic process (about 70%). The

highest predicted oil yield for both the enzymatic process with Multifect CX GC and the

corresponding non-enzymatic process (citric-phosphate buffer at pH 5.0) was very low,

about 20%, indicating that this enzyme did not have a significant effect on the oil

extraction yield. This result is in contrast with that obtained with corn germ (Moreau and

others 2004) where Multifect CX GC improved the oil extraction yield significantly as

compared to the control. This might be because of the differences in chemical

composition of WG and corn germ. Fiber content of corn germ (11.4%) (Ronyai and

others 1998) is much higher than that of WG (3%) (Barnes 1982). Since fiber is a

substrate for cellulase, Multifect CX GC works better with high fiber content material.

Cellulase alone is probably not enough to destroy the WG cell structure and release the oil

because of its low fiber and high protein contents.

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CHAPTER V

CONCLUSION

In this study four enzymes, Viscozyme L, Multifect CX 13L, Multifect CX GC and

Alcalase 2.4L FG, were screened for their efficacies to extract oil from WG. Two different

buffer systems (boric acid-NaOH and Tris-HCl) were employed for Alcalase 2.4L FG

(protease). The results from the screening experiments showed that all four enzymes

failed to improve oil extraction yield when compared to the corresponding controls under

the conditions chosen for the screening studies. Alcalase 2.4L FG and Multifect CX GC

were selecetd for optimization of processing parameters for maximum oil extraction yield

by using RSM. The corresponding non-enzymatic processes were also optimized. In

general, the models developed for oil extraction yield satisfactorily explained the

relationship between oil yield and processing parameters in most processes, expect for the

process with Alcalase –T. The results showed that the effects of processing parameters

and their interactions varied depending on both enzyme type and buffer system. The

highest predicted oil yield was about 40% when Alcalase-B was used for extraction.

However, this yield was much lower than that of the corresponding non-enzymatic

process (about 70%). The highest predicted oil yield with Multifect CX GC was about

20%, which was not significantly different from that of the corresponding non-enzymatic

process. In conclusion, AEOE was not effective in extracting oil from WG within the

range of processing parameters investigated in this study.

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FUTURE RESEARCH

In this study, the experimental data from the RSM design showed that the Alcalase-T

process resulted in the highest oil extraction yield observed. However, the model

developed for this system had a low R2 (0.49). Further research should be conducted to

refine experimental range within which a model can satisfactorily explain the relationship

between oil extraction yield and the processing parameters, and thus maximizing the oil

extraction. Since the non-enzymatic process at pH 8.0 can produce an oil yield as high as

70%, an extraction process involving a non-enzymatic process followed by an enzymatic

treatment should be considered with the objective of achieving higher oil yields. Mixtures

of protease and cellulase should also be examined for their combined efficiency to

recover oil from WG.

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Table 1: Coded and actual levels of the independent variables.

Independent variables Factor level

-1.68 -1 0 +1 +1.68

Liquid: solid Ratio 4 7.5 12 16.5 20

Enzyme concentration (%) 0.1 1.1 2.55 4 5

Extraction time (h) 0.5 5.25 12.25 19.25 24

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Table 2: Experimental design for non-enzymatic processes by Response Surface Methodology.

Run Liquid : solid ratio Extraction time

1 -1 -1 2 -1 1 3 1 -1 4 1 1 5 -1.68 0 6 0 1.68 7 1.68 0 8 0 -1.68 9 0 0 10 0 0

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Table 3: Experimental design for enzymatic processes by Response Surface Methodology.

Run Liquid: solid ratio Enzyme concentration Extraction time

1 -1 -1 -1 2 -1 -1 1 3 -1 1 -1 4 1 -1 -1 5 -1 1 1 6 1 -1 1 7 1 1 -1 8 1 1 1 9 -1.68 0 0

10 0 -1.68 0 11 0 0 -1.68 12 1.68 0 0 13 0 1.68 0 14 0 0 1.68 15 0 0 0 16 0 0 0

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Table 4: Proximate composition of wheat germ.

Component g/100g germ *

Moisture 11.01 ± 0.19

Oil 11.17 ± 0.12

Protein 33.79 ± 0.32

Starch 9.08 ± 0.08

Ash 4.86 ± 0.02

Other components (deduced by difference) 30.09

*Values are means ± SD.

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Table 5: Particle size distribution of ground wheat germ.

Particle size (µm) Weight percentage (%)

>500 5.85

150-500 88.58

<150 3.86

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Table 6: Enzymes used in this study and their activities.

Enzyme Activity a Activityb

Viscozyme L 170 FBG/g 100FBG/g

Multifect CX 13L 2294 CMC/g 3900CMC/g

Multifect CX GC 4338 CMC/g 3200CMC/g

Alcalase 2.4L FG 12.7 U/g 2.4 AU/g

a Initial activity of the enzymes prior to enzyme screening tests. b Activity declared by the suppliers.

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Table 7: Observed and predicted oil extraction yield (%) for non-enzymatic processes.

Run pH 8.0 (Boric acid-NaOH) pH 8.0 (Tris-HCl) pH 5.0 (Citric-phosphate) Observed

value Predicted

value Observed

value Predicted

value Observed

value Predicted

value 1 19.10 17.72 35.54 30.97 10.10 16.38 2 18.50 19.28 9.64 6.32 17.03 16.29 3 42.83 42.99 38.56 36.38 4.83 3.18 4 25.66 27.97 7.64 6.71 9.06 7.39 5 15.62 16.34 17.42 20.5 17.07 17.31 6 23.27 21.65 3.97 5.17 11.39 12.25 7 47.70 46.54 25.27 25.66 2.61 3.89 8 31.99 32.94 48.07 50.77 2.07 2.91 9 22.48 22.38 6.77 8.72 8.55 9.17 10 22.89 22.38 7.05 8.72 8.21 9.17

Refer to Table 2 for experimental design.

45

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Table 8: Observed and predicted oil extraction yield (%) for enzymatic processes.

Run Alcalase-B Alcalase-T Multifect CX GC

Observed value

Predicted value

Observed value

Predicted value

Observed value

Predicted value

1 8.09 5.16 41.41 14.67 9.47 11.04 2 8.55 9.42 20.44 24.7 13.06 14.98 3 20.77 17.38 56.94 49.72 8.97 10.13 4 19.46 17.38 48.89 40.15 4.43 3.87 5 5.61 1.72 22.16 20.99 14.40 15.92 6 27.58 25 59.00 56.32 7.57 7.38 7 36.32 29.49 66.45 52.28 2.57 1.62 8 20.23 17.19 12.87 29.7 7.59 6.98 9 2.79 5.1 10.63 23.11 22.99 19.99

10 11.94 13.03 13.97 29.25 9.23 8.08 11 11.16 17.36 12.49 41.6 3.34 3.09 12 24.48 29.72 53.46 53.5 3.90 5.67 13 9.49 16.75 37.77 36.37 7.18 6.98 14 8.36 10.62 46.11 31.07 12.02 10.9 15 17.14 16.14 19.88 20.46 8.51 8.73 16 15.66 16.14 21.90 20.46 8.86 9.38

Refer to Table 3 for experimental design.

46

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Table 9: Analysis of variance for response surface quadratic models for the non-enzymatic processes.

Non-enzymatic processes Source Sum of squares Degree of freedom Mean square F-value P > F

pH 8.0 (Boric acid-NaOH)

Model 2009.12 5 401.82 144.61 <0.0001 Residual 38.9 14 2.78 Lack of fit 26.56 3 8.85 7.89 0.0044 Pure error 12.34 11 1.12 Total 2048.02 19 coefficient of variance=6.17%, R2=0.9810

pH 8.0 (Tris-HCl)

Model 4411.16 5 882.23 78.14 <0.0001 Residual 158.07 14 11.29 Lack of fit 124.77 3 41.59 13.74 0.0005 Pure error 33.3 11 3.03 Total 4569.23 19 coefficient of variance=16.81%, R2=0.9654

pH 5.0 (Citric-Phosphate)

Model 464.95 5 92.99 46.27 <0.0001 Residual 28.13 14 2.01 Lack of fit 22.04 3 7.35 13.26 0.0006 Pure error 6.09 11 0.55 Total 492.08 19 coefficient of variance=15.59%, R2=0.9429

P < 0.05 indicates statistical significance.

47

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Table 10: Analysis of variance for response surface quadratic models for the enzymatic processes.

Enzymatic processes Source Sum of squares Degree of freedom Mean square F-value P > F

Alcalase-B

Model 1951.57 9 216.84 9.66 <0.0001 Residual 493.93 22 22.45 Lack of fit 466.64 5 93.33 58.14 <0.0001 Pure error 27.29 17 1.61 Total 2445.5 31 coefficient of variance=30.62%, R2=0.7980

Alcalase-T

Model 5450.64 9 605.63 2.33 0.0509 Residual 5715.66 22 259.8 Lack of fit 5639.49 5 1127.9 251.74 <0.0001 Pure error 76.17 17 4.48 Total 11166 31 coefficient of variance=47.38%, R2=0.4881

Multifect CX GC

Model 704.39 9 78.27 30.9 <0.0001 Residual 55.73 22 2.53 Lack of fit 52.53 5 10.51 55.75 <0.0001 Pure error 3.2 17 0.19 Total 760.12 31 coefficient of variance=17.67%, R2=0.9267

P < 0.05 indicates statistical significance.

48

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Table 11: Estimated coefficients of the quadratic models for non-enzymatic processes.

Ratio and time represent liquid: solid ratio and extraction time, respectively.

pH 8.0 (Boric acid-NaOH) pH 8.0 (Tris-HCl) pH 5.0 (Citric-phosphate)

Variable Parameter Estimate p Value Variable Parameter

Estimate p Value Variable Parameter Estimate p Value

intercept 12.02 0.0113 intercept 76.01 <0.0001 intercept 12.72 0.0027

Ratio 0.1 0.8451 ratio -4.58 0.0005 ratio -1.11 0.0211

ratio*ratio 0.14 <0.0001 ratio*ratio 0.22 <0.0001 ratio*ratio 0.022 0.174

Time 0.22 0.4832 time -4.88 <0.0001 time 0.94 0.0033

time*time 0.035 0.0009 time*time 0.14 <0.0001 time*time -0.012 0.1356

ratio*time -0.13 <0.0001 ratio*time -0.04 0.3091 ratio*time -0.021 0.1994

49

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Table 12: Estimated coefficients of the quadratic models for enzymatic processes.

Alcalase-B Alcalase-T Multifect CX GC

Variable Parameter Estimate p Value Variable Parameter

Estimate p Value Variable Parameter Estimate p Value

intercept -13.11 0.3259 intercept 20.7 0.6454 intercept 21.36 <0.0001

ratio 0.75 0.5932 ratio -3.15 0.508 ratio -2.26 <0.0001

ratio*ratio 0.2 0.6935 ratio*ratio 0.28 0.114 ratio*ratio 0.064 0.0009

conc 7.88 0.0493 conc 13.19 0.317 conc 0.85 0.509

conc*conc -0.21 0.6963 conc*conc 2.06 0.2618 conc*conc -0.2 0.2695

time 1.03 0.2066 time -1.41 0.603 time 0.57 0.0441

time*time -0.016 0.5019 time*time 0.11 0.1523 time*time -0.013 0.1152

ratio*time 0.027 0.4857 ratio*time 0.049 0.7069 ratio*time -0.0035 0.7872

ratio*conc -0.0044 0.9809 ratio*conc -0.88 0.1691 ratio*conc -0.052 0.4072

conc*time -0.49 0.0004 conc*time -0.95 0.025 conc*time 0.046 0.2575 Ratio, conc and time represent liquid: solid ratio, enzyme concentration and extraction time, respectively.

50

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Figure 1: Structure of Wheat grain (Modified from Fenneman 1985).

Bran

Embryo

Germ

Endosperm

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Figure 2: Structure of an oil body (Waltermann and Steinbuchel 2005).

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Figure 3: Aqueous enzymatic oil extraction process.

Oil-bearing material

Grinding

Mixing with water or buffer Enzyme

Incubation

Centrifugation

Oil-containing liquid phase Solid phase

Recovering of oil

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Figure 4: A schematic of aqueous enzymatic oil extraction procedure employed in this study.

Oil-bearing material

Grinding

Mixing with water or buffer Enzyme

Incubation

Centrifugation

Liquid phase Solid phase

Washed with 180ml Deionized water

Centrifugation

Oil-containing liquid phase Solid phase

Dried at 85 °C, weighed and ground, and then determined for oil content

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Figure 5: Oil extraction yields by different enzymes.

Control 1: With deionized water. Control 2: With citric-phosphate buffer at pH 5. Control 3: With boric acid-NaOH buffer at pH 8.0. Control 4: With Tris-HCl buffer at pH 8.0. Viscozyme L: Viscozyme L in citric-phosphate buffer at pH 5. Multifect CX 13L: Multifect CX 13L in citric-phosphate buffer at pH 5. Alcalase-B: Alcalase 2.4L FG in boric acid-NaOH buffer at pH 8.0. Alcalase-T: Alcalase 2.4L FG in Tris-HCl buffer at pH 8.0. Multifect CX GC: Multifect CX GC in citric-phosphate buffer at pH 5.

Error bars represent SD. Means with the same letter are not significantly different from each other (P<0.05).

a a

bc

a a

d

c

a

0.0

10.0

20.0

30.0

40.0

50.0

60.0

Contro

l 1

Contro

l 2

Contro

l 3

Contro

l 4

Viscoz

yme L

Multife

ct CX13

L

Alcalas

e-B

Alcalas

e-T

Multife

ct CX G

C

Oil

Extra

ctio

n Y

ield

(%O

il Ex

tract

ion

Yie

ld (%

)

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Figure 6: Change in activity of Alcalase 2.4L FG during experimental period.

Act

ivity

(U/g

)

Week 1 Week 2 Week 3 Week 6 Week 7

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Figure 7: Change in activity of Multifect CX GC during experimental period.

Act

ivity

(CM

C/g

)

Week 1 Week 4 Week 5

4800

4600

4400

4200

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Figure 8: Response surface for oil extraction yield by non-enzymatic process in boric acid-NaOH buffer at pH 8.0.

Liquid: solid Ratio

Extraction Time (h)

Oil

Extra

ctio

n Y

ield

(%)

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Figure 9: Response surface contour for oil extraction yield by non-enzymatic process in boric acid-NaOH buffer at pH 8.0.

Extraction Time (h)

Liqu

id: s

olid

Rat

io

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Figure 10: Response surface for oil extraction yield by non-enzymatic process in Tris-HCl buffer at pH 8.0.

Liquid: solid Ratio

Extraction Time (h)

Oil

Extra

ctio

n Y

ield

(%)

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Figure 11: Response surface contour for oil extraction yield by non-enzymatic process in Tris-HCl buffer at pH 8.0.

Extraction Time (h)

Liq

uid:

sol

id R

atio

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Figure 12: Response surface for oil extraction yield by non-enzymatic process in citric-phosphate buffer at pH 5.0.

Liquid: solid Ratio

Extraction Time (h)

Oil

Extra

ctio

n Y

ield

(%)

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Figure 13: Response surface contour for oil extraction yield by non-enzymatic process in citric-phosphate buffer at pH 5.0.

Extraction Time (h)

Liq

uid:

sol

id R

atio

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Figure 14: Response surface for oil extraction yield by enzymatic process with Alcalase-B, as a function of liquid: solid ratio and extraction time at enzyme concentration of 0.1%.

Extraction Time (h)

Liquid: solid Ratio

Oil

Extra

ctio

n Y

ield

(%)

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Figure 15: Response surface contour for oil extraction yield by enzymatic process with Alcalase-B, as a function of liquid: solid ratio and extraction time at enzyme concentration of 0.1%.

Extraction Time (h)

Liq

uid:

sol

id R

atio

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Figure 16: Response surface for oil extraction yield by enzymatic process with Alcalase-B, as a function of liquid: solid ratio and extraction time at enzyme concentration of 2.5%.

Extraction Time (h)

Liquid: solid Ratio

Oil

Extra

ctio

n Y

ield

(%)

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Figure 17: Response surface contour for oil extraction yield by enzymatic process with Alcalase-B, as a function of liquid: solid ratio and extraction time at enzyme concentration of 2.5%.

Extraction Time (h)

Liq

uid:

sol

id R

atio

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Figure 18: Response surface for oil extraction yield by enzymatic process with Alcalase-B, as a function of liquid: solid ratio and extraction time at enzyme concentration of 5%.

Extraction Time (h)

Liquid: solid Ratio

Oil

Extra

ctio

n Y

ield

(%)

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Figure 19: Response surface contour for oil extraction yield by enzymatic process with Alcalase-B, as a function of liquid: solid ratio and extraction time at enzyme concentration of 5%.

Extraction Time (h)

Liq

uid:

sol

id R

atio

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Figure 20: Response surface for oil extraction yield by enzymatic process with Multifect CX GC, as a function of liquid: solid ratio and extraction time at enzyme concentration of 0.1%.

Extraction Time (h)

Liquid: solid Ratio

Oil

Extra

ctio

n Y

ield

(%)

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Figure 21: Response surface contour for oil extraction yield by enzymatic process with Multifect CX GC, as a function of liquid: solid ratio and extraction time at enzyme concentration of 0.1%.

Extraction Time (h)

Liq

uid:

sol

id R

atio

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Figure 22: Response surface for oil extraction yield by enzymatic process with Multifect CX GC, as a function of liquid: solid ratio and extraction time at enzyme concentration of 2.5%.

Extraction Time (h)

Liquid: solid Ratio

Oil

Extra

ctio

n Y

ield

(%)

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Figure 23: Response surface contour for oil extraction yield by enzymatic process with Multifect CX GC, as a function of liquid: solid ratio and extraction time at enzyme concentration of 2.5%.

Extraction Time (h)

Liq

uid:

sol

id R

atio

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Figure 24: Response surface for oil extraction yield by enzymatic process with Multifect CX GC, as a function of liquid: solid ratio and extraction time at enzyme concentration of 5%.

Extraction Time (h)

Liquid: solid Ratio

Oil

Extra

ctio

n Y

ield

(%)

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Figure 25: Response surface contour for oil extraction yield by enzymatic process with Multifect CX GC, as a function of liquid: solid ratio and extraction time at enzyme concentration of 5%.

Extraction Time (h)

Liq

uid:

sol

id R

atio

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Figure 26: Response surface for oil extraction yield by enzymatic process with Alcalase-T, as a function of liquid: solid ratio and extraction time at enzyme concentration of 0.1%.

Extraction Time (h)

Liquid: solid Ratio

Oil

Extra

ctio

n Y

ield

(%)

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Figure 27: Response surface contour for oil extraction yield by enzymatic process with Alcalase-T, as a function of liquid: solid ratio and extraction time at enzyme concentration of 0.1%.

Extraction Time (h)

Liq

uid:

sol

id R

atio

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Figure 28: Response surface for oil extraction yield by enzymatic process with Alcalase-T, as a function of liquid: solid ratio and extraction time at enzyme concentration of 2.5%.

Extraction Time (h)

Liquid: solid Ratio

Oil

Extra

ctio

n Y

ield

(%)

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Figure 29: Response surface contour for oil extraction yield by enzymatic process with Alcalase-T, as a function of liquid: solid ratio and extraction time at enzyme concentration of 2.5%.

Extraction Time (h)

Liq

uid:

sol

id R

atio

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Figure 30: Response surface for oil extraction yield by enzymatic process with Alcalase-T, as a function of liquid: solid ratio and extraction time at enzyme concentration of 5%.

Extraction Time (h)

Liquid: solid Ratio

Oil

Extra

ctio

n Y

ield

(%)

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Figure 31: Response surface contour for oil extraction yield by enzymatic process with Alcalase-T, as a function of liquid: solid ratio and extraction time at enzyme concentration of 5%.

Extraction Time (h)

Liq

uid:

sol

id R

atio

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VITA

MEIXHEN XIE

Candidate for the Degree of

Master of Science Thesis: AQUEOUS ENZYMATIC EXTRACTION OF WHEAT GERM OIL Major Field: Food Science Biographical:

Personal Data: Born in Hainan, China, on April 12, 1982, the daughter of Mr. and Mrs. Xiuhong Xie

Education: Received Bachelor of Science degree in Food Science from China

Agricultural University, Beijing, China in June 2004. Completed the requirements for the Master of Science in Food Science at Oklahoma State University, Stillwater, Oklahoma in December, 2009. Experience: Employed by Oklahoma State University, Department of Biosystems

and Agricultural Engineering as a graduate assistant; Oklahoma State University, Department of Biosystems and Agricultural Engineering, 2008 to present.

Professional Memberships: Institute of Food Technologists, American Oil

Chemists’ Society.

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Name: Meizhen Xie Date of Degree: December, 2009 Institution: Oklahoma State University Location: Stillwater, Oklahoma Title of Study: AQUEOUS ENZYMATIC EXTRACTION OF WHEAT GERM OIL Pages in Study: 81 Candidate for the Degree of Master of Science

Major Field: Food Science Scope and Method of Study: The objective of this study is to investigate the aqueous

enzymatic extraction of wheat germ oil. Four enzymes (Viscozyme L, Multifect CX 13l, Multifect CX GC and Alcalase 2.4L FG) were used to compare their effectiveness on oil extraction yield. Response surface methodology was applied to investigate the effects of processing parameters, and optimize the aqueous enzymatic oil extraction process.

Findings and Conclusions: The results of this study showed that Alcalase 2.4L FG was the

only enzyme that affects the oil extraction yield. The optimization of the aqueous extraction of oil with this enzyme in boric acid-NaOH buffer resulted in about 40% oil extraction yield. However, this is much lower than the highest oil yield given by the corresponding non-enzymatic process (about 70%). In conclusion, the aqueous enzymatic process was not effective in extracting oil from wheat germ within the range of this study.

ADVISOR’S APPROVAL: Dr. Nurhan Dunford