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This is to certify that the
dissertation entitled

PHYSICOCHEMICAL PROPERTIES OF FLOUR PROTEINS IN

RELATION TO THE TEXTURAL AND STRUCTURAL PROPERTIES

OF WHITE SALTED NOODLES

presented by

RITU SAINI

has been accepted towards fulfillment
of the requirements for the

Doctoral degree in Food Science and Human Nutrition

 

 

 

(\VM J3

Major Protessor’s Signature

"99L W, '2 cc“!

 

Date

MSU is an affirmative-action, equal-opportunity employer

PLACE IN RETURN BOX to remove this checkout from your record.
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DATE DUE DATE DUE DATE DUE

A0612352bbsi’

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

6/07 p:lClRC/DateDue.indd—p.1

PHYSICOCHEMICAL PROPERTIES OF FLOUR PROTEINS IN RELATION TO
THE TEXTURAL AND STRUCTURAL PROPERTIES OF WHITE SALTED
NOODLES

By

Ritu Saini

A DISSERTATION
Submitted to
Michigan State University
in partial fiilfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY

Department of Food Science and Human Nutrition

2007

ABSTRACT
PHYSICOCHEMICAL PROPERTIES OF FLOUR PROTEINS IN RELATION TO
THE TEXTURAL AND STRUCTURAL PROPERTIES OF WHITE SALTED
NOODLES
By

Ritu Saini

The specific objectives of following study were: (1) to examine correlations
between the physicochemical properties of wheat flour, wheat protein composition and
texture properties of white salted noodles, 2) to establish a bench-scale noodle-making
method and compare it with an already established pilot-scale noodle-making procedure
for the evaluation of texture properties of noodles: 3) to study the effect of wheat protein
content on the textural, cooking and structural properties of noodles, and 4) to study the
effect of wheat flour constituents on the textural, cooking and structural properties of
noodles.

CorrelatiOns data suggested that both protein content and protein composition
play roles in governing the texture of noodles. The amount of total flour protein was
positively related to hardness, gumminess, and chewiness of cooked noodles. Size-
exclusion high performance liquid chromatography (SE-HPLC) data revealed that the
amount of different protein fractions is more important than their relative proportions in
total flour protein. It was found that the proportion of low molecular weight
glutenins/gliadins and albumins/globulins (in total flour protein) were related positively
and negatively, respectively, to the hardness, gumminess, and chewiness of cooked

noodles. The proportion of B-gliadins in total alcohol-soluble proteins was found to relate

strongly with the texture parameters of noodles. Prediction equations were developed for
texture parameters of noodles using SE—HPLC and rapid-visco analyzer data.

The bench-scale method developed for evaluation of cooked noodle texture using
~10g flour samples showed similar trends in the texture parameters as observed using the
pilot—scale procedure. Results also showed that the bench-scale noodle-making procedure
could discriminate among wheat flours on the basis of their noodle-making properties.

Through reconstitution studies, it was observed that with increases in the protein

content of the flour samples hardness, gumminess, and chewiness of cooked noodles
increased, and adhesiveness and resilience of the noodles decreased. Higher F max and

higher residual forces were observed during force relaxation of cooked noodle samples
with higher protein content. The microstructure of raw noodle samples containing the
highest protein level showed more developed and more continuous protein matrix when
compared to samples with lower protein content.

From second set of reconstitution studies, it was found that the starch fraction of
wheat flour plays a dominant role in governing the texture of noodles, followed by water-

soluble fractions and then the type of protein (provided the protein content of flour is kept
constant). Higher Fmax and higher residual forces were observed during force relaxation
of cooked noodle samples with NuHorizon starch fraction and. NuHorizon water-soluble
fraction. Both Caledonia and NuHorizon gluten fractions increased the Fmax and residual

forces of cooked noodles. NuHorizon gluten fraction also increased the continuity of
protein matrix and reduced voids in the microstructure of noodles. NuHorizon glutenin-

rich acid-insoluble fraction was most probably responsible for this observation.

DEDICATION

To My Parents, my siblings and my sweet little nephew

iv

ACKNOWLEDGEMENTS

I would like to express my sincere gratitude to Dr. Perry K.W. Ng, my major
advisor, for his support, patience and encouragement through out my graduate studies and
especially during my dissertation. His technical and editorial advice was essential for the
completion of this dissertation and has taught me innumerable lessons on the workings of
academic research in general.

I would also like to thank my committee members, Dr. James F. Steffe, Dr. Gale
Strasburg and Dr Russell Freed for their time, understanding and thoughtful suggestions.
Special thanks are due to Dr. James F. Steffe for his time, involvement and suggestions at
almost each and every stage of this dissertation work.

Thanks are extended to Dr. Gary Hou of Wheat Marketing Center, Portland,
Oregon for providing wheat flour samples, some of the analytical and noodle texture data
for this study. I would like to acknowledge Dr. Melinda Frame and Dr. Joanna Whallon
for their help and advice in using confocal microscope for collection and interpretation of
data for this dissertation. I also want to thank Alicia Pastor at Advanced Microscopy
Center for her help in sample preparation for confocal microscopy work. Thanks are due
to Dr Jim Pestka for the use of his Sonic Dismembrator for HPLC studies.

Special thanks to Edmund Tanhehco, my labmates Yun and George and friends at
and outside MSU. Last but not the least, I want to express my gratitude to my parents,
sister (her family) and my brother for their love, encouragement, and help that kept me

going through Graduate school.

TABLE OF CONTENTS

 

 

LIST OF TABLES ............................................................................... x
LIST OF FIGURES ........................................................................... xiii
KEY TO SYMBOLS AND ABBREVIATIONS ........................................... xv
CHAPTER 1
INTRODUCTION ..................... 1
1.1 LITERATURE CITED ............................................................................................. 6
CHAPTER 2
LITERATURE REVIEW ..................... - -7
2.1 WHEAT PROTEINS ................................................................................................ 8
2.1.1 Albumins and Globulins .................................................................................. 8
2.1.2 Gliadins ............................................................................................................ 9
2.1.3 Glutenins .......................................................................................................... 9
2.2 FLOUR POLYPEPTIDES AND WHEAT QUALITY .......................................... 10
2.2.1 Durum Wheat Quality .................................................................................... 10
2.2.2 Hexaploid Wheat Quality .............................................................................. 11
2.2.3 Molecular Weight Distribution of Wheat Proteins ........................................ 13
2.3 CHARACTERIZATION OF WHEAT FLOUR AND GLUTEN PROTEINS 14
2.3.1 Quality Characteristics of Wheat Flour ......................................................... 14
2.3.2 Size—Exclusion High Performance Liquid Chromatography ......................... 15
2.3.3 Gel Electrophoresis ........................................................................................ 16
2.3.4 Study of Protein Network by Confocal Laser Scanning Microscopy ............ 17
2.3.5 Fractionation and Reconstitution Studies ...................................................... 19
2.4 ASLAN NOODLES ................................................................................................ 22
2.4.1 Processing of Noodles .................................................................................... 22
2.4.2 Quality Attributes of Noodles ........................................................................ 25
2.4.3 Measurement of Cooked Noodles Texture .................................................... 25
2.4.4 Texture Profile Analysis of Noodles .............................................................. 28
2.4.5 Noodle Texture and Wheat Proteins .............................................................. 30
2.5 LITERATURE CITED ........................................................................................... 35
CHAPTER 3

RELATIONSHIP BETWEEN PHYSICOCHEMICAL PROPERTIES OF WHEAT
FLOUR, WHEAT PROTEIN COMPOSITION AND TEXTURAL PROPERTIES

 

OF COOKED WHITE SALTED NOODLES... 46
3.1 ABSTRACT ........................................................................................................... 47
3.2 INTRODUCTION .................................................................................................. 49
3.3 MATERIALS AND METHODS ........................................................................... 52

3.3.1 Wheat Flour Samples ..................................................................................... 52
3.3.2 Physicochemical Analysis of Flour Samples ................................................. 52
3.3.3 Protein Composition of Flour Samples .......................................................... 52

vi

3.3.3.1 Size-Exclusion High Performance Liquid Chromatography ................ 53
3.3.3.2 Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis (SDS-

PAGE) ..................................................................................... 54
3.3.3.3 Acid-Polyacrylamide Gel Electrophoresis (A-PAGE) ......................... 55
3.3.4 Preparation of Noodles .................................................................................. 55
3.3.4.1 Cooking of Noodles .............................................................................. 56
3.3.4.2 Texture Analysis of Cooked Noodles ................................................... 56
3.3.5 Statistical Analysis ......................................................................................... 57
3.4 RESULTS AND DISCUSSION ............................................................................. 58
3.4.1 Physicochemical Properties of Wheat Flour Samples ................................... 58
3.4.2 Protein Composition of Wheat Flour Samples .............................................. 59
3.4.3 Correlations between Physicochemical Properties of F lours and Texture
Properties of Cooked Noodles ...................................................................................... 61
3.4.4 Correlations between Protein Composition and Texture Properties of Cooked
Noodles ......................................................................................................................... 64
3.4.5 Prediction of Noodle Texture Properties ....................................................... 67
3.5 SUMMARY ............................................................................................................ 71
3.6 LITERATURE CITED ........................................................................................... 72
CHAPTER 4

COMPARISON OF A BENCH-SCALE NOODLE MAKING PROCEDURE WITH
A PILOT-SCALE PROCEDURE TO EVALUATE TEXTURAL PROPERTIES OF

 

COOKED NOODLES 88
4.1 ABSTRACT ........................................................................................................... 89
4.2 INTRODUCTION .................................................................................................. 90
4.3 MATERIALS AND METHODS ........................................................................... 93

4.3.1 Wheat Flour Samples ..................................................................................... 93
4.3.2 Physicochemical Analysis of Wheat Flour Samples ..................................... 93
4.3.3 Bench-Scale Noodle Making ......................................................................... 93
4.3.3.1 Procedure ............................................................................................ 93

4.3.3.2 Cooking of Noodles ............................................................................ 94

4.3.3.3 Texture Analysis of Cooked Noodles ................................................. 95

4.3.4 Pilot-Scale Noodle Making ............................................................................ 95
4.3.4.1 Procedure ............................................................................................ 95

4.3.4.2 Cooking of Noodles .......................................................... 96

4.3.4.3 Texture Analysis of Cooked Noodles ................................................. 96

4.3.5 Statistical Analysis ......................................................................................... 97
4.4 RESULTS AND DISCUSSION ............................................................................. 98
4.4.1 Physicochemical Properties of Wheat Flour Samples ................................... 98
4.4.2 Comparison of Bench-Scale and Pilot-Scale Procedure ................................ 98
4.4.3 Predicting Pilot-Scale Texture Properties using Bench-Scale Texture Data 102

4.5 SUMMARY .......................................................................................................... 103
4.6 LITERATURE CITED ......................................................................................... 104

vii

CHAPTER 5
EFFECT OF GLUTEN PROTEIN CONTENT ON THE TEXTURE, COOKING
PROPERTIES, AND MICROSTRUCTURE OF WHITE SALTED NOODLES

....................................................................................................... 11 4
5.] ABSTRACT ......................................................................................................... 115
5.2 INTRODUCTION ................................................................................................ 116
5.3 MATERIALS AND METHODS ......................................................................... 119

5.3.1 Wheat Flour Samples ................................................................................... 119
5.3.2 Flour Quality Tests ...................................................................................... 119
5.3.3 Fractionation of F lours ................................................................................. 119
5.3.4 Preparation of Noodles from Original Parent Flour Samples ...................... 120
5.3.5 Preparation of Noodles from Reconstituted Flour Samples ........................ 121
5.3.6 Cooking Properties of Noodles .................................................................... 122
5.3.7 Texture Analysis of Cooked Noodles .......................................................... 123
5.3.8 Force Relaxation Test of Cooked Noodles .................................................. 123
5.3.9 Microstructure of Raw Noodles ................................................................... 124
5.3.10 Statistical Analysis ..................................................................................... 125
5.4 RESULTS AND DISCUSSION ........................................................................... 126
5.4.1 Physicochemical Analysis of Flours ............................................................ 126
5.4.2 Yields and Proximate Analysis of Flour Fractions ...................................... 126
5.4.3 Properties of Parent and Reconstituted Parent F lours ................................. 127
5.4.3.1 Noodle Texture and Cooking Properties ............................................. 127

5.4.3.2 Force Relaxation Behavior ................................................................. 129

5.4.3.3 Microstructure of Raw Noodles .......................................................... 131

5.4.4 Effect of Protein Content ............................................................................. 133
5.4.4.1 Noodle Texture and Cooking Properties ............................................. 133

5.4.4.2 Force Relaxation Behavior ................................................................. 135

5.4.4.3 Microstructure of Raw Noodles .......................................................... 137

5.5 SUMMARY .......................................................................................................... 139
5.6 LITERATURE CITED ......................................................................................... 140

CHAPTER 6
EFFECT OF FLOUR CONSTITUENTS ON THE TEXTURE, COOKING
PROPERTIES, AND MICROSTRUCTURE OF WHITE SALTED NOODLES

........................................................................................................ 163
6.1 ABSTRACT ......................................................................................................... 164
6.2 INTRODUCTION ................................................................................................ 166
6.3 MATERIALS AND METHODS ......................................................................... 168

6.3.1 Wheat Flour Samples ................................................................................... 168
6.3.2 Flour Quality Tests ...................................................................................... 168
6.3.3 Fractionation of F lours ................................................................................. 168
6.3.4 Preparation of Noodles from Reconstituted Parent Flour Samples ............. 169
6.3.5 Preparation of Noodles from Reconstituted Flour Samples with Interchanged

Fractions ...................................................................................... 169
6.3.6 Cooking Properties of Noodles .................................................................... 169
6.3.7 Texture Analysis of Cooked Noodles .......................................................... 170

viii

6.3.8 Force Relaxation Test of Cooked Noodles .................................................. 170

6.3.9 Microstructure of Raw Noodles ................................................................... 170

6.3.10 Statistical Analysis ..................................................................................... 171

6.4 RESULTS AND DISCUSSION ........................................................................... 172

6.4.1 Physicochemical Analysis of Flours ............................................................ 172

6.4.2 Yields and Proximate Analysis of Flour Fractions ...................................... 172

6.4.3 Effect of Flour Constituents on the Texture of Cooked Noodles ................ 172

6.4.3.1 Effect of the Starch Fraction ............................................................... 173

6.4.3.2 Effect of the Gluten Fraction .............................................................. 174

6.4.3.3 Effect of the Water-Soluble Fraction .................................................. 174

6.4.3.4 Effect of Acid-soluble and Acid-insoluble Gluten Fractions ............. 175

6.4.4 Effect of Flour Constituents on the Cooking Properties of Noodles ........... 175

6.4.5 Effect of Flour Constituents on the Force Relaxation Behavior of Cooked

Noodles ...................................................................................... 176

6.4.6 Effect of Flour Constituents on the Microstructure of Raw Noodles ................ 177

6.5 SUMMARY .......................................................................................................... 179

6.6 LITERATURE CITED ..................................................................... 181
CHAPTER 7

SUMMARY ........................................................................................ 192
CHAPTER 8

FUTURE RECOMMENDATIONS .......................................................... 196

APPENDICES .................................................................................... 198
APPENDIX I

EXPERIMENTAL PROCEDURES, PHYSICOCHEMICAL PROPERTIES AND
PROTEIN COMPOSITION OF WHEAT FLOUR SAMPLES USED IN
CHAPTER 3 ....................................................................................... 199

APPENDIX 11

EFFECT OF GLUTEN PROTEIN CONTENT ON THE TEXTURE, COOKING
PROPERTIES, AND MICROSTRUCTURE OF WHITE SALTED
NOODLES ......................................................................................... 218

APPENDIX III

EFFECT OF FLOUR CONSTITUENTS ON THE TEXTURE, COOKING
PROPERTIES, AND MICROSTRUCTURE OF WHITE SALTED
NOODLES ........................................................................................ 261

ix

LIST OF TABLES

CHAPTER 3
3.1 Varieties, Origin and Grade of the Flour Samples Used in this Study (n=39). . ...76

3.2 Mean, Standard Deviation and Ranges of the Physicochemical Properties
and Noodle Texture Parameters of the Wheat Flour Samples (n=39). . . . . . . . ........77

3.3 Electrophoresis Data of the Wheat Flour Samples .................................... 78

3.4 Pearson’s Coefficients of Correlation (r) between the Physicochemical Properties
and Texture Profile Analysis Parameters of Cooked Noodles ...................... 79

3.5 Pearson’s Coefficients of Correlation (r) between the Protein Composition of
Flours, separated with various methods, and Texture Profile Analysis (TPA)
Parameters of Noodles .................................................................... 80

3.6 Coefficients of SE-HPLC data, intercept, r-square, F and Probability of F of the
Prediction Equations, and Root Mean Square Error (RMSE) from their
validation for Noodle Texture Parameters ............................................. 81

3.7 Coefficients of SE-HPLC and RVA data and intercept of the Prediction Equations
for Noodle Texture Parameters ......................................................... 82

3.8 The r-square, F and Probability of F of the Prediction Equations of Noodle
Texture Properties from the SE-HPLC and RVA data, and Root Mean Square
Error (RMSE) from their validation for Noodle Texture
Parameters ................................................................................. 83
CHAPTER4
4.1 Variety, Origin and Grade of the Flour Samples Used in this Study (n=30) ....106
4.2 Physicochemical Properties of Wheat Flour Samples ............................... 107

4.3 Comparison of Noodle Texture by Two Different Noodle Making
Procedures ................................................................................. 108

4.4 Texture Properties of Noodles Obtained from the Bench-Scale Noodle Making
Procedure .................................................................................. 109

4.5 Texture Properties of Noodles Obtained from the Pilot-Scale Noodle Making
Procedure .................................................................................. 110

4.6 Correlation of Noodle Texture Parameters Obtained fi'om Bench-Scale Noodle
Making Procedure and Noodle Texture Parameters from Pilot-Scale Noodle
Making (n=30) ............................................................................ 111

4.7 Coefficients of Noodle Texture Parameters Obtained from Bench-Scale Noodle
Making, intercept, r-square, F and Probability of F of the Prediction Equation for

Noodle Texture Parameters from Pilot-Scale Noodle Making ..................... 112
CHAPTER 5
5.1 Physicochemical Properties of Parent F lours ......................................... 145

5.2 Yield and Proximate Analysis of Fractions Isolated from Two
Wheat Varieties ............................................................................ 146

5.3 Comparison of Textural Parameters of Parent and Reconstituted Parent
Cooked Noodles ........................................................................... 147

5.4 Comparison of Cooking Properties of Parent and Reconstituted Parent
Cooked Noodles ........................................................................... 148

5.5 Comparison of Force Relaxation Behavior of Parent and Reconstituted
Parent Cooked Noodles ................................................................... 149

5.6 Effect of Protein Content on the Textural Parameters of Cooked Noodles ....... 150
5.7 Effect of Protein Content on the Cooking Properties of Cooked Noodles. . . . . ...151

5.8 Effect of Protein Content on the Force Relaxation Behavior of
Cooked Noodles ........................................................................... 152

5.9 Effect of Protein Content on the Amount of Protein Matrix (% of total area)
in the Confocal Laser Scanning Microscope Cross-Sectional Images of Raw
Noodles .................................................................................... 153
CHAPTER 6

6.1 Effect of Flour Constituents of the Two Wheat Varieties on the Texture
Properties of Cooked Noodles ........................................................... 183

6.2 Effect of Protein Fractions of the Two Wheat Varieties on the Textural
Properties of Cooked Noodles ........................................................... 184

xi

6.3 Effect of Flour Constituents on the Cooking Properties of Noodles ............... 185
6.4 Effect of Protein Fractions on the Cooking Properties of Noodles ................ 186

6.5 Effect of Flour Constituents on the Force Relaxation Properties of
Cooked Noodles ........................................................................... 187

xii

LIST OF FIGURES

Page
CHAPTER 2
2.1 Classification of noodles based on their processing steps. . . . . . ....24

2.2 Typical texture profile analysis of Chinese raw noodles showing the areas and
distances used to calculate texture parameters...... . . . . . . .........29

CHAPTER 3

3.1 An example of a size-exclusion HPLC chromatogram of wheat proteins (Sample

3.2 Sodium dodecyl sulfate polyacrylamide gel electrophoretic patterns of wheat flour
samples # 1-10 used in this study, under reducing conditions. . . . . ...85

3.3 Acid polyacrylamide gel electrophoretic patterns of wheat flour samples # 1-10
used in this study86

3.4 Densitometric pattern of the reference wheat variety, Neepawa on acid-
polyacrylamrdegel87

CHAPTER 4

4.1 Comparison of predicted and actual values of texture parameters of noodles as
obtained from the pilot-scale method (Data from sample # 21-30 was used). . ..1 13

CHAPTER 5

5.1 Farinographs of (A) Caledonia and (B) NuHorizon showing differences In
theirmixingbehaviors... . 154

5.2 Force relaxation curves of cooked noodles obtained from parent and reconstituted
parent flourslSS

5.3 Linearized force relaxation curves of cooked noodles obtained from parent and
reconstituted parent flourslS6

5.4 Microstructure (cross-section) of raw noodles prepared from Caledonia parent
(CP) flour as observed with Confocal Laser Scanning Microscope. . . . . . . . 1 57

xiii

5.5 Microstructure (cross-section) of raw noodles prepared from NuHorizon parent
(NP) flour as observed with Confocal Laser Scanning Microscope
................................................................................................ 158

5.6 Effect of protein content on the force relaxation curve of the cooked noodles
prepared fi'om Caledonia flour ................................................................ 159

5.7 Effect of protein content on the linearized force relaxation curve of cooked
noodles prepared fiom Caledonia flour .................................................... 160

5.8 Effect of protein content on the microstructure (cross-section) of raw noodles
(Caledonia) as observed with Confocal Laser Scanning Microscope . . . ..161

5.9 Effect of protein content on the microstructure (cross-section) of raw noodles
(NuHorizon) as observed with Confocal Laser Scanning Microscope ............ 162

CHAPTER 6

6.1 Effect of starch, gluten and water-soluble fraction on the microstructure (cross-
section) of raw noodles obtained from Caledonia reconstituted flour as observed
with Confocal Laser Scanning Microscope ........................................ 188

6.2 Effect of starch, gluten and water-soluble fractions on the microstructure (cross-
section) of raw noodles obtained from NuHorizon reconstituted flour as observed
with Confocal Laser Scanning Microscope ........................................... 189

6.3 Effect of gliadin-rich and glutenin-rich fractions on the microstructure (cross-
section) of raw noodles obtained from Caledonia reconstituted flour as observed
with Confocal Laser Scanning Microscope ........................................... 190

6.4 Effect of gliadin-rich and glutenin-rich fractions on the microstructure (cross-

section) of raw noodles obtained from NuHorizon reconstituted flour as observed
with Confocal Laser Scanning Microscope ........................................... 191

Note: Images in this dissertation are presented in color.

xiv

A%

AACC

AN OVA

HMW-GS

kD

LMW-GS

CLSM

MMT

MWD

PAGE

RP-HPLC

SDS-PAGE

SE-HPLC

TPA

TEMED

KEY TO SYMBOLS AND ABBREVIATIONS

Absorbance Area Percentage

Absorbance Area

American Association of Cereal Chemists

Analysis of Variance

High Molecular Weight Glutenin Subunits

Kilo Daltons

Low Molecular Weight Glutenin Subunits

Confocal Laser Scanning Microscope

Million Metric Tonn

Molecular Weight Distribution

Poly Acrylamide Gel Electrophoresis
Reversed Phase High Performance Liquid Chromatography
Sodium Do-decyl Poly Acrylamide Gel Electrophoresis
Size-Exclusion High Performance Liquid Chromatography
Texture Profile Analysis

Tetra Methyl Ethylene Diamene

XV

Chapter 1
INTRODUCTION

In the marketing year 2005-06, United States produced about 57 million metric
tons (MMT) of wheat. AbOut 30 MMT of this wheat was used domestically and 27 MMT
was exported. Although US. exports more wheat than any other country in the world, its
market share in global trade is only about 24% (US Wheat Associates 2006). The biggest
wheat export markets in East Asia are Japan and China who imported over 3 MMT and 2
MMT, respectively, of US. wheat in the year 2004. South Korea has consistently been
the next largest customer in East Asia. South Korea imported 1.17 MMT of US. wheat in
the year 2004. Following South Korea is Taiwan, which purchased 86%, or 935,000
metric tons, of its wheat imports for the same marketing year from the US. (KACC
2006)

The US market share in world wheat trade has declined during the last three
decades; from 40% during the 1975-79 period, to 30% during the 1985-89 period, to 24%
during the 1995-99 period. This share was about ~ 25% in 2005 (NICPRE 2005). With
increased integration of world grain markets, U.S. producers are facing growing
competition from other grain suppliers especially from Australia and Canada. Grain
buyers demand consistency and quality in addition to competitive prices. The increasing
demand for quality has been attributed to many factors including the growth in disposable
incomes, which has resulted in consumers becoming more sophisticated in their
purchases. Another factor that has contributed to the increased demand for quality and
consistency has been the mechanization of milling and end product manufacturing, which
requires consistent inputs for proper end-product characteristics. Wheat flour noodles are
an important part of the Asian diet and are also popular in many countries outside of

Asia. About 40% of the wheat flour used in the US wheat importing countries goes into

noodle making (Hou and Kruk 1998). When it comes to noodle-making, wheat from
Australia and Canada is given preference over US wheat due to their ability to produce
better quality noodles. For example, South Korea sourced all of its wheat from the United
States until 1985 when Australia began aggressively promoting its noodle wheat, which
fully meets South Korean noodle manufacturers‘ specifications at a favorable price (Dong
2002). Considering that over fifty percent of US. wheat production is exported, it is
important that US. wheat stays competitive in the global market. In order to maintain or
improve its share of wheat export in the international market, it is important that US.

continues to improve the quality of its wheat varieties grown.

Texture is an important quality attribute of noodles that affects consumer
acceptability. Noodle texture is affected both by wheat starch and wheat proteins. Starch
requirements for good quality noodles are established; however the role of proteins is not
very clear. Various researchers have reported contradictory results, and different views
exist over the relative importance of protein content versus protein composition in
relation to noodle quality. Very little systematic work has been done to date to determine
the optimum wheat protein composition and gluten composition (in terms of glutenin to
gliadin ratio and glutenin subunits) required for desirable dough properties and product
characteristics. It is known that the molecular weight distribution (MWD) of wheat
proteins plays an important role in deciding the properties of bread dough and end
products. But, very minimal work has been done in establishing the effect of MWD of
proteins on the texture properties of cooked noodles (Park et al 2003 and Ohm et a1

2006)

Very few fractionation and reconstitution studies have been reported to establish
the effect of wheat proteins on noodle texture properties. According to Oh et a1 (1985),
glutenins play a very important role in determining the texture of noodles. The high
molecular weight glutenin fraction of soft noodle making wheat flour was replaced with
the high molecular weight glutenin fraction of hard noodle making wheat and it was
observed that the cutting strength of the cooked noodles was increased to a level
equivalent to that of the hard control. However, the results obtained by Toyokawa et al
(1989) were in contrast to the results obtained by Oh et al (1985). Toyokawa et al (1989)
observed that interchanging the gluten fraction of different wheat classes did not affect
the texture of cooked noodles. Rho et al (1989) used reconstitution studies to measure
and show that the increase in gluten content improved the cutting stress of noodles but
decreased their surface firmness. Oh et al (1985) and Rho et a1 (1989) used objective
methods of texture measurement, whereas in the study of Toyokawa et al (1989), a
trained sensory panel evaluated the difference between the samples. None of these studies
attempted to observe the effect of protein content or protein composition on the structural

properties of noodles.
The specific objectives of this research work were:

1. To establish correlations between wheat flour protein quantity parameters, protein
composition, dough mixing properties and noodle texture parameters as obtained

from texture profile analysis.

2. To compare texture properties of noodles obtained from a bench-top noodle

making machine and a pilot scale noodle making machine.

3. To conduct reconstitution studies in order to:

a) Establish the effect of increasing gluten protein content on the texture and

force-relaxation properties of cooked noodles.

b) Identify the effect of wheat flour components on the texture and force-

relaxation properties of cooked noodles.

4. To study the microstructure of uncooked noodle samples obtained from
reconstitution studies from Objective 3 to gain a better understanding of the role

of gluten proteins in noodle making.

The information generated through this study is aimed at enhancing our
understanding of the role of wheat proteins in noodle-making. The long-term goal of this
work is to help breeders and geneticists to accelerate the breeding of competitive new
wheat varieties that will eventually enable U.S. wheat growers to re-establish lost market
share in the Asian region. The following dissertation entails: 1) Literature review, 2)
Relationship between physicochemical properties of wheat flour, wheat protein
composition and texture profile analysis (TPA) parameters of white salted noodles, 3)
Comparison of a bench-top noodle making procedure with a pilot-scale noodle making
procedure, 4) Effect of protein content on the texture, cooking properties and
microstructure of white salted noodles and 5) Effect of flour constituents on the texture,
cooking properties and microstructure of white salted noodles. The chapters in this
dissertation were written in the journal paper format and thus some of the information
presented here might appear repetitive. Appendices containing detailed procedures and

raw data are presented at the end of the dissertation.

1 .1 LITERATURE CITED

Dong, J. 2002. Pacific North West suppliers: Working to meet South Korea’s rising
demands for milling-quality wheat. In: Ag Exporter, December.

Hou, G., and Kruk, M. 1998. Asian noodle technology. AIB Technical Bulletin. Vol. XX,
Issue 12.

KACC. 2006. Wheat trade: Exports to East Asia. In: Kansas Asia community connection.

NICPRE Quarterly. 2005. Wheat export market development: A case study of facility
investment for direct shipment to Mexico. National Institute for Commodity
Promotion Research and Evaluation. Vol. 11.

Oh, N. H., Seib, P. A., Ward, A. B., and Deyoe, C. W. 1985. Noodles. VI. Functional
properties of wheat flour components in oriental dry noodles. Cereal Foods World.
30:176—178.

Ohm, J. B., Ross, A. S., Ong, Y. —L., and Peterson, C. J. 2006. Using multivariate
techniques to predict wheat flour dough and noodle characteristics from size-
exclusion HPLC and RVA data. Cereal Chem. 83:1-9

Park, C. S., Hong, B. H., and Baik, B. K. 2003. Protein quality of wheat desirable for
making fresh white salted noodles and its influences on processing and texture of
noodles. Cereal Chem. 80:297-303.

Rho, K. L., Chung, O. K., and Seib, P. A. 1989. Noodles VII. Investigating the surface
firmness of cooked oriental dry noodles made from hard wheat flours. Cereal Chem.
65:320-326.

Toyokawa, H., Rubenthaler, G. L., Powers, J. R., and Schanus, E. G. 1989. Japanese
noodle qualities. 1. Flour components. Cereal Chem. 66:382-3 86.

US Wheat Associates. 2006. Annual Report.

Chapter 2
LITERATURE REVIEW

2.1 WHEAT PROTEINS

According to Osborne (1907), wheat proteins can be classified into four major
fractions based on their solubility in different solvents: albumins (soluble in water and
dilute buffers), globulins (soluble in saline solutions), gliadins (extractable in 70—90%
aqueous alcohol), and glutenins (soluble in dilute acid or alkali). Gliadins and glutenins
are the two main groups of storage proteins, also known as gluten proteins, in wheat. The
properties of hydrated gluten or wheat flour dough depend on these two groups; hydrated
gliadin exhibits viscous properties, whereas hydrated glutenin has strong elastic
properties (Southan and MacRitchie 1999). The commercially desirable visco-elastic
properties required for good performance in processing wheat flour dough for the
production of leavened bread and other foods, results from the combined contributions of
these two main types of proteins. Accordingly, most research on wheat proteins has

focused on glutenins and gliadins, but more particularly on glutenins.

2.1.1 Albumins and Globulins

The apparent molecular weights of albumins and globulins, as obtained from
SDS-PAGE are <30,000 Da. They are physiologically active proteins and many of them
are enzymes and enzyme inhibitors. Genes for the major albumins and globulins of wheat
proteins are located on chromosomes 3, 4, 5, 6 and 7 (Gianibelli et al 2001a). They have
lower amounts of glutamic acid and proline and more lysine, arginine and aspartic acid as
compared to gluten proteins (Hoseney 1998). Nutritionally, they have a very good amino
acid balance. The soluble proteins constitute about 1.5% of the total endosperm proteins;

the remaining 85% is gluten proteins.

2.1. 2 Gliadins

Gliadins are heterogeneous mixtures of single-chained polypeptides and can be
divided into four groups on the basis of their mobility upon acid - polyacrylamide gel
electrophoresis (acid-PAGE): 0t- (fastest mobility), 13-, y-, and m-gliadins (slowest
mobility). Their molecular weights lie in the range of 5 30,000 Da to 75,000 Da (Bushuk
and Zillman 1978). Genes coding these proteins are located on the short arms of the
group 1 and 6 chromosomes (Wrigley and Shepherd 1973; Brown and Flavell 1981). The
group 1 chromosomes control all the co-gliadins, most of the y-gliadins and a few of the
B-gliadins, whereas genes on the group 6 chromosomes code for some y-gliadins, most of

the B-gliadins and all of the a-gliadins.

2.1.3 Glutenins

Glutenins, on the other hand, are heterogeneous mixtures of polymers formed by
disulfide-bond linkages of polypeptides that can be classified into four groups (the A-, B-,
C-, and D-regions) according to their electrophoretic mobility upon sodium do-decyl
sulfate polyacrylamide gel electrophoresis (SDS-PAGE) after reduction of their disulfide
(S-S) bonds. The A-group, with an apparent molecular weight range of 80,000-120,000,
corresponds to the high molecular weight-glutenin subunits (HMW-GS) (Payne and
Corfield 1979). The B- group (42,000-51,000 Da) and C-group (30,000-40,000 Da) are
low molecular weight-glutenin subunits (LMW-GS) distantly related to y- and OL- gliadins
(Payne and Corfield 1979; Payne et a1 1985). Finally, the D-group, also belonging to the

LIVIW-GS group, is highly acidic and related to (n- gliadins (Jackson et al 1983).

The HMW-GS are encoded at Glu-I loci on the long arm of group 1
chromosomes (1A, 1B, 1D) (Bietz et al 1975; Payne et al 1987). These loci are named
GIu-AI, Glu-BI, and Glu—DI, respectively. Each locus includes two genes linked together
encoding two different types of HMW-GS: x- and y- type subunits (Payne et a1 1981 and
Payne et a1 1987). The x-type subunits generally have slower electrophoretic mobilities
upon SDS-PAGE and higher molecular weights than the y-type subunits. The LMW-GS
are controlled by genes at the Glu-3 loci on the short arms of chromosomes 1A, 1B and
1D. The LMW-glutenin polypeptides are synthesized under the control of structural
genes located on these same chromosomes, but close to the Gli-I genes. Payne et al
(1984a) reported that wheat gluten proteins comprise approximately 50% gliadin, 10%

HMW glutenins, and 40% LMW glutenins.

2. 2 FLOUR POLYPEPTIDES AND WHEAT QUALITY

Identification of specific polypeptides, the presence or absence of which alters
aspects of grain quality, has helped breeders in the past to alter quality in predictable
directions by crossing and selecting for such polypeptides. Many attempts have been
made to correlate specific gluten proteins with rheological properties and bread- and

pasta-making qualities of bread wheat and durum wheat, respectively.

2. 2.1 Durum Wheat Quality

Durum wheats have excellent rheological properties for the production of pasta,
as the doughs are stable and flow readily under the pressures required for extrusion to
make various types of pastas. Superior cooking quality of spaghetti, especially firmness

of cooked spaghetti, has been related to strong gluten strength of durum wheats, their

10

high glutenin content and their high glutenin-gliadin ratio (Matsuo and Irvine 1970;
Walsh and Gilles 1971; Wasik and Bushuk 1975). Specific gluten polypeptides have also
been related to rheological properties of durum wheats and their pasta-making quality.
Damidaux et a1 (1978) found a consistent relationship between the presence of two 7-
gliadin bands (designated bands 42 and 45 on the basis of their electrophoretic mobilities)
and the viscoelastic properties of gluten (required for good pasta-making abilities of
wheat). Varieties containing band 45 were found to have gluten of superior
viscoelasticity compared to those with band 42. Later on, it was Shown that the gene
responsible for these gliadins was very closely associated with the genes for LMW
glutenins that were responsible for pasta quality (Payne et al 1984b). It was Shown that
LMW-1 was present in durum wheat varieties that contained gliadin band-42, and that
LMW-2, was present in band-45 types. With the availability of an Italian variety that
contained both gliadin band-42 and the LMW-2 group of glutenin proteins, it was later
observed by Pogna et al (1988) that the variety had strong gluten characteristics and it
was concluded that the LMW-2 glutenin proteins were actually responsible for

differences in gluten viscoelasticity.

The HMW—glutenin polypeptides appear to be poor indicators of gluten strength
in durum wheat as no successful correlations have been found between the two.
However, it has been shown that quantitatively the glutenin fractions play an important

Part in pasta quality, and particularly in cooking quality (Matsuo et al 1972).

2. 2.2 Hexaploid Wheat Quality

In contrast to the information on durum wheat (a tetraploid), there is no consensus

on the associations between the presence of specific gliadin components and aspects of

11

hexaploid wheat grain quality. Some researchers have associated specific gliadin alleles
with bread making quality, but it is now believed that these proteins may not have direct
effects on wheat quality in terms of dough strength. This role may instead be due to the
LMW-GS that genetically are tightly linked to the gliadins. A number of studies have
revealed that the allelic variation at the LMW-GS loci is associated with significant
differences in dough quality of bread (Gupta et a1 1994). The LMW-glutenin subunits
constitute about one-third of the total seed protein and about 60% of the total glutenins
(Bietz and Wall 1973), but they have received much less research attention than the
HMW-GS mainly due to the difficulty in separating them in one-dimensional SDS-

PAGE, which is primarily due to the overlapping between LMW-GS and gliadins.

Several HMW—GS have been closely associated with bread-making quality of
hexaploid wheats. Pioneering work by Payne and coworkers (1987) established that dough
strength and baking performance of wheat cultivars were each related to allelic variation in
HMW- GS. As a result of the correlations of different alleles with dough properties, a system of
quality scores was assigned to HMW-GS. The quality scores assigned to the HMW-GS range
firm 0 (null allele) to 4. For example, the HMW-GS pair 5+10 coded by Glu- DI has been
assigned a score of 4, as this pair has been associated with the greatest dough strength. Its Glu-
DI counterpart, the pair 2+12, on the other hand, has been assigned a score of 2, reflecting its
association with dough weakness. A given cultivar can then be assigned a Glu-l score, which is
the sum of the contributions of each of the three HMW-GS loci. These differences in dough
Strength have been attributed to differences in molecular size of glutenin polymers, deduced
fi‘om solubility measurements (Gupta and MacRitchie 1994). Reference to HMW-GS

Composition has proven valuable in the segregation of lines in the process of breeding for

12

specific quality targets.

2.2.3 Molecular Weight Distribution of Wheat Proteins

The size distribution of molecules governs the properties of synthetic polymers,
such as strength of a polymer composite (Weegels et a1 1996 a, b). By analogy, Southan
and MacRitchie (1999) suggest that Size distribution should also be important for gluten
proteins. The molecular weight distribution (MWD) of wheat proteins can be viewed as
the relative amounts of monomeric proteins and polymeric proteins or the MWD of
polymeric proteins. The MWD of polymeric proteins in turn depends on the ratio of
HMW-GS to LMW-GS. It varies from cultivar to cultivar and is genetically controlled. It
is known that wheat protein forms a continuous network during dough development and,
like any other colloidal system, properties of dough also depend on the continuous phase
or gluten matrix (Southan and MacRitchie 1999). The MWD of proteins is considered to
be one of the main determinants of dough physical properties. It affects physical
properties of dough such as mixing properties (F arinograph and Mixograph) and dough
extension properties (Extensigraph and Alveograph). It has been shown that dough
strength, as measured by mixograph dough development time and extensigraph
maximum resistance, is positively correlated with the percentage of polymeric proteins
relative to the total protein (Southan and MacRitchie 1999). These physical properties of
the dough determine the suitability of wheat flour for a particular end-use and have also
been related to the final product quality. Determining the optimum MWD for a given

end-use is certainly useful.

The relative proportion of monomeric and polymeric proteins can be determined

by means of size-exclusion HPLC (Batey et a1 1991; Dachkevitch and Autran 1989).

13

However, it is difficult to measure true MWD since currently no methods are available to
completely solubilize total wheat proteins without modifying them first. Glutenin
proteins are difficult to solubilize because of their large size and limited number of
ionizable groups. SDS-PAGE coupled with densitometry and multi-stacking SDS-PAGE
gels can also be used to determine the MWD of wheat proteins (Khan and Huckle 1992;
Bekes et a1 1996). Field Flow Fractionation (FFF) and Multi Angle Laser Light
Scattering (MALLS) are relatively new techniques that can be used to estimate the MWD

of wheat proteins (Southan and MacRitchie 1999).

Given that the quantity and composition of wheat flour proteins is primarily
responsible for determining dough and end-product characteristics in wheat-derived
products such as breads (Gianibelli et al 2001b) and pasta (Troccoli et al 2000), it then
follows that these same factors could be crucial in determining the processing and end-

product quality characteristics of noodles.
2. 3 CHARACTERIZATION OF WHEAT FLOUR AND GLUTEN PROTEINS

2. 3.1 Quality Characteristics of Wheat Flour

Both chemical and physical tests are used to determine the quality characteristics
of wheat flour. The most common chemical tests are moisture, ash, protein, fat and
damaged starch contents. For flour, moisture, ash, protein, and wet gluten contents and
gluten index are generally used to determine suitability of the flour for a particular end-
use. Farinograph, Mixograph and Extensigraph are the most common physical tests.
Farinograph and mixograph are the torque measuring devices that provide information

about water absorption of the flour, mixing time and mixing tolerance of the dough.

14

Extensigraph measures the resistance to extension and extensibility of the dough by
stretching a test piece of the dough at a given rate and direction until it breaks. The rapid
visco analyzer is used to measure the pasting properties of flour or starch. It has been
used extensively to predict eating quality of noodles (Panozzo and McCormick 1993;

Collado and Corke 1996).

2. 3.2 Size-Exclusion High Performance Liquid Chromatography

Various methods have been used to determine the size distribution of the gluten
proteins. Gel filtration chromatography was initially used for the size—based separation
and comparison of wheat flour proteins in their native states but it was replaced by SE-
HPLC because of its good resolution and reproducibility (Bietz 1984, 1986). The
methodology accurately separates the three main classes of wheat endosperm proteins:
glutenin, gliadin, and albumin-globulin. Proteins from flour are extracted using SDS in
sodium phosphate buffer. The extracted proteins are then passed through a size-exclusion
column and eluted with either dilute SDS in phosphate buffer or acetonitrilezwater
(50:50) solvent. The proteins move through the column based on their molecular size,
larger protein molecules eluting out earlier than smaller molecules. The results obtained
with this technique have been highly correlated to breadmaking quality, in particular the
first peak of the chromatogram (polymeric proteins) (Batey et al 1991). More recently,
Bean at al (1998) developed a faster alternative to SE—HPLC methods based on nitrogen
combustion that allowed rapid quantitation of insoluble polymeric protein in flour. A
simplification of the SE-HPLC procedure by Batey et al (1991) has also been reported

(Larroque and Bekes 2000).

Sing et a1 (1990) proposed an alternative method to completely solubilize the total

15

flour proteins. They used ultrasonic probes to cause shear degradation of large gluten
polymers in order to solubilize total protein from the flour sample. By means of SE-
HPLC and SDS-PAGE, they showed that, if controlled properly, only the largest glutenin
polymers were degraded and the degradation products were still too large to affect the
size-based fractionation of total proteins into glutenins, gliadins and albumin/globulins.
Moreover, this procedure requires a smaller sample size and less time than the other
procedures to solubilize proteins. Since then, this sonication procedure has been
successfirlly used by various researchers to characterize total wheat flour proteins. Very
recently, Ohm et al (2006) used SE-HPLC data and the sonication procedure (along with

RVA data) to successfully predict mixing and noodle characteristics of flour.

2. 3.3 Gel Electrophoresis

The effect of glutenin proteins on wheat quality has largely been considered in relation
to subunit composition, and electrophoretic techniques such as SDS-PAGE have been
instrumental in identifying the polymorphism of the HMW-GS (N g and Bushuk 1987). The
flour protein is extracted with a solvent containing SDS and reduced with mercaptoethanol.
The SDS causes the proteins to unfold and gives them an overall negative charge. The reduced
protein aliquot is then loaded onto SDS-polyacrylamide gels which are connected to a power
Supply. The negatively charged proteins migrate towards the positive electrode at rates based
on their molecular weights. In other words, smaller proteins migrate farther than larger

molecules during a given period of time. Protein bands are developed with an appropriate

Staining dye solution, when the run is complete.

SDS-PAGE has been widely used by scientists to determine molecular weights of

Wheat proteins (Ng and Bushuk 1987; Ng and Bushuk 1989; Lookhart and Albers 1988) and

16

also to determine their MWD and predict quality of flour and end products. A two-step SDS-
PAGE method (Singh and Shepherd 1988), reversed phase high performance liquid
chromatography (RP-HPLC) and improved capillary electrophoresis (Bean and Lookhart
2000) are some of the techniques that allow clear characterization of all glutenin subunits (both
HMW and LMW-GS). Multistacking SDS gel electrophoresis, initiated by Khan and
Huckle (1992), when combined with integration tools, based on densitometric scanning
or image analysis of the gel patterns, provides a quantitative profile of size distribution of

the non-reduced polymeric proteins (Wrigley et al 1993; Bekes et al 1996).

Gliadin proteins can be identified by acid-PAGE (Bushuk and Zillman 1978). The
protein separation in acid-PAGE is based on the electric charge and molecular size of the
protein molecules. Proteins with more positive charges move farther than those with fewer
positive charges. Proteins that have the same degree of positive charge are separated on the
basis of their molecular size; smaller molecular weight molecules migrate faster than larger
molecules. Acid-PAGE has also been used for predicting end-product quality. Hou et a1 1996
showed that the quantities of certain gliadins and total gliadins are associated with the cookie-

and cake—baking properties of soft wheat flours.

2. 3.4 Study of Protein Network by Confocal Laser Scanning Microscopy

Confocal microscopy is based on the principle that the light from the objective’s
fOcal point is focused to a point precisely at the pinhole, and is passed through the
detector. Only negligible amounts of light from the out-of-focus region can pass through
the pinhole and reach the detector. With out-of-focus light virtually removed, contrast
and resolution are greatly enhanced in all images, and it becomes possible to study

Samples to depths of hundreds of microns (Whallon 2001). Most confocal microscopes

17

use lasers as their light source, hence the name confocal laser scanning microscopy
(CLSM). Confocal images can be obtained in reflection and fluorescent mode. In
reflection microscopy, the light hits the specimen and gets reflected. Only the light that
passes through the objective contributes to the image. In fluorescence microscopy, after
the light hits the specimen, the electrons in the specimen are brought into an excited state,
and then photons are emitted as longer wavelengths, namely fluorescent light. The
fluorescent light that passes through the objective contributes to the image. Confocal
microscopes can also be operated in the non-confocal mode as in transmitted images. In
transmission microscopy, the light passes through the Specimen, and the detector present
on the other side of the sample collects the image. By means of various light source lasers
(argon ion, helium-neon and krypton-argon) and barrier filters (band-pass and long-pass)
of various wavelengths, it is possible to use a variety of stains and to get images from
variety of Specimens (Whallon 2001). CLSM provides resolution of about 0.1 pm, which
is better than the resolution of conventional light microscopes. Unlike electron
microscopy, the sample preparation is not so laborious and time consuming and it is not
essential to embed or fix the sample. Good quality images can be obtained from about 5—
10 pm thick samples and it is possible to view live biological samples. CLSM comes
with an option of performing optical sectioning; which means that it is possible to view

the same section repeatedly under the same or different imaging conditions (Whallon

2001).

Several studies have reported using CLSM to study the microstructure of cereal
and cereal products. Heertje et a1 (1987) used fluorescence CLSM to study the structural

Changes in rising dough. The structure of bread has also been studied by Vodovotz et a1

18

(1996) using CLSM. Fardet et a1 (1998) used CLSM for textural image analysis of
protein networks in pasta as influenced by technological processes. Zweifel (2003) used
CLSM to establish that high temperature drying of pasta preserves the protein network
and restricts swelling of starch. Lee et a1 (2001) used CLSM to demonstrate structural
differences between non-developed, partially developed and fully developed doughs.
Seetharaman et al (2004) used fluorescent confocal microscopy to prove that the formula
water affected pretzel dough development and texture quality of the final product. Most
recently, CLSM was used by Peighambardoust et al (2006) to observe gluten network as
affected by simple shear and z-blade mixing. No attempts have been made so far to study

the microstructure of Asian noodles using CLSM.

2. 3.5 Fractionation and Reconstitution Studies

Fractionation and reconstitution of wheat flour components is the most direct
method for investigating and establishing the effect of individual flour components
(MacRitchie 1985). Using suitable procedures, wheat flour is fractionated into its
constituents, like starch, water soluble, glutenins, gliadins, etc. The functionality of each
of these components is then evaluated by either varying its amount in given flour or by
interchanging the separated fractions between flours of different product quality
(Uthayakumaran et al 1999). In order to get meaningful results from fractionation and
reconstitution procedures, it is important that there be negligible or minimal change in the
functionality of all flour constituents during fractionation. Reconstituted ‘control’ flour,

prepared by mixing all the fractions in the same ratio as obtained from the parent flour, is

used for comparison purposes.

Various procedures have been described in literature to separate flour into its

19

main constituents of starch, gluten proteins and lipids; gluten proteins may further be
fractionated into gliadins and glutenins. A very good comparison of three different
fractionation procedures by Chen and Bushuk (1970), MacRitchie (1978) and Hoseney et
al (1969a, b) was drawn by Chakraborty and Khan (1988a, b). Chen and Bushuk’s (1970)
procedure was based on sequential separation of albumin and globulins, gliadins, and
soluble and insoluble-glutenins using 0.5M salt, 70% ethanol and 0.05M acetic acid
solution, respectively. MacRitchie’s (1978) procedure involved the use of chloroform to
de-fat the flour; defatted flour was kneaded and washed with water to separate gluten and
starch and gluten was further fractionated into acid-soluble and acid-insoluble fractions
using 0.1M acetic acid. Hoseney’s (1969a, b) procedure, on the other hand, used flour-
water slurry as starting material; gluten, starch and water-soluble fractions were separated
by simple kneading and washing with water followed by centrifugation. Gluten was
solubilized using 0.005M lactic acid. Chakraborty and Khan (1988a, b) showed that the
protein fi'actions (albumins, globulins, gliadins and glutenins) obtained from different
fractionation procedures were different composition-wise, owing to the solubility
differences of gluten proteins in different solvents, starting material used, and the
sequence in which different fractions were separated. They also pointed out that these
differences can result in the differences in their functional properties and it is possible to

arrive at conflicting conclusions depending upon the fractionation procedure followed.

Various modifications in the fractionation procedures have been suggested since
then in order to maintain the functionality of gluten proteins. A study conducted by
IVIacRitchie (1985) showed that the functional properties of gluten proteins during the

fractionation procedure depend upon the water temperature, isolation pH and time of

20

exposure to acid. The author suggested the use of very dilute HCl along with high-speed
mixers to separate gluten into glutenins and gliadins. Further, the author showed that the
reconstituted flour of particle size < 250 um had similar mixing properties as that of the
parent flour. This study was followed by the work of Gupta et al (1993) wherein a
sequential method of protein fractionation was reported. It was found that the fractions
obtained at pH 5.3 and 5.1 were predominantly gliadins whereas those at pH 3.5 and 3.1
were largely glutenins; between 5.1 and 3.5 were the intermediate types (mixture of
gliadins and glutenins). These fractionation and reconstitution types of studies have been

extensively used to study the contribution of gluten proteins in bread baking.

The effect of individual proteins (HMW-GS, LMW-GS and gliadins) and their
ratios on dough properties can be evaluated by studying the mixing behavior of a base
flour, modified either by incorporation or addition of the specific proteins (Bekes et al
1994) or by means of reconstitution studies (Uthayakumaran et al 1999, 2000). Many
fractionation procedures have been reported to separate the glutenins fi'om other classes
of wheat proteins. The more widely used fractionation methods have been procedures
based on the differential solubility of polymeric glutenin and the monomeric proteins in
various solvents and at various pH levels. Some of the frequently used methods involve a
modified Osborne sequential fractionation (Chen and Bushuk 1970; Bietz and Wall
1975), pH precipitation (Orth and Bushuk 1973), and various other solvent fractionation

approaches (Danno 1981; MacRitchie 1978, 1985 and 1987; Kruger et al 1988; Burnouf
and Bietz 1989). Fu and Sapirstei‘n (1996) have developed a fractionation method based
on differential solubility of gluten proteins in 50% and 70% propan-l-ol; however, the

alcohol used in the procedure denatures the protein.

21

2. 4 ASIAN NOODLES

Asian wheat-flour noodles are one of the principal forms in which wheat flour is
consumed as a foodstuff and constitute an important end product for US wheat growers.
The amount of flour used for noodle making in Asia accounts for about 40% of total flour
consumed (Hou and Kruk 1998). Asian noodles are primarily made from flour milled
from either hard-grained or soft-grained common wheat. These noodle products
originated in Asia and are distinct from European style pastas, which are typically made
from semolina milled from durum wheat by extrusion. There is no systematic
classification or nomenclature for Asian noodles. Very broadly speaking, they can be
classified on the basis of the raw material used, based on whether or not salt is used
(white or yellow noodles), based on the width of the noodle strands, and based on the
way they are processed (fresh, dried, boiled or steamed). Chinese type noodles are
generally made from hard wheat flour, characterized by bright creamy white or bright
yellow color and a firm texture, whereas, Japanese noodles are typically made from soft
wheat flour of medium protein strength. It is desirable to have a creamy white color and a

soft and elastic texture in Japanese noodles.

2.4.1 Processing of Noodles

The general processing steps of noodle making involve: 1) Mixing of raw
materials, 2) Resting, 3) Dough sheeting, 4) Compounding, 5) Sheeting/Rolling and 6)
Slitting. Mixing of ingredients is usually carried out in horizontal or vertical mixers. The
main ingredients are water and flour; other ingredients like salt, sodium hydroxide,
Sodium and potassium carbonate, gums, eggs and polyphosphates, etc., depend upon the

Iloodle type. About 30-35% water (w/w) is added along with other ingredients and mixed

22

for about 10-15 min to give crumbly dough. Optimum water absorption is determined by
flour proteins, pentosans and damaged starch content and is judged by the dough
handling properties. The restricted amount of water in the formula helps in the final
drying process, delays noodle discoloration, and gives good strength to the internal
noodle structure thereby preventing losses during packaging and distribution. Due to low
formula water, gluten development is minimal during noodle flour mixing; this improves
the sheetability and uniformity of the dough. After mixing, the dough is rested for about
20-40 min for uniform hydration of flour particles. Uniform distribution of water results
in a smooth sheet (with fewer dry patches), smooth noodle surface and also improves
starch gelatinization; even hydration of flour particles also helps in better gluten

development during sheeting of the noodle dough.

The rested dough is then passed through sheeting rolls to form a noodle sheet,
which is compounded and then passed again through rolls to form a single sheet. The roll
gap is adjusted such that the dough thickness is reduced to 20-40% of its initial thickness.
The compounded sheet is then rested again for 30-40 min to relax the dough in order to
facilitate subsequent sheeting. The relaxed dough is then sheeted through pairs of rolls,
several times, with progressively decreasing roll gap. The final roll gap is adjusted,
according to noodle type, to give the desired noodle thickness. The noodle sheet is then
passed through the slitting machine for cutting into noodle strands of desired width and
length. The noodles may be sold as ‘fresh’ after cutting or may be processed further by

drying, parboiling, boiling, steaming or frying depending upon the noodle type. The

Classification of noodles based on their processing steps is summarized in Figure 2.1.

23

Mixing of Ingredients

1

Resting

I

Sheeting and Compounding

Resting/Relaxation of dough

 

 

Sheeting
1 Cutting ——h Drying l
ChifcleRlaw Dried
Udon . Cooking Chinese Raw
Chuka-men WaV'"9 Steaming Parboiling, boiling Udon
' Chuka-men
Thar Bamec Soba
Steaming Rinsing and
1 Cooling
Frying 1
Instant Fried Noodles Draining
Oiling
Hookien
Chinese Wet

Fig. 2.1. Classification of noodles based on their processing steps.
(References: Hou and Kruk 1998; Hatcher 2001)

24

Almost all Asian noodles are processed by the basic 'mix, sheet and cut’ process.
However, very little is known about the optimum dough properties associated with good
noodle making, optimum gluten protein composition for hypothesized optimum dough

properties, and whether these dough requirements are shared among various noodle

types.

2.4.2 Quality Attributes of Noodles

Process performance, color and texture of cooked noodles are important attributes
that are judged while evaluating wheat varieties for any noodle making. Color and texture
of noodles are the key quality factors that affect consumer acceptability of the product.
Color of noodles should be bright, either white or yellow depending upon the noodle
type, free of dark specks or discoloration; and minimal darkening over a 48-hour period
is desirable for fresh noodles. Texture characteristics however, are more complicated, less
understood and difficult to define. Chinese raw noodles should be hard and elastic in bite
with stable texture in hot water, whereas, a soft and elastic texture is preferred in the case
of Japanese udon noodles. Chinese wet noodles should be hard to bite, chewy, elastic and
less sticky. Alkaline Japanese ‘ramen’ noodles should be firm, springy, not sticky, and
smooth (Crosbie et al 1999). Other alkaline noodles like Cantonese and Hookien noodles

also prefer textural properties similar to ramen noodles.

2.4.3 Measurement of Cooked Noodles Texture

Ross (2006) recently provided an excellent review on the instrumental
measurement of texture properties of wheat flour noodles. Compressive methods (cutting,

Compression, texture profile analysis, extrusion, stickiness and creep test) and tensile tests

25

have been used by researchers to measure textural properties of cooked noodles.
According to the reviewer, uniaxial compression or cutting is the most widely method
used by the researchers. AACCI Approved Method 66-50 (AACCI 2007) is based on the
compressive cutting method described by Oh et a1 (1983). In this method, a plexiglas
blade (50 x 1mm), attached to the cross-head of Instron, was used to cut three strands of
noodles cross-wise. Maximum cutting stress (MCS) and the work required to cut per unit

area were determined. Both of these parameters showed significant positive correlations

With sensory firmness.

Oh et al (1983) also reported compressing the noodles to a pre-defined stress of
1 -3 kg/cm2 and recording the compression-recovery curve. Compression slope, resistance

to compression and recovery were measured. Resistance to compression and the recovery
from compression each had a highly significant correlation with sensory chewiness. Yun
ct a1 (1997) also reported a significant correlation between sensory elasticity of noodles
and compressive force peak area divided by time. The methods of Oh et a1 (1983) have
been modified many times since then, in terms of number of noodle strands tested, strain
applied, blade type, cross-head speed, etc. (Graybosch et a1 2004; Hatcher et al 2002;
Kl‘uger et al 1994; Huang and Morrison, 1988; Sasaki et al 2004; Yun et al 1997).
Recently, it was also shown that compressing the noodles lengthwise might provide

better discrimination between the samples (Zhao and Seib 2005).

A method to evaluate surface firmness of noodles was described by Oh et a1
(1 985) wherein the initial slope of the time—force curve was measured. Surface stickiness
of noodles can be measured by applying a defined force to the noodle surface and

measuring the force required to pull the probe away from the surface (Dunnewind et al

26

 

2004). Attempts have been made to measure smoothness of noodles using friction
measurements with glass, teflon and stainless steel slides (Rice and Caldwell 1996; Miki
et al 1996). Texture Profile Analysis (TPA) is another method that has been very widely
used by researchers to evaluate textural properties of cooked noodles. A detailed

description of TPA is presented in the next section.

Tensile tests have been used to measure hardness and extensibility or
stretchability of noodles. Ross et a1 (1998) showed that the parameters measured by
tensile testing (peak force at extension and the initial slope) were significantly correlated
with sensory softness of noodles. Seib et a1 (2000) used a special device to mount the
noodle sample and stretched the sample using an L-shaped hook to measure tensile

Properties of noodles.

Principles of firndamental rheology have also been used to establish the physical
attributes of noodle sheets and cooked noodles. Amongst fundamental tests, dynamic
oscillatory tests using plate/plate geometry tests are the most common ones used for
noodles. Using dynamic rheometers, properties such as storage modulus (G’), loss
modulus (G”) and phase angle (8) are measured. Cooked noodles have been reported to
have tan 5 values <<l indicating solid-like behavior (range 0.15-0.25) in the study by
Sasaki et al (2004) where this method was used to show the effect of amylose content on
C00ked noodle properties. Tanifuji et al (2003) demonstrated that with an increase in
armylose content and strength of gluten, cooked noodles showed more solid-like and more
clasfic behavior (G’ and tan 6 both increased). Creep test and stress relaxation tests have
also PCGn reported to describe the behavior of noodle dough. Hatcher et a1 (2002) used

the creep test to show that noodle dough with less starch damage exhibited more

27

extensibility than dough samples with high damaged starch. Sasaki et a1 (2004) used a
creep meter to study the effect of amylose content on the rheological properties of
noodles. They showed that the maximum creep compliance was significantly negatively
correlated with the amylose content. By stress relaxation test, Hatcher et a1 (2005)

showed that an increase in amylose content increased the stiffness of noodles.

2-4-4 Texture Profile Analysis of Noodles

Texture profile analysis (TPA), as measured by texture analyzer, involves a two-
cycle compression of the bite-sized samples of the food while a force-time curve is
recorded. A typical force-time curve obtained from TPA is shown in Figure 2.2 and it can
be analyzed as described by Boume (1968) and Peleg (1976). The peak force on the first
compression cycle is defined as hardness. The ratio of the positive force areas under the
first and second compressions (Area 2/Area l) is defined as cohesiveness. The negative
force area of the first bite (Area 3) is called adhesiveness and is the work required to pull
the probe away from the sample. Springiness is the height recovered by the sample
between the end of the first bite and the start of the second bite (Length 2/Length 1).
G\llnrniness is the product of hardness and cohesiveness; and chewiness is the product of
gumminess and Springiness. Resilience is the ratio between the area obtained during
Withdrawal from the first compression and the area of the first compression (Area 4/Area
5)- TPA provides the advantage of measuring a number of parameters from a single test.
These parameters, especially hardness, have been correlated very well with the sensory
assessment of noodles. Tang et a1 (1999) have demonstrated significant correlations
between TPA-derived Springiness and the values for sensory elasticity. Results from Ross

(2006) and Epstein et al (2002) suggested that there might be some redundancy in the

28

 

 

 

 

 

 

 

Area 3

Fig. 2.2 Typical texture profile analysis of Chinese raw noodles showing the areas
and distances used to calculate texture parameters.

(Hardness= Peak force during first compression; Cohesiveness= Area 2/Area 1;
Spnnginess= Length 2/Length 1; Gumminess= Hardness x Cohesiveness; Chewiness=
G11mminess x Springiness; and Resilience= Area 5/Area 4).

29

measurements obtained from TPA as significant correlations exist between certain pairs

of TPA attributes in noodle testing (between hardness and chewiness, and cohesiveness

and resilience).

It has been shown by Baik et al (1994) that strain levels <70% are not sufficient to
discriminate between noodle samples and that strain >70% and close to 90% gave
undesirable cutting action in TPA. Thus, for noodles, about 70-75% strain is applied. As
cooked noodles are not very homogenous, because of micro-cracks or discontinuities in
the dough, it is important to have at least 5-10 measures on each sample and report their
averages. Both rectangular and cylindrical probes of varying dimensions have been used
to obtain TPA measurements of noodles (Baik et al 1994; Baik et a1 2003; Graybosch et

al 2004; Kim and Seib 1993; Kim and Cha 1998; Tam et al 2004).

2.4.5 Noodle Texture and Wheat Proteins

Research on the functionality of wheat flour components contributing to noodle
quality indicates that starch and proteins have a major influence on the texture of noodles
made from different wheats. In contrast to the extensive literature on starch requirements
for a good quality noodle, little has been reported on the properties of wheat proteins
necessary to produce good quality noodles. Both protein content and protein quality have
been indicated to play roles in determining noodle texture (Miskelly and Moss 1985; Oh
et 31 1985a; Toyokawa et al 1989; Baik et a1 1994; Kruger et al 1994; Yun et al 1996;

Ross et a1 1997; Huang and Morrison 1988; Park et al 2003).

Protein content of wheat has been found to have a positive relationship with

texmral properties, especially hardness of cooked noodles. Hardness of cooked noodles

30

increases Significantly as protein content is increased. A higher cutting stress of noodles

prepared from high protein content flours than those from low protein content flours was

reported by Oh et al (1985a) and Kruger et a1 (1994). Baik et a1 (1994) also reported that
when udon noodles were made from high-protein-content flour, they had higher scores
for hardness, cohesiveness, gumminess and chewiness (from texture profile analysis) and
those that were prepared from soft wheat flour had lower values. Similar trend was
observed for Cantonese and instant noodles (Baik et a1 1994). While investigating the
properties of Australian flours that influence the texture of yellow alkaline noodles, Ross
et a1 (1997) concluded that increased flour protein content gave significantly firmer and
more elastic noodles (on the basis of sensory evaluation). Park et a1 (2003) reported that
hardness of cooked noodles increased significantly as protein content was increased,
althOUgh there were no significant differences in adhesiveness, springiness, and

COhesiveness of noodles obtained from flours of different protein content within the same

CultiVars,

Dough rheology indicators of protein quality have been shown to relate to noodle
eating characteristics. Miskelly and Moss (1985) showed harder bite qualities in noodles
made from doughs with higher extensograph maximum resistance values and Crosbie et
al (I 999) showed similar increases in hardness in relation to increased Farinograph dough
stability. Yun et al (1996) reported that mixograph mixing time correlated positively with
Elasticity, eating quality and total noodle score. Sedimentation volume (an index of
PFOtein quality) also eXhibits positive relationships with the texture of cooked noodles
(Huang and Morrison 1988; Baik et a1 1994; Ross et al 1997; Park et al 2003). Huang and

Morrison (1988) showed that SDS (sodium do-decyl sulfate) sedimentation volumes of

31

both Chinese and British common hard wheats were significantly correlated with
maximum cutting stress and maximum compression stress of both white salted and
yellow alkaline noodles. Baik et a1 (1994) found that a relationship exists between SDS
sedimentation volume and chewiness of udon noodles, whereas in the case of yellow
alkaline noodles, SDS sedimentation volume was found to be significantly and positively
related to noodle firmness and elasticity (Ross et a1 1997). The study conducted by Ross
et a1 (1997) suggested that protein content has a more substantial role in determining
noodle texture than protein quality. Previously, though, both Huang and Morrison (1988)
and Baik et al (1994) had demonstrated a stronger relationship between SDS
sedimentation volume (a measure of protein quality) and noodle texture than the
relationship they observed between protein content and noodle texture. The discrepancy

in results was attributed to the different genetic background of sample sets used in these

studies.

Thus, there is a question in noodle research about the relative importance of
Protein content compared to protein composition in determining the texture of noodles.
Some results suggest that protein content is the dominant factor, whereas others indicate
the importance of gluten protein composition. Some of the previous work is not definitive
and is even self-contradictory. For instance, Jun et al (1998) suggested that the strong bite
0f alkaline noodles is not so much a result of the inherent strength of the protein but of
the higher protein content of flours generally chosen for alkaline noodle production and
the Strengthening effect of alkaline salts (Moss et al 1986) used in the formulations.
However, in the same study, Jun et a1 (1998) suggested that a lower gluten index, an

md‘cator of gluten quality, and hence of protein composition, of flours specific for

32

alkaline noodle production was an indication of the 'mellow' gluten that they considered
was required for alkaline noodle production. Clearly further refinement of the

understanding of the relative importance and interaction of the two factors, protein

content and protein composition is required.

Very little systematic work has been done to determine the effect of variations in
glutenin and gliadin composition on noodle making. Nakamura (1993) concluded from
his comparison of endosperm storage proteins of different wheat varieties that a subunit
with an estimated molecular weight of 53 kD was related to good noodle viscoelasticity.
It was also shown that the loss in viscoelasticity was accompanied by the disappearance
of this subunit and appearance of a 129kD subunit. Using Canadian spring wheat
genotypes, Wesley et al (1999) showed that the presence of a specific gliadin component
and the presence of a low molecular weight glutenin subunit (LMW-GS) 45 were both
related to significant increase in dough strength, noodle viscoelasticity and the force
needed to cut the noodles. Beasley et a1 (2002) showed that puncture force, measured on
raw noodle dough, was significantly affected by variation in high molecular weight
glutenin subunits (HMW-GS) encoded by Glu-BI and Glu-DI loci. However, in this
case, in contrast to the Canadian work reviewed above, the changes in dough properties
related to glutenin variation were not carried through to the cooked noodles. Huang and

Morrison (1988) also related the presence of a specific y-gliadin band in Chinese wheats

With good noodle-making quality.

Oh et al (1985b) had earlier used the more fundamental approach of fractionation
and rec0nstitution to provide evidence for the fact that glutenins have a primary role in

determining noodle texture. In this study, a high molecular weight glutenin fraction taken

33

fi'om a wheat variety that produced hard noodles was used to replace the counterpart
fi-action fi'om the wheat variety that made soft noodles. When this was done, the cutting
strength of the cooked noodles was increased to a level equivalent to that of the hard
control. The converse was also observed. However, the results obtained by Toyokawa et
a] ( 1989) were in contrast to the results obtained by Oh et al (1985b). Through
reconstitution studies it was observed that interchanging the gluten fraction of different
wheat classes did not affect the texture of the cooked noodles. Thus, it is clear that a
substantial knowledge gap exists in the understanding of the contributions of gluten

proteins to noodle quality.

This dissertation work is aimed at determining the coefficients of correlations
between the physicochemical properties of wheat flours, their wheat protein composition
and texture profile analysis (TPA) parameters of white salted noodles. A bench-top
noodle making procedure was used to prepare noodles from ~10g wheat flour and
compare and contrast them on the basis of their texture properties. Fractionation-
rEconstitution method was used to observe the direct effect of protein content on the

texture, cooking properties, and microstructure of white salted noodles. The effect of
flour constituents (starch, gluten and water-solubles) on the texture, cooking properties
and microstructure of white salted noodles was also studied using fractionation-

rficonstitution methods.

34

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45

Chapter 3

RELATIONSHIP BETWEEN PHYSICOCHEMICAL PROPERTIES OF WHEAT
FLOUR, WHEAT PROTEIN COMPOSITION AND TEXTURAL PROPERTIES
OF COOKED WHITE SALTED NOODLES

46

3.1 ABSTRACT

Physicochemical properties and protein composition of 39 selected wheat flour
samples were evaluated and correlated with the textural properties of white salted
noodles. Flour samples were analyzed for their protein and wet gluten contents,
sedimentation volume, starch-pasting properties, and dough mixing properties by
Farinograph and Extensigraph. Molecular weight distribution (MWD) of wheat flour
proteins was determined using size-exclusion high performance liquid chromatography
(SE-HPLC), sodium-dodecyl polyacrylamide gel electrophoresis (SDS-PAGE), and
Acid-PAGE. Textural properties of white salted noodles were obtained using texture
prOfile analysis (TPA). Hardness, springiness, gumminess, and chewiness of cooked
noodles were found to be related to the dough mixing properties. Both protein content
and protein composition were found to be related to TPA parameters of noodles. The
amount of total flour protein was positively related to hardness, gumminess and
chewiness of noodles. The absolute amounts (AA) of different peak proteins obtained
from SE-HPLC data showed positive correlations with the hardness, gumminess,
chewiness and springiness of noodles. The proportion of these peak proteins (A%) were
however, not significantly related to texture parameters. The proportion of low molecular
weight glutenins/gliadins and albumins/globulins as observed from SDS-PAGE were
related positively and negatively, respectively, to the hardness, gumminess and chewiness
of cooked noodles. Amongst the alcohol-soluble proteins (from Acid-PAGE data), [3-
gliadins showed strong correlations with the texture properties of cooked noodles. For the
selected flour samples, the total protein content of flour had a stronger relationship with

the noodle texture properties than did the relative proportion of different protein sub-

47

groups. Prediction equations were developed for TPA parameters of cooked noodles
using SE-HPLC and rapid visco-analysis (RVA) data of the 30 flour samples and it was
found that about 75% of the variability in noodle hardness, gumminess, and chewiness
values could be explained by protein composition and starch pasting properties combined
together. About 50% of the variations in cohesiveness and springiness were accounted for

by these prediction equations.

48

3.2 INTRODUCTION

About 50% of the total wheat produced in the US. is exported (US Wheat
Associates 2006). The biggest wheat export markets are Asian countries like China,
Japan, South Korea and Taiwan (KACC 2006). Noodles are one of the most important
staple foods in these Asian countries (Huang and Morrison 1988) and about 40% of the
wheat flour used in these countries goes into noodle-making (Hou and Kruk 1998).
Australian and Canadian wheats are given preference over US wheat, when it comes to
noodle-making, as they perform better in terms of processing and final noodle quality. In
order to increase the US. share in international export markets, intensive breeding efforts
are underway to develop wheat cultivars that process better on noodle-making equipment
and also provide excellent quality final products.

Texture is probably the most important quality attribute of noodles that affects
consumer acceptance (Sasaki et al 2004). Noodle texture is affected both by the pasting
properties of flour and flour proteins. The pasting properties of flours have been
extensively studied in relation to the textural properties. Flour pasting characteristics are
mainly influenced by starch properties (Konik et a1 1994). Softness and cohesiveness of
noodles have been associated with low starch gelatinization temperature (Nagao 1977),
high starch peak viscosity (Oda et al 1980; Crosbie 1991; Konik et al 1992; Crosbie et a1
1992; Yun et al 1996) and high swelling power of starch (Crosbie 1991; Crosbie et al

1992; Toyokawa et al 1989; Konik et a1 1993; Wang and Seib 1996; Yun et al 1996).

Both protein quantity and protein quality have been indicated in literature to play
a role in deciding the quality of noodles. White salted noodle flour typically contains 8-

1 0% protein (Zhao and Seib 2005; Hou and Kruk 1998). A positive relationship between

49

protein content and textural properties of noodles, especially hardness, has been reported
by many researchers (Miskelley and Moss 1985; Oh et al 1985; Baik et al 1994; Kruger
et a1 1994; Yun et al 1996; Ross et a1 1997; Park et a1 2003). The surface smoothness of
cooked noodles was found to be negatively related to flour protein content (Moss et al
1987). Dough rheology indicators of protein quality have also been shown to relate to
noodle eating characteristics. Miskelly and Moss (1985) showed harder bite qualities and
more elasticity in noodles made from doughs with higher Extensigraph maximum
resistance values. Crosbie et al (1999) showed similar increases in the hardness of
noodles in relation to increased Farinograph dough stability. Yun et a1 (1996) reported
that Mixograph mixing time correlated positively with elasticity, eating quality and total
noodle score. But still very little information is available on the optimum dough

requirements for noodle-making.

Although, it has been established that the wheat protein (especially gluten)
composition, proportion of high molecular and low molecular weight proteins, and also
the presence or absence of specific glutenin subunits greatly affect the mixing properties
and the breadmaking quality of flours, very few studies have reported on the effects of a
specific subunit or a specific group of wheat proteins, or the effects of molecular weight
distribution of flour proteins, on noodle-making properties. Huang and Morrison (1988)
related the presence of a specific y-gliadin band in Chinese wheats to good noodle-
making quality. Wesley et al (1999) also reported the relationship between the presence
0f a specific gliadin component and low molecular weight glutenin subunit (LMW-GS)

and increases in viscoelasticity and hardness of noodles. Beasley et al (2002) showed

that puncture force, measured on raw noodle dough, is affected by variation in high

50

molecular weight glutenin subunits (HMW-GS). Park et a1 (2003) reported that the
proportion of salt-soluble proteins in wheat flour negatively affected the hardness of
noodles. By means of size exclusion high performance liquid chromatography (SE-
HPLC), Ohm et al (2006) showed that the amounts of specific protein groups might be
more important than their proportion in total protein in governing the textural properties

of noodles.

It is important to further research the relationship between wheat protein
composition, dough mixing properties and texture properties of noodles in order to get a
better insight into the roles of proteins in noodle-making. The specific objectives of this
study were: 1) To observe for correlations between the physicochemical properties of
selected wheat varieties and textural properties of their noodles as measured by texture
profile analysis (TPA); 2) To obtain correlations between the composition of wheat
proteins (measured by SE-HPLC and electrophoresis) and TPA parameters; and 3) To

establish prediction equations for texture properties of noodles.

51

3.3 MATERIALS AND METHODS

3.3.1 Wheat Flour Samples

Thirty-nine wheat flour samples, including thirty-three hard wheats, three dark
northern spring wheats and three soft wheats, were procured from the Wheat Marketing
Center (WMC), Portland, Oregon. The samples were from the crop years 2003, 2004 and
2005 and were part of the Asian Products Collaborative Study conducted by the WMC
during those years. The information regarding the variety, origin and grade of the

samples is listed in Table 3.1.

3.3.2 Physicochemical Analysis of Flour Samples

The flour samples were analyzed for their moisture, protein, ash, and wet gluten
contents, and sedimentation volume using AACCI (2007) Approved Methods 44-19, 46-
13, 08-03, 38-12, and 56-61A, respectively. Wet gluten was dried for 4 min in a Glutork
machine (Model 2020, Huddinge, Sweden) to determine dry gluten content. Starch
pasting properties of wheat flours were measured by a rapid visco analyzer, RVA—4
series (Newport Scientific, NSW, Australia) using AACCI Approved Method 76-21.
Dough mixing properties were determined by Farinograph and Extensigraph according to
AACCI Approved Methods 54-21 and 54-10, respectively. The Farinograph and

Extensigraph data were provided by the WMC, Portland, Oregon.

3.3.3 Protein Composition of Flour Samples

The proportions of glutenins, gliadins, and albumins/globulins, in the wheat flour

samples were determined by SE-HPLC under non-reduced conditions and by sodium

52

dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) under reduced
conditions. The gliadin proteins were further divided into sub-groups a, B, y, and (o-

gliadins by means of acid polyacrylamide gel electrophoresis (A-PAGE).

3.3.3.1 Size-Exclusion High Performance Liquid Chromatography

Extraction of total proteins Flour proteins were extracted by the procedure of Ohm et a1
(2006). One hundred and sixty milligrams of flour sample (adjusted to 14% moisture
content) was mixed with 20 ml of 0.1M sodium phosphate buffer (pH 6.9) with 1% (w/v)
SDS. The mixture was sonicated using Sonic Dismembrator 60 (Fisher Scientific,

Hampton, NH) for 3 min at the SW power setting. After sonication, the mixture was
heated in a water bath at 65°C for 30 min to stabilize the extract. The mixture was then

centrifirged for 30 min at 37,000 x g using a Beckman J2-21M centrifuge (Beckman
Coulter Inc., Fullerton, CA). The supernatant was filtered through 0.45 pm filter paper
(Millipore Co., Bedford, MA). Twenty uL of the sample extract was used for each run.
Each flour sample was extracted in duplicate and at least two chromatographic runs were
performed for each extract.

Run Conditions SE-HPLC was performed using a Waters 600E multisolvent delivery
system (Millenium 2010, Waters, Milford, MA) according to the procedure of
Dachkevitch and Autran (1989). A Biosep-SEC-S-4000 size-exclusion column
(Phenomenex, Torrance, CA) was used with a guard column (KJO-4282, Phenomenex,
Torrance, CA). The protein fractions were eluted from the column using 0.1M phosphate
buffer (pH 6.9) containing 0.1% SDS. The flow rate was 0.7 ml/min at ambient
temperature with a run time of 30 min. Proteins were detected at 214 nm using a Waters

996 photodiode array detector. The column was calibrated with non-reduced protein

53

molecular weight standards (Sigma Chemical Co., St. Louis, MO): thyroglobulin
(669,000), alcohol dehydrogenase (150,000), albumin (66,000), and carbonic anhydrase
(29,000).

Chromatogram Analysis The chromatogram was divided into five regions based on the
molecular weights of the eluting proteins (discussed in section 3.4.2) according to Mujoo
and Ng (2003). Absorbance Area (AA) and Percentage Area (A%) were calculated for

each chromatogram using Millenium software (Waters, Milford, MA).

3.3.3.2 Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis (SDS-PA GE)

Wheat flour samples were analyzed for their protein composition under reduced
condition using the SDS-PAGE method described by Ng and Bushuk (1987) with minor
modifications (Appendix I-A). Forty milligrams of flour was used from which total
reduced proteins were extracted. Eight ul of extracted sample was loaded on the gel for
electrophoresis. Protein molecular weight markers were obtained from Sigma (Sigma
Chemical Co., St. Louis, MO) and run on each gel. A reference hard wheat variety,
Neepawa, was also run on each gel. Electrophoresis was run in gels 1.5 mm thick (18 cm

wide and 16 cm long) in a vertical electrophoresis apparatus (Hoefer Scientific
Instruments, San Francisco, CA) at 200 C for 16 hr at a constant current of 10 mA per gel.

Each flour sample was run in at least duplicate. Afier staining, the proteins from each
lane of the gel were quantified by a reflectance scanning densitometer (GS 300, Hoefer
Scientific Instruments, San Francisco, CA) with GS 365W sofiware. The gels were
divided into regions for high molecular weight (HMW) glutenins, low molecular weight
(LMW) glutenins/gliadins, and albumins/globulins according to Singh et al (1990)

(discussed in section 3.4.2).

54

3.3.3.3 Acid-Polyacrylamide Gel Electrophoresis (A -PA GE)

Alcohol-soluble flour proteins were analyzed by A-PAGE using the procedure
described by Ng et a1 (1988) with minor modifications (Appendix I-B). Ethanol-soluble
proteins were extracted from 100 mg of flour sample. Eight ul of extracted sample were
loaded on the gel. Neepawa was used as a reference wheat variety for the identification of
gliadin sub-groups and was run on each gel. Each flour sample was run in at least
duplicate. Electrophoresis was run in gels 1.5 mm thick (18 cm wide and 16 cm long) in

a vertical electrophoresis apparatus (Hoefer Scientific Instruments, San Francisco, CA) at
20°C for ~ 3 hr at a constant current of 30 mA per gel. After staining, the proteins from

each lane of the gel were quantified by a transmittance/reflectance seaming densitometer
(GS 300, Hoefer Scientific Instruments, San Francisco, CA) with GS 365W software.
The gliadin patterns on the gels were divided into sub-groups a, B, y, and (o- gliadins

according to Bushuk and Sapirstein (1991) (discussed in section 3.4.2).

3.3.4 Preparation of Noodles

Noodles were prepared according to the method described by Hou 2007. A
horizontal pin mixer was used to prepare noodle dough from 1000 g of flour sample. The
flour was mixed with water (28% w/w) and salt (1.2% w/w, on flour weight basis) for 2
minutes at 90 rpm. The beaters were cleaned and the dough was mixed again for 8 min at
mixer speed of 120 rpm. After cleaning the beaters again, the dough was mixed for
additional 2 min, total mixing time being 12 min. The crumbly dough was rested for 30
min in a plastic bag at room temperature. The rested dough was compressed between two
pairs of rolls of a noodle machine (Ohtake, Model WR8-10, Tokyo Menki Co., Ltd,

Japan), each pair set at a 3 mm. gap. The compressed dough sheet was folded once in

55

between passage through each of the three pairs of rolls set at 5-mm gaps. The dough
sheet was rolled around a rolling pin and rested again, in a plastic bag, for 30 min at room
temperature. It was then passed through progressively reducing gaps of 4, 3, 2 and 1.5
mm (four times through each gap). The final thickness of the noodle sheet was 1.2 i 0.03
mm. The dough sheet was cut into 2.5 mm wide noodle strips. The noodles were stored in

a plastic bag for 24 hr before measuring their textural properties.

3.3.4.1 Cooking of Noodles

Noodles (100 g) were added to 1 L of boiling de-ionized water and cooked for
optimum cooking time. The optimum cooking time was judged by the disappearance of

central uncooked core in the noodles. The cooked noodles were transferred into a
colander and rinsed with tap water at 27°C for 10 see with slow stirring. The colander

was tapped 10 times and the noodles were then transferred to a bowl. The texture of

noodles was analyzed within 5 min of cooking.

3.3.4.2 Texture Analysis of Cooked Noodles

Texture analyzer, TA-XT2 (Texture Technologies, Scarsdale, NY) was used to
measure the texture properties of cooked noodles. Texture profile analysis (TPA) was
performed according to the procedure described by Hou ( 1997). Five strands of cooked
noodles were compressed with a 5 mm thick flat probe to 70% of their original height.
Cross-head speed was set at 1 mm/sec. From the force-time curve of TPA, hardness,
cohesiveness, springiness, gumminess, and chewiness of noodles were measured
according to Bourne (1968) and Peleg (1976). The texture data for cooked noodles was

obtained from the WMC, Portland, Oregon.

56

3.3.5 Statistical Analysis

Pearson correlation coefficients were determined among the flour chemical
properties, dough mixing properties, and the texture properties of cooked noodles using
the CORR procedure (SAS 9.1, Cary, NC). Data from all 39 samples was used to obtain
coefficients of correlation. A step-wise multiple regression procedure (REG) was

followed to develop prediction equations, for the dependent variables, using the
maximum r2 improvement option. Data from 30 wheat flour samples (Sample # 1-30)
was used to generate prediction equations. The performance of regression equations was
evaluated by coefficient of determination (r2). The equations were validated using data

from a separate set of 9 samples (Sample # 31-39).

57

3.4 RESULTS AND DISCUSSION

3.4.1 Physicochemical Properties of Wheat Flour Samples

The physicochemical properties of the 39 flour samples used in this study and the
respective textural properties of cooked noodles prepared from them are summarized in
Table 3.2. The average, range and standard deviation of selected parameters are
presented. The moisture content and ash content of the flour samples ranged from 11.9 -
14.0% and 0.34 - 0.57%, respectively. A wide range of protein content (8.4 - 13.5%)
existed among the different flour samples. Wet gluten and dry gluten yields of flours
ranged from 23.0 - 41.6% and from 7.7 — 14.2%, respectively. The range for
sedimentation volume was 16.4 — 68.8 cc. The RVA data showed that the studied flour
samples also exhibited a wide range in their pasting properties. Peak viscosity ranged
between 153 - 266 RVU. Breakdown viscosity, which is a measure of paste stability,
ranged from 41 — 130 RVU in the current study. The final paste viscosity varied from 165
— 308 RVU and set-back viscosity, from 80 - 142 RVU. This shows that the samples
chosen for this study represented a wide range of flour quality.

Dough mixing properties of flours are mainly affected by quantity and quality of
protein (Farrand 1969; Finney and Shogren 1972). The ranges for Farinograph properties
were: 53.3 - 72.6% for water absorption, 2 to 9 min for dough development time (peak
time), 3.7 - 46.5 min for stability, and 2 - 85 BU for mixing tolerance index (MTI).
Mixing time and MTI are used as indices to differentiate among the gluten strengths of
samples. Stronger flours have longer mixing times and lower MTI values (Shuey 1982).
In the present study, hard wheat flours generally exhibited longer mixing times and

greater tolerance to mixing than sofi wheat flours. The studied samples also exhibited

58

variation in their extension properties as measured by Extensigraph. The extensibility of
doughs varied fiom 12.8 to 23.0 cm and the resistance to extension ranged from 291 to
665 BU. In general, gliadins are known to contribute to dough extensibility and glutenins
to dough strength and elasticity (Wall 1979).

TPA parameters of cooked noodles varied considerably among the samples. The
range for hardness, gumminess and chewiness of noodles were 9.61 — 13.41 N, 6.20 to
8.67 N and 6.2 to 8.29 N, respectively. The cohesiveness of noodles varied from 0.612 —
0.669 and the springiness from 0.935 — 0.971. Amongst all texture parameters measured,
hardness of noodles had the widest range in values. Thus, the 39 chosen flour samples

represent a wide range of flour quality and a wide range of noodle texture properties.

3.4.2 Protein Composition of Wheat Flour Samples

An example of a typical SE-HPLC elution profile obtained from the total protein
extract of wheat flour is shown in Figure 3.1. The profile is similar to the results reported
by Dachkevitch and Autran (1989), Mujoo and Ng (2003) and Morel et a1 (2003). The
chromatogram was divided into five regions based on the molecular weights of the
eluting proteins (according to Mujoo and Ng 2003). Peak 1 (7.4-8.7 min) of SE-HPLC
corresponds to the aggregated material or HMW glutenin proteins eluted at the void
volume of the column. Peak 2 (87-116 min) consists of aggregates of polymeric glutenin
with a continuous molecular size range between 669,000 and 150,000. Peak 3 (11.6-12.6
min) and Peak 4 (12.6-13.5 min) correspond to proteins with ranges of molecular weights
of 150,000 — 66,000 and 66,000 — 29,000, respectively, and are referred to as gliadin
proteinsl Peak 5 (>13.5 min) corresponds to the molecular weight (<29,000) of

monomeric salt-soluble proteins (Dachkevitch and Autran 1989). Both Absorbance Area

59

(AA) and Percentage Area (A%) were calculated for each chromatogram (data not
shown). The relative proportions of peak 1, peak 2 and peak 3 proteins were 11.7 -—
15.28%, 19.05 — 26.49%, and 3.45 — 11.03%, respectively. The gliadin—like proteins
(peak 4) were found to be in the range of 13.15 to 21.15% of total extracted flour protein.
Peak 5 proteins were present in highest proportion (33.48 to 44.30 %) in all the studied
flour samples.

Figure 3.2, depicts the SDS-PAGE electrophoretic patterns of the wheat flour
proteins of ten of the studied samples under reduced conditions. The electrophoregram
was divided into subgroups: HMW glutenins (>84,000), LMW glutenins and gliadins
(84,000-29,000), and albumins/globulins (<29,000) based on their molecular weights
according to Singh et a1 (1990). The densitometer data obtained for the SDS-PAGE
patterns of wheat flour samples indicated that the LMW glutenins and gliadins group of
proteins was present in the highest proportion in all the flour samples (Table 3.3). Similar
ratios were reported by Lee (2002) for native flour while studying the doughs developed
to various extents.

An example of the A-PAGE patterns of alcohol-soluble proteins for the flour
samples used in this study is presented in Figure 3.3. Reference band 50 (followed by a
distinctive doublet of lower mobility) was identified from the A-PAGE pattern of the
reference cultivar Neepawa. The electrophoregram was divided into 4 subgroups: a (>
68.6), B (53.2-68.6), 7 (40.4-53.2), and co-gliadins (< 40.4) based on the relative mobility
of gliadins as described by Bushuk and Sapirstein 1991. Figure 3.4 shows the pattern
obtained for reference wheat variety Neepawa after reading it through the densitometer. It

is clear that there were distinct boundaries between adjacent gliadin subgroups. The

60

densitometer data (Table 3.3) indicated that, in general, the B-gliadins were present in the
highest proportion in the alcohol-soluble flour protein extract, followed by y-, then a- and
lastly m-gliadins. These results are in general agreement with the results of Hou et al
(1996) for soft wheat cultivars and of Branlard and Dardevet (1985) for bread wheat

flours.

3.4.3 Correlations between Physicochemical Properties of Flours and Texture

Properties of Cooked Noodles

The correlation coefficients observed between the selected physicochemical
properties of flours and TPA parameters of noodles are summarized in Table 3.4. The
hardness, gumminess and chewiness of noodles significantly increased with an increase
in the total protein content of the wheat flour samples. It has been previously reported
that the hardness or cutting stress of cooked noodles has a positive correlation with the
protein content of flour samples (Oh et a1 1985; Huang and Morrison 1988; Baik et al
1994; Kruger et a1 1994; Ross et a1 1997; Park et a1 2003). Correlation coefficients for
hardness, gumminess, and chewiness of noodles with the wet and dry gluten contents of
flours were lower than what was observed for total protein content and were not
statistically significant. No significant correlations were observed between the
cohesiveness and springiness of noodles with total protein content, or with either wet
gluten or dry gluten contents of flour samples. The SDS-sedimentation volume, which is
used as a measure of both protein content and protein quality, has also been reported to
relate positively with the hardness and chewiness of noodles (Park et a1 2003; Ross et a1
1997; Baik et a1 1994; Kruger et a1 1994; Huang and Morrison 1988; Oh et a1 1985). The

sample set used in this study, however, did not show any significant correlations between

61

SDS-sedimentation volume and TPA parameters of cooked noodles. These observations
can be related to the findings of Ross et a1 (1997) where lower correlation coefficients for
hardness of noodles were observed with the sedimentation volume than with protein
content. Results in the present study also suggest that the protein content of flour has
stronger effects on noodle texture than does the protein quality, as measured by SDS-
sedimentation volume (at least for this sample set).

Starch pasting properties have been reported to play important roles in
determining the textural properties of noodles. Peak viscosity of starch exhibited a
positive relationship with the cohesiveness of noodles at the 5% significance level (Table
3.4). A similar relationship has been reported by Baik and Lee (2003) for white salted
noodles. No correlations were observed between peak viscosity of starch and hardness of
noodles. However, peak viscosity of starch has previously been negatively correlated to
the hardness of noodles (Nagao et a1 1977; Moss 1979; Oda et a1 1980; Crosbie 1991;
Konik et al 1992; Crosbie et a1 1992; Yun et al 1996; Baik and Lee 2003). The
differences in observations could partially be attributed to the different genetic
background of the sample set used in this study or the differences in RVA profiles used in
these studies. Yun et a1 (1996) showed that different RVA profiles can contribute to the
differences in the statistical relationships between viscosities and textural properties of
noodles.

Significant negative correlation coefficients between breakdown viscosity and
hardness of noodles have been reported earlier by many researchers (Nagao et al 197 7;
Moss 1979; Oda et a1 1980; Crosbie 1991; Konik et a1 1992; Crosbie et a1 1992; Yun et al

1996; Baik and Lee 2003). But for the sample set used in this study, breakdown viscosity

62

of flours exhibited a slightly positive relationship with the cohesiveness of noodles (r =
0.305, significant at the 10% level) (Table 3.4). Since pasting properties of starch are
determined under conditions of high shear (where granule structure can be disrupted),
Ross et al (1997) pointed out that the pasting analyses of starch may not very closely
resemble the pasting properties of starch in noodles which is a static gel. According to the
authors, the structure of starch in gel produced during flour swelling volume test more
closely resembles the structure of starch in cooked noodles.

The final paste viscosity and setback viscosity were found to be positively related
with the hardness, gumminess and chewiness of noodles. Baik and Lee (2003) and Yun et
a1 (1996) also reported a similar relationship of setback viscosity with hardness of
noodles. No significant relationships were observed between any of the starch pasting
properties and springiness of noodles, except for a slightly positive correlation of
springiness (r = 0.288) with setback viscosity at the 10% level of significance (Table
3.4).

The Farinograph data obtained for the 39 wheat flour samples was also used to
evaluate for correlations with the TPA parameters of noodles. The mixing time (or peak
time) of dough had significantly positive correlations with the hardness (r = 0.380,
P<0.05), gumminess (r = 0.421, P<0.01) and chewiness of noodles (r = 0.428, P<0.01).
Farinograph stability was also correlated positively with hardness, gumminess and
chewiness of noodles. A positive but weak correlation (r = 0.284, P<0.l) was observed
between stability of the doughs and springiness of noodles prepared from those flours. It

has been reported earlier for Japanese alkaline noodles that the stability of doughs

63

positively influences the texture score of noodles (given by a trained sensory panel on the
basis of overall evaluation of texture properties) (Crosbie et a1 1999).

The Extensigraph data obtained for flour samples showed that the hardness,
springiness, gumminess and chewiness of noodles were each negatively correlated with
the extensibility of the dough but positively correlated with the resistance of the dough to
extensibility. The area under the extensibility curve was found to be positively related to
hardness, gumminess and chewiness of noodles. It is known that gliadins contribute to
dough extensibility and that glutenins are responsible for dough strength and elasticity
(Wall 1979). The amount and proportion of these two groups of proteins in total flour
proteins might thus be related to the texture quality of noodles. It was shown previously
by Miskelly and Moss (1985) that strong flours with high resistance to extensibility give
firmer and more elastic noodles than weaker flours. In their study, noodle quality was

evaluated subjectively by a sensory panel.

3.4.4 Correlations between Protein Composition and Texture Properties of Cooked

Noodles

The correlation coefficients observed between the protein composition and TPA
parameters of the noodle samples are listed in Table 3.5. In SE-HPLC, absorbance area
(AA) represents the quantitative variations in a particular protein group whereas the area
percentage (A%) represents the relative proportion of that particular group in total
extracted flour protein. From the SE-HPLC data, it was observed that hardness (r =
0.397), springiness (r = 0.372), gumminess (r = 0.366) and chewiness (r = 0.383) of
noodles were positively associated with the amount of proteins (AA) under peak 1.

However, only springiness (r = 0.344) of noodles was found to be positively related to

64

the relative proportion (A%) of peak 1 protein. According to Dachkevitch and Autran
(1989), this protein fraction (peak 1) corresponds to the HMW glutenin proteins.

The amount of protein aggregates in the 669,000 to 150,000 molecular weight
range (AA of peak 2, glutenins) positively affected the gumminess and chewiness,
hardness and springiness of noodles (at the 5% and 10% levels, respectively), but the
relative proportion of this group (A%) of proteins in flour was not important. This means
that the absolute amounts of these proteins are important for texture properties of cooked
noodles but their relative proportion in total flour protein is not significant. These results
are in agreement with the results reported earlier by Ohm et a1 2006. They also showed
that the amount of polymeric proteins eluting earlier in the SE-HPLC column influences
hardness and chewiness of noodles.

The peak 3 proteins (co-gliadins) did not exhibit any relationship with the texture
parameters of noodles. The amount of peak 4 proteins (AA), with molecular weights
between 66,000 and 29,000, was found to positively affect the hardness of noodles.
G-umminess and chewiness of noodles also had slightly positive but statistically
insignificant relationships with the gliadin proteins on SE-HPLC profile (Table 3.5). No
correlation was observed between cohesiveness and springiness of noodles with either
amounts (AA) or relative proportion (A%) of gliadins (peak 4). This fraction (peak 4) of
protein is mainly composed of alcohol-soluble gliadins (Dachkevitch and Autran 1989).

The amount of proteins eluting at the end of separation (albumins/globulins) were
also found to be positively associated with the hardness, gumminess, and chewiness of
noodles. Ohm et a1 2006, however, reported that higher amounts and relative proportions

of albumins/globulins type of proteins decrease the hardness and chewiness of noodles.

65

The different observations could be attributed to different sample sets used in the two
studies. Also, different SE-HPLC column and different elution solvents were used for the
separation of wheat proteins in these two studies. Ohm et a1 (2006) used a Biosep-SEC-S-
4000 column (600 x 7.5 mm) and an acetonitrilezwater (50:50) mixture with 0.1% tri-
fluoroacetic acid as an elution solvent. Whereas, in the present study a Biosep-SEC-S-
4000 column (300 x 7.8 mm) and a 0.1M phosphate buffer (pH 6.9) containing 0.1%
SDS was used as an eluting solvent. The differences in the SE-HPLC conditions and use
of different sample sets might result in the differences in correlations observed between
the albumins/globulin proteins and the textural properties of cooked noodles. Like the
results from Ohm et al (2006), our SE-HPLC data also indicates that the textural
properties of cooked noodles are influenced more by the quantity of different protein
fractions (AA) than by the proportion of these fractions in total flour protein (A%).

The results obtained from SDS-PAGE patterns of total wheat proteins (under
reduced conditions) were also correlated with the texture properties of cooked noodles.
The albumins and globulins of wheat proteins (molecular weight < 29,000) separated by
SDS-PAGE, under reduced conditions, revealed negative relationships with the hardness,
springiness, gumminess and chewiness of noodles (Table 3.5). These results were in
agreement (unlike SE-HPLC results) with the findings of Ohm et al 2006 where negative
correlations were observed for hardness and chewiness of noodles with the
albumins/globulins of wheat flour proteins separated by SE-HPLC column. Park et al
(2003) also reported that the proportion of wheat flour proteins soluble in 0.5M NaCl,
i.e., albumins/globulins, negatively affects the hardness of noodles. The higher the

percentage of these proteins (albumins and globulins) in total flour protein, the lower the

66

hardness value of noodles prepared from those flours. In the present study, the protein
fraction representing the group of LMW-GS and gliadins (on reduced SDS-PAGE) was
observed to be positively related with hardness, gumminess and chewiness values of
noodles (Table 3.5). These results correspond with the results from SE-HPLC data
collected under non-reducing conditions (Table 3.5). No correlations were observed
between the proportion of HMW-GS and any of the texture properties of noodles for the
sample set studied.

From Acid-PAGE data, it was found that the proportion of B-gliadins in total
alcohol-soluble proteins was negatively associated with the hardness, springiness,
gumminess and chewiness of noodles. Proportion of y-gliadins was significantly
positively correlated with the cohesiveness of cooked noodles. This is in general
agreement with Huang and Morrison (1988) who earlier reported that the presence of a
specific y-gliadin band (45.5) in Chinese wheats was related to strong flour gluten

properties and good cooking quality of noodles.

3.4.5 Prediction of Noodle Texture Properties

An important objective of this study was to be able to predict noodle texture
properties on the basis of flour properties. The texture parameters of cooked noodles (as
obtained from TPA) showed maximum correlation with the absorbance area (AA) of SE-
HPLC data. Thus, the AA data of 30 flour samples (Sample # 1-30, Table 3.1) was used
to generate prediction equations for noodle texture parameters. A separate set of 9
samples (Sample # 31-39, Table 3.1) was used to validate those prediction equations. The

following prediction equations were obtained:

67

Hardness = 7.36 + (-1.23E-6 x P3) + (—5.88E—7 x P4) + (-3.55E-7 x P5) +
(5.12E-7 x Total) ......................................................... (1)

Springiness = 0.934 + (7.025E-9 x P1) + (2.896E-9 x P2) + (-3.500E-9 x P5)
+ (6.993E-10 x Total) .................................................. (2)

Gumminess = 4.49 + (2.24E-7 x P2) + (-5.60E-7 x P3) + (-2.56E-7 x P4) +
(15913-7 x Total) ....................................................... (3)

Chewiness = 4.12 + (5.67E-7 x P1) + (7.86E-7 x P2) + (2.97E-7 x P4) +
(5.21E-7 x P5) + (-3.84E-7 x Total) ................................... (4)

where, P1, P2, P3, P4, and P5 are the AA values of peak 1, peak 2, peak 3, peak 4
and peak 5, respectively, under the SE-HPLC curve and ‘Total’ is the total area under the
SE-HPLC curve. The coefficients, intercept, r2, F-values and Prob >F of the prediction
equations and the root mean square error (RMSE) obtained from the validation of these
prediction equations are given in Table 3.6. No prediction equation could be obtained for
cohesiveness of noodles (significant at the 1% or 5% level) using SE-HPLC data. From
the r2 values of these prediction equations, it is clear that protein composition (AA) of
flours can account for approximately 35% of the variability in the textural quality of
noodles.

From previous reports and results from this study, it is clear that the starch pasting
properties play a very important role in determining the texture of noodles. It has also
been shown earlier for noodles that the use of both protein and starch properties data
improves the prediction ability of equations generated through multiple regression
analyses (Konik et al 1993, 1994; Yun et a1 1996; Ohm et a1 2006). In the present study,

SE-HPLC and RVA data were combined in order to improve the r2 values for better

68

prediction of texture properties of noodles; the AA data and RVA data of 30 flour
samples (Samples # 1-30, Table 3.1) were used to generate prediction equations for
noodle texture parameters. A separate set of 9 samples (Samples # 31-39, Table 3.1) was
used to validate those prediction equations. The following prediction equations were

obtained:

Hardness = 2.20 + (-1.12E-7 x P2) + (-1.13E-6 x P3) + (~1.16E—6 x P4) + (-6.20E-7 x P5)
+ (7.60E-7 x Total) + (50015-2 x SB) + (-o.201~:-3 x PV)........................(5)

Cohesiveness = 0.536 + (-1.769E-8 x P1) + (1.096E-8 x P3) + (7.027E-9 x P4) +
(5.682E-4 x PV) + (-2.18lE-4 x BK) ......................................... (6)

Springiness = 0.916 + (1.456E-8 x P1) + (1.13559 x P4) + (-391 1139 x P5) +
(1.326E-4 x PV) + (-2.196E-4 x FV) + (4.580 E-4 x SB) ................... (7)

Gumminess = 0.38 + (5.19E-7 x P1) + (5.85E-7 x P2) + (2.25E-7 x P5) +
(-1.63E-7 x Total) + (1.94E-3 x FV) + (2.87E-2 x SB) ..................... (8)

Chewiness = 0.09 + (5.68E-7 x P1) + (5.46E-7 x P2) + (1 .89E-7 x P5) +
(-1.48E-7 x Total) + (12313-3 x PV) + (30713-2 x SB) ....................... (9)

where P1, P2, P3, P4, and P5 are the AA values of peak 1, peak 2, peak 3, peak 4
and peak 5, respectively, under the SE-HPLC curve and ‘Total’ is the total area under the
SE-HPLC curve. PV is the peak viscosity, SB is the set-back viscosity, BK is the

breakdown value and FV is the final viscosity of flour as obtained from RVA. The
coefficients, intercept, r2, F-values and Prob >F of the prediction equations and the root

mean square error (RMSE) obtained from the validation of these prediction equations are
given in Tables 3.7 and 3.8. It was found that the SE—HPLC and RVA data combined

together could explain about 75% of the variability in the hardness, gumminess, and

69

chewiness of the cooked noodle samples, and about 45% and 53% of the variability in

their cohesiveness and springiness, respectively.

70

3.5 SUMMARY

Amongst the measured flour physicochemical properties, protein content and
starch pasting properties were found to have more influence on the textural properties of
white salted noodles than any other parameter studied. Hardness, gumminess, and
chewiness of cooked noodles were significantly positively related to the total protein
content of flour samples and their final paste viscosity and setback viscosity. Peak
viscosity of flour was also positively related to the cohesiveness of cooked noodles.
Correlations of noodle texture parameters with the stability of the doughs as measured by
F arinograph and Extensigraph data indicate that the protein strength of the wheat flours
(which is influenced by protein composition) also determines the texture properties of
noodles. Determination of protein composition by SE-HPLC indicated that the quantities
of different protein fractions in flour contribute more to the texture of cooked noodles
than the relative proportion of these fractions out of the total protein. From SDS-PAGE
performed under reduced conditions, it was observed that the albumins/globulins fraction
of proteins was negatively related to the hardness of cooked noodles, whereas the fraction
representing LMW glutenins/gliadins was positively related to the hardness, gumminess,
and chewiness of noodles. The proportion of B-gliadins in total alcohol-soluble proteins
was negatively associated with the hardness, springiness, gumminess and chewiness of
noodles, whereas the cohesiveness of noodles was positively related to the proportion of
y-gliadins. The prediction models developed using SE-HPLC and RVA data of the flour
samples were able to estimate the textural properties of cooked noodles with minimum
deviation from the counter part texture data obtained using pilot-scale noodle making

procedures.

71

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75

TABLE 3.1 Varieties, Origin and Grade of the Flour Samples Used
in this Study (n=39)

 

 

Sample Variety Origina Gradeb
No.

1 NDO3-2986 ND HW

2 ALTURAS ID SW

3 SD97W604 SD HW

4 NDO3-2985 ND HW

5 WA00-7931 WA HW

6 BZ998-447W WA/MT HW

7 NuSky MT HW

8 WA7936 WA HW

9 OR942496 OR HW
10 Common HRS de DNS
11 Blanca Grande WA HW
12 Comm-Mostly Trego NE HW
13 Common SW de SW
14 AH/APH Philippines HW
15 Platte CO HW
16 ID377S WA HW
17 Comm-HRW de HR
18 Thai Ctrl. Thailand HW
l9 WSU7936-Low WA HW
20 WSU7936-Hi WA HW
21 Philippines-A Control HW
22 Taiwan-AH Control HW
23 APH Control HW
24 APW Control HW
25 SWH Commercial SW

26 NuHorizon - Conrad MT HW
27 ID0604 ID HW
28 NuFrontier - Choteau MT HW
29 Briggs-Brookings SD DNS
30 Granger-Brookings SD HR

31 MTCL 0306 MT HW
32 ID 0597/Lochsa ID HW
33 Otis WA HW
34 Wendy SD HW
35 SD97W609 SD HW
36 NDSW 0345 ND HW
37 Laughlin-Wilbur BR WA HW

7030

38 Antelope NE HW
39 Philippines Control Philippines DNS

 

3ND: North Dakota; ID: Idaho; SD: South Dakota; WA: Washington; MT: Montana;
OR: Oregon; de: Portland, Oregon; NE: Nebraska and; CO: Colorado.

bHW: Hard white wheat; SW: Sofi white wheat; DNS: Dark northern spring

wheat; and HR: Hard red wheat.

76

TABLE 3.2 Mean, Standard Deviation and Ranges of the Physicochemical
Properties and Noodle Texture Parameters of the Wheat Flour Samples (n=39)

 

 

 

 

 

 

Analytical Propertiesll Mean SDb Minimum Maximum
Moisture Content (%)
12.8 0.5 11.9 14.0
Ash Content (%) 0.48 0.04 0.34 0.57
Protein Content (%) 11.3 1.2 8.4 13.5
Wet gluten (%) 31.4 4.2 23.0 41.6
Dry Gluten (%) 11.1 1.5 7.7 14.2
Sediment Volume (cc) 52.0 11.6 16.4 68.8
Pasting Properties
Peak Viscosity 226 25 153 266
Breakdown Viscosity 81 19 41 130
Final Viscosity 258 28 165 308
Set-back Viscosity 113 14 80 142
Farinograph
Absorption (%) 65.5 5.0 53.5 72.5
Peak time (min) 4.5 2.0 2.0 9.0
Stability (min) 14.0 10.0 3.5 46.5
MTI (BU) 25 17 2 85
Extensigraph (n=33)
Resistance (BU) 458 94 291 665
Extensibility (cm) 17.7 2.4 12.8 23.0
Noodle Texture Properties
Hardness (N) 11.56 0.85 9.61 13.41
Cohesiveness 0.640 ' 0.010 0.612 0.669
Springiness 0.957 0.010 0.935 0.971
Gumminess (N) 7.39 0.56 6.20 8.67
Chewiness (N) 7.08 0.57 6.20 8.29

 

aAsh, protein, wet gluten and dry gluten percentages are on 14% moisture
basis; pasting properties are in RVU (units used in the RVA procedure);
MTI: Mixing tolerance index; BU: Brabender units; and N: Newtons.
bSD: Standard deviation.

77

TABLE 3.3 Electrophoresis Data (% protein) of the Wheat Flour Samples

 

 

 

 

SDS-PAGE“ Acid-PAGE”
Sample LMWG Albumins
# HMWG + + (.0 y B a
Gliadins Globulins

1 9.00 69.15 21.85 15.45 30.35 36.70 17.50
2 8.75 67.15 24.10 16.55 34.40 35.85 13.20
3 7.60 68.95 23.45 20.75 23.70 39.35 16.20
4 7.40 70.95 21.65 20.35 28.15 34.20 17.30
5 9.40 69.00 21.60 16.40 27.50 37.10 19.00
6 8.55 66.10 25.35 13.65 23.90 34.60 27.85
7 7.05 71.60 21.35 14.30 27.05 31.10 27.55
8 9.50 66.45 24.05 19.15 28.05 32.60 20.20
9 9.95 64.00 26.05 16.85 29.65 37.65 15.85
10 7.25 72.15 20.60 17.60 29.20 32.10 21.10
11 7.20 73.15 19.65 17.30 26.55 31.40 24.75
12 6.15 74.70 19.15 12.70 29.70 35.60 22.00
13 6.15 72.05 21.80 13.50 30.25 36.45 19.80
14 6.65 75.05 18.30 12.30 30.60 36.45 20.65
15 5.65 73.70 20.65 14.85 30.95 38.75 15.45
16 6.50 72.75 20.75 12.85 28.10 31.75 27.30
17 6.40 72.05 21.55 13.85 26.70 37.10 22.35
18 4.45 64.95 30.60 17.40 26.45 32.30 23.85
19 6.70 66.75 26.55 16.55 28.40 32.50 22.55
20 8.20 66.05 25.75 18.60 25.75 32.35 23.30
21 8.35 70.80 20.85 17.00 29.15 34.55 19.30
22 7.15 71.75 21.10 17.60 29.05 35.10 18.25
23 7.55 69.55 22.90 17.85 27.20 34.95 20.00
24 5.90 67.05 27.05 19.00 31.10 31.00 18.90
25 6.25 74.25 19.50 15.60 28.25 34.20 21.95
26 5.90 67.30 26.80 14.65 29.05 36.35 19.95
27 6.60 66.00 27.40 15.75 23.35 44.20 16.70
28 4.10 73.70 22.20 13.20 27.15 40.90 18.75
29 5.90 69.35 24.75 16.35 29.75 39.25 14.65
30 6.25 74.40 19.35 15.75 26.75 40.35 17.15
31 5.95 73.75 20.30 17.25 28.55 32.10 22.10
32 6.40 68.20 25.40 15.95 22.55 37.50 24.00
33 7.80 66.10 26.10 17.95 29.25 35.75 17.05
34 6.30 63.25 30.45 24.30 23.35 38.35 14.00
35 6.20 66.85 26.95 17.70 28.55 33.35 20.40
36 6.40 70.40 23.20 17.15 23.60 37.50 21.75
37 7.00 69.70 23.30 14.95 23.75 30.85 30.45
38 7.40 73.15 19.45 14.80 24.00 37.90 23.30
39 7.10 73.85 19.05 17.35 28.35 37.05 17.25

 

aSDS-PAGE: Sodium dodecyl polyacrylamide gel electrophoresis; HMWG: High molecular

weight glutenins; and LMWG: Low molecular weight glutenins.
bAcid-PAGE: Acid polyacrylamide gel electrophoresis; (0: Omega gliadins; y: Gamma

gliadins; 0: Beta gliadins; and 0.: Alpha gliadins.

78

TABLE 3.4 Pearson’s Coefficients of Correlation (r) between the Physicochemical
Properties and Texture Profile Analysis Parameters of Cooked Noodles

 

 

 

 

 

Analytical Property Hardness Cohesiveness Springiness Gumminess Chewiness
Protein Content 0.350** -0. 105 0.178 0.316** 0.3 16**
Wet Gluten 0.273 0.007 0.181 0.273 0.277
Dry Gluten 0.244 0.033 0.148 0.251 0.251
Sedimentation Value 0.069 -0.096 0.040 0.048 0.050
Pasting Properties
Peak Viscosity 0.143 0.363" 0.145 0.241 0.246
Breakdown Viscosity 0.030 0.305* 0.167 0.115 0.126
Final Viscosity 0.340** 0.119 0.160 0.364" 0.364"

Set-back Viscosity 0.478*** 0.010 0288* 0.467*** 0.475***
Farinograph

Absorption -0.132 0.151 0.055 -0.076 -0.068

Peak Time 0.381 ** 0.182 0.252 0.421*** 0428*"

Stability 0.325" 0.209 0284* 0.393“ 0.399“

MTI -0.222 -0.018 0.188 -0.233 -0.190
Extensi graph 3 (n=33)

Resistance 0.383" -0.093 0.353M 0.374“ 0.387**

Extensibility -0.362** -0.112 -0.576*** -0.385** -0.436**
Area Under the Curve 0451*" -0.233 0.226 0.405" 0.401"

 

*, **, and ***, significantly different at the 10%, 5%, and 1% levels, respectively.

aExtensigraph values were available only for 33 flour samples.

79

TABLE 3.5 Pearson’s Coefficients of Correlation (r) between the Protein Composition of
Flours, separated with various methods, and Texture Profile Analysis ('1‘ PA) Parameters

 

 

 

 

 

of Noodles

Corrhrgctiesliltlion Hardness Cohesiveness Springiness Gumminess Chewiness
HPLCa (AA)
P1 0.397“ -0.092 0.372** 0.366** 0.383“
P2 0311* 0.099 0.305* 0.333” 0.347**
P3 -0.015 0.182 0.276 0.035 0.060
P4 0.340“ -0.117 0.031 0.296 0.280
P5 0.352“ -0.030 0.100 0.334** 0.325"
Total 0.359" 0.002 0.230 0.351M 0.354M
HPLCa (A%)
P1 0.165 -0.165 0.344” 0.124 0.135
P2 -0.041 0.212 0.205 0.024 0.048
P3 -0.243 0.244 0.203 -0.169 -0.141
P4 0.128 -0.204 -0.232 0.065 0.035
P5 0.041 -0.103 -0.278 0.006 -0.022
SDS-PAGEb
HMWG 0.091 0.161 0.254 0.122 0.147
LMWG/Gliadins 0.355" 0.001 0.296 0.341 ** 0.349"
Alb/G10 -0.411*** -0.067 -0.414*** -0.409*** -0.427***
Acid-PAGEc
(0 -0.097 0.067 -0.25 -0.072 -0.095
7 0.056 0.387" 0.304 0.156 0.178
[3 -0.325** -0.237 -0.366** —0.387** -0.405***
01 0.276 -0.112 0.238 0.244 0.257

 

*, **, and ***, significantly different at the 10%, 5%, and 1% levels, respectively.
aP1: Peak 1; P2: Peak 2; P3: Peak 3; P4: Peak 4; and P5: Peak 5 proteins separated by SE-HPLC.
bHMWG: High molecular weight glutenins; LMWG: Low molecular weight glutenins; Alb:
Albumins;

and Glo: Globulins separated by SDS-PAGE.
co): Omega gliadins; y: Gamma gliadins; [3: Beta gliadins; and 11: Alpha gliadins separated by
Acid-PAGE.

80

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TABLE 3.8 The r-square, F and Probability of F of the Prediction Equations
of Noodle Texture Properties from the SE-HPLC and RVA data, and Root Mean
Square Error (RMSE) from their validation for Noodle Texture Parameters

 

 

Texture Prob
Parameter R2 F > F RMSE
Hardness 0.72 7.91 <0.0001 0.89

Cohesiveness 0.45 3.91 0.0098 0.018
Springiness 0.53 4.27 0.0049 0.013

Gumminess 0.75 11.33 <.0001 0.69
Chewiness 0.74 11.15 <.0001 0.67

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Chapter 4

COMPARISON OF A BENCH-SCALE NOODLE MAKING PROCEDURE WITH
A PILOT-SCALE PROCEDURE TO EVALUATE TEXTURAL PROPERTIES OF
COOKED NOODLES

88

4.1 ABSTRACT

A small scale noodle making procedure is needed to evaluate texture properties of
cooked noodles when the amount of wheat flour available for testing is quite limited. The
main objective of this study was to develop a bench-scale noodle-making method, based
on already widely used pilot-scale methods, to measure texture properties of noodles
prepared from 10 g of wheat flour. A 1000-g pilot scale published procedure and an
experimental 10-g bench scale procedure were compared using thirty flours varying in
their physicochemical properties and noodle-making qualities. The texture parameters
(hardness, cohesiveness, springiness, gumminess and chewiness) as obtained from
Texture Profile Analysis of cooked noodles were used to draw comparisons between the
two procedures. Very good agreement was observed in the hardness, gumminess and
chewiness values of noodles obtained from both the procedures, whereas cohesiveness
and springiness did not correlate. Similar trends were observed in the overall texture
properties of noodles. Results also showed that the bench-scale noodle-making procedure
could discriminate among wheat flours on the basis of their noodle-making properties. By
means of regression prediction equations, it was found it is possible to predict results
from the pilot-scale procedure on the basis of texture values obtained from the bench-
scale procedure. Thus, the bench-scale procedure can be useful for measuring noodle
texture properties of early generations of wheat breeding lines and for other applications

where a limited amount of sample is available, as in reconstitution studies.

89

4.2 INTRODUCTION

The general processing steps of noodle making involve: mixing of raw materials,
resting of dough, sheeting and compounding of the dough, followed by final sheeting and
then slitting. Mixing of ingredients is usually carried out in horizontal or vertical mixers
(Nagao 1996). About 30—35% water is added along with other ingredients and mixed for
about 10-15 min to give crumbly dough. Optimum water absorption is determined by
flour proteins, pentosans and damaged starch content (Hou and Kruk 1998). After
mixing, the dough is rested for about 20-40 min for uniform hydration of flour particles.
Uniform distribution of water results in a smooth noodle sheet, smooth noodle surface
and improved starch gelatinization (Hatcher 2001). The rested dough is passed through
sheeting rolls to form a noodle sheet, which is compounded and then passed again
through rolls to form a single sheet. The compounded sheet is then rested again for 30-40
min to relax the dough in order to facilitate subsequent sheeting. The relaxed dough is
sheeted through several pairs of rolls, with progressively decreasing roll gaps. It is
desirable that the reduction ratio of thickness at any pass be adjusted to two-thirds to
avoid damage to the gluten network (Nagao 1996). The final roll gap is adjusted
according to the noodle type. The noodle sheet is finally passed through the slitting
machine to cut the sheet into noodle strands of desired width and length.

Noodle-making procedures using different sample sizes, varying from 100 g to
1000 g, have been reported in the literature (Oh et a1 1983; Toyokawa et al 1989; Baik et
al 1994; Crosbie et a1 1999; Hatcher et al 2002; Park et a1 2003; Ohm et al 2006; Hou
2007). All these procedures involve basic mixing, resting, sheeting and cutting steps as

described above and use pilot-scale noodle making machines. In research, though, often

90

only small amounts of samples are available, amounts that are insufficient to run on these
machines. This presents a challenge for the researchers evaluating plant breeders’ wheat
lines for noodle quality (Kovac et a1 2003) or when performing reconstitution studies to
evaluate the effect of flour constituents on noodle quality (Sissons et al 2002).
Fractionation of flour into its components is an energy intensive (because of freeze
drying) and tedious process; It takes about four days to obtain fractions from 100 g of
flour. Obtaining large quantities of fractions for noodle-making (~ 500 to 1000g for one
batch) is not very practical. Preparing noodles using a bench—scale machine (with ~ 10 g
flour) could be a more feasible approach when evaluating samples of limited quantity.

The literature contains very limited information on noodle quality evaluation
using small scale noodle making equipments. Beasley et a1 (2002) used 10 g of flour to
prepare noodles on a micro-scale (25 mm diameter) noodle making machine. Hand-
driven pasta type machines have also been used to prepare noodles from as little as 25 g
of flour (Sui et a1 2006). Kovac et al (2003) developed a small scale noodle sheeting
machine that could make noodles from 5-50 g of flour and produce results similar to a
pilot sheeting facility. Viscoelasticity of cooked noodles made on their small-scale
machine correlated highly with the viscoelasticity of noodles made on a pilot-scale
machine.

In the present study, comparisons were made between the qualities of noodles
made from a bench-scale noodle-making machine available in the market to prepare
noodles from 10 g flour and the quality of those prepared on a pilot-scale machine. The
specific objectives of this study were (1) to develop a modified noodle making procedure

using a bench-scale machine; (2) to compare it with a published pilot-scale noodle-

91

making procedure and evaluate its suitability for evaluation of noodle texture properties,
and (3) to develop prediction equations, for pilot-scale noodle properties using bench-

scale procedure data, and validate those equations.

92

4.3 MATERIALS AND METHODS

4.3.1 Wheat Flour Samples

Thirty wheat flour samples were procured from the Wheat Marketing Center
(WMC), Portland, Oregon. The samples were from the crop years 2003, 2004 and 2005
and were part of the Asian Products Collaborative Study conducted by the WMC every
year. The information regarding variety, origin and grade of the samples is listed in Table
4.1. Wheat variety Caledonia (sofi wheat) and Sharpshooter (hard wheat) were used to
conduct preliminary experiments (for the bench-scale procedure) for optimization of

formula water, mixing time and cooking time of noodles.

4.3.2 Physicochemical Analysis of Wheat Flour Samples

The flour samples were analyzed for their contents of moisture, protein, ash and
wet gluten using AACCI (2007) Methods 44-19, 46-13, 08-03 and 38-12, respectively.
Dough mixing properties were determined by Farinograph according to Approved
Method 54-21. Farinograph data was obtained from WMC, Portland, Oregon. All the

analyses were performed in duplicate.

4.3.3 Bench-Scale Noodle Making

4.3.3.1 Procedure

A 10-g Mixograph (National Mfg. Co., Lincoln, NE) was used to prepare noodle
dough from 10 g (14% m.b.) of flour. The flour was first dry mixed for 30 see after which
31% (w/w) water and 1.2% (w/w) salt (on a flour weight basis) were added to the flour

over the next 30 sec. The dough was mixed for an additional 2 min and then scraped to

93

clean the dough from the blades and bottom of the mixer. Mixing was continued for an
additional 3 min; total mixing time was 6 min. The crumbly dough was pressed lightly by
hand and rested for 30 min in poly bags at room temperature. The rested dough was then
sheeted four times, folding the dough sheet between each pass, through a 1.6 mm gap
between the rolls of a bench-scale noodle making machine (Model KPRA, Kitchen Aid,
St. Joseph, MI). The noodle sheet was allowed to rest again, in poly bags, for 30 min.
After the second resting, the noodle sheet was further reduced in thickness by passing the
dough sheet through a gap of 1.3 mm and then 1.1 mm (four times through each gap),
folding the dough sheet between each pass. The dough sheet was finally passed through a
roll gap of 0.8 mm four times (without folding) to get a uniform noodle sheet.
Immediately afier the final sheeting, the sheet was cut into 1.5 mm wide noodle strips
using a bench-scale noodle cutter (Model KPRA, Kitchen Aid, St. Joseph, MI). The
noodle strips were cut into noodle strands of about 5 cm in length. The noodle strands
were then stored in poly bags at room temperature for 24 hr before measuring their

textural pr0perties. Noodle samples were prepared in triplicate for each flour sample.

4.3.3.2 Cooking of Noodles

Noodles were cooked one day after storage at room temperature. Noodles (~10 g)
were added to 150 m1 of boiling distilled water in a beaker and cooked for 3 min while
stirring the water gently every 30 sec to prevent noodles from sticking to the bottom of
the beaker. The cooked noodles were transferred into a colander and rinsed with room
temperature distilled water (150 ml) followed by draining for 30 sec. The surface water
was removed by shaking the colander 10 times. The cooked noodles were then held in

distilled water (350 ml) for 1 min at room temperature and then drained for 30 sec,

94

followed by shaking the noodles in the colander 10 times. The texture analysis was
performed within 5 min of cooking the noodles. The cooked noodles were held in

distilled water at room temperature while performing the texture analysis.

4.3.3.3 Texture Analysis of Cooked Noodles

A texture analyzer, TA-XT2 (Texture Technologies, Scarsdale, NY) was used to
measure the texture properties of the cooked noodle samples. The load cell was calibrated
with a 2 kg test weight. A set of five strands of cooked noodles was placed on a flat metal
plate and compressed crosswise twice, with a 3 mm X 70 mm metal probe (TA-42), to
70% of their original height. Pre-test speed was 4 mm/sec; test—speed and post-test speeds
were 1 mm/sec. From the force-time curve of texture profile analysis (TPA), hardness,
adhesiveness, cohesiveness, springiness gumminess, chewiness and resilience of noodles
were measured according to Boume (1968) and Peleg (1976). At least five measurements

were taken for each replicate.

4.3.4 Pilot-Scale Noodle Making

The texture data for pilot-scale prepared noodles was obtained from the WMC,

Portland, Oregon.

4.3.4.1 Procedure

Noodles were prepared according to the method described by Hou 2007. A
horizontal pin mixer was used to prepare noodle dough from 1000 g of flour sample. The
flour was mixed with water (28% w/w) and salt (1.2% w/w, on flour weight basis) for 2
minutes at 90 rpm. The beaters were cleaned and the dough was mixed again for 8 min at

mixer speed of 120 rpm. After cleaning the beaters again, the dough was mixed for

95

additional 2 min. Total mixing time was 12 min. The crumbly dough was rested for 30
min, in a plastic bag, at room temperature. The rested dough was compressed between
two pairs of rolls of a noodle machine (Ohtake, Model WR8—10, Tokyo Menki Co., Ltd,
Japan), each pair set at a 3 mm gap. The compressed dough sheet was folded once in
between passage through each of the three pairs of rolls set at 5-mm gaps. The dough
sheet was rolled around a rolling pin and rested again, in a plastic bag, for 30 min at room
temperature. The dough sheet was passed through progressively reducing gaps of 4, 3, 2
and 1.5 mm (four times through each gap). The final thickness of the noodle sheet was
1.2 d: 0.03 mm. The dough sheet was cut into 2.5 mm wide noodle strips. The noodles

were stored in a plastic bag for 24 hr before measuring their textural properties.

4.3.4.2 Cooking of Noodles

Pilot-scale noodles (100 g) were added to 1 L of boiling deionized water and
cooked for a pre-determined optimum cooking time (Hou 2007). Disappearance of
central uncooked core of noodles was used as a measure of optimum cooking time. The
cooked noodles were transferred into a colander and rinsed with tap water at room
temperature for 10 see with slow stirring. The colander was tapped 10 times and the
noodles were then transferred to a bowl. The texture of noodles was analyzed within 5

min of cooking.

4.3.4.3 Texture Analysis of Cooked Noodles

A texture analyzer, TA-XT2 (Texture Technologies, Scarsdale, NY), was used to
measure the texture properties of cooked noodles. The TPA was performed according to

the procedure described by Hou (1997). Five strands of cooked noodles were

96

compressed, with a 5 mm thick flat probe, to 70% of their original height. From the
force-time curve of TPA, hardness, cohesiveness, springiness, gumminess and chewiness

of noodles were measured according to Boume (1968) and Peleg (1976).

4.3.5 Statistical Analysis

Statistical analysis was performed using SAS version 9.1 (SAS Institute Inc.,
Cary, NC). ANOVA was performed using a general linear model procedure to determine
significant differences between the samples. Means were compared using Fisher’s least
significant difference (LSD) procedure. Significance was defined at the 5% level unless
mentioned otherwise. Replicated results were reported as mean values. All 30 samples
were used to obtain correlation coefficients between texture parameters of noodles
obtained by pilot-scale and bench-scale procedures. The CORR procedure was used to
obtain correlation coefficients. Data from 20 wheat flour samples (Sample # 1-20 in
Table 4.1, crop year 2003 and 2004) were used to generate prediction equations using the
REG procedure. The equations were validated using data from a separate set of remaining
10 samples (Sample # 21-30 in Table 4.1, crop year 2005). The performance of
regression equations was evaluated by coefficient of determination (r2) of the prediction
equations and the root mean square error (RMSE), and correlation coefficients (r)

between actual and predicted values.

97

4.4 RESULTS AND DISCUSSION

4.4.1 Physicochemical Properties of Wheat Flour Samples

Thirty flour samples with different flour properties were used to compare the
bench-scale and pilot-scale noodle making procedures. The physicochemical properties
of these flour samples are listed in Table 4.2. The moisture content and ash content of the
flour samples ranged from 11.89 - 14.05% and 0.34 - 0.52%, respectively. A wide range
of protein content (8.09 - 13.55%) existed among the flour samples. Similar to protein
content, wet gluten content also showed wide range (21.2 - 37.9%). The F arinograph data
revealed that the water absorption values of flour samples were between 53.5% and
74.2%. The mixing time varied from 1.5 to 8 min and mixing tolerance index (MTI)
values ranged greatly from 2 to 95 BU. Mixing time and MTI values indicate that the
sample set used in this study also varied in terms of strength of gluten protein. Thus, the
30 chosen flour samples represented a wide range of flour quality and therefore were a
good set with which to validate the bench-scale procedure for distinguishing between

texture properties of noodles.

4.4.2 Comparison of Bench-Scale and Pilot-Scale Procedure

Caledonia, a soft wheat variety with 7% protein content, and Sharpshooter, a hard
wheat variety with 12% protein content, were used to optimize the formula water, mixing
time and cooking time of noodles for the bench-scale procedure (data not shown). A
constant water absorption (31% w/w) was used to prepare noodles from all the flour
samples using the bench-scale procedure. Water less than 31% produced excessively dry

noodle dough resulting in material loss during noodle processing. Mixing time of 6 min

98

was found to be sufficient in order to uniformly distribute formula water in the dough and
to obtain uniform granulation of the noodle dough. Formula water and mixing time were
optimized by subjectively evaluating the dough for proper hydration, uniform distribution
of water and uniform granulation; all these attributes are important for good sheetability
of dough (Hou 1998). Cooking time was judged by the disappearance of the white
uncooked core of noodles; cooking for 3 min in boiling water was sufficient for all the
samples included in this study.

Four soft wheat flour samples (Alturas—2004, Alturas-2005, commercial flour, and.
a common soft wheat flour) and four hard wheat flour samples (NDO3-2985, WA00-
7931, BZ998-447W, and NuSky) were used to closely compare the bench-scale and pilot-
scale noodle making procedures in terms of noodle texture properties (Table 4.3). It
appeared that both the procedures were able to significantly differentiate between the
flours on the basis of the textural properties of noodles prepared from them. For the eight
studied samples, similar trends were observed in the overall properties of noodles as
determined by both of the procedures.

It was obvious that the noodles obtained from the pilot—scale method had higher
values for hardness, gumminess and chewiness than the noodles tested using the bench-
scale procedure. The hardness of noodles, as determined by TPA, is defined as the peak
force during the first compression of the test sample. The peak force value depends on the
hardness of noodles and the contact area between the noodles being tested and the TPA
probe. The bench-scale noodles were 1.5 mm wide and were tested with a 3 mm wide
probe; the total contact area for force measurements was 5 x 1.5 mm x 3 mm or 22.5 mm2

(for 5 noodle strands). For noodles tested using the pilot-scale procedures, the contact

99

area between the noodles and the probe was 5 x 2.5 mm x 5 mm (62.5mm2); this larger
contact area likely contributed to the increased hardness values for noodles tested by this
procedure. The difference in hardness of noodles can also be attributed in part to their
thickness, 1.2 mm for fresh pilot-scale noodles and 0.8 mm for fresh bench-scale noodles
(assuming that they swell by the same degree during cooking). Formula water (28% in
case of pilot-scale and 31% in case of bench-scale procedure) also affects the final
thickness and hardness of cooked noodles as determined by TPA. Park and Baik (2002)
reported an increase in the thickness of cooked noodles with decreased water absorption.
It has also been shown by earlier workers (Oh et a1 1983) that the maximum cutting stress
or hardness of noodles increases with increase in the thickness of cooked noodles. The
noodles prepared fiom pilot-scale procedure (by WMC, Oregon) were thicker than the
noodles prepared from the bench-scale procedure, hence, showed higher hardness values.
In the present study, however, the stress values of noodles were quite comparable. For
example, for Alturas-2005 the stress values were 0.13 N/mm2 by the bench-scale
procedure and 0.15 N/mm2 by the pilot-scale procedure. The difference in stress values
could be due to the different machines, different sheeting rolls or different sheeting
conditions used for noodle-making in each of the procedures.

The gumminess and chewiness of noodles are calculated as hardness x
cohesiveness and as hardness x cohesiveness x springiness, respectively. Thus, the
differences in gumminess and chewiness values can be partially explained by the
differences in the hardness values. The values of cohesiveness and springiness of noodles
obtained from two different procedures were quite comparable in their magnitudes.

Similarity in cohesiveness and springiness values is not surprising considering that these

100

parameters are measured as ratios of areas and lengths, respectively, and not as absolute
values. Cohesiveness was measured as the ratio between the area under the second
compression peak and the area under the first compression peak, and springiness of
noodles was the ratio between height of the noodles on the second compression and the
height of the noodles on the first compression.

The noodle texture data, for all 30 flour samples, obtained from both the
procedures is presented in Tables 4.4 and 4.5. The bench-scale procedure showed trends
in the hardness, gumminess and chewiness of noodles similar to the trends obtained fiom
the pilot-scale procedure. Correlation coefficients were obtained between TPA
parameters of noodles obtained from bench-scale and pilot—scale procedures. As shown in
Table 4.6, a good agreement was observed in the hardness (r = 0.785), gumminess (r =
0.904) and chewiness (r = 0.830) values obtained from both the procedures.
Cohesiveness and springiness values of noodles obtained using both procedures were,
however, not significantly correlated. The bench-scale procedure can thus be used to
evaluate flour samples for overall textural properties of noodles. Additionally, the results
were highly reproducible with a coefficient of variation of less than 10% among
replicates for the TPA parameters (data not shown). An important point to mention here
is, since the bench-scale procedure requires only 10 g of flour sample, it may be better
suited for applications where sample size is limited, especially in evaluating breeders’
wheat lines and for reconstitution studies. Because of the down-scale of the size of the
machines, bench-scale procedures also provide cost-effectiveness by saving on the power
requirements, maintenance of machines and cost of ingredients required to prepare

noodle samples.

101

4.4.3 Predicting Pilot-Scale Texture Properties using Bench-Scale Texture Data

Regression equations were developed for pilot-scale hardness, gumminess and
chewiness using values from the bench-scale method. Out of a total of 30 samples, data
from 20 representative wheat flour samples was used to develop the regression equations,
and the remaining 10 samples (also varying in texture properties) were used to validate

those equations. The following prediction equations were obtained:

Hardnessps = 3.27 X Hardness},S + 12.39 ........................................ (1)
Gumminessps = 3.06 X Gumminess!)S + 29.06 ................................... (2)
Chewinessps = 2.22 X Chewinessbs + 259.56 ................................... (3)

The r2, F -values and Prob >F for equations (1), (2) and (3) are listed in Table 4.7.
It can be seen for all three equations that the 1'2 values were significant below the 1%
level. The predicted and actual values, obtained for the pilot-scale procedure, for
hardness, gumminess and chewiness of 10 samples, were compared. A comparison of
predicted and actual values for these parameters is shown in Figure 4.1. The correlation
coefficients were obtained between the actual and predicted values of hardness,
gumminess and chewiness of noodles. It is very clear from the r-values, r = 0.74
(P<0.05), 0.89 (P<0.01) and 0.89 (P<0.01) for hardness, gumminess and chewiness,
respectively, that very good agreement existed between the predicted and actual values.
The RMSE values (Table 4.7) also indicate that the actual and predicted values were very
close in their magnitude. For the large set of samples studied, therefore, texture data from
noodles produced by the bench-scale procedure could be used to predict counter part

texture values for noodles produced by the pilot-scale method.

102

4.5 SUMMARY

This study demonstrated that the bench-scale noodle making procedure can be
used to evaluate noodle texture properties and also to differentiate between flour samples
on the basis of their noodle making properties. Noodles prepared from the bench-scale
procedure had lower values for hardness, gumminess and chewiness; however
cohesiveness and springiness were of the same magnitude as those of noodles from the
same flour made from a pilot-scale procedure. The noodles prepared by the bench-scale
procedure showed similar trends in their overall texture properties as the noodles
prepared from the pilot-scale procedure. A good degree of agreement (r value) was
observed between. the respective hardness, gumminess and chewiness values obtained
from both of the procedures. By means of regression prediction equations, it was also
shown that it is possible to predict the pilot-scale texture values from bench-scale texture
data. The bench-scale procedure can thus be successfully used for screening wheat flours
for noodle texture parameters with an added advantage of small sample size requirement

and cost-effectiveness.

103

4.6 LITERATURE CITED

AACC International. 2007. Approved Methods of the American Association of Cereal
Chemists, 10th Ed. Method 44-19, 46-13, 08-03 and 38-12 and 54-21. The
Association: St. Paul, MN.

Baik, B. K., Czuchajowska, Z., and Pomeranz, Y. 1994. Role and contribution of starch
and protein contents and quality to texture profile analysis of oriental noodles. Cereal
Chem. 712315-320.

Beasley, H. L., Uthayakumaran, S., Stoddard, F. L., Partridge, S. J ., Daqiq, L., Chong, P.,
and Bekes, F. 2002. Synergistic and additive effects of three high molecular weight

glutenin subunit loci. 11. Effects on dough functionality and end-use quality. Cereal
Chem. 79:301-307.

Boume, MC. 1968. Textural profile of ripening pears. J. Food Sci. 33:223-226.

Crosbie, G. B., Ross, A. S., Moro, T., and Chiu, P. C. 1999. Starch and protein quality
requirements of Japanese alkaline noodles (Ramen). Cereal Chem. 76:328-334.

Hatcher, D. W. 2001. Asian noodles processing. Pages 131—157 in: Cereals Processing
Technology. G. Owens, ed. Woodhead Publishing Ltd.: Cambridge, England.

Hatcher, D. W., Anderson, M. J ., Desjardins, R. G., Edwards, N. M., and Dexter, J. E.
2002. Effects of flour particle size, and starch damage on processing and quality of
white salted noodles. Cereal Chem. 79:64-71.

Hou, G. 2007. Asian products collaborative project, Portland, OR.

Hou, G., and Kruk, M. 1998. Asian noodle technology. AIB Technical Bulletin. Vol. XX,
Issue 12.

Hou, G., Kruk, M., Petrusich, J., and Colletto, K. 1997. Relationships between flour
properties and Chinese instant fried noodle quality for selected U.S. wheat flours and
Chinese commercial noodle flours. J. Chinese Cereals Oils Assoc. 12 (3):7-13.

Kovac, M. I. P., Fu, B. X., Woods, S. M., Dahlke, G., Wang, C., Sarkar, A. K., and Khan,
K. 2003. A small scale laboratory noodle sheeting machine. J. Texture Stud. 33:559-
569.

104

Nagao, S. 1996. Processing technology of noodle products in Japan. Pages 19-194 in:
Pasta and noodle technology. J. E. Kruger, R. B. Matsuo and J. W. Dick, eds. AACC,
St. Paul, MN.

Oh, N. H., Seib, P. A., Deyoe, C. W., and Ward, A. B. 1983. Noodles.I. Measuring the
textural characteristics of cooked noodles. Cereal Chem. 60:433-438.

Ohm, J. 3., Ross, A. S., Ong, Y. -L., and Peterson, C. J. 2006. Using multivariate
techniques to predict wheat flour dough and noodle characteristics from size-
exclusion HPLC and RVA data. Cereal Chem. 83:1-9.

Park. C. S., and Baik, B. K. 2002. Flour characteristics as related to optimum water
absorption of noodle dough for making white salted noodles. Cereal Chem. 79:867-
873.

Park, C. 8., Hong, B. H., and Baik, B. K. 2003. Protein quality of wheat desirable for
making fresh white salted noodles and its influence on processing and texture of
noodles. Cereal Chem. 80:297-303.

Peleg, M. 1976. Tetxure profile analysis parameters obtained by an Instron universal
testing machine. J. Food Sci. 41 :721-722.

Sissons, M. J., Gianibelli, M. C., and Batey, I. L. 2002. Small-scale reconstitution of
durum semolina components. Cereal Chem. 79:675-680.

Sui, 2., Lucas, P. W., and Corke, H. 2006. Optimal cooking time of noodles related to
their notch sensitivity. J. Texture Stud. 37:428-441.

Toyokawa, H., Rubenthaler, G. L., Powers, J. R., and Schanus, E. G. 1989. Japanese
noodle qualities. I. Flour components. Cereal Chem. 66:382-386.

105

TABLE 4.1 Variety, Origin and Grade of the Flour Samples
Used in this Study (n=30)

 

 

8211:3316 Variety Origina Gradeb
1 NDO3-2985 ND HD
2 WA00-7931 WA HD
3 BZ998-447W WA/MT HD
4 NuSky MT HD
5 Cmm.HRS de DNS
6 Comm-Mostly Trego NE HD
7 Comm-SW de SW
8 Blanca Grande CA HD
9 Comm-Mostly Trego KS/CO HD
10 Comm-HRW de HR
11 1133775 WA HD
1 2 Alturas ID SW
13 WSU793 6-Low WA HD
14 WSU7936-Hi WA HD
1 5 HRS Commercial NS
1 6 Philippines-A Control HD
17 Blanca Grande CA HD
18 APH Control HD
19 Platte CO HD
20 SWH Commercial SW
21 ID0604 ID HD
22 NuFrontier - Choteau MT HD
23 Granger-Brookings SD HR
24 Alturas ID SW
25 MTCL 0306 MT HD
26 Platte CO HD
27 Wendy SD HD
28 Trego NE HD
29 Antelope NE HD
30 Philippines Control Philippines DNS

 

aND: North Dakota; ID: Idaho; SD: South Dakota; WA: Washington; MT:

Montana; de: Portland, Oregon; NE: Nebraska; and CO: Colorado.

bHD: Hard white wheat; DNS: Dark northern spring; SW: Soft white wheat; NS:

Northern spring wheat; and HR: Hard red wheat.

106

TABLE 4.2 Physicochemical Properties' of Wheat Flour Samples

 

 

Sample Moisture Protein Ash Wet Water Peak MTIb
No Content Content Content Gluten Absorption Time (BU)
' (%) (%) (%) (%) (%) (mm)
1 13.2 13.0 0.51 36.4 70.1 3.5 20
2 12.9 10.7 0.34 29.9 64.8 6.0 30
3 13.4 12.0 0.44 31.3 65.4 5.5 20
4 13.7 11.8 0.45 32.9 62.6 7.5 35
5 12.8 13.5 0.48 35.7 67.1 7.0 10
6 13.8 11.5 0.46 31.7 62.7 3.0 5
7 13.1 8.9 0.41 23.0 54.0 1.5 65
8 13.2 11.2 0.39 32.0 74.2 4.5 10
9 13.3 9.9 0.46 26.9 63.6 2.5 25
10 12.7 10.7 NA 28.8 66.4 3.5 30
11 12.3 10.6 NA 24.1 68.0 2.5 35
12 12.0 7.3 NA 21.2 53.5 1.5 95
13 13.2 9.2 NA 24.5 66.9 2.0 35
14 12.4 10.3 0.42 28.5 68.3 2.5 20
15 12.3 13.0 0.52 32.8 68.2 8.0 20
16 12.6 11.2 0.44 31.3 66.8 7.5 20
17 12.3 9.3 0.44 23.0 72.9 2.5 45
18 12.4 12.9 0.47 36.4 68.8 7.0 30
19 11.9 11.3 0.52 33.1 66.8 6.5 40
20 11.9 8.4 0.44 23.1 54.5 2.0 65
21 12.5 9.7 0.48 25.9 70.5 2.5 44
22 14.0 10.5 0.44 28.4 64.9 2.0 17
23 12.8 12.1 0.49 34.7 67.3 3.0 7
24 12.0 8.1 0.45 25.2 54.7 1.5 56
25 13.3 11.0 0.41 29.5 64.3 2.5 14
26 12.7 11.9 0.58 36.0 67.9 6.0 27
27 13.1 10.6 0.50 28.8 60.2 2.0 11
28 13.2 9.6 0.40 27.5 65.5 2.0 35
29 12.6 11.9 0.51 33.4 62.7 6.0 34
30 12.8 12.7 0.48 37.9 69.0 4.0 2

 

a Protein, ash content, wet gluten percentages are on 14% moisture basis.
b MTI: Mixing tolerance index; and BU: Brabender units.

107

TABLE 4.3 Comparison of Noodle Texture by Two Different Noodle Making

 

 

Proceduresa
Sampleb Hardness Cohesiveness Springiness Gumminess Chewiness

(N) (N) (N)
Bench-Scale
Alturas-2005 3 .00e 0.681b 0.95 0bc 2.04ef 1.94def
Comm.SWH 3.54c 0.665c 0.956ab 2.35bc 2.26c
Alturas-2004 2.92e 0.659c 0.942c 1.92f 1.81f
Common SW 3.27d 0.680b 0.95 8ab 2.23cd 1.86ef
NDO3-2985 3.32d 0.635d 0.95 8ab 2.11de 2.07d
WA00-7931 3.20d 0.704a 0.964ab 2.25c 2.01 de
BZ998-
447W 3.75b 0.6530 0.960ab 2.45b 2.51b
NuSky 4.06a 0.680b 0.967a 2.76a 2.88a
Pilot-Scale
Alturas 9.44e 0.647abc 0.939b 6.10d 5.73e
Comm.SWH 12.17bc 0.631cde 0.956ab 7.67b 7.34bc
Alturas 9.00e 0.663a 0.947ab 5 .96d 5 .64e
Common SW 1 1.22d 0.630cde 0.953ab 7.080 6.74d
NDO3-2985 11.66cd 0.6l7de 0.967a 7.15c 6.95cd
WA00-7931 1 1.20d 0.656ab 0.959ab 7.37bc 7.07bcd
BZ998-
447W 12.61ab 0.613e 0.961 ab 7.72b 7.43b
NuSky 13.26a 0.639bcd 0.966a 8.46a 8.18a

 

2‘ANOVA was conducted separately on bench-scale and pilot-scale data; means followed by
same letters in a column (for a particular procedure) are not significantly different; Significance
was defined at the 5% level.

bSee Table 4.1 for details on samples.

108

TABLE 4.4 Texture Properties 'b of Noodles Obtained from the Bench-Scale

 

 

Noodle Making Procedure

Sample Hardness Cohesiveness Springiness Gumminess Chewiness

No. (N) (N) (N)
1 3.32ij 0.6351 0.958abcd 2.11no 2.07jklm
2 3203' 0.704a 0.964ab 2.25ijk 2.011mn
3 3.750d 0.653hijk 0.960abc 2.45defg 2.51bc
4 4.06a 0.680cd 0.967a 2.76a 2.88a
5 3.84bc 0.683bcd 0.961abc 2.63b 2.5%
6 3.77Cd 0.696ab 0.954abcd 2.63b 2.43cd
7 3.27ij 0.6800(1 0.958abc 2.23jklm 1.86op
8 3.251j 0.688bc 0.955abcd 2.24jk1 2.27fgh
9 3.251j 0.653hijk 0.958abcd 2.12mno 1.91nop
10 3.36hi 0.660fghij 0.960abc 2.22jklmn 2.031mn
1 1 3.74Cde 0.652jk 0.957abcd 2.43efg 2.33defg
12 2.92k 0.659ghij 0.9420(1 1.92p 1.81p
13 3.51fgh 0.6521jk 0.952abcd 2.281j 2.17hijk
14 3.82130 0.654hijk 0.938d 2.50cdef 2.35defg
15 3.94ab 0.644kl 0.952abcd 2.54bcde 2.42cde
16 3.85bc 0.679cd 0.947abcd 2.61b 2.48de
17 3.241;“ 0.670defg 0945de 217an 2.05klmn
18 3.77de 0.692abc 09523de 2.62b 2.5066
19 3.84130 0.665efghi 0.955abcd 2.55m 2.44cd
20 3.54fg 0.665efgh 0.956abc 2.35ghi 2.26ghi
21 3.54fg 0.612m 0.94lcd 2.17klmn 2.04klmn
2?- 3.52fgh 0.6361 0.959abc 2.24jk1 2.15hijkl
23 3.57ef 0.645kl 0.959abc 2.31hij 2.21 ghij
24 3.00k 0.681cd 0.950abcd 2.040 1.94mnop
25 3.65efd 0.662efghij 0.941cd 2.41fgh 2.27efgh
26 3.87bc 0.673def 0.946bcd 2.60bc 246de
27 3.27ij 0.650jk 0.94lcd 2.13lmno 2.001mno
28 3.40ghi 0.662efghij 0.9420d 2.251jk 2.12ijkl
29 3.79de 0.674de 0.950abcd 2.56bcd 2.43cd
3O 3.76cd 0.674de 0.950abcd 2.54bcde 2.4lcdef

 

a’Reported numbers are the mean of three values.
t’Within each column, means followed by the same letters are not significantly different;
Significance was defined at the 5% level.

109

TABLE 4.5 Texture Properties 'b of Noodles Obtained from the Pilot-Scale
Noodle Making Procedure

 

 

Sample Hardness Cohesiveness Springiness Gumminess Chewiness
NO- (N) (N) (N)
1 11.66fghij 0.617jk 0.967abcde 7.191 6.95hij
2 11.20hijk 0.656abcdef 0.959abcdefg 7.37hi 7.07fghi
3 12.61bcde 0.613k 0.96labcdef 7.72fgh 7.43efg
4 13 .26abc 0.639defghij 0.966abcde 8.46abc 8.18ab
5 12.64bcde 0.643bcdefghi 0.969abcd 8.12cdef 7.86de
6 13.41 ab 0.647bcdefghi 0.956abcdefg 8.67ab 8.29a
7 l 1.22ijkl 0.630hijk 0.953abcdefg 7.07ij 6.74in
8 10.93jk1m 0.664ab 0.958abcdefg 7.25i 6.95ij
9 10.33mno 0.653bcdefgh 0.955abcdefg 6.74jk 6.43k1
10 12.09efgh 0.612k 0.959abcdefg 7.39hi 7.09fghi
1 l 1 1.08jklm 0.654bcdefg 0.972ab 7.25i 7.04ghij
12 9.00q 0.663abc 0.947efg 5.96n 5.64n
13 1069an 0.656abcdef 0.9510defg 7.01ij 6.66jk
l4 12.16defg 0.654bcdefg 0.965abcde 7.95defg 7.67cde
15 12.45cdef 0.65 8abcde 0.964abcde 8.19cde 789de
16 12.58bcde 0.659abcd 0.968abcd 8.28bcd 8.01abc
17 9.56opq 0.677a 0.951bcdefg 6.47klm 6.151m
18 13.13abc 0.634fghijk 0.965abcde 8.32abcd 8.02abc
19 12.97abcd 0.650bcdefgh 0.974a 8.43abc 8.21ab
20 12.17defg 0.631hijk 0.956abcdefg 7.67gh 7.34efgh
21 9.6 1 opq 0.645bcdefghi 0.951bcdefg 6.201mn 5.89mn
22 10.86jklm 0.626ijk 0.95defg 6.79jk 6.45k1
23 10.39lmno 0.632ghijk 0.951cdefg 6.56kl 6.24lm
24 9.44pq 0.647bcdefghi 0.939g 6.10mn 5.73n
25 11.28hijk 0.641cdefghi 0.957abcdefg 7.22i 6.92ij
26 13.74a 0.632ghijk 0.951bcdefg 8.67a 8.25ab
27 11.46ghijk 0.618jk 0.941 fg 7.08ij 6.66jk
28 9.99nop 0.678a 0.96abcdefg 6.78jk 6.51kl
29 12.19defg 0.636efghij 0.971abc 7.75 fgh 7.52de
30 1 1.98efghi 0.657abcde 0.947efg 7.86efg 7.45ef

 

aReported numbers are the mean of two values.

1’Within each column, means followed by the same letters are not significantly
different; Significance was defined at the 5% level.

110

TABLE 4.6 Correlation of Noodle Texture Parameters Obtained from Bench-Scale
Noodle Making Procedure and Noodle Texture Parameters from Pilot-Scale Noodle
Making (n=30)

 

 

Texture
Parameter Hardnesspsa Cohesivenessps Springinessps Gumminessp5 Chewinessps
Hardnessbsb 0.785** -0125 0.582** 0.815“ 0.824“
CohesivenessbS 0360* 0.245 0.172 0.437* 0426*
Springinessbs 0.301 * -0.339 0.266 0.231 0.245
Gumrninessbs 0.851“ -0.039 0.598M 0.904“ 0.908M
Chewinessbs 0.783" -0.071 0.611” 0.821" 0.830M

 

a'ps: Pilot-scale noodle making method .
bbs: Bench-scale noodle making method.
*and **, significant at 5% and 1% level, respectively.

111

00508 wafimfi 0:000: 03800—5 ”mac

.002? 0000:0000 000 3300 0003000 00.00 000000 0008 000m ”mg/Eu
00506 mac—«E 0:000: 0.000-:0c0m ”00..

00030000 0030605 0080:0w 0“ 00m: 003 om; a 038% Eob 0000“

 

 

23 500.0 5. :6 02.0 0003 mm.~ - - 300053000
24.0 500.0 00.2 _ 03.0 00.3 - 002m - 300058800
.80 500.0 3.9 55.0 3.2 - - Rd 6330:0003
meM m m N. 308005 300033000 300058800 0300000003 00000803
A no.5 SHEEP

 

”50.02 0.0002 20500:.— E0..._ 23050.3.— 003x08
0:000 Z 00.. .0003035— 00333.5 05 u0 “— u0 00:30:00.— 000 ..— .00000010 4000000.: .w0302
0:000 Z 0.00m-._000m 80.: 003039 00000—0000m 255,—. 0:502 ..0 80035000 Ev ”ma—fin.

112

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E 1
E, .
a 1
8 1 0
§ 1 o0 1
.5 1 .
5 1 o
.1: O. 1
U
7 ° 0
3, o
2; 1
1 1
L 1
5 .1 2 v 2 _ 2 - . .. 2 a 2 7 2,1
5 6 7 8 9
Observed Chewiness (N.mm)
r=0.89
9 '1' — — — — — — — " — — "1
A 1 O
0 1 1
m 8 .
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E 7 1 O .
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6 7 8 9
Observed Gumminess (N)
r=0.74
14 F 7 ~--—-- ~—
1 1
A 13
E. 1 9 1
a O 9 1
1: 12 1 O
E 1 ° ’ ' 1
3 11 - °
‘12 1 ° 1
' |
E 10 1 . 1
9 1.- . ._-_fi* . 2w -. -. 22-22-.
9 10 11 12 13 14

Observed Hardness (N)

Fig. 4.1 Comparison of predicted and actual values of texture parameters of noodles
as obtained from the pilot-scale method (Data from sample # 21-30 was used).

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Chapter 5

EFFECT OF GLUTEN PROTEIN CONTENT ON THE TEXTURE, COOKING
PROPERTIES, AND MICROSTRUCTURE OF WHITE SALTED NOODLES

114

5.1 ABSTRACT

Two wheat varieties, Caledonia (soft wheat) and NuHorizon (hard wheat) were
fractionated into starch, gluten and water-soluble fractions. These fractions were used to
produce reconstituted flours with four different protein levels (6.5, 8.0, 9.5 and 11.4% for
Caledonia, and 6.3, 7.9, 9.4, and 10.9% for NuHorizon). Noodles were prepared from
these reconstituted flours and cooked noodles were tested for their texture, cooking yield,
cooking loss, and force relaxation behavior. The microstructure of uncooked noodles was
observed using Confocal Laser Scanning Microscope (CLSM). It was found that the
hardness, gumminess and chewiness of cooked noodle samples significantly increased
with increases in the protein content of reconstituted flours. The adhesiveness and
resilience of cooked noodles slightly decreased with increase in protein content of the
samples. Cohesiveness and springiness of noodles were unaffected. Cooking data showed

that increasing the protein content of the samples decreased the yield of cooked noodles,
and cooking loss. Higher Fmax, and higher residual force were observed during force

relaxation of cooked noodles with higher protein content. It also means that noodles,
from both wheat varieties, became more elastic with increases in protein content. For
both varieties, the microstructure of raw noodle samples containing the highest protein
level showed more developed and more continuous protein matrix when compared to
samples with lower protein content. The CLSM z-sectioning and quantification of
proteins showed definite increase in the amount of protein matrix in the raw noodle
samples as the amount of protein was increased. Overall, noodles from both Caledonia
and NuHorizon flours showed similar changes in their textural, cooking, and structural

properties of noodles with increases in their protein content.

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5.2 INTRODUCTION

Color and texture of noodles are the key quality factors that affect consumer
acceptability of the product (Park and Baik 2002). Color of the noodles should be bright,
either white or yellow depending upon the noodle type, and free of dark specks or
discoloration; minimal darkening over a 48 hr period is desirable for fresh noodles (Hou
and Kruk 1998; Wang et a1 2002). Texture of noodles, however, is more complicated,
difficult to define and varies with the type of noodles and regional preferences. Both
protein content (Miskelly and Moss 1985; Oh et al 1985a; Baik et a1 1994; Kruger et al
1994; Yun et al 1996; Ross et a1 1997; Park et al 2003) and protein quality (Miskelly and
Moss 1985; Huang and Morrison 1988; Baik et al 1994) have been indicated to play roles

in deciding the texture of cooked noodles.

Wheat flour with ~10% protein content is considered suitable for white salted
noodle-making (Park et a1 2003; Hou 2001). A positive relationship has been reported
between protein content and textural properties of noodles (especially hardness) by many
researchers (Miskelley and Moss 1985; Oh et al 1985a; Baik et al 1994; Kruger et al
1994; Yun et al 1996; Ross et a1 1997; Park eta12003). It was also shown that the surface
smoothness of cooked noodles is negatively related to flour protein content (Huang and
Morrison 1988). However, only very few direct studies have been conducted to support
the role of protein quantity in noodle-making; Rho et a1 (1989) used fractionation-
reconstitution methods to discuss the role of gluten protein content in deciding the color
and texture of dried oriental noodles. Surface firmness and cutting stress were used as
parameters to judge the quality of cooked noodles. There is no direct evidence of the role

of proteins in governing the texture profile analysis (TPA) parameters or cooking

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properties such as cooking loss and cooking yield of noodles. TPA of noodles provides
an advantage of measuring multiple parameters on the noodles simultaneously; some of
these parameters have been significantly correlated with their sensory counterparts (Ross

2006)

The organization of proteins, starch and other polymers, at the microscopic level,
is very important and plays a critical role in the texture of food products. Scanning
electron microscopes and confocal laser scanning microscopes (CLSM) are very useful
tools that allow us to view the three-dimensional organization and interactions of these
components (Fardet et a1 1998). CLSM provides several advantages over scanning
electron microscopes as the sample preparation is not very elaborate and it is also
possible to scan through different layers of a sample (z-sectioning) without destroying the
sample (especially useful for the study of protein networks). A large number of images
can be rapidly obtained and processed with CLSM. CLS microscopy has been used
earlier to study dough structure (Lee et a1 2001; Peighambardoust et al 2006) and a few
studies have also reported the structure of pasta products (Zweifel et a1 2003; F ardet et a1
1998). The effect of gluten protein content on the ultrastructure of noodles, however, has
not been studied. The three dimensional organization of food components affects the
macroscopic structure (shape of food particles) and the overall textural properties of
foods (Fardet et a1 1998). Stress relaxation and creep recovery are one of the simpler
methods used to obtain structural information about the final food products or
intermediate stages like dough. Stress relaxation involves instantaneous application of
strain on the test sample and the change in stress or force is recorded as a function of

time, whereas creep involves application of constant stress, during which change in strain

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is recorded (Steffe 1996). Cooked noodles are highly viscoelastic in structure (Ross
2006) and have been shown exhibit stress relaxation properties (Hatcher 2004; Hatcher et

a1 2005) and creep recovery (Sasaki et a1 2004).

The objective of this study was to use fractionation-reconstitution procedures to
understand the role of gluten protein quantity on the textural, cooking, and structural
properties of white salted noodles. The structural properties of cooked noodles were
studied, at the macroscopic level, using a force relaxation method. LSC microscopy was

used to observe the microstructure of raw noodles prepared from reconstituted flours.

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5.3 MATERIALS AND METHODS

5.3.1 Wheat Flour Samples

Two wheat cultivars, Caledonia (Soft White, crop year 2001) and NuHorizon
(Hard White, crop year 2005) were used for this study. The two cultivars were selected
based on their protein content, dough-mixing and noodle-making properties. Caledonia
and NuHorizon were tempered overnight to 14.5% and 15.5% moisture content,
respectively. The wheats were milled on a Buhler MLU-202 Automatic Mill (Buhler AG,

Uzwil, Switzerland) to obtain straight grade flour from the wheat samples.

5.3.2 Flour Quality Tests

Flour moisture, protein, ash and wet gluten contents were analyzed using AACCI
Approved Methods 44-19, 46-13, 08-03 and 38-12, respectively (AACCI 2007). Dough
mixing properties were determined by F arinograph and Mixograph, according to AACCI
Methods 54-21 and 54-40A, respectively. Starch pasting properties were measured by a
Rapid-Visco Analyzer, RVA—4 series (Newport Scientific, NSW, Australia) using

AACCI Method 76-21 (AACCI 2007). All analyses were performed in duplicate.

5.3.3 Fractionation of Flours

F lours were fractionated into three components: starch, gluten and water-solubles
using the procedure described by MacRitchie (1985) with some modifications. Flour (100
g, 14% m.b.) was mixed into dough with an amount of water according to its F arinograph
water absorption; the dough was mixed for half a minute, just enough to give a cohesive

mass that was easy to handle. The starch and water-soluble fractions were isolated by

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hand kneading the dough in small aliquots of distilled water (total of 800 ml) and gluten

was obtained as a viscoelastic mass. Water and dough temperature were maintained at
15°C throughout the washing process; 15°C temperature results in efficient separation of

gluten without compromising much on the functional properties of gluten (MacRitchie
1985). The distilled water-starch slurry was centrifuged at 5,000 x g for 10 min using a
Sorvall RC-SB centrifuge (Dupont, Wimington, DE) and the supernatant was decanted.
The supernatant (water-soluble fraction) was frozen in aluminum trays immediately and
freeze dried. The starch (sediment) was spread in aluminum pans and allowed to air-dry
at room temperature for 72 hr. Air-dried starch has been used before in reconstitution
studies to establish the effect of flour fractions on frozen bread doughs (Lu and Grant
1999). The wet gluten was divided into six parts, frozen and freeze-dried within 48hr.
The air-dried starch and freeze-dried gluten fractions were initially ground using a Model
4E grinding mill (Quaker City Mill, Philadelphia, PA) and then finally ground to a
particle size of S 250 u (74 mesh screen) using a coffee grinder. According to MacRitchie
(1985), particle size of S 250 1.1 of reconstituted flour gave the same mixing properties as
that of the parent flour. All the fractions were weighed and analyzed for their moisture

and protein content following AACCI Methods 44-19 and 46-13, respectively. All the

fractions were stored at 4°C in polybags with desiccant until needed.

5.3.4 Preparation of Noodles from Original Parent Flour Samples

Noodles were prepared from parent flours (CP and NP) using the bench-scale
procedure described in Chapter 4 (the only difference was that instead of constant
formula water optimum formula water was used in this study). Optimum water required

for noodle-making, for each parent flour, was determined by mixing 10 g of that flour (on

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14% moisture basis) in a 10-g Mixograph (National Mfg. Co., Lincoln, NE), with
varying, amounts of water, for 6 min for each trial. The appearance (no dry patches) and
handling properties (neither too tight nor droopy) of the dough sheet were used to judge
the optimum amount of water for noodle-making. The optimum formula water used to
prepare noodles from parent flour samples is listed in Table 5.4. The noodle strands were
stored in polybags at room temperature for 24 hr before measuring their textural,
cooking, and force relaxation properties. Samples for the CLSM were rapidly frozen

using dry ice and stored in the freezer until CLSM examination.

5.3.5 Preparation of Noodles from Reconstituted Flour Samples

Reconstituted parent samples (CR and NR) were prepared by mixing starch,
water-solubles and gluten fractions in the same proportions as obtained from the original
parent flour by the fractionation procedure. Test samples were prepared by varying the
protein content of the reconstituted flours. Calculated amounts of gluten fraction from the
respective parent flour were used to increase the protein content of reconstituted flours.
Four different levels of protein were tested for both Caledonia (6.5, 8.0, 9.5, and 11.4%
as CRPl, CRP2, CRP3, and CRP4, respectively) and NuHorizon (6.3, 7.9, 9.4, and
10.9% as NRPl, NRP2, NRP3, and NRP4, respectively). (Note: Sample CR is same as
samples CRPl and sample NR is same as sample NRP4). Increase in gluten fraction or
protein was compensated for by an equivalent decrease in the starch content of the
reconstituted flour. The amount of the water-soluble fraction was kept constant for all test
samples of a particular flour (Caledonia or NuHorizon). Total mass of the reconstituted

flour was kept constant at 10 g (on 14% moisture basis).

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Optimum water absorption for reconstituted noodle doughs was calculated by
mixing 2 g reconstituted flour in a 2-g Mixograph (National Mfg. Co., Lincoln, NE) with
varying amounts of water. The appearance and handling properties of the dough sheet
were used to judge the optimum amount of water for noodle-making. The optimum
formula water used to prepare noodles from reconstituted parent and reconstituted test
samples is listed in Tables 5.4 and 5.7, respectively. Noodles were prepared the same way

as mentioned above for original parent control samples.

5.3.6 Cooking Properties of Noodles

Noodles were cooked one day after storage at room temperature. Noodles (~10 g)
were added to 150 ml of boiling distilled water in a beaker and cooked for 3 min while
stirring the water gently every 30 sec to prevent noodles from sticking to the bottom of
the beaker. The cooked noodles were transferred into a colander and rinsed with distilled
water (150 ml) at room temperature followed by draining for 30 sec. The cooked noodles
were held in distilled water (250 ml) for 1 min at room temperature and then drained for
30 sec, followed by shaking the colander with the noodles 10 times to remove surface
water. The cooked noodles were then weighed to calculate cooking yield. The cooking
water and rinsing water were collected and combined and dried to measure cooking loss,
using the procedure given in Approved Method 66-50 (AACCI 2007). Cooking yield and
cooking loss were calculated as follows:

Cooking yield: (Weight of cooked noodles/Noodle weight before cooking) x 100

Cooking loss= (Residue in cooking water/Noodle weight before cooking) x 100

Texture analysis was performed within 5 min of cooking the noodles. The cooked

noodles were held in distilled water at room temperature until texture analysis.

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5.3.7 Texture Analysis of Cooked Noodles

A texture analyzer, TA-XT2 (Texture Technologies, Scarsdale, NY) was used to
measure the texture parameters of the cooked noodle samples. The load cell was
calibrated with a 2 kg test weight. A set of five strands of cooked noodles was placed on
the flat metal platform and compressed crosswise twice, with a 3 mm X 70 mm metal
probe (model TA-42), to 70% of their original height. The cross-head speed was 1
mm/sec. From the force-time curve of the texture profile analysis (TPA), hardness,
adhesiveness, cohesiveness, springiness, gumminess, chewiness, and resilience of
noodles were measured according to Boume (1968) and Peleg (1976). Hardness is
measured as the peak force on the first compression cycle. Cohesiveness is the ratio of
the positive force areas under the first and second compression curves. The negative force
area between the first bite and second bite is the work required to pull the probe away
from the sample and is called adhesiveness. Springiness is the noodle height recovered
between the end of the first bite and the start of the second bite; Gumminess is the
product of hardness and cohesiveness; and chewiness is the product of gumminess and
springiness. Resilience is the ratio between the area under the curve obtained during the
withdrawal from the first compression and the area under the first compression curve.
The thickness of noodles was also determined using texture analyzer. At least five

measurements were taken for each replicate.

5.3.8 Force Relaxation Test of Cooked Noodles

The force relaxation test was performed, in non-linear viscoelastic range with
20% deformation, using TA-XT2 on cooked noodles immediately following the TPA

test. A set of five strands of cooked noodles was placed on a flat metal platform and

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compressed crosswise to 20% of their original height with a 3 mm X 70 mm metal probe
(model TA-42). The change in force with time was measured for 120 sec. Compression
speed of 5 mm/sec was used to give instantaneous strain to the samples; test speed was
0.5 mm/sec (Singh et a1 2006). Preliminary tests were done to optimize the strain level
for this experiment. Strain levels of 5, 10 and 20% were tried and it was found that 20%
strain provided the most consistent results. Maximum force (F max) and residual force at
60 sec during force relaxation were recorded. The time required for the noodles to relax
to 85% of F.max was used as a measure of relaxation time (Hatcher 2005). Percentage

stress relaxation (%SR) was measured at t = 30 sec using the formula:
% SR= (Ft x 100 / Fmax)

Force relaxation data was linearized according to Peleg and Normand (1983) using the

following equation:
Fmax/(Fmax-Ft)=k1/t+k2 ......... or
t / Yt= k1 + k2t
where Yt= [(Fmax- Ft )/Fmax] and Ft is the force at any time t. The graph of t / Yt versus t

was used to calculate the constants kl (intercept) and k2 (slope) using the above

equation.

5.3.9 Microstructure of Raw Noodles

The procedure of Lee et a1 (2000) was used to prepare samples for LSC
microscopy. A Zeiss LSM 5 Pascal (Carl Zeiss, Inc., Thomwood, NY) was used to
observe the microstructure of uncooked noodle strands. The frozen noodle strands were

cut mid length, using a very sharp razor blade, to obtain thin cross-sections. While

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sectioning, dry ice was used to maintain noodles in frozen conditions to minimize any
deformation before examination under the microscope. The sections were defrosted at
ambient temperature for 15 min. Fluorescein isothiocyanate (FITC) was used to label the
proteins in the noodle samples. FITC conjugates with the s-amino group of amino acids
and this conjugated compound absorbs 488 nm wavelength and emits a longer
wavelength of 525 nm (Strasburg and Ludescher 1995). The stained samples were
allowed to dry at room temperature in the dark (due to the light sensitivity of FITC). A
drop of immersion oil (Zeiss Irnmersol) was placed on the top of the sample, followed by
a cover slip and finally another drop of oil to achieve higher resolution. The microscopic
structure of the noodle samples was observed under a 40X oil 1.3 NA. objective lens
with 1.5 zoom. The field of view under the microscope was 153.6 X 153.6 pm. The
transmitted image of starch granules was collected under plain polarized light. A confocal
fluorescent image of stained proteins was collected from the same area. Both the images
were collected using a 488 argon-ion laser. A band pass filter (505-600 nm) was used for
the detection of FITC. The two images were overlaid to give a complete picture of the
starch-protein organization in noodles. A z-series was collected with a z-interval of 2 pm
to avoid any artifacts. The amount of protein matrix was measured as a percentage of
total area, from the three representative layers of a z-series, using the ‘Area’ function of
the Pascal software. At least three images were collected for each noodle sample. The

confocal images in this dissertation are presented in color.

5.3.10 Statistical Analysis

Statistical analysis was performed using SAS version 9.1 (SAS Institute Inc.,

Cary, NC). ANOVA was performed using a general linear model procedure to determine

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significant differences between the samples. Means were compared by using Fisher’s

least significant difference (LSD) procedure. Significance was defined at the 5% level.

5.4 RESULTS AND DISCUSSION

5.4.1 Physicochemical Analysis of Flours

The chemical composition and physical dough properties of parent Caledonia and
NuHorizon flours are summarized in Table 5.1. NuHorizon had higher total protein, wet
gluten and dry gluten contents than Caledonia. The starch pasting properties indicated
that although Caledonia starch swelled slightly more than NuHorizon starch (peak
viscosity), it also had higher breakdown and less final viscosity in comparison to starch
from NuHorizon. The Farinograph and Mixograph data revealed that NuHorizon flour
was much stronger than Caledonia flour. The differences in gluten protein properties and
dough mixing behavior were quite evident from Figure 5.1. Caledonia dough took less
time to develop to peak consistency (l min) than the NuHorizon dough (6 min).
NuHorizon also had lower mixing tolerance values and higher stability than the
Caledonia dough. Generally, stronger flours have longer mixing times and lower mixing
tolerance Index (MTI) values (Shuey 1982). Thus, it was clear that NuHorizon flour was
stronger than the Caledonia flour which is consistent with the former variety being a hard

wheat and the latter a soft wheat.

5.4.2 Yields and Proximate Analysis of Flour Fractions

The moisture content and protein content of the starch, gluten and water-soluble
fractions obtained from Caledonia and NuHorizon flours are presented in Table 5.2. The

total recovery of material during fractionation was 97.7% for Caledonia flour and 97.4%

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for NuHorizon flour. The protein content of the gluten fraction obtained from Caledonia
was lower than the protein content of the gluten fraction obtained from NuHorizon. The
Caledonia starch and water-soluble fractions had higher protein contents than the
respective starch and water-soluble fractions obtained from NuHorizon. The gluten from
Caledonia was difficult to recover probably because of its weak nature (evident from
Farinograph data MTI values) and some might have been lost in the starch and water-

soluble fractions during the fractionation procedure.

5.4.3 Properties of Parent and Reconstituted Parent Flours

5.4.3.1 Noodle Texture and Cooking Properties

Tables 5.3 and 5.4 show the texture and cooking properties, respectively, of the
noodles prepared from the two parent flours and their reconstituted parent flours. The
optimum water required to make noodles from parent flours was 32% in the case of
Caledonia and 31% in the case of NuHorizon. It was indicated earlier that the optimum
water absorption for noodle-making depends on the protein content, protein quality,
damaged starch content, pentosan content and particle size of the flour (Oh et al 1985a;
Park and Baik 2002). TPA results indicate that there were significant differences in the
texture properties of cooked noodles prepared from Caledonia and NuHorizon parent
flours (CP and NP, respectively). Noodles obtained from NP were thicker than the
noodles obtained from CP (Table 5.3). Thickness of noodles is positively influenced by
the protein content (Kruger et a1 1994; Park et al 2003), particle size, and starch damage
of the flour samples (Hatcher et a1 2002). The hardness, gumminess, and chewiness of
noodles obtained from NP flour were each significantly higher than those of the noodles

from CP flour. The noodles from CP flour were more cohesive and more resilient than

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the noodles from NP flour. There were no significant differences between the
adhesiveness of noodles obtained from CP and NP flours, as measured by texture
analyzer. The differences in TPA parameters of Caledonia and NuHorizon can be
explained, in part, by the differences in the starch pasting properties of their parent flours
(Table 5.1). CP flour had higher peak viscosity, higher breakdown, and lower final
viscosity than NP flour. It has been shown earlier that the peak viscosity and breakdown
viscosity of flour have negative relationships with the hardness of noodles (Nagao et a1
1977; Moss 1979; Oda et al 1980; Crosbie 1991; Konik et a1 1992; Crosbie et al 1992;
Yun et a1 1996; Baik and Lee 2003) and positive relationships with the cohesiveness of
noodles (Baik and Lee 2003). Final paste viscosity has been related positively with the
hardness of noodles (Yun et al 1996; Baik and Lee 2003). These differences in the
pasting properties of flours can explain lower hardness values and higher cohesiveness
values of noodles from CP flour. Higher protein content of NP flour also contributed
towards high hardness values of NP noodles (Oh et al 19853; Huang and Morrison 1988;
Baik et a1 1994; Kruger et a1 1994; Ross et a1 1997; Park et a1 2003).

Higher values of cooking loss (Table 5.4) in the case of Caledonia (6.44%)
indicate more solids leached out into the cooking water than for NuHorizon (4.6%) and
also indicate a weaker gluten matrix in Caledonia noodles. Higher cooking yield is an
indication of more water uptake by Caledonia noodles during cooking. It is possible that
the voids present in Caledonia noodles shown upon microscopy (section 5.4.3.3) retain
extra water upon cooking. Voids have been reported earlier in the microstructure of
noodles (Moss et a1 1987). Seib et a1 (2000) also suggested that the increase in void

volume of alkaline noodles might be responsible for the increase in their cooking yield.

128

To check the efficiency of the fractionation procedure, a comparison was made
between the parent flours and their respective reconstituted flours. Slight differences were
observed between the TPA parameters of parent (CP and NP) and reconstituted parent
(CR and NR) noodles (Table 5.3). The differences between the parent flour and its
reconstituted flour indicate loss of material and possibly changes in the functional
properties of flour components during fractionation. The optimum amount of water
required to prepare noodle dough from reconstituted flours was higher than that needed
by their parent flours (Table 5.4). Cooking loss and cooking yield were also slightly
affected (Table 5.4). The cooking yields of reconstituted parent flour noodles were higher
than the cooking yield of parent flour noodles for both Caledonia and NuHorizon. No
specific trend was observed in the case of cooking loss between noodles from a parent
and its reconstituted parent flour. It has been observed earlier that reconstituted noodles
have a weaker structure than the noodles obtained from their parent flours (Oh et al

1985b; Rho et a1 1989).

5.4.3.2 Force Relaxation Behavior

Figures 5.2 and 5.3 depict the force relaxation curve and linearized force relaxation
curve, respectively, of cooked noodles from Caledonia and NuHorizon parent and
reconstituted parent flours. Two minutes for the force relaxation tests were chosen
because longer times resulted in drying out of noodles and changes in their rheological
properties (Singh et a1 2006). When noodles were compressed to an instantaneous strain,
a quick and large decrease in force was observed with time followed by attainment of a
non-zero equilibrium or residual force (Figure 5.2). This type of curve confirms the

viscoelastic solid nature of cooked noodles. The residual force is dependent on the

129

molecular structure of the material being tested (Steffe 1996). A clear distinction in the
force relaxation curves of CP and NP noodles was observed (Figure 5.2). Parameters
obtained from analyses of the force relaxation curves of the parent and reconstituted
parent noodles are given in Table 5.5. NuHorizon cooked noodles had significantly
higher Fmax and higher residual force than Caledonia noodles. From the equation for
Hookean solids:
G=E8

where o is the stress, E is the modulus of elasticity and c is the strain, it is known
that ‘E’ is directly proportional to the initial stress/force ‘6’. Higher Fmax or higher initial
force at 20% deformation thus means higher elastic modulus of the sample. Cooked
noodles prepared fiom NuHorizon flour were thus more elastic than the noodle prepared
from Caledonia.

The % stress relaxation (%SR) indicates elasticity of the test sample: the higher
the %SR, the more elastic the material (Singh et a1 2006). Cooked noodles from CP flour
had slightly higher %SR than that of noodles from NP which means that CP noodles were
more elastic than NP noodles. Relaxation time (RT) can be defined as the time that it
takes a macromolecule to be stretched out when deformed (Steffe 1996). A higher RT
indicates a more elastic nature of the sample (Singh et a1 2006) and slower relaxation
time indicates stiffer noodles (Hatcher 2005). No statistically significant difference was
observed between the relaxation times of cooked noodles from CP and NP flours. The
linear force relaxation curves (Figure 5.3) were used to calculate constant k1 and k2 for
each sample. Constant k1 represents the initial decay or relaxation rate and can be

interpreted as the viscous component (Peleg and Normand 1983). The values of k1 were

130

not significantly different between CP and NP noodles. Peleg and Normand (1983)
mentioned that it is very difficult to interpret the values for constant k1 if the initial force
decay is too fast. By comparing food samples with different viscoelasticities, Singh et a1
(2006) also concluded that constant k1 was not very sensitive to the viscoelasticity of
food materials but the constant k2 was considered to be a better indicative of general
rheological characteristics of the test material. The constant k2 represents the solidity or
elasticity of the food materials. Similar to %SR data, the values of k2 obtained for
noodles from both parent flour varieties also indicate that CP noodles were slightly more
elastic than NP noodles. Although the differences in force relaxation parameters (%SR,
k1 and k2) of Caledonia and NuHorizon parent noodle were statistically significant, the
difference might not be sufficiently high to have practical significance.

The noodles made from reconstituted parent flours (CR and NR) did not show any
differences in their force relaxation properties. This lack of differences could possibly be
due to changes that occurred in the functional properties of flour constituents of both

flours during the fractionation procedure.

5.4.3.3 Microstructure of Raw Noodles

Figures 5.4A and 5.5A (red) represent the starch present in the raw noodle strands
of Caledonia and NuHorizon parent flours, respectively. Wheat flour contains two types
of starch granules: large lenticular (20—40 11) and small spherical granules (2-10 11)
(Hoseney 1994). Both large and small starch granules (with crosses inside) were quite
evident in the transmitted images observed under polarized light. Figures 5.4B and 5.5B
(green) represent the protein (matrix) around the starch granules of Caledonia and

NuHorizon, respectively. These two images were made possible by staining the protein

131

with FITC and collecting the confocal fluorescent image using appropriate filters. Figures
5.4C and 5.5C represent the overlaid images of starch and protein matrix of Caledonia
and NuHorizon parent noodles, respectively, and give an overall picture of the starch and
protein organization in the raw noodle strand. A series of images (z-series, not shown)
was taken from the same area to be sure of the structure as seen in Figures 5.4 and 5.5. It
is evident that the Caledonia noodles were made up of loosely arranged starch granules,
with very little or practically no developed protein matrix. There were many gaps or void
spaces in the Caledonia parent noodles. On the other hand, the protein matrix was very
well deveIOped, continuous and homogeneous in the case of NuHorizon noodles. The
starch granules appear to be more aligned and elongated in one direction, whereas the
starch granules in Caledonia appear more round. The z-sectioning of the same area
confirmed that the reported observations were not the result of any artifact caused by the
sample preparation method (sectioning or staining of the sample). The quantification of
protein matrix of CP and NP noodles (Table 5.9) also showed that the area covered by
protein matrix was significantly higher in NP noodles than in the CP noodles. The
overlaid images of noodles obtained from reconstituted parent Caledonia (CR) and
reconstituted parent NuHorizon (NR) flours are shown in Figures 5.8A and 5.9A,
respectively. No significant differences were observed in microstructure of noodles

obtained from parent and respective reconstituted parent flours.

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5.4.4 Effect of Protein Content

The effect of protein content on noodle textural, cooking and structural properties was

observed by increasing the protein content of reconstituted flours.

5.4.4.1 Noodle Texture and Cooking Properties

An overall increase in the thickness of noodles was observed for both Caledonia
and NuHorizon samples when protein content was increased from 6.5-11.4% and 6.3-
10.9%, respectively (Table 5.6). The positive relationship between thickness of noodles
and protein content of flours was also reported by Kruger et a1 (1994) and Park et a1
(2003). No significant differences were observed in the thickness of cooked noodles at
the intermediate protein levels of 8.0% and 9.5% for both varieties. The thicknesses of
Caledonia noodles were quite comparable to NuHorizon noodles at each given protein
level. Increase in the protein content of reconstituted flours positively affected the
hardness of noodles. Many researchers have observed earlier, and agreed upon, that the
hardness of noodles as determined by TPA or maximum cutting stress in the uniaxial
compression tests increases with increase in protein content (Miskelley and Moss 1985;
Oh et al 1985a; Toyokawa et a1 1989; Baik et a1 1994; Ross et a1 1997; Hatcher et a1
1999). The hardness values of reconstituted samples were quite comparable at the same

protein levels irrespective of the flour type (Caledonia or NuHorizon).

A small decrease in adhesiveness of noodles was observed with increase in
protein content. A complete disappearance of adhesiveness peak (peak below the
horizontal line between two compression cycles, data not shown) was observed in some

replicates of reconstituted flour samples with 11.5% protein content (for both Caledonia

133

and NuHorizon). Cohesiveness of noodles was unaffected by the protein content of both
Caledonia and NuHorizon samples. Reconstituted noodles obtained from NuHorizon, in
general, were less cohesive than the reconstituted noodles from Caledonia at all protein
levels. Cohesiveness of noodles might be related to the pasting properties of starch; it has
been shown earlier in Chapter 3 and also by Baik and Lee (2003) that the peak viscosity
of starch is positively related to cohesiveness of noodles. Springiness of noodles did not
change significantly with an increase in protein content and there were no significant

differences between the Caledonia and NuHorizon noodles at all protein levels.

Gumminess and chewiness of noodles followed the same trend as hardness, which
is not surprising because gumminess is calculated as the product of hardness and
cohesiveness, and chewiness is a product of gumminess and. springiness. At protein levels
of 9.5% and above, Caledonia noodles CRP3 and CRP4 appeared to be significantly
more chewy and gummy than NuHorizon noodles NRP3 and NRP4, respectively. The
resilience of noodles decreased from 0.491 to 0.430 in the case of Caledonia and from
0.458 to 0.397 in the case of NuHorizon with increases in protein content from 6.5% to
11.5%. Resilience of noodles has been related both positively (Ross 2006) and negatively
with the hardness of noodles (Epstein et a1 2002). Noodles obtained from reconstituted
Caledonia were more resilient than noodles from NuHorizon at each respective protein
level.

When the protein contents of reconstituted flours (both Caledonia and
NuHorizon) were increased, it was found that the optimum water required to obtain good
noodle dough (neither too dry nor too sticky) decreased (Table 5.7). This observation was

in general agreement with the findings of Oh et al (1985a), Park and Baik (2002) and of

134

Park et al (2003), where negative relationships between protein content and optimum
water absorption of noodle dough have been reported.

Loss of solids in cooking water was significantly influenced by protein content of
the reconstituted sample. Cooking loss consistently decreased with increases in the
protein content of both Caledonia and NuHorizon test samples (Table 5.7). The decrease
in cooking loss was probably due to more protein network formation (discussed in later
sections) at higher levels of protein. Protein network helps in holding the starch granules
and other flour components together during dough mixing and cooking. At the same
protein level, noodles made from NuHorizon reconstituted flour showed higher cooking
loss than the noodles from Caledonia reconstituted flours. Cooking yield values clearly
indicate that the water uptake during cooking of noodles decreased with increasing
protein content. This could be due to the effect of increasing protein on the pasting
properties of starch. It was observed that with an increase in protein content of Caledonia
reconstituted flour, the peak viscosity of the flour decreased (data not shown). Decrease
in cooking yield can also be explained by the more continuous gluten network that forms
in raw noodles at higher protein levels (discussed in section 5.4.4.3), thereby eliminating

any voids where water can reside upon cooking of noodles.

5.4.4.2 Force Relaxation Behavior

A force relaxation test was conducted on cooked noodles from reconstituted
flours with varying protein contents in order to investigate the possible effect of gluten
protein content on the structure or viscoelastic properties of noodles. The relaxation
parameters obtained for Caledonia and NuHorizon reconstituted flours with increasing

protein content are listed in Table 5.8. There was a shift in the force relaxation curve to

135

higher force values (Figure 5.6) but the shape of the curve did not change with increase in

protein content of Caledonia samples. The same trend was obtained for NuHorizon
samples. A substantial increase in the Fmax and residual force of cooked noodles was

observed when protein content was increased from 6.5% to 11.5% which indicates that
with increase in the protein content of flours the elasticity of noodles also increase.

With increase in protein content of flours there was a statistically significant but
small decrease in the values for relaxation time, % SR and k2. This trend was observed
for both Caledonia samples (weak protein) and NuHorizon samples (strong protein). In

the present study, the time required for the cooked noodles to decrease to 85% of their

Fmax was taken as the measure of relaxation time. It appears for both flours, that with an

increase in protein content, the 0.85 Fm,Ix was attained sooner, which would mean that

though noodles are harder to bite at first, subsequent decay will be faster at higher protein
levels. The decrease in the relaxation time, % SR and k2 indicates that with increase in
protein content of samples elasticity of samples is decreasing. This observation is quite
contrary to what we know about the nature of gluten protein and the role of protein
content in the quality of other wheat products like bread. Gluten proteins are known for
their unique viscoelastic properties and also for attributing the same properties to end
products like bread. Also, since the differences in the values of these parameters are very
small it is possible that these parameters are not the best indicatives of the relaxation
behavior of cooked noodles.

Within each protein level, NuHorizon noodle samples had slightly higher %SR
values than did Caledonia noodles samples, indicating that reconstituted NuHorizon

samples were more elastic than their counterpart reconstituted Caledonia samples.

136

Whether the differences may be attributed to starch properties, protein quality or the

water-soluble fraction of the flours used is not yet clear.

5.4.4.3 Microstructure of Raw Noodles

The CLSM images of the microstructure of Caledonia and NuHorizon
reconstituted raw noodles, as affected by protein content, are displayed in Figures 5.8 and
5.9. All noodles samples were obtained by adding the optimum amounts of water to the
respective reconstituted flour sample and mixing for 6 min. All doughs were given the
same sheeting and cutting regimen during noodles making, so the differences observed in
the confocal images from one flour type are primarily due to the different protein levels
of the samples. It is very clear from the confocal images that in the raw noodles prepared
from Caledonia reconstituted flour with 6.5% protein (Figure 5.8A), starch appears as
very loosely arranged discrete granules with minimal or no protein matrix formation. The
starch granules are more or less round in shape. With an increase in protein content of the
reconstituted flours, an increase in protein matrix (green) was observed in the raw noodle
samples (Table 5.6); for example, there is more green area in Figure 5.8 B (8.0% protein)
than in Figure 5.8A (6.5% protein). In Figure 5.83, the starch granules still appear
discrete but there is more protein matrix around and across the starch granules. In the
Caledonia raw noodle with 9.5% protein (Figure 5.8C), it appears that starch granules
begin aligning in one direction; a slightly more elongated shape of starch is also
observed. Additionally, it appears that the empty spaces between the starch granules are
now filled with the protein/protein matrix. At ~11.5% protein content (Figure 5.8D), a
continuous and homogeneously developed protein matrix is observed. Starch granules

seem to be perfectly aligned and elongated unidirectionally and are tightly packed with

137

minimal discontinuities in the structure. Similar effects of protein content were observed
on the microstructures of NuHorizon reconstituted raw noodles (Figure 5.9). However, at
each protein level, it appears that the protein in NuHorizon noodles is more developed
than the protein in the Caledonia samples, and that the starch granules are more
connected. The measurement of protein matrix (green area) showed that there was a
definite increase in the protein matrix of raw noodle samples with increases in the protein
content of reconstituted flours (Table 5.9). The amount of protein matrix was minimal in
samples with lowest protein content and maximum in the samples with highest protein
content.

The microstructure of the raw noodles can help explain the differences in the
cooking properties of both the flours. At a low protein level, it is easier for the starch
granules to move out and leach into the cooking water, leading to higher cooking loss
values. At higher protein contents, though, the protein matrix helps in holding the starch
granules and other flour components together in their respective positions within the

noodle strand during cooking, and thus minimizes the cooking loss.

138

5.5 SUMMARY

This study demonstrated that the protein content of plays a very important role in
the texture of noodles. For both Caledonia (weak flour) and NuHorizon (strong flour)
flours, it was observed that the hardness, gumminess and chewiness of noodles increased
with the increase in the protein content of reconstituted flours. On the other hand, the
adhesiveness and resilience of noodles decreased with increase in the protein content of
reconstituted flours. Cohesiveness and springiness of noodles did not change with
increase in the protein content of flours. At each protein level, the texture properties of
both Caledonia and NuHorizon noodles showed quite comparable texture parameters;
only difference was that Caledonia noodles were slightly more cohesive and slight more
resilient than NuHorizon noodles. It was also shown that both the cooking loss and
cooking yield of noodles decreased with increase in the protein content of flour. A
possible explanation for this observation lies in the microstructure of noodles as observed
by CLSM in this study. It was observed that with an increase in the protein content of the
reconstituted flours the protein matrix in raw noodles became more continuous and the
starch granules appeared more connected and embedded in the protein matrix (which
prevents them from leaching out in the cooking water). It was also concluded that the
increase in the protein content of flours made the noodles more elastic and more solid-
like which again could be due to better connectivity between the starch granules. Overall,
increasing the protein content of flours showed a significant impact on the textural,
cooking properties and microstructure of noodles, irrespective of different starch pasting

properties and different protein quality of the flours.

139

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144

TABLE 5.1 Physicochemical Properties of Parent Flours

 

 

Propertiesa Caledonia NuHorizon
Moisture (%) 12.3 12.5
Ash (%) 0.41 0.46
Protein (%, on 14%m.b.) 7.0 11.4
Wet gluten (%) 19.7 30.1
Dry Gluten (%) 6.3 10.6
Pasting Properties (in RVU)
Peak Viscosity 219.3 208.5
Breakdown 90.8 45.6
Final Viscosity 226.2 272.5
Set-back Viscosity 97.7 109.6
Farinograph Properties
Water Absorption (%) 48.7 60.0
Dough Development Time
(min) 1.0 6.0
Stability (min) 1.5 9.0
Mixing Tolerance Index (BU) 150.0 30.0
Mixograph Properties
Midline Peak Time (min) 4.9 5.2
Midline Peak Height (BU) 18.9 30.7
Width at Peak 6.3 12.5
Width at 6.0 min 5.9 12.3

 

aReported numbers are the average of two values.

145

TABLE 5.2 Yield and Proximate Analysis of Fractions Isolated
from Two Wheat Varieties

 

 

Fraction Yield“b Moisture Proteinb
(%) (%) (%)
Caledonia
Starch 89.2 9.9 2.1
Gluten 6.2 5.2 61.0
Water-Solubles 4.5 6.5 19.8
NuHorizon
Starch 81.2 8.9 1.9
Gluten 12.6 4.1 65.9
Water-Solubles 6.2 4.7 17.1

 

alYield was calculated on the basis of total material recovered after fractionation.
ineld and protein content are on 14%moisture basis.

146

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147

TABLE 5.4 Comparison of Cooking Properties of Parent and Reconstituted Parent

 

 

Cooked Noodles
Sam lea Protein Optimum Formula Cooking Loss Cooking Yield
9 (%) Water (%) (%) (%)
CP 7.0 32.0 6.44ab 251.50b
CR 6.5 34.0 5.60b 270.87a
NP 11.4 31.0 4.60d 221.14c
NR 10.9 34.0 5.28c 226.57c

 

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NR: NuHorizon reconstituted parent.

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(P<0.05).

148

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152

TABLE 5.9 Effect of Protein Content on the Amount of Protein Matrix'
(% of total area) in the Confocal Laser Scanning Microscope
* Cross-Sectional Images of Raw Noodles

 

 

 

Caledonia NuHorizon
Area Area
Flour Sample Protein (%) (%) Protein (%) (%)
Parent 7.0 48.16 11.4 67.14
Reconstituted
1 6.5 49.71 6.3 56.68
2 8.0 58.24 7.9 65.11
3 9.5 64.83 9.4 67.65
4 11.4 68.31 10.9 69.96

 

 

2‘All the values are averages of the results obtained from 3 images.

153

 

Fig. 5.1 Farinographs of (A) Caledonia and (B) NuHorizon showing differences in
their mixing behaviors.

154

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Fig. 5.4 Microstructure (cross-section) of raw noodles prepared from Caledonia
parent (CP) flour as observed with Confocal Laser Scanning Microscope.

A: Starch granules as observed under polarized light; B: Fluorescent image of protein
matrix under laser light (488nm), C: Overlaid image, S: Starch granules; P: Protein
matrix. Scale bar = 20 pm.

157

 

Fig. 5.5 Microstructure (cross-section) of raw noodles prepared from NuHorizon
parent (NP) flour as observed with Confocal Laser Scanning Microscope.

A: Starch granules as observed under polarized light; B: Fluorescent image of protein
matrix under laser light (488nm), C: Overlaid image S: Starch granules; P: Protein
matrix. Scale bar = 20 pm.

158

 

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160

 

Fig. 5.8 Effect of protein content on the microstructure (cross-section) of raw
noodles (Caledonia) as observed with Confocal Laser Scanning Microscope.

Samples: Noodles from Caledonia reconstituted flours A) CRPl, Caledonia reconstituted
protein 1 (6.5% p.c.); B) CRP2, Caledonia reconstituted protein 2 (8.0% p.c.); C) CRP3,
Caledonia reconstituted protein 3 (9.5% p.c.); and D) CRP4, Caledonia reconstituted
protein 4 (11.4% p.c.); p.c.: protein content. Scale bar = 20 pm.

161

31111::

 

Fig. 5.9 Effect of protein content on the microstructure (cross-section) of raw
noodles (NuHorizon) as observed with Confocal Laser Scanning Microscope.

Samples: Noodles from NuHorizon reconstituted flours A) NRPl, NuHorizon
reconstituted protein 1 (6.3% p.c.); B) NRP2, NuHorizon reconstituted protein 2 (7.9%
p.c.); C) NRP3, NuHorizon reconstituted protein 3 (9.4% p.c.); and D) NRP4, NuHorizon
reconstituted protein 4 (10.9% p.c.); p.c.: protein content. Scale bar = 20 pm.

162

 

Chapter 6

EFFECT OF FLOUR CONSTITUENTS ON THE TEXTURE, COOKING
PROPERTIES, AND MICROSTRUCTURE OF WHITE SALTED NOODLES

163

6.1 ABSTRACT

The primary objective of this research was to fractionate two flours into major
flour components (starch, gluten and water-solubles) and determine the contribution of
these fractions to the texture, cooking properties and microstructure of noodles. A hard
wheat (NuHorizon) and a soft wheat (Caledonia) flour differing in their physicochemical
properties and noodle-making properties were used. Replacement of Caledonia starch
fraction with an equivalent amount of NuHorizon starch fraction resulted in increased
hardness, adhesiveness, gumminess and chewiness of cooked noodles. Cohesiveness and
resilience of cooked noodles decreased and the springiness remained unaffected. Reverse
trends were observed in the texture parameters of noodles when the starch from
NuHorizon was replaced with the Caledonia starch. The starch fraction was also found to
affect the cooking loss and cooking yield of noodles. Exchange of the gluten fraction
between Caledonia and NuHorizon, however, slightly affected only the cohesiveness and
gumminess of noodles. No change was observed in the hardness of noodles. Both
cooking loss and cooking yield were decreased upon replacement of the Caledonia
protein fraction with the counterpart NuHorizon fraction and increased with the opposite
replacement. The NuHorizon water-soluble fraction was found to increase the hardness,
gumminess and chewiness of noodles, and the cohesiveness and resilience of noodles
decreased when the Caledonia water-soluble fraction was replaced with the NuHorizon
water-soluble fraction. No changes in the texture or cooking properties of noodles were
observed when the gliadin or glutenin fraction of NuHorizon was exchanged with the
respective gliadin or glutenin fraction of Caledonia. It was concluded that the starch

fraction contributed most to the texture properties of noodles. Negligible changes were

164

observed in the texture properties of noodles when the gluten fractions of NuHorizon and
Caledonia were interchanged. It was also observed that with NuHorizon starch the
elasticity of cooked noodle samples was more than with Caledonia starch. With
NuHorizon total gluten, more continuity was observed in the protein matrix of

microstructure of raw noodles.

165

6.2 INTRODUCTION

Texture is one of the most important quality attributes of cooked noodles that
affect their consumer acceptance (Sasaki et a1 2004). Oriental noodles can be divided
widely into Chinese and Japanese types. Chinese noodles typically use strong, higher
protein flours from hard wheat. Japanese noodles are made with low protein flours
derived from soft wheat. Chinese raw (fresh) noodles should be hard and elastic in bite
with stable texture in hot water, whereas, a soft and elastic texture is preferred in the case
of Japanese udon noodles. Chinese wet noodles (parboiled) should be hard to bite, chewy,
elastic and less sticky. Alkaline Japanese ‘ramen’ noodles (with added potassium
carbonate and sodium carbonate) should be firm, springy, not sticky, and smooth
(Crosbie et al 1999). By means of correlation studies, starch, protein content, and protein
composition of flours have been indicated to contribute to the texture of cooked noodles.
The main disadvantage of using correlation studies is that they are indirect studies and no
cause-and-effect type conclusions can be drawn from such experiments. Very few direct
studies have been conducted to examine the effect of these flour constituents on the
texture and structure parameters of noodles.

Fractionation and reconstitution of wheat flour components is considered the most
direct method to establish the fimctionality of flour constituents in various wheat-based
products. By means of fractionation-reconstitution studies, the functionality of each of
the separated flour protein components can be evaluated by varying its amount in given
flour or by interchanging separated fractions between flours of different final product
quality. The fractionation and reconstitution techniques have been applied to bread-

making (Chen and Bushuk 1970; Finney 1971; Hoseney et al 1969a, b; MacRitchie 1985)

166

and to cakes, cookies and noodles (Oh et a1 1985; Rho et a1 1989; Toyokawa et a1 1989).
Oh et a1 (1985) have earlier used the fimdamental approach of fractionation and
reconstitution to provide evidence for the fact that glutenins have an important role in
determining cooked noodle texture. In this study, a high molecular weight glutenin
fraction taken from a wheat variety that produced hard noodles was used to replace the
same fraction from a wheat variety that made sofi noodles. When this was done, the
cutting strength of the cooked noodles was increased to a level equivalent to that of the
hard control. Another study, reported by Toyokawa et a1 (1989), showed that
interchanging the gluten fraction of different wheat classes does not affect the texture of
cooked noodles. A sensory panel was used to evaluate the quality of cooked noodles in
the case of Toyokawa et a1 (1989), whereas for Oh et a1 (1985), a uniaxial compression
method was used. Both the studies reported that starch plays the most important role in
governing the texture of noodles.

The objective of this study was to further enhance our understanding of the effect
of different flour constituents on texture profile analysis parameters, cooking properties,
and the force relaxation behavior of cooked noodles. The effect of these flour constituents
on the microstructure of uncooked noodles was also studied by confocal laser scanning

microscope (CLSM).

167

6.3 MATERIALS AND METHODS

6.3.1 Wheat Flour Samples

Wheat flour samples were the same as described in Chapter 5 (Section 5.3.1).
6.3.2 Flour Quality Tests
Flour quality tests were performed as described in Chapter 5 (Section 5.3.2).

6.3.3 Fractionation of Flours

Both, Caledonia and NuHorizon flours were fractionated according to MacRitchie
(1985) into starch, gluten and water-soluble fractions. The details of the fractionation
procedure are described in Chapter 5 (Section 5.3.3). The dried and ground gluten
fraction was further fractionated into acid-soluble and acid-insoluble gluten. Dried gluten
was first mixed with water (30 x weight of gluten), then mixed thoroughly while reducing
the pH to 5.1 with 2N HCl at room temperature. The acid-soluble fraction (supernatant)
was removed by centrifuging the mixture at 2300 x g for 10 min using a Sorvall RC-SB
centrifuge (Dupont, Wimington, DE). The final pH of both acid-soluble (gliadin-rich) and
acid-insoluble (glutenin-rich) fractions were brought to 5.8 using 0.1N NaOH. Using this
procedure avoids prolonged exposure of the proteins to acid conditions (MacRitchie
1985). The acid-soluble and acid-insoluble fractions were frozen immediately and freeze-
dried within 24 hr. The dried fractions were first ground using a mortar and pestle, then

fiirther ground using a coffee grinder to < 250 microns and stored in sealed containers at

4°C until analyses.

168

6.3.4 Preparation of Noodles from Reconstituted Parent Flour Samples

Reconstituted parent samples, CCC and NNN (CCC: starch, gluten and water-
solubles from Caledonia and NNN: starch, gluten and water-solubles from NuHorizon),
were prepared by mixing starch, water-solubles and gluten fractions in the same
proportions as obtained from the original parent flour by the fractionation procedure.
Noodles were prepared according to the procedure described in Chapter 5 (Section 5.3.4),

then stored in polybags at room temperature for 24 hr until further analyses.

6.3.5 Preparation of Noodles from Reconstituted Flour Samples with Interchanged

Fractions

Reconstituted test samples were prepared by singly interchanging the equivalent
amounts of the respective fractions (starch, gluten and water-solubles) of Caledonia and
NuHorizon; total protein was kept constant for all Caledonia (at 6.5%) and NuHorizon (at
10.9%) test samples. Constant water absorption (34%) was used for all reconstituted
samples. Noodles were prepared the same way as mentioned above for reconstituted
parent samples. The noodle strands were stored in polybags at room temperature for 24 hr
before measuring their cooking, textural and force relaxation properties. Raw noodle
samples for the CLSM were rapidly frozen using dry ice and stored in the freezer until

CLSM examination.

6.3.6 Cooking Properties of Noodles

Noodles were cooked in boiling water for 3 minutes. The cooking loss and
cooking yield were calculated according to Approved Method 66-50 (AACCI 2007). The

detailed procedure for cooking and evaluating cooking properties of noodles is described

169

in Chapter 5 (Section 5.3.6). Texture analysis was performed within 5 min of cooking the
noodles. The cooked noodles were held in distilled water at room temperature until

texture analysis.

6.3.7 Texture Analysis of Cooked Noodles

Cooked noodles were evaluated for their texture parameters using a Texture
Analyzer TA-XT2 (Texture Technologies, Scarsdale, NY) according to the procedure
described in Chapter 5 (Section 5.3.7). A set of five strands of cooked noodles was
compressed crosswise twice, with a metal probe (model TA-42), to 70% of their original
height. From the force-time curve of the texture profile analysis (TPA), hardness,
adhesiveness, cohesiveness, springiness, gumminess, chewiness, and resilience of

noodles were measured according to Boume (1968) and Peleg (1976).

6.3.8 Force Relaxation Test of Cooked Noodles

The cooked noodles were also tested for their force relaxation properties at 20%

deformation as described in Chapter 5 (Section 5.3.8).

6.3.9 Microstructure of Raw Noodles

Frozen raw noodle samples were sectioned and stained with fluorescein
isothiocyanate according to the procedure of Lee et al (2000), and the microstructure of
raw noodles was observed using a Zeiss LSM 5 Pascal (Carl Zeiss, Inc., Thomwood, NY)
(procedure is discussed in detail in Chapter 5, Section 5.3.9). At least three images were

collected for each noodle sample.

170

6.3.10 Statistical Analysis

Statistical analysis was performed using SAS version 9.1 (SAS Institute Inc.,
Cary, NC). ANOVA was performed using a general linear model procedure to determine
significant differences between the samples. Means were compared by using Fisher’s

least significant difference (LSD) procedure. Significance was defined at the 5% level.

171

6.4 RESULTS AND DISCUSSION

6.4.1 Physicochemical Analysis of Flours

The chemical composition and physical dough properties of parent Caledonia and

NuHorizon flours are same as summarized in Chapter 5 (Table 5.1).

6.4.2 Yields and Proximate Analysis of Flour Fractions

The moisture content and protein content of the starch, gluten and water-soluble
fractions obtained from Caledonia and NuHorizon flours are same as presented in
Chapter 5 (Table 5.2).

From a previous study (Chapter 5, section 5.4.3) it is clear that the reconstituted
parent flours (obtained using a modified MacRitchie 1985 procedure) exhibited close
similarity to their respective parent flours with respect to the texture and structure of the
noodles prepared from them. Since the functional properties of flour constituents are
well-maintained even after subjecting the flour to a fractionation procedure, the
reconstituted flours provide a good system to observe the direct effect of flour
constituents by interchanging the fi'actions between two flours exhibiting differences in

the properties of interest.

6.4.3 Effect of Flour Constituents on the Texture of Cooked Noodles

Table 6.1 shows the effect of flour constituents (starch, gluten and water solubles)

on the texture properties of cooked noodles prepared from reconstituted flour samples.

172

6.4.3.1 Effect of the Starch Fraction

It was observed that when the starch fraction of Caledonia was substituted with
that of NuHorizon (samples CCC and NCC), there was an increase in the hardness,
adhesiveness, gumminess, and chewiness of cooked noodles. Cohesiveness and resilience
of these noodles were decreased and the springiness remained unaffected. Both the
samples, CCC and NCC, had the same type and same amount of protein (6.5%).
Substituting the starch fraction of NuHorizon with that of Caledonia (samples NNN and
CNN), however, decreased the hardness, adhesiveness, gumminess and chewiness of
cooked noodles. Cohesiveness and resilience of these noodles were increased, but the
springiness of the noodles was again not affected by the exchange of starch fractions.
These results clearly show that the exchange of the starch fraction from the two cultivars
resulted in changes in the texture parameters of cooked noodles.

The differences observed in the texture properties of these noodles could be
attributed to the characteristics of the starch fraction of each cultivar. Caledonia and
NuHorizon differ in their pasting properties (Chapter 5, Table 5.1). Caledonia flour had
higher peak viscosity, higher breakdown, and lower final viscosity than NuHorizon flour.
It has been shown earlier that the peak viscosity and breakdown viscosity of flour have
negative relationships with the hardness of noodles (Nagao et a1 1977; Moss 1979; Oda et
a1 1980; Crosbie 1991; Konik et a1 1992; Crosbie et al 1992; Yun et a1 1996; Baik and
Lee 2003) and positive relationships with the cohesiveness of noodles (Baik and Lee
2003). F inal paste viscosity has been related positively with the hardness of noodles (Yun

et a1 1996; Baik and Lee 2003). These differences in the pasting properties of flours can

173

explain lower hardness values and higher cohesiveness values of noodles containing the

Caledonia starch fraction.

6.4.3.2 Effect of the Gluten Fraction

When the entire gluten fractions of Caledonia and NuHorizon were exchanged
(Table 6.1), the NuHorizon gluten had a negative effect on the cohesiveness and
resilience of cooked noodles and Caledonia gluten had a positive effect on the
cohesiveness of noodles. Hardness, adhesiveness, and springiness of noodles were not
affected by the type of gluten protein. Caledonia gluten fraction had a net positive effect
on the gumminess and chewiness of noodles. Similar results were reported by T oyokawa
et a1 (1989) for Japanese cooked noodles. By means of fractionation-reconstitution
studies, they showed that the hardness and viscoelasticity of noodles were not affected by
the type of gluten. A sensory panel was used in their study to differentiate among noodle
samples. However, neither of the above mentioned results are in agreement with the
observations of Oh et a1 (1985) who reported that interchanging the gluten fractions
between two different wheat varieties affected the cutting stress and surface firmness of

noodles (indicative of hardness of noodles).

6.4.3.3 Effect of the Water-Soluble Fraction

The water-soluble fraction consists of some starch, water-soluble proteins and
water-soluble polysaccharides (such as pentosans) that are present in the wheat flour.
When the water-soluble fractions were exchanged between Caledonia and NuHorizon
(Table 6.1), NuHorizon water-soluble fraction showed a positive effect on hardness,

gumminess, and chewiness and Caledonia water-soluble fraction showed a negative

174

effect on these parameters of cooked noodles. On the other hand, cohesiveness and
resilience of noodles were negatively affected by the NuHorizon water-soluble fraction
and positively affected by the Caledonia water-soluble fraction. Adhesiveness and

springiness of noodles were not affected by exchange of the water-soluble fractions.

6.4.3.4 Effect of Acid-soluble and Acid-insoluble Gluten Fractions

Gluten fractions of both Caledonia and NuHorizon parent flours were further
fractionated into acid-soluble (mainly gliadins) and acid-insoluble (mainly glutenins)
fractions. When the gliadin-rich acid-soluble gluten fraction of Caledonia was replaced
with the gliadin-rich acid-soluble gluten fraction of NuHorizon (samples CCCC and
CNCC in Table 6.2), no differences were observed in the TPA parameters of the cooked
noodles. Similarly, when the gliadin-rich acid-soluble gluten fraction of NuHorizon was
replaced with the gliadin-rich acid-soluble gluten fraction of Caledonia (samples NNNN
and NCNN in Table 6.2), the texture parameters of noodles obtained from these flours
did not change. Additionally, no changes were observed in the texture properties of
noodles when the glutenin-rich acid-insoluble fractions of Caledonia and NuHorizon
were exchanged. These data indicate that at the same protein content, the type of gluten

protein has a very minimal effect on the texture parameters of noodles.

6.4.4 Effect of Flour Constituents on the Cooking Properties of Noodles

When the starch fractions of Caledonia and NuHorizon were exchanged, it was
observed that the NuHorizon starch fraction caused a decrease in the cooking loss and
cooking yield of noodles (Table 6.3) and the Caledonia starch fraction caused an increase

in the cooking loss and cooking yield of noodles. Interchange of both Caledonia and

175

NuHorizon gluten fractions caused decreases in cooking loss and cooking yield of cooked
noodles. No differences were observed in the cooking properties of samples when either
gliadin-rich acid-soluble or glutenin-rich acid-insoluble fractions were interchanged
(Table 6.4). When the water-soluble fraction of Caledonia was replaced with the water-
soluble fraction of NuHorizon, both cooking loss and cooking yield of noodles decreased
(Table 6.3) but when the NuHorizon water-soluble fraction was replaced with the
Caledonia water—soluble fraction, cooking loss did not change much and cooking yield

was also unaffected.

6.4.5 Effect of Flour Constituents on the Force Relaxation Behavior of Cooked

Noodles
When the starch fraction of Caledonia was replaced with the starch fraction of
NuHorizon, both maximum force (Fmax) and residual force of cooked noodles increased

considerably during the force relaxation test (Table 6.5). When NuHorizon starch was
replaced with Caledonia starch, a slight but statistically significant decrease was observed

in Fmax and residual force of noodles. All other force relaxation parameters remained

unaffected by the exchange of starch fractions. From the equation for Hookean solids:
o=Ee

where o is the stress, E is the modulus of elasticity and a is the strain, it is known that ‘E’

is directly proportional to the initial stress/force ‘0’. Higher Fmax or higher initial force at

20% deformation thus means higher elastic modulus of the sample. Following this

equation, it can thus be suggested that the starch fraction of NuHorizon was associated

with an increase in the elasticity of noodles.

176

Both Caledonia and NuHorizon gluten fractions increased the Fmax (elasticity)

and residual force of noodles, but other force relaxation parameters did not change again.
When the noodle samples obtained by exchanging gliadin-rich and glutenin-rich fractions
of Caledonia and NuHorizon were subjected to force relaxation tests, no meaningful
results could be obtained because of the high variability in the data points (data not
shown). The NuHorizon water-soluble fraction was found to be responsible for increases
in the maximum and residual forces of noodles and the Caledonia water-soluble fraction

was associated with decreases in these forces (Table 6.5).

6.4.6 Effect of Flour Constituents on the Microstructure of Raw Noodles

The CLSM images of the microstructure of Caledonia and NuHorizon
reconstituted raw noodles, as affected by the studied flour constituents, are displayed in
Figures 6.1 and 6.2. The microstructure of the Caledonia samples did not change when
either their starch or water-soluble fraction was replaced with the respective NuHorizon
starch or water-soluble fraction. (Figure 6.2 A, B and D). However, when the gluten
fraction of Caledonia was replaced with the gluten fraction of NuHorizon (Figure 6.2 C),
the gaps or voids between the starch granules were fewer and the protein matrix appeared
more continuous. Fewer voids and increased continuity of protein matrix provides an
explanation to earlier observations that replacement of Caledonia gluten with NuHorizon
gluten caused decreases in cooking yield and cooking loss of noodles. As discussed
previously (Chapter 5), voids allow cooking water to be retained in the noodles and may
cause an increase in the cooking yield of noodles. In addition to cooking loss, the
continuity of protein matrix also affects the mechanical strength of noodles which is

especially important in the case of dry noodles. The NuHorizon samples did not show

177

any changes in the microstructure of raw noodles when any of the starch, gluten or water-
soluble fractions were replaced with the respective fraction from Caledonia (Figure 6.2).
This observation can be explained by the conclusions drawn from the previous study
(Chapter 5) where it was shown that at higher protein levels even Caledonia protein
fraction gave similar microstructure and texture of noodles as NuHorizon protein
fraction.

When the glutenin-rich fraction of Caledonia was replaced with that of
NuHorizon (Figure 6.3C), it was observed that the continuity of the protein matrix
increased and the starch granules appeared more connected with fewer voids. No other
major changes were observed when the acid-soluble or acid-insoluble fractions of
Caledonia and NuHorizon were exchanged.

The starch and water-soluble fractions of flour, thus, did not seem to affect the
microstructure of raw noodles as observed by CLSM. Stronger gluten protein (from
NuHorizon), however, did affect the continuity of protein matrix of raw noodles and also
decreased the cooking loss and cooking yield of noodles. It also appeared that the
glutenin-rich fraction affected the microstructure of noodles more than the gliadin-rich

fraction.

178

6.5 SUMMARY

This study demonstrated that amongst the starch, gluten and water-soluble
fractions of the two flours studied, starch plays a dominant role in governing the texture
of noodles. The flour with higher peak viscosity, higher breakdown, and lower final
viscosity (Caledonia) was associated with the low hardness, adhesiveness, gumminess
and chewiness values of cooked noodles and higher cohesiveness and resilience values of
noodles. Hardness, adhesiveness, and springiness of noodles were not affected by the
type of gluten protein. Weaker gluten from Caledonia had a positive effect on the
cohesiveness and thus, gumminess and chewiness of cooked noodles. No changes were
observed in the texture properties of noodles when either the glutenin-rich acid-insoluble
fractions or the gliadin-rich acid-soluble fractions of Caledonia and NuHorizon were
exchanged. The NuHorizon (a hard wheat) water-soluble fraction had a positive effect on
hardness, gumminess, and chewiness and a negative effect on the cohesiveness and
resilience of noodles. Adhesiveness and springiness of noodles were not affected by
exchanging the water-soluble fractions of Caledonia and NuHorizon.

When starch fraction of Caledonia was replaced with starch fraction of NuHorizon an
increase in the maximum force (F max) and residual force of cooked noodles was observed

during force relaxation test of noodles. Opposite results were observed when the
Caledonia starch fraction was used in place of the NuHorizon starch fraction. Exchange

of gluten fractions between Caledonia and NuHorizon reconstituted flours increased the
Fmax and residual forces of cooked noodles when compared to their reconstituted parent

counterparts.

179

The starch and water-soluble fractions of either flour did not affect the microstructure of
raw noodles but did change the cooking properties of noodles. There is a possibility that
the exchange of the respective counterpart starch and water-soluble fractions between
Caledonia and NuHorizon flours is associated with the changes in the interactions
between the starch, water-soluble and proteins fractions of the flours resulting in the
changes in the cooking loss or cooking yield of noodles. The NuHorizon gluten fraction
appeared to increase the continuity of protein matrix and decrease the voids in the
microstructure of noodles which can be associated with the decrease in the cooking loss
and cooking yield of cooked noodles made with the NuHorizon gluten fraction (CNC)
relative to the noodles prepared from reconstituted Caledonia parent (CCC) . From the
CLSM, it also appeared that the glutenin-rich fraction of NuHorizon was related to the

continuity of protein matrix in the microstructure of noodles.

180

6.6 LITERATURE CITED

AACC International. 2007. Approved Methods of the American Association of Cereal
Chemists, 10th Ed. Method 66-50. The Association: St. Paul, MN.

Chen, C. H., and Bushuk, W. 1970. Nature of proteins in triticale and its parental species.
I. Solubility characteristics and amino acid composition of endosperm proteins. Can.
J. Plant Sci. 5029-14.

Crosbie, G. B., Ross, A. S., Moro, T., and Chiu, P. C. 1999. Starch and protein quality
requirements of Japanese alkaline noodles (Ramen). Cereal Chem. 762328-334.

Hoseney, R. C., Finney, K. F., Shorgen, M. D., and Pomeranz, Y. 1969a. Functional
(bread-making) and biochemical properties of wheat flour components. II. Role of
water solubles. Cereal Chem. 46:1 17-125.

Hoseney, R. C., Finney, K. F., Shorgen, M. D., and Pomeranz, Y. 1969b. Functional
(bread-making) and biochemical properties of wheat flour components. 111.
Characterization of gluten protein fractions obtained by ultracentrifugation. Cereal
Chem. 46:126-135.

F inney, K. F. 1971. Fractionating and reconstituting techniques to relate functional (bread
making) to biochemical properties of wheat-flour components. Cereal Sci. Today.
16:342-356.

MacRitchie, F. 1985. Studies of the methodology for fractionation and reconstitution of
wheat flours. J. Cereal Sci. 3:221-230.

Oh, N. H., Seib, P. A., Ward, A. B., and Deyoe, C. W. 1985b. Noodles. VI. Functional
properties of wheat flour components in oriental dry noodles. Cereal Foods World.
30:176-178.

Rho, K. L., Chung, O. K., and Seib, P. A. 1989. Noodles VIII. The effect of wheat flour
lipids, gluten, and several starches and surfactants on the quality of oriental dry
noodles. Cereal Chem. 65:320-326.

Sasaki, T., Kohyama, K., Yasui, T., and Satake, T. 2004. Rheological properties of white

salted noodles with different amylose content at small and large deformation. Cereal
Chem. 81:226-231.

181

Toyokawa, H., Rubenthaler, G. L., Powers, J. R., and Schanus, E. G. 1989. Japanese
noodle qualities. I. Flour components. Cereal Chem. 66:382-3 86.

182

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Fig. 6.1 Efl'eet of starch, gluten and water-soluble fraction on the microstructure
(cross-section) of raw noodles obtained from Caledonia reconstituted flour as
observed with Confocal Laser Scanning Microscope.

Samples: Noodles from Caledonia reconstituted flours A) CCC; B) CCN; C) CNC; and
D) NCC. Scale bar = 20 pm. For sample details please see Table 6.1.

188

 

Fig. 6.2 Effect of starch, gluten and water-soluble fractions on the microstructure
(cross-section) of raw noodles obtained from NuHorizon reconstituted flour as
observed with Confocal Laser Scanning Microscope.

Samples: Noodles from NuHorizon reconstituted flours A) NNN; B) NNC; C) NCN; and
D) CNN. Scale bar = 20 pm. For sample details please see Table 6.1.

189

 

Fig. 6.3 Effect of gliadin-rich and glutenin-rich fractions on the microstructure
(cross-section) of raw noodles obtained from Caledonia reconstituted flour as
observed with Confocal Laser Scanning Microscope.

Samples: Noodles from Caledonia reconstituted flours A) CCCC; B) CNCC; and C)
CCNC. Scale bar = 20 pm. For sample details please see Table 6.2.

190

 

Fig. 6.4 Effect of gliadin-rich and glutenin-rich fractions on the microstructure
(cross-section) of raw noodles obtained from NuHorizon reconstituted flour as
observed with Confocal Laser Scanning Microscope.

Samples: Noodles from NuHorizon reconstituted flours A) NNNN; B) NCNN; and C)
NNCN. Scale bar = 20 pm. For sample details please see Table 6.2.

191

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Chapter 7
SUMMARY

192

Noodle texture is affected both by wheat starch and wheat proteins. Though the
starch requirements for good quality noodles have been established, the role of proteins is
still not clear. In order to understand the effect of wheat protein content and wheat protein
composition on the texture and structure of white salted noodles, this study used two
approaches: an indirect approach by means of correlations using wheat varieties that
differ in their physicochemical properties and noodle-making abilities, and a direct
approach by means of fractionation-reconstitution studies.

From correlation studies using 39 different wheat varieties, it was observed that
both protein content and starch pasting properties of flours had strong relationships with
the texture parameters of cooked noodles. The dough mixing properties, which are
influenced by both protein content and protein quality, were also significantly correlated
with the texture of cooked noodles. The study of molecular weight distribution of flour
proteins by means of size-exclusion high performance liquid chromatography (SE-
HPLC) revealed that the texture parameters of noodles were more related to the actual
amounts of proteins within different peaks than the relative proportions of proteins from
the peaks in the total flour protein. According to sodium-dodecyl polyacrylamide gel
electrophoresis, it was found that the proportion of low molecular weight
albumins/globulins type proteins in total wheat proteins was negatively associated with
the hardness of noodles for the studied sample set. Amongst the alcohol soluble flour
proteins, B-gliadins and y-gliadins were associated with the texture parameters of
noodles. Prediction equations were also developed and tested for texture parameters of
noodles using SE-HPLC and starch pasting properties data. Protein quantity and starch

pasting properties together were able to explain about 75% of the variability in the

193

hardness, gumminess and chewiness of noodles made from a variety of wheat flour
samples.

A bench-top noodle-making procedure was developed to prepare noodles from
~10g of flour. Results demonstrated that the overall textural quality of noodles obtained
from developed bench-top and pilot-scale procedures were quite comparable, and that the
bench-top procedure had the ability to differentiate among flour samples with different
noodle-making properties.

The fractionation-reconstitution data from two parent flours, namely Caledonia (a
soft wheat) and NuHorizon (a hard wheat), suggested that protein content of flours has a
significant effect on the texture and structural properties of noodles. The hardness,
gumminess and chewiness of cooked noodles increased when protein content of either of
the reconstituted flours was increased. On the other hand, adhesiveness and resilience of
noodles exhibited a negative trend with increases in protein content of flour samples. The
results obtained from confocal laser seaming microscopy (CLSM) work showed that
with increases in protein content of reconstituted flours, the protein matrix of raw noodles
increased and contributed to decreased cooking loss and decreased cooking yield of
noodles. Irrespective of the differences in their starch pasting properties and protein
quality, Caledonia and NuHorizon reconstituted flours produced noodles with similar
texture properties and microstructure at equal protein contents. The elasticity of the
cooked noodle samples also increased with increases in the protein content of
reconstituted flours for both Caledonia and NuHorizon flours.

Amongst the main constituents of flours (starch, protein and water-soluble), the

starch fraction of flours was found to have the most effect on the texture properties of

194

cooked noodles. It was also observed that the starch fraction of flours had more impact on
the elasticity of noodles than the gluten protein fractions. The type of protein (weak or
strong) did not associate well with the texture properties of the cooked noodles if the
starch source (soft or hard wheat) and protein content are kept constant. Overall, the
texture properties of cooked noodles were found to be most influenced by the pasting
properties of starch, followed by the protein content, and lastly by the type of protein
proteins present in the flour studied. The microstructure of raw noodles, however, was
most affected by the flour protein content, then the type of proteins and finally by the

starch component.

195

Chapter 8
FUTURE RECOMMENDATIONS

196

The following are the recommendations for further research:

1)

2)

3)

4)

5)

6)

In order to better understand the roles of proteins in noodle-making, relationships
should be examined between the presence or absence of particular glutenins or
gliadins, their amounts and relative proportions to each other, and the texture

parameters of noodles.

Near—isogenic lines differing only in allelic expression of a protein at one
particular locus should be used to study relationships between protein parameters
and noodle texture parameters. Near-isogenie lines will help in observing the
direct result of presence or absence of specific protein subunits on noodle texture

properties.

Fundamental rheology should be used for better understanding of the effect of
proteins on noodle dough that is only partially developed and the texture of

cooked noodles prepared from such doughs.

A better method (objective) needs to be developed for judging the optimum water

absorption of flours for noodle making.

The microstructure of cooked noodles should also be studied to identify and

establish the roles and importance of protein matrix in noodle-making.

The importance of starch-protein interactions in noodle making should likewise

be investigated for both raw and cooked noodles.

197

APPENDICES

198

 

APPENDIX I
EXPERIMENTAL PROCEDURES, PHYSICOCHEMICAL

PROPERTIES AND PROTEIN COMPOSITION OF WHEAT FLOUR
SAMPLES USED IN CHAPTER 3

199

A. Procedure for Sodium Dodecyl Polyacrylamide Gel Electrophoresis

a) Extraction of Total Protein

Total wheat proteins were extracted according to Ng and Bushuk (1987). Briefly,
40 mg of sample was mixed with lml extraction buffer solution and vortexed every 15 min
for 2 hr at room temperature. After 2 hr, samples were heated at 100°C for 2.5 min. The
sample was allowed to cool for at least half an hour. Eight uL of the extract from top of the
sample was loaded on the gels for electrophoresis. The extraction buffer consisted of
66.7% (v/v) of distilled water, 28.3% (v/v) of extraction buffer stock and 5% (v/v) of 2-
mercaptoethanol. The extraction buffer stock contained 40.2% (v/v) distilled water, 20.8%
(v/v) 1M Tris-HCl buffer (pH 6.8), 33.3% (v/v) glycerol, 6.6% (w/v) SDS and 0.03%
(w/v) Pyronin Y. Protein molecular weight markers were obtained from Sigma (Sigma
Chemical Co., St. Louis, MO) and run on each gel. A reference variety, Neepawa, was also
run on each gel.
b) Gel Preparation

The separating gel (T = 17.3% , C = 0.45%) consisted of 14.79 m1 of 35% (w/v)
acrylamide, 1.16 ml of 2% (w/v) bis-acrylamide, 11.28 ml of 1M Tris-HCl buffer (pH 8.8),
0.86 ml of distilled water, 0.3 ml of 10% (w/v) SDS, 0.75 ml of freshly prepared 1% (w/v)
ammonium persulfate (APS), and 24 pl of N, N, N’, N’-tetramethylethylenediamene
(TEMED). The stacking gel (T = 4%, C = 1.72% ) was composed of 1.14 ml of 35% (w/v)
acrylamide, 0.35 ml of 2% (w/v) bis-acrylamide, 1.25 ml of 1M Tris-HCl buffer (pH 6.8),
6.78 ml of distilled water, 0.1 ml of 10% (w/v) SDS, 0.37 ml of freshly prepared 1%

(w/v) APS, and 12.5 pl of TEMED.

200

c) Run Conditions

Electrophoresis was run in gels 1.5 mm thick (18 cm wide and 16 cm long) with a
vertical electrophoresis apparatus (Hoefer Scientific Instruments, San Francisco, CA) at
20° C for 16 hr at a constant current of 10 mA per gel.
d) Staining of Gels

After the run, each gel was rinsed twice in the rinsing solution (10% of 100%
trichloroacetic acid solution, 33% methanol and 57% water). The gels were then stained
overnight with a Coomassie Brilliant Blue (G-250) (CBBG) staining solution. The staining
solution was prepared by mixing 1 g CBBG with 500 ml of water and 500 ml of 2N
HZSO4. The mixture was allowed to stand for 4 hr and then filtered through Whatrnan No.
1. One liter of filtrate was mixed with 111 ml of 10N potassium hydroxide and 155.5 m1
of 100% w/v trichloroacetic acid. The gels were washed several times with distilled water

during a period of 24 hr before analysis.

LITERATURE CITED
Ng, P. K. W., and Bushuk, W. 1987. Glutenin of Marquis wheat as a reference for

estimating molecular weights of glutenin subunits by sodium dodecyl sulfate-
polyacrylamide gel electrophoresis. Cereal Chem. 64:324-327.

201

B. Procedure for Acid-Polyacrylamide Gel Electrophoresis

a) Extraction of ethanol-soluble proteins

Ethanol-soluble proteins were extracted (according to Ng and Bushuk 1988) from
100 mg of flour sample with 200 pl of 70% ethanol for 15 min. The samples were
centrifuged, using Sorvall MC 12 V centrifuge (Dupont, Wimington, DE) at 12,000 x g for
2 min at room temperature. An aliquot (100 p1) of supernatant was collected and mixed
with 125 p1 of extract dilution solution. Extract dilution solution was 40% sucrose and
0.5% methyl green dye in aluminum lactate buffer (0.25% w/v, pH 3.1). Eight microliters
of sample per well was loaded on the gel. Neepawa was used as a reference wheat variety
for the identification of gliadin sub-groups and was run on each gel. Each flour sample was
run in at least duplicate.
b) Gel Preparation

Each gel was prepared from 40 ml of 0.25% w/v aluminum lactate buffer (pH 3.1),
4 g acrylamide, 0.4 g bis-acrylamide, 0.04 g ascorbic acid, 100 pl of 0.56% ferrous sulfate
heptahydrate solution and 120 pl of 0.6% H202.
c) Run Conditions

Electrophoresis was run in gels 1.5 mm thick (18 cm wide and 16 cm long) with a
vertical electrophoresis apparatus (Hoefer Scientific Instruments, San Francisco, CA) at
20°C for ~ 3 hr at a constant current of 30 mA per gel.
(1) Staining of Gels

After the run, each gel was stained overnight with a Coomassie Brilliant Blue (R-

250) staining solution. The staining solution consisted of 8 ml of stock dye solution (1%

202

dye in 95% ethanol) in 200 ml of destaining solution (12% trichloroacetic acid). The
stained gels were rinsed with water twice and then destained in the destaining solution
(12% trichloroacetic acid) for 6 hr. The destained gels were rinsed with water before being

scanned.

LITERATURE CITED

Ng, P. K. W., Scanlon, M. G., and Bushuk, W. 1988. A catalog of biochemical fingerprints
of registered Canadian wheat cultivars by electrophoresis and high-performance liquid
chromatography. Food Science Department, University of Manitoba, Winnipeg,
Manitoba, Canada. Publication 139.

203

C. Pilot-Scale Noodle-Making Procedure

Noodles were prepared according to the method described by Hou 2007. A
horizontal pin mixer MT-1-3 was used to prepare noodle dough from 1000 g of flour
sample. The flour was mixed with water (28%) and salt (1.2% on flour weight basis) for 2
minutes at 90 rpm. The beaters were cleaned and the dough was mixed again for 8 min at a
mixer speed of 120 rpm. After cleaning the beaters again, the dough was mixed for an
additional 2 min. Total mixing time was 12 min. The crumbly dough was rested for 30 min
in a plastic bag at room temperature. The rested dough was sheeted between two pairs of
rolls of a noodle machine (Ohtake, Model WR8-10, Tokyo Menki Co., Ltd, Japan), each
pair set at a 3 mm gap. The compressed dough sheet was compounded between each of
three pairs of rolls set at 5 mm gaps. The dough sheet was rolled around a rolling pin and
rested again in a plastic bag for 30 min at room temperature. The dough sheet was passed
through progressively reducing gaps of 4, 3, 2 and 1.5 mm (four times through each gap).
The final thickness of the noodle sheet was 1.2 i 0.03 mm. The dough sheet was cut into
2.5 mm wide noodle strips. The needles were stored in a plastic bag for 24 hr before

measuring their textural properties.

LITERATURE CITED

Hou, G. 2007. Asian products collaborative project, Portland, OR.

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TABLE 2. Dough Mixing Properties of the Wheat Flour Samples

 

 

 

Farinograph Extensigraph2|
Sample Water T1)?“ Stability MTIb 13 R A
Absorption (%) 0:35 (min) (BU) (cm) (BU) (cmz)
1 66.8 5.0 9.1 30 21.3 530 142
2 53.3 3.5 3.7 85 20.2 325 88
3 60.2 8.5 19.2 20 14.3 470 87
4 70.1 3.5 8.2 20 18.7 440 106
5 64.8 6.0 9.4 30 18.1 350 86
6 65.4 5.5 12.3 20 18.3 490 114
7 62.6 7.5 11.1 35 17.5 575 124
8 65.2 7.0 1 1.5 30 16.0 490 102
9 67.1 2.0 6.0 35 17.3 530 121
10 67.1 7.0 46.5 10 15.6 665 126
11 64.6 5.0 23.3 10 16.3 530 110
12 62.7 3.0 10.4 5 17.8 540 125
13 54.0 2.0 4.1 65 14.6 320 68
14 67.4 6.0 9.5 35 20.4 490 128
15 67.5 5.0 9.7 25 19.8 460 119
16 65.5 4.0 12.7 10
17 66.4 4.0 9.4 30 -------------- NA ------------
18 66.5 3.5 15.1 10
19 66.9 2.0 8.1 35 14.6 385 71
20 68.3 2.5 18.4 20 15.2 494 92
21 66.8 7.5 34.9 20 ______________ NA ____________
22 69.1 8.0 30.0 10
23 68.8 7.0 9.9 30 23.0 361 104
24 72.6 2.5 8.2 35 15.7 388 76
25 54.5 2.0 3.4 65 -------------- NA ------------
26 66.8 2.5 14.0 25 18.0 618 139
27 70.6 2.5 1.9 44 13.0 321 59
28 64.9 2.0 9.7 17 16.0 512 103
29 67.1 7.0 14.4 7 17.0 411 84
30 67.3 3.0 13.5 7 18.0 554 125
31 64.3 2.5 45.5 14 16.0 574 115
32 71.5 9.5 15.3 16 19.0 432 106
33 66.4 5.5 9.8 16 17.0 291 66
34 60.3 2.0 9.1 11 17.0 307 72
35 59.0 2.5 9.7 20 19.0 441 113
36 70.4 3.5 10.4 21 21.0 465 121
37 72.3 5.0 9.5 19 22.0 423 121
38 62.7 6.0 9.7 34 16.0 409 83
39 69.0 4.0 19.2 2 22.0 513 142

 

aE: Extensibility; R: Resistance to extension; A: Area under the curve.
bMTI: Mixing tolerance index; BU: Arbitrary units in farinograph and extensigraph.

207

Table 3. Texture Properties of the Cooked Noodles Prepared from the Wheat

Flour Samples

 

Hardness Cohesiveness Springiness Gumminess Chewiness

 

Sample (N) (Ratio) (Ratio) (N) (N)
1 11.17 0.638 0.963 7.12 6.85
2 10.53 0.646 0.971 6.79 6.59
3 11.73 0.638 0.953 7.47 7.12
4 11.66 0.617 0.967 7.19 6.95
5 11.24 0.656 0.959 7.37 7.07
6 12.61 0.613 0.961 7.73 7.43
7 13.26 0.639 0.966 8.46 8.18
8 11.22 0.638 0.945 7.15 6.76
9 10.84 0.636 0.960 6.89 6.62
10 12.64 0.643 0.969 8.12 7.86
11 11.76 0.64 0.962 7.52 7.24
12 13.41 0.647 0.956 8.67 8.29
13 11.22 0.63 0.953 7.07 6.74
14 11.43 0.655 0.968 7.48 7.24
15 12.30 0.635 0.958 7.80 7.47
16 11.40 0.635 0.958 7.24 6.93
17 12.09 0.612 0.959 7.40 7.09
18 11.51 0.644 0.958 7.40 7.09
19 10.69 0.656 0.951 7.01 6.66

20 12.17 0.654 0.965 7.95 7.67
21 12.58 0.659 0.968 8.28 8.01
22 12.48 0.668 0.968 8.33 8.06
23 13.13 0.634 0.965 8.32 8.02
24 10.43 0.669 0.964 6.97 6.72
25 12.17 0.631 0.956 7.67 7.34
26 11.26 0.631 0.959 7.10 6.81
27 9.61 0.645 0.951 6.20 5.89
28 10.86 0.626 0.950 6.79 6.45
29 11.40 0.637 0.946 7.25 6.86
30 10.39 0.632 0.951 6.56 6.24
31 11.28 0.641 0.957 7.23 6.92
32 10.43 0.64 0.950 6.68 6.34
33 11.25 0.652 0.939 7.33 6.89
34 11.47 0.618 0.941 7.08 6.66
35 11.11 0.653 0.944 7.25 6.85
36 10.76 0.625 0.935 6.73 6.29
37 11.06 0.641 0.962 7.09 6.82
38 12.19 0.636 0.971 7.75 7.52
39 11.98 0.657 0.947 7.87 7.45

 

208

TABLE 4. SE-HPLC Data (Absorbance Area) of the Wheat Flour Samples

 

 

 

Absorbance Areas (AA)a
Sample
P1 P2 P3 P4 P5 Total
1 3275512 5923056 2363598 4014395 8528248 24104809
2 3083227 6019498 2198673 3396494 8026380 22724272
3 3123581 4926969 892888 5471116 11464344 25878898
4 3812169 6745700 2985530 5358808 9516819 28419027
5 3103432 5096672 2308705 3580857 9040087 23129753
6 3817763 5715466 2018940 4323648 9105513 24981329
7 3816955 6160659 2016826 4830924 9734963 26560327
8 3099013 5217007 2311648 3770008 8244917 22642593
9 3186735 5529630 2404674 3805157 8632291 23558487
10 4229589 6642172 2371299 5413175 11341156 29997391
11 3974511 6893935 3207938 3825714 11185327 29087426
12 3524472 6499238 1871129 4244359 9740215 25879413
13 2311351 4650613 1846129 3246981 7538003 19593077
14 3126431 6097433 2145469 4026064 8936987 24332383
15 3373676 6014113 1901532 3953099 9030232 24272652
16 3682703 5747267 2588410 3235596 9450935 24704911
17 3503443 5317250 1877116 4192777 9286097 24176683
18 3651958 5906764 2453810 3523921 9618547 25155000
19 2835475 5006331 1960985 3294836 7906711 21004339
20 3569040 5410701 2549283 3992259 9169230 24690513
21 3526656 6480393 2192775 4423412 9485654 26108889
22 3920160 6800319 2526093 4892482 10407719 28546773
23 3755709 7215763 2538303 5062058 10409753 28981587
24 3048224 5511391 2131388 4030339 8497922 23219264
25 2189616 4555690 1672832 2971701 7044996 18434835
26 3504286 5342710 1576758 3900542 8861707 23186003
27 2865112 4934631 2082614 3983166 7725725 21591248
28 3212883 5644702 1856668 3668855 8601951 22985059
29 3643362 6263586 2617651 5112641 10602245 28239485
30 3301559 6130443 1811307 4226669 8910369 24380346
31 3195766 5502496 1738450 3960377 9566598 23963688
32 3333386 6017794 2728441 4025546 10621842 26727010
33 2715027 5366609 2211513 3814912 8462724 22570785
34 27061941 4542244 887676 4722664 9955957 22814734
35 3076850 5439739 1710117 3642339 7994412 21863457
36 4212827 7415145 2862806 5687247 11194820 31372844
37 3481975 7134643 2657299 4424286 10917525 28615727
38 3236946 5860353 2144518 4322836 10397266 25961919
39 3284894 6567696 2516497 5096506 10571044 28036638

 

aP1: Peak 1; P2: Peak 2; P3: Peak 3; P4: Peak 4; P5: Peak 5 proteins.

209

TABLE 5. SE-HPLC Data (Area 0/o) of the Wheat Flour Samples

 

 

 

Area % (A %) a
Sample
P2 P3 P4 P5

1 13.59 24.56 9.81 16.66 35.38
2 13.57 26.49 9.68 14.95 35.31
3 12.06 19.05 3.45 21.15 44.30
4 13.41 23.75 10.51 18.86 33.48
5 13.42 22.04 9.98 15.48 39.08
6 15.28 22.88 8.08 17.31 36.44
7 14.38 23.20 7.59 18.19 36.64
8 13.69 23.04 10.21 16.65 36.41
9 13.52 23.48 10.21 16.15 36.64
10 14.10 22.14 7.90 18.05 37.81
11 13.68 23.70 11.03 13.15 38.44
12 13.62 25.12 7.23 16.40 37.63
13 11.80 23.74 9.42 16.57 38.47
14 12.85 25.06 8.82 16.55 36.72
15 13.89 24.78 7.83 16.29 37.21
16 14.91 23.27 10.48 13.10 38.25
17 14.49 21.99 7.76 17.34 38.41
18 14.52 23.49 9.76 14.01 38.23
19 13.48 23.85 9.34 15.69 37.64
20 14.46 21.91 10.33 16.17 37.13
21 13.52 24.82 8.40 16.94 36.32
22 13.73 23.83 8.85 17.13 36.46
23 12.96 24.90 8.76 17.47 35.91
24 13.13 23.74 9.18 17.36 36.60
25 11.89 24.70 9.07 16.13 38.21
26 15.05 23.08 6.81 16.82 38.24
27 13.27 22.85 9.65 18.44 35.78
28 13.98 24.57 8.08 15.96 37.42
29 12.90 22.18 9.27 18.11 37.54
30 13.55 25.15 7.42 17.34 36.55
31 13.34 22.96 7.25 16.53 39.92
32 12.47 22.53 10.20 15.07 39.73
33 12.03 23.78 9.79 16.90 37.50
34 11.86 19.92 3.90 20.70 43.63
35 14.07 24.88 7.82 16.66 36.56
36 13.43 23.64 9.13 18.13 35.69
37 12.17 24.93 9.29 15.46 38.15
38 12.46 22.58 8.26 16.65 40.04
39 11.71 23.43 8.98 18.18 37.70

 

a'Pl: Peak 1; P2: Peak 2; P3: Peak 3; P4: Peak 4; P5: Peak 5 proteins.

210

Table 6. Noodle Texture Properties of Wheat Flour Samples

 

Hardness Cohesiveness Springiness Gumminess Chewiness

 

Sample
(8) (g) (g)

1 1138.35 0.638 0.963 725.77 698.51
7- 1073.10 0.646 0.971 692.66 672.18
3 1195.95 0.638 0.953 761.89 725.78
4 1189.05 0.617 0.967 733.26 708.89
5 1146.05 0.656 0.959 751.04 720.37
6 1285.20 0.613 0.961 787.49 756.94
7 1351.40 0.639 0.966 862.52 833.44
8 1 143.75 0.638 0.945 728.82 689.07
9 1104.65 0.636 0.960 702.50 674.62
10 1288.40 0.643 0.969 827.51 801.50
11 1199.15 0.640 0.962 767.05 737.96
12 1367.40 0.647 0.956 884.02 844.83
13 1143.95 0.630 0.953 721.01 687.16
14 1165.25 0.655 0.968 762.96 738.23
15 1254.25 0.635 0.958 795.25 761.97
16 1161.60 0.635 0.958 737.81 706.93
17 1232.40 0.612 0.959 753.85 722.63
18 1173.30 0.644 0.958 754.79 723.03
19 1089.50 0.656 0.951 714.42 679.20
20 1240.10 0.654 0.965 810.58 782.02
21 1282.65 0.659 0.968 843.81 816.97
22 1272.30 0.668 0.968 849.28 822.00
23 1338.25 0.634 0.965 847.92 817.63
24 1063.35 0.669 0.964 711.00 685.02
25 1241.00 0.631 0.956 782.26 748.13
26 1147.37 0.631 0.959 724.26 694.64
27 979.48 0.645 0.951 631.62 600.49
28 1106.64 0.626 0.950 692.19 657.31
29 1162.32 0.637 0.946 739.51 699.55
30 1058.73 0.632 0.951 669.03 636.01

 

211

Table 6. Noodle Texture Properties of Wheat Flour Samples ...contd

 

Hardness Cohesiveness Springiness Gumminess Chewiness

 

Sample
(8) (g) (g)
31 1149.45 0.641 0.957 736.50 705.04
32 1063.21 0.640 0.950 680.58 646.54
33 1146.83 0.652 0.939 747.27 701.89
34 1168.74 0.618 0.941 721.90 678.96
35 1132.85 0.653 0.944 739.45 698.27
36 1097.06 0.625 0.935 685.58 641.04
37 1127.47 0.641 0.962 722.83 695.04
38 1243.08 0.636 0.971 789.67 766.81
39 1220.99 0.657 0.947 801.77 759.08

 

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217

APPENDIX II
EFFECT OF GLUTEN PROTEIN CONTENT ON THE TEXTURE,
COOKING PROPERTIES, AND MICROSTRUCTURE OF WHITE
SALTED NOODLES

218

—-+—NRP4
- - - - NRP3
—0—NRP2
+NRP1

Force (g)

 

 

 

0 20 40 ()0 80 100 120

Fig 1. Effect of protein content on the force relaxation curve of the cooked noodles
prepared from NuHorizon flour.
Samples: NRPl, NuHorizon reconstituted protein 1 (6.3% p.c.); NRP2, NuHorizon
reconstituted protein 2 (7.9% p.c.); NRP3, NuHorizon reconstituted protein 3 (9.4% p.c.);
NRP4, NuHorizon reconstituted protein 4 (10.9% p.c.); p.c.: protein content.

219

350

300 I ,/

250i / -—+—NRP4
200: / --——NRP3

—o—— NRPZ

150 -' / NRP]

t/Yl (s)

O 20 40 60 80 100 l 20

Fig 2. Effect of protein content on the linearized force relaxation curve of the
cooked noodles prepared from NuHorizon flour.
Samples: NRPl, NuHorizon reconstituted protein 1 (6.3% p.c.); NRP2, NuHorizon
reconstituted protein 2 (7.9% p.c.); NRP3, NuHorizon reconstituted protein 3 (9.4% p.c.);
NRP4, NuHorizon reconstituted protein 4 (10.9% p.c.); p.c.: protein content.

220

Sample A. Caledonia Parent (CP): 3 Replicates

 

Figure A1. Image of cross-section of raw noodles of Caledonia parent (CP) flour as
obtained from confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

221

 

Figure A2. Image of cross-section of raw noodles of Caledonia parent (CP) flour as
obtained from confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

222

 

Figure A3. Image of cross-section of raw noodles of Caledonia parent (CP) flour as
obtained from confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix and 3: Overlaid image

223

 

Figure A4. Z-sectioning of cross-section of raw noodles of Caledonia parent (CP)
flour as obtained from confocal laser scanning microscope. Scale bar = 20 microns.

A1, A2 and A3 are 3 replicates of sample A (CP); 1, 2 and 3 are three z-layers used to
calculate protein matrix

224

Sample B. Caledonia Reconstituted Parent (CR): 3 replicates

 

Figure Bl. Image of cross-section of raw noodles of Caledonia reconstituted parent
(CR) flour as obtained from confocal laser scanning microscope. Scale bar = 20
microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

225

 

Figure BZ. Image of cross-section of raw noodles of Caledonia reconstituted parent
(CR) flour as obtained from confocal laser scanning microscope. Scale bar = 20
microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

226

 

Figure B3. Image of cross-section of raw noodles of Caledonia reconstituted parent
(CR) flour as obtained from confocal laser scanning microscope. Scale bar = 20
microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

227

 

Figure B4. Z-sectioning of cross-section of raw noodles of Caledonia reoconsituted
parent (CR) flour as obtained from confocal laser scanning microscope. Scale bar =
20 microns.

Bl, BZ and B3 are 3 replicates sample B (CR); 1, 2 and 3 are three z-layers used to
calculate protein matrix

228

Sample C. Caledonia Reconstituted Protein Level 1 (CRPl): 3 replicates

 

Figure C1. Image of cross-section of raw noodles of Caledonia reconstituted Protein
Level 1 (CRPl) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

229

 

Figure C2. Image of cross-section of raw noodles of Caledonia reconstituted protein
level 1 (CRPl) flour as obtained from confocal laser scanning microscope. Scale bar
= 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

230

 

Figure C3. Image of cross-section of raw noodles of Caledonia reconstituted protein
level 1 (CRPl) flour as obtained from confocal laser scanning microscope. Scale bar
= 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

231

 

ituted

lllg microscope.

f cross-section of raw noodles of Caledonia reconst

ioning o

Z-sect
protein level 1 (CRPl) flour as obtained from confocal laser scann

Figure C4

o

= 20 microns.

Scale bar

C1, C2 and C3 are 3 replicates sample C (CRPl); 1, 2 and 3 are three z-layers used to

calculate protein matrix

232

Sample D. Caledonia Reconstituted Protein Level 2 (CRP2): 3 replicates

 

Figure D1. Image of cross-section of raw noodles of Caledonia reconstituted protein
level 2 (CRP2) flour as obtained from confocal laser scanning microscope. Scale bar
= 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

233

 

Figure D2. Image of cross-section of raw noodles of Caledonia reconstituted protein
level 2 (CRP2) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

234

 

Figure D3. Image of cross-section of raw noodles of Caledonia reconstituted protein
level 2 (CRP2) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix and 3: Overlaid image

235

 

D3-2 ' - 03-3

Figure D4. Z-sectioning of cross-section of raw noodles of Caledonia reconstituted
protein level 2 (CRP2) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

D1, D2 and D3 are 3 replicates sample D (CRP2); 1, 2 and 3 are three z-layers used to
calculate protein matrix

236

Sample E. Caledonia Reconstituted Protein Level 3 (CRP3): 3 replicates

 

Figure El. Image of cross-section of raw noodles of Caledonia reconstituted protein
level 3 (CRP3) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

237

 

Figure E2. Image of cross-section of raw noodles of Caledonia reconstituted protein
level 3 (CRP3) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

238

 

Figure E3. Image of cross-section of raw noodles of Caledonia reconstituted protein
level 3 (CRP3) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

239

 

E3-1

Figure E4. Z-sectioning of cross-section of raw noodles of Caledonia reconstituted
protein level 3 (CRP3) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

E1, E2 and E3 are 3 replicates sample E (CRP3); 1, 2 and 3 are three z-layers used to
calculate protein matrix

240

Sample F. NuHorizon Parent (NP): 3 replicates

 

Figure F1. Image of cross-section of raw noodles of NuHorizon parent (NP) flour as
obtained from confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

241

 

 

Figure F2. Image of cross-section of raw noodles of NuHorizon parent (NP) flour as
obtained from confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

242

 

Figure F3. Image of cross-section of raw noodles of NuHorizon parent (NP) flour as
obtained from confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

243

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Figure F4. Z-sectioning of cross-section of raw noodles of NuHorizon Parent (NP)
flour as obtained from confocal laser scanning microscope. Scale bar = 20 microns.

F 1, F2 and F3 are 3 replicates sample F (NP); 1, 2 and 3 are three z-layers used to
calculate protein matrix

244

Sample G. NuHorizon Reconstituted parent (NR): 3 replicates

 

Figure G1. Image of cross-section of raw noodles of NuHorizon reconstituted parent
(NR) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.
1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

245

 

Figure G2. Image of cross-section of raw noodles of NuHorizon reconstituted parent
(NR) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

246

 

Figure G3. Image of cross-section of raw noodles of NuHorizon reconstituted parent
(NR) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

247

 

Figure G4. Z-sectioning of cross-section of raw noodles of NuHorizon reconstituted
parent (NR) flour as obtained from confocal laser scanning microscope. Scale bar =
20 microns.

G1, G2 and G3 are 3 replicates sample G (NR); 1, 2 and 3 are three z—layers used to
calculate protein matrix

248

Sample H. NuHorizon Reconstituted Protein Level 3(NRP3): 3 replicates

 

Figure H1. Image of cross-section of raw noodles of NuHorizon reconstituted
protein level 3 (NRP3) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

249

 

Figure H2. Image of cross-section of raw noodles of NuHorizon reconstituted
protein level 3 (NRP3) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

250

 

Figure H3. Image of cross-section of raw noodles of NuHorizon reconstituted
protein level 3 (NRP3) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

1: lrnage of starch granules, 2: Image of protein matrix, and 3: Overlaid image

251

 

Figure H4. Z-sectioning of cross-section of raw noodles of NuHorizon reconstituted
protein level 3 (NRP3) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

H1, H2 and H3 are 3 replicates sample H (NRP3); 1, 2 and 3 are three z-layers used to
calculate protein matrix

252

Sample I. NuHorizon Reconstituted Protein Level 2 (NRP2): 3 replicates

 

Figure 11. Image of cross-section of raw noodles of NuHorizon reconstituted protein
level 2 (NRP2) flour as obtained from confocal laser scanning microscope. Scale bar
= 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

253

 

Figure 12. Image of cross-section of raw noodles of NuHorizon reconstituted protein
level 2 (NRP2) flour as obtained from confocal laser scanning microscope. Scale bar
= 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

254

 

Figure 13. Image of cross-section of raw noodles of NuHorizon reconstituted protein
level 2 (NRP2) flour as obtained from confocal laser scanning microscope. Scale bar
= 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

255

 

Figure I4. Z-sectioning of cross-section of raw noodles of NuHorizon reconstituted
protein level 2 (NRP2) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

11, 12 and I3 are 3 replicates sample I (NRP2); 1, 2 and 3 are three z-layers used to
calculate protein matrix

256

Sample .1. NuHorizon Reconstituted Protein Level 1 (NRPl): 3 replicates

 

Figure J1. Image of cross-section of raw noodles of NuHorizon reconstituted protein
level 1 (NRPI) flour as obtained from confocal laser scanning microscope. Scale bar
= 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

257

 

Figure J2 Image of cross-section of raw noodles of NuHorizon reconstituted protein
level 1 (NRPl) flour as obtained from confocal laser scanning microscope. Scale bar
= 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

258

 

Figure J3. Image of cross-section of raw noodles of N uHorizon reconstituted protein
level 1 (NRPl) flour as obtained from confocal laser scanning microscope. Scale bar
= 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

259

(‘\ 9
"451“?“ Syn-$4

 

Figure J4. Z-sectioning of cross-section of raw noodles of NuHorizon reconstituted
protein level 1 (NRPl) flour as obtained from confocal laser scanning microscope.
Scale bar = 20 microns.

J 1, J2 and J3 are 3 replicates sample I (NRPl); 1, 2 and 3 are three z-layers used to
calculate protein matrix

260

APPENDIX III
EFFECT OF FLOUR CONSTITUENTS ON THE TEXTURE, COOKING
PROPERTIES, AND MICROSTRUCTURE OF WHITE SALTED NOODLES

261

Sample A. Caledonia Parent (CP): 3 replicates

 

Figure A1. Image of cross-section of raw noodles of Caledonia parent (CP) flour as
obtained from confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

262

 

Figure A2. Image of cross-section of raw noodles of Caledonia parent (CP) flour as
obtained from confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

263

 

Figure A3. Image of cross-section of raw noodles of Caledonia parent (CP) flour as
obtained from confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

264

 

Figure A4. Z-sectioning of cross-section of raw noodles of Caledonia parent (CP)
flour as obtained from confocal laser scanning microscope. Scale bar = 20 microns.

A1, A2 and A3 are 3 replicates sample A (CP); 1, 2 and 3 are three z-layers used to
calculate protein matrix

265

Sample B. CCC, (Starch, Gluten, and Water-soluble fraction from Caledonia): 3
replicates

 

Figure B]. Image of cross-section of raw noodles of CCC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

266

 

Figure B2. Image of cross-section of raw noodles of CCC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

267

 

Figure B3. Image of cross-section of raw noodles of CCC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

268

 

med

1‘ raw noodles of CCC flour as obta'

IOIl O

f cross-sect

ronrng 0

Figure B4. Z-sect

20 microns.

Scale bar

Ing microscope.

from confocal laser scann

B1, B2 and B3 are 3 replicates sample B (CCC); 1, 2 and 3 are three z-layers used to

calculate protein matrix

269

Sample C. CNC (Starch and Water-soluble from Caledonia and Gluten from
NuHorizon): 3 replicates

 

Figure C1. Image of cross-section of raw noodles of CNC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

270

 

Figure C2. Image of cross-section of raw noodles of CNC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

271

 

Figure C3. Image of cross-section of raw noodles of CNC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

272

 

Figure C4. Z-sectioning of cross-section of raw noodles of CNC flour as obtained
from confocal laser scanning microscope. Scale bar = 20 microns.

C1, C2 and C3 are 3 replicates sample C (CNC); 1, 2 and 3 are three z-layers used to
calculate protein matrix

273

Sample D. NuHorizon Parent (NP): 3 replicates

 

Figure D1. Image of cross-section of raw noodles of NuHorizon parent (NP) flour as
obtained from confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

274

 

Figure D2. Image of cross-section of raw noodles of NuHorizon parent (NP) flour as
obtained from confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: Image of Protein matrix and 3: Overlaid image

275

 

Figure D3. Image of cross-section of raw noodles of NuHorizon parent (NP) flour as
obtained from confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: Image of Protein matrix and 3: Overlaid image

276

 

Figure D4. Z-sectioning of cross-section of raw noodles of NuHorizon Parent (NP)
flour as obtained from confocal laser scanning microscope. Scale bar = 20 microns.

D1, D2 and D3 are 3 replicates sample D (NP); 1, 2 and 3 are three z-layers used to
calculate protein matrix

277

Sample E. NNN, (Starch, Gluten, and Water-soluble fraction from NuHorizon)

 

Figure E1. Image of cross-section of raw noodles of NNN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: Image of Protein matrix and 3: Overlaid image

278

 

Figure E2. Image of cross-section of raw noodles of NNN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

279

 

Figure E3. Image of cross-section of raw noodles of NNN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

280

 

Figure E4. Z-sectioning of cross-section of raw noodles of NNN flour as obtained
from confocal laser scanning microscope. Scale bar = 20 microns.

E1, E2 and E3 are 3 replicates sample E (NNN); 1, 2 and 3 are three z-layers used to
calculate protein matrix

281

Sample F. NNC (Starch and Gluten from NuHorizon and Water-soluble fraction
from Caledonia): 3 replicates

 

Figure F1. Image of cross-section of raw noodles of NNC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

282

 

Figure F2. Image of cross-section of raw noodles of NNC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

283

 

Figure F3. Image of cross-section of raw noodles of NNC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1 : Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

284

 

Figure F4. Z-sectioning of cross-section of raw noodles of NNC flour as obtained
from confocal laser scanning microscope. Scale bar = 20 microns.

F1, F2 and F3 are 3 replicates sample F (NNC); 1, 2 and 3 are three z-layers used to
calculate protein matrix

285

Sample G. NCN (Starch and Water-soluble fractions from NuHorizon and Gluten
from Caledonia):3 replicates

 

Figure G1. Image of cross-section of raw noodles of NCN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

286

 

Figure G2. Image of cross-section of raw noodles of NCN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

287

 

Figure G3. Image of cross-section of raw noodles of NCN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

288

 

Figure G4. Z-sectioning of cross-section of raw noodles of NCN flour as obtained
from confocal laser scanning microscope. Scale bar = 20 microns.

G1, G2 and G3 are 3 replicates sample G (NCN); 1, 2 and 3 are three z-layers used to
calculate protein matrix

289

Sample H. CNN (Starch from Caledonia, Gluten and Water-soluble fractions from
NuHorizon): 3 replicates

 

Figure H1. Image of cross-section of raw noodles of CNN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

290

 

Figure H2. Image of cross-section of raw noodles of CNN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

291

 

Figure H3. Image of cross-section of raw noodles of CNN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

292

 

Figure H4. Z-sectioning of cross-section of raw noodles of CNN flour as obtained
from confocal laser scanning microscope. Scale bar = 20 microns.

H1, H2 and H3 are 3 replicates sample H (CNN); 1, 2 and 3 are three z-layers used to
calculate protein matrix

293

Sample I. CCCC (Starch, gliadin-rich, glutenin-rich and water-soluble fractions
from Caledonia): 3 replicates

 

Figure 11. Image of cross-section of raw noodles of CCCC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

294

 

Figure 12. Image of cross-section of raw noodles of CCCC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.
1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

295

 

Figure I3. Image of cross-section of raw noodles of CCCC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

296

 

Figure 14. Z—sectioning of cross-section of raw noodles of CCCC flour as obtained
from confocal laser scanning microscope. Scale bar = 20 microns.

II, 12 and 13 are 3 replicates sample I (CCCC); l, 2 and 3 are three z-1ayers used to
calculate protein matrix

297

Sample J. CNCC (Starch, Glutenin-rich and Water-soluble fraction from
Caledonia, and Gliadin-rich fraction from NuHorizon): 3 replicates

 

Figure J1. Image of cross-section of raw noodles of CNCC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

298

 

Figure J2 Image of cross-section of raw noodles of CNCC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

299

 

Figure J3. Image of cross-section of raw noodles of CNCC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of starch granules, 2: Image of protein matrix, and 3: Overlaid image

300

       

K

J31-

Figure J4. Z—sectioning of cross-section of raw noodles of CNCC flour as obtained
from confocal laser scanning microscope. Scale bar = 20 microns.

J 1, J2 and J3 are 3 replicates sample J (CNCC); 1, 2 and 3 are three z-layers used to
calculate protein matrix

301

Sample H. CCNC (Starch, Gliadin-rich and Water-soluble fraction from Caledonia
and Glutenin-rich fraction from NuHorizon): 3 replicates

 

Figure H1. Image of cross-section of raw noodles of CCNC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: Image of Protein matrix and 3: Overlaid image

302

 

Figure H2. Image of cross-section of raw noodles of CCNC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: lrnage of Protein matrix and 3: Overlaid image

303

 

Figure H3. Image of cross-section of raw noodles of CCNC flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: Image of Protein matrix and 3: Overlaid image

304

 

rned

f cross-section of raw noodles of CCNC flour as obta

ing 0

tion
from confocal laser scanning m

. Z-sec

H4

Figure

20 microns.

icroscope. Scale bar

2 and 3 are three z-layers used to

calculate protein matrix

HZ and H3 are 3 replicates sample H (CCNC); 1,

9

H1

305

Sample I. NNNN (Starch, Gliadin-rich, Glutenin-rich and water-soluble fractions
from NuHorizon)

 

Figure 11. Image of cross-section of raw noodles of NNNN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: Image of Protein matrix and 3: Overlaid image

306

 

Figure 12 Image of cross-section of raw noodles of NNNN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: Image of Protein matrix and 3: Overlaid image

307

 

Figure 13 Image of cross-section of raw noodles of NNNN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: Image of Protein matrix and 3: Overlaid image

308

 

Figure 14. Z-sectioning of cross-section of raw noodles of NNNN flour as obtained
from confocal laser scanning microscope. Scale bar = 20 microns.

11, 12 and 13 are 3 replicates sample I (NNNN); 1, 2 and 3 are three z-layers used to
calculate protein matrix

309

Sample J. NCNN (Starch, Glutenin-rich and water-soluble fractions from
NuHorizon and Gliadin-rich fraction from Caledonia)

 

Figure J1 Image of cross-section of raw noodles of N CNN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: Image of Protein matrix and 3: Overlaid image

310

 

Figure J2 Image of cross-section of raw noodles of NCNN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: Image of Protein matrix and 3: Overlaid image

311

 

Figure J2 Image of cross-section of raw noodles of NCNN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: Image of Protein matrix and 3: Overlaid image

312

 

._ v"! i
I 6'21”.“
r ‘ . I. ' ,.,‘ I

Figure J4. Z-sectioning of cross-section of raw noodles of NCNN flour as obtained
from confocal laser scanning microscope. Scale bar = 20 microns.

J 1, J2 and J3 are 3 replicates sample J (NCNN); 1, 2 and 3 are three z-layers used to
calculate protein matrix

313

Sample K. NNCN (Starch, Gliadin-rich and water-soluble fractions from
NuHorizon and Glutenin-rich fraction from Caledonia)

 

Figure K1 Image of cross-section of raw noodles of NNCN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: Image of Protein matrix and 3: Overlaid image

314

 

Figure K2 Image of cross-section of raw noodles of NNCN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: Image of Protein matrix and 3: Overlaid image

315

 

Figure K31mage of cross-section of raw noodles of NNCN flour as obtained from
confocal laser scanning microscope. Scale bar = 20 microns.

1: Image of Starch granules, 2: Image of Protein matrix and 3: Overlaid image

316

 

Figure K4. Z-sectioning of cross-section of raw noodles of NNCN flour as obtained
from confocal laser scanning microscope. Scale bar = 20 microns.

K1, K2 and K3 are 3 replicates sample K (NNCN); 1, 2 and 3 are three z-layers used to
calculate protein matrix

317