EFFECT OF OPERATING VARIABLE PARAMETERS ON
CHARACTERISTICS OF EXTRUDED WHEAT FLOUR
ADEKOYA, OLUWATAMILORE HENRY
JULY, 2023
EFFECT OF OPERATING VARIABLE PARAMETERS ON
CHARACTERISTICS OF EXTRUDED WHEAT FLOUR
A FINAL YEAR RESEARCH PROJECT
BY
ADEKOYA, OLUWATAMILORE HNERY
(18CF023931)
PRESENTED TO
THE DEPARTMENT OF CHEMICAL ENGINEERING
IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE AWARD OF
THE DEGREE OF BACHELOR OF ENGINEERING (B.Eng.) IN CHEMICAL
ENGINEERING, COVENANT UNIVERSITY, OTA
JULY, 2023
CERTIFICATION
I, Oluwatamilore Henry Adekoya, hereby declare that the contained report on " Effect of
Extruder Screw Speed, Feed Moisture Content and Extrusion Temperature on
Characteristics of Extruded Wheat Flour" was researched, and the results analyzed,
under the supervision of Professor James A. Omoleye and approved, having satisfied the
partial requirements for the award of Bachelor of Engineering in Chemical Engineering
(B.Eng.), Covenant University, Ota.
Oluwatamilore H. Adekoya
Signature and Date
(Project Student)
Professor James A. Omoleye
Signature and Date
(Project Supervisor)
Professor Vincent E. Efeovbokhan
Signature and Date
(Head of Department)
ii
DEDICATION
I express my gratitude to God for His divine favor, peace, and guidance during my entire
five-year journey at Covenant University, which culminated in the successful completion
of this research project. Furthermore, I would like to dedicate this project report to my
parents, Mr. Olatunji Adekoya and Mrs. Kemi Adekoya, as well as my sisters, Toluwani
Adekoya, Timileyin Adekoya and Teniola Adekoya, for their constant and unwavering
support.
iii
ACKNOWLEDGEMENT
First and foremost, I would like to acknowledge my God for His divine guidance and
unwavering support throughout my academic journey.
I want to express my deep appreciation to our Chancellor, Bishop David O. Oyedepo, for
being an exceptional agent of change, and the visionary behind the concept that gave birth
to this unique institution. I would like to extend my gratitude to the Vice-Chancellor,
Professor Abiodun H. Adebayo, for his remarkable efforts in promoting research and
fostering an environment of academic excellence at this university. I would like to
acknowledge the Dean of Student Affairs, Mrs. Sola Coker, for her invaluable
contributions in creating a conducive environment for students to flourish in their
academic pursuits.
I want to express my heartfelt appreciation to my supervisor, Professor James A. Omoleye,
for his invaluable aid, encouragement, and mentorship throughout this project. I would
also like to extend my thanks to every lecturer in the Department of Chemical Engineering
for imparting the necessary theoretical knowledge, and to all the technologists who
provided assistance, contributing to the success of this research project.
I am immensely grateful to the Jim Ovia Foundation Leadership Scholarship and the
Africa-America Institute for their financial support, which has made it possible for me to
attend Covenant University. Without their generosity, this opportunity would not have
been possible. I would also like to acknowledge Dr. Ada Peters, Mrs. Omidiora, Mr. Isaac,
Mr. Samson, and other members of the international office for creating memorable
experiences during my time at Covenant University.
I would like to acknowledge my project partners, Amadi and Tosin, for their valuable
contributions to this research work. Additionally, I am grateful to my friends in CU, Jubilee
estate and Eyita for their unwavering support and encouragement. Finally, I want to
express my deepest appreciation to my parents, Mr. Olatunji Adekoya and Mrs. Kemi
Adekoya, as well as my sisters, Toluwani Adekoya, Timileyin Adekoya, and Teniola
Adekoya, for their constant love, encouragement, and unwavering support throughout my
academic journey.
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ABSTRACT
Food extrusion using a single screw extruder is an economical method of food processing
that offers great versatility, allowing for the processing of various food products and the
utilization of food waste. This study investigates the impact of extrusion parameters,
namely extrusion temperature (40-60°C), screw speed (60-80 rpm), and feed moisture
content (27-33% wb), on the characteristics of extruded wheat flour. Central composite
design was employed to design the experiment and analyze the data using Minitab
statistical software. The study examined the effects of these parameters on extrusion rate,
bulk density, water absorption index (WAI), water solubility index (WSI) and, softening
time in different temperatures of water of extruded wheat flour. The findings revealed that
screw speed positively affected extrusion rate, bulk density and WSI but negatively
affected softening time and WAI of extrudate wheat flour. Extrusion temperature
positively affected extrusion rate and WAI but had a negative effect on the bulk density,
WSI and softening time. Feed moisture content had a positive effect on extrusion rate,
WAI and softening time but negatively affected bulk density and WSI of extrudate
product. The response variables fell within the following ranges: extrusion rate of 1.342.79 g/s, bulk density of 0.667-0.989 g/cm3, WAI of 2.121-4.142 g/g, WSI of 5.84-20.22%,
and softening time of 6.34-8.33 minutes, 4.14-5.20 minutes, and 2.90-3.52 minutes at
60°C, 80°C, and 90°C water temperature, respectively, for the extruded wheat flour.
Notably, the optimized values of extrusion parameters were found to be the combination
consisting of 60°C extrusion temperature, 80 rpm screw speed, and 30.48% (wb) feed
moisture content resulted in higher water absorption index and extrusion rate along with
lower bulk density, softening time, and WSI for the extruded product.
v
TABLE OF CONTENT
CERTIFICATION
ii
DEDICATION
iii
ACKNOWLEDGEMENT
iv
ABSTRACT
v
LIST OF TABLES
ix
LIST OF FIGURES
x
LIST OF PLATES
xi
CHAPTER ONE INTRODUCTION
1
1.1 Background of Study
1
1.2 Statement of Problem
2
1.3 Aim and Objectives of the Study
4
1.3.1 Aim of the study
4
1.3.2 Objectives of the study
4
1.4 Justification of Study
5
1.5 Scope of Study
5
CHAPTER TWO LITERATURE REVIEW
2.1 Wheat Flour
7
7
2.1.1 Factors that cause variation in wheat flour
7
2.1.2 Processing of wheat
9
2.1.3 Advantages of wheat flour
10
2.1.4 Industrial application of wheat
12
2.2 Overview of Extrusion Technology
14
2.2.1 Screw extruders
14
2.2.2 History of screw extruders
14
2.2.3 Components of the extruder
15
2.2.4 Types of extrusion
20
2.3 Food Extrusion
27
2.3.1 Instrumentation for extrusion processing
vi
28
2.3.2 Measuring and controlling fundamental variables
28
2.3.3 Measurement of extrudate product variables
32
2.4 Effects of Extrusion Parameters on Extrudate variables
35
2.4.1 Bulk density
35
2.4.2 Expansion
36
2.4.3 Hardness
37
2.4.4 Water adsorption index (WAI) and water solubility index (WSI)
38
2.5 Optimization of Food Extrusion Process
39
2.5.1 Optimization using response surface
41
2.5.2 Composite design (CCD)
41
2.5.3 Box-Behnken design (BBD)
42
2.6 Review of Past Works
43
CHAPTER THREE METHODOLOGY
44
3.1 Materials
44
3.2 Equipment and Apparatus
44
3.2.1 Equipment
44
3.2.2 Apparatus
47
3.3 Procedure
47
3.3.1 Changes to the existing single screw extruder
47
3.3.2 Design of experiment
47
3.3.3 Extrusion process
48
3.3.4 Bulk density test
49
3.3.5 Water adsorption index (WAI) and water solubility index (WSI)
50
3.3.6 Softening time
50
3.3.7 Response models and optimization
50
3.4 Precaution Taken
50
CHAPTER FOUR RESULTS AND DISCUSSION
4.1 Results
52
52
4.1.1 Results on extrusion rate
54
4.1.2 Results on bulk density
56
4.1.3 Results on water adsorption index
58
vii
4.1.4 Results on water solubility index
60
4.1.5 Results on softening time at different temperature
62
4.2 Discussion of Results
69
4.2.1 Extrusion rate
69
4.2.2 Bulk density
71
4.2.3 Water adsorption index
72
4.2.4 Water solubility index
73
4.2.5 Softening time at different temperature
74
CHAPTER FIVE CONCLUSION AND RECOMMENDATIONS
77
5.1 Conclusion
77
5.2 Contribution to Knowledge
78
5.3 Recommendation
78
REFERENCES
79
APPENDICES
84
Appendix A: Extrusion Process
84
Appendix B: Bulk Density Test
85
Appendix C: Water Adsorption Index Test
86
Appendix D: Water Solubility Index Test
87
viii
LIST OF TABLES
TABLE
3.1
Design of experiment
TITLE
PAGE
49
4.1
Values of multi-level independent variables
52
4.3
Regression coefficients for independent variables and product responses
54
4.4
Regression coefficients for independent variables for extrusion rate
54
4.5
Regression coefficients for independent variables for bulk density
56
4.6
Regression coefficients for independent variables for WAI
58
4.7
Regression coefficients for independent variables for WSI
60
4.8
Regression coefficients for independent variables for softening time at 60℃ 62
4.9
Regression coefficients for independent variables for softening time at 80℃ 64
4.10
Regression coefficients for Independent variables for softening time at 90℃ 66
4.11
Optimized extrusion parameters
67
4.12
Optimized response variables
68
4.13
Quadratic models developed for each response variables
68
A-1
Extrusion Process Raw Data
84
B-1
Bulk density test raw data
85
C-1
Water adsorption index raw data
86
D-1
Water solubility index raw data
87
ix
LIST OF FIGURES
FIGURE
TITLE
2.1
Schematics of an extruder with major parts
PAGE
16
2.3
Schematic diagram of metal extrusion process
22
2.4
Direct extrusion
22
2.5
Indirect extrusion
23
2.6
Hydrostatic extrusion
24
2.7
Lateral extrusion
24
2.8
Three types of impact extrusion
25
2.9
Blow film extrusion
26
2.10
Simple food extrusion process
28
4.1
Surface plot of extrusion rate vs moisture content, screw speed
55
4.2
Surface plot of extrusion rate vs moisture content, extrusion temperature
55
4.3
Pareto chart of standardized effects for extrusion rate
55
4.4
Surface plot of bulk density vs moisture content, screw speed
56
4.5
Surface plot of bulk density vs moisture content, extrusion temperature
57
4.6
Pareto chart of standardized effects for bulk density
57
4.7
Surface plot of WAI vs moisture content, extrusion temperature
58
4.8
Surface plot of WAI vs screw speed, extrusion temperature
59
4.9
Pareto chart of standardized effects for WAI
59
4.10
Surface plot of WSI vs moisture content, screw speed
60
4.11
Surface plot of WSI vs moisture content, extrusion temperature
61
4.12
Pareto chart of standardized effects for WSI
61
4.13
Surface plot of softening time at 60℃ vs moisture content, screw speed
62
4.14
Surface plot of softening time at 60℃ vs moisture content, temperature
63
4.15
Pareto chart of standardized effects softening time at 60℃
63
4.16
Surface plot of softening time at 80℃ vs moisture content, screw speed
64
4.17
Surface plot of softening time at 80℃ vs moisture content, temperature
65
4.18
Pareto chart of standardized effects softening time at 80℃
65
4.19
Surface plot of softening time at 90℃ vs moisture content, screw speed
66
4.20
Surface plot of softening time at 90℃ vs moisture content, screw speed
67
4.21
Pareto chart of standardized effects softening time at 90℃
67
x
LIST OF PLATES
PLATE
3.1
TITLE
Wheat flour
3.2
Centrifuge
45
3.3
Weighing balance
45
3.4
Single screw extruder
45
3.5
Measuring cylinder
46
3.6
Spatula
46
3.7
Mortar and pestle
46
xi
PAGE
44
CHAPTER ONE
INTRODUCTION
1.1 Background of Study
Extrusion cooking is a continuous process in which materials, typically food products or
plastics, are converted to fluid and forced through a small opening or die to form specific
shapes. This process occurs by action of high temperatures, pressures, and shear stresses.
Extrusion is a flexible and effective procedure that uses high-temperature, short-time (HTST) thermal processes. From a range of basic ingredients, such as grains, extrusion process
can produce a variety of ready to eat meals such as cereal or pasta. The quality and texture
of extrusion-produced goods are also consistent (Choton, Gupta, Bandral, Anjum, &
Choudary, 2020).
The food sector has a variety of issues that extrusion cooking addresses. Extrusion
technique eliminates waste by creating products with an extended shelf life, which
eliminates the need for refrigeration or preservatives. As a result of the process's ability to
regulate process factors like temperature and pressure, the end product's quality is
consistent and reproducible. Finally, compared to other methods of producing food, the
process' overall manufacturing cost is substantially cheaper since it is highly automated,
uses less manpower, and enables continuous production (Egal, 2019).
Extrusion cooking involves forcing food materials through a heated barrel that contains a
screw or other mechanical device that pushes the mixture while applying pressure and heat
concurrently. An extruder is a machine employed in the process of extrusion. Its
fundamental parts consist of a barrel, either a single or twin screw, heating and cooling
jackets, a die, a hooper, and controls for regulating screw speed and temperature. There
are two classifications of extruders: single screw and twin-screw (Sobowale, Adebo, &
Adebiyi, 2018).
To make wheat suitable for human consumption, it is processed into a fine powder known
as wheat flour. Depending on its gluten content, wheat can be classified as “soft” with low
gluten levels, or “hard” with high gluten concentrations. The extrusion process for wheat
flour entails mixing it with water to create a paste, which is then extruded through a
machine to produce various products like breakfast cereals, snacks, pasta, and pet food.
While the extrusion process is inherently a simple technological procedure, its regulation
becomes challenging due to the significant impact of various process factors. The quality
and uniformity of the extruded product are ultimately impacted by extrusion variables,
1
which have a substantial influence on the extrusion process. For instance, if the
temperature is too low, the material could not flow well and could cause blockages, which
would result in waste. A weak and brittle extrudate may arise from under-extrusion and
poor layer adhesion if the speed is too high. A die that is too big can result in poor
resolution and detail, while a die that is too tiny might result in longer extrusion rates and
perhaps not producing enough material.
Extrusion variables can be classified into two categories: independent and dependent.
Independent factors, such as feed moisture content, screw speed, and extrusion
temperature, can be controlled or adjusted. On the other hand, dependent variables, such
as extrudate qualities (texture, color, water absorption index, water solubility index, and
bulk density), as well as extrudate attributes (viscosity, flow rate, and system pressure),
are influenced by changes in the independent variables. (Ruiz-Gutiérrez, SánchezMadrigal, & Quintero-Ramos, 2018).
Understanding how to modify these factors can aid in extrusion process optimization,
leading to improved extrudate quality, quicker extrusion times, and reduced material and
energy waste. Additionally, knowing how these factors interact might make it simpler to
detect and fix problems when they occur by aiding in troubleshooting. Because it enables
the extrusion process to be optimized, understanding how extruder variables impact
extrusion is crucial.
The objective of this research is to investigate how independent extrusion variables
(temperature, moisture content, and screw speed) impact dependent variables (extrusion
rate, bulk density, water adsorption index, water solubility index, and softening time in
60°C, 80°C, and 90°C water). By analyzing these relationships, the study aims to
contribute to the optimization of wheat flour extrusion processes.
1.2 Statement of Problem
The global population is projected to reach 9.9 billion by the year 2050 (IISD's SDG
Knowledge Hub, 2020). As the population expands, the demand for food also increases,
leading to a surge in waste and byproducts. Currently, approximately 1.6 billion tons of
food, valued at $1.2 trillion, are lost or wasted annually, accounting for one-third of the
total food production. Unfortunately, this problem is anticipated to exacerbate in the
coming decades, with food waste projected to rise to 2.1 billion tons by 2030, amounting
to $1.5 trillion in losses – a one-third increase in just a decade (Detisch, 2018), because of
the problems with trash management and dumping, the buildup of these industrial
2
wastes has a detrimental effect on the ecosystem (Debomitra, Richter, Pichmony, Bon-Jae,
& Ganjyal, 2021).
The food-processing industry generates substantial quantities of solid and liquid waste
during manufacturing, preparation, and consumption. This results in the loss of valuable
biomass and essential nutrients, while also contributing to escalating disposal problems
and potential pollution concerns. Such wastes are a significant cause of environmental
damage, leading to the loss of aesthetic value, the production of unpleasant odors, and
smoke pollution from improper burning. India, being the world's second-largest producer
of fruits and vegetables, wastes around 18% of its produce, amounting to a value of $7
billion (Khedkar & Singh, 2018). If not adequately managed, the sheer volume of food
waste can overwhelm disposal facilities, they could be harmful to health of persons, serve
as a haven for disease-carrying vectors. When it rains, dumping waste into water bodies,
could clog drainage systems and result in flooding, which could result in the loss of lives
and property. In addition, waste from the food processing industry is frequently rich in
organic matter. They decay anaerobically if disposed of improperly, producing methane,
a very potent greenhouse gas. Methane has a far larger potential for global warming than
carbon dioxide and contributes to climate change (Betz, Buchli, Göbel, & Müller, 2015).
The United Nations has identified food waste disposal as a worldwide issue as it accounts
for roughly 8% of GHG emissions. The environmental issues associated with disposing of
food waste have gotten worse over time and hence stimulated the need for proper
management of food waste (Kaur, Rani, & Yogalakshmi, 2020).
Food extrusion involves feeding raw ingredients through an extruder at specific
temperatures, pressures, and shear forces to form a cooked, structured product with the
necessary texture and functional qualities. Today, food extrusion is frequently used for
food processing for a variety of reasons, including its adaptability, which enables it to
process various food products, as well as its comparatively cheap operating costs and
minimum energy usage (Cotacallapa-Sucapuca, et al., 2021). Food extrusion technology
also provides a means to valorise food wastes by utilizing vegetables and fruits in form of
pomace, a solid remains of fruit after pressing for juice and a source of dietary fiber. This
technology uses nutritious fruit waste to colour cereals and ready-to-eat snacks, offering
consumers looking to make healthier decisions an enticing substitute. Including fruits and
vegetables in extruded products is a practical way to cut down on food waste and improve
the nutritional value of the final product (Offiah, Kontogiorgos, & Falade, 2018).
3
Waste generation is a necessary part of life; it cannot be prevented, but it can be managed.
There are several waste management techniques that can help minimize waste and one of
such technique is to domesticate technologies, such as food extrusion, that allow for
reduced waste production. These technologies are typically domesticated by process
optimization. Process optimization is examining and modifying numerous elements of a
process, such as equipment and parameters, to obtain a desired result more effectively with
minimal consumed resources and at a minimal cost. Process optimization plays a crucial
role in waste management by reducing waste generation, improving efficiency, and
minimizing resource consumption.
By understanding the impact of screw speed, extruder temperature and feed moisture
content on extrudate characteristics such as bulk density, water adsorption index, water
solubility index, softening time, and compressive force required to break the extrudate,
food producers can identify the optimal combination of settings that yield the desired
product quality. This knowledge contributes to domestication of food extrusion technology
thus minimizing waste and maximizing revenue and effectiveness.
1.3 Aim and Objectives of the Study
1.3.1 Aim of the study
The objective of this project is to examine how temperature, screw speed, and feed
moisture content influence the extrusion rate, bulk density, water adsorption index, water
solubility index, and softening time of extruded wheat flour in water at temperatures of
60°C, 80°C, and 90°C.
1.3.2 Objectives of the study
The specific objectives of the study are to:
I.
Use Composite design on Minitab statistical software (Version 20.3) to design the
extrusion experiment;
II.
III.
Extrude wheat flour using a single screw extruder;
Examine the influence of independent variables (extrusion temperature, moisture
content and extruder screw speed) on dependent variables (bulk density, water
adsorption index, water solubility index, and softening time);
IV.
Use response surface models to determine the effect of extrusion temperature,
moisture content and extruder screw speed on each dependent variable and,
4
V.
Determine the optimized combination of independent process variables that yield
the best dependent variables.
1.4 Justification of Study
Chemical engineers have a strong background in process engineering, which makes them
adept at analyzing and optimizing various parameters in food processing. This study
investigates the effects of extrusion temperature, feed moisture content, and extruder screw
speed on bulk density, softening times, and water adsorption index amongst other
physicochemical properties of extrudate products. By systematically studying and
manipulating these variables, one can identify the optimal conditions that lead to desired
product characteristics. This optimization process can help improve production efficiency,
reduce energy consumption, and minimize waste generation, thus contributing to
domesticating food extrusion technology. By encouraging food extrusion, this study will
contribute to SDG 3 - Good Health and Well-being since extrusion cooking is used in
valorizing agricultural wastes, SDG 8 - Decent Work and Economic Growth by creating
job opportunities in the food industry, and SDG 13 – Climate Action by reducing methane
emissions from landfills.
In addition, domesticating food extrusion contributes to SDG 9: Industry, Innovation, and
Infrastructure and SDG 12: Responsible Consumption and Production, which promotes
sustainable resource use and waste reduction. This study also contributes to SDG 2 - zero
hunger by production of cheap nutritious food products, especially in developing countries
where food insecurity is prevalent. The efficiency of food production and processing can
be improved by optimizing food extrusion procedures. Optimized extrusion techniques can
help to increase food availability, decrease food loss and waste, and promote food security
by maximizing the use of raw materials, and lowering waste creation.
1.5 Scope of Study
All the aspects to be addressed in this study are mentioned below;
1. Wheat flour as extrusion feedstock
2. A review of existing literature on effect of extrusion parameters on wheat flour and
other related crop to assess the current date and identify the gaps.
3. Examine the influence of independent variables on extrudate characteristics
5
4. Statistical analysis of on extrusion rate, bulk density, water adsorption index, water
solubility index, and softening time in different temperatures of water of extruded
wheat flour.
5. Development and optimization of response surface models that give a relation
between the extrusion parameters and response variables
6
CHAPTER TWO
LITERATURE REVIEW
2.1 Wheat Flour
Wheat flour is a finely ground product made from ground wheat grains. It is greatly applied
in various food applications. Wheat flour is made up of starch, proteins, fats and small
amounts of vitamins and minerals. Starch makes up majority of the grain's composition.
There are numerous types of wheat flour, and the variances are as a result of the types of
wheat grain, the components of wheat grain employed, how the wheat was processed, and
any additives added to the flour (Rattray, 2023). Approximately 600 million tonnes of
wheat are produced worldwide each year, making it one of the most significant grains.
About 70% of wheat is utilized in food production. Processing wheat requires milling,
which is crucial. Flour manufactured from wheat is used to make goods including bread,
cakes, cereal, macaroni, and noodles.
2.1.1 Factors that cause variation in wheat flour
2.1.1.1 Variance based on wheat grain
Wheat grain is either classified as soft or hard depending on their gluten content. If the
gluten content is high, wheat grains are referred to as hard and soft if gluten content is low.
Gluten is a type of protein that accounts for the elastic qualities of wheat flour. The more
gluten a wheat has, the simpler it is for the flour to develop a strong structure that can
capture yeast waste gases during kneading and successfully rise during baking. A flour
with less gluten has a lighter, less chewy texture, like those used in cakes. Flour's gluten
content will vary depending on where it was milled and how the wheat crop grows. Hard
red wheat, soft red wheat, durum wheat, and white wheat are the four principal wheat kinds
farmed worldwide. Flour with a high gluten level is made from hard red wheat, whereas
flour with a low gluten content is made from soft red wheat. Semolina flour made from
durum is processed and mostly used to make macaroni pasta. Of all the wheat flours that
are produced in large quantities, semolina flour has the most gluten. Low gluten flour is
made from white wheat (Chu, 2014).
Hard wheat is used to make bread flour and high gluten flour. While bread flour has an
average gluten content of 11.5%, high gluten flour has an average gluten content of 13%.
The difference between the two types of flour is that some high gluten flours have had
their starch percentage reduced, raising the gluten concentration to 14%. Usually, these
flours are used to make bread. High gluten flour is only used for highly elastic breads like
7
bagels and pizza. Soft wheat is used to make cake flour, which has a low (8–10%) gluten
level. This flour may also be used to make delicate cakes. To make all-purpose flour, hard
and soft wheat grains are combined. The range of gluten content of the all-purpose flour is
9–12%. This flour may be used to produce both bread and cakes, making it the most
adaptable. However, compared to using bread or cake flour, your breads won't be as chewy
and your cakes won't be as soft. Pastry flour is a blend of hard and soft wheat flours, with
a focus on soft. The typical gluten concentration is 9–10%. Pastry flour can be used to
make pie crusts.
2.1.1.2 Variance based on part of wheat grain included
Wheat grain is made up of three parts; endosperm, germ and bran. Endosperm makes up a
significant portion of wheat flour. It is the biggest portion of the wheat kernel, accounting
for 83% of the weight of the kernel, and it provides the majority of the nutrients for the
growing wheat plant. The endosperm of the wheat is ground into a fine powder when it is
milled into flour, and this powder serves as the foundation for white or refined wheat flour.
The majority of the protein (gliadin and glutenin) and carbohydrates (mainly starch) are
found in the endosperm. Compared to the bran and germ parts of the wheat kernel, the
endosperm of wheat includes trace amounts of lipids, fibre, vitamins, and iron in addition
to carbohydrates and proteins (Senay, 2020).
When producing refined white flour, the germ and bran of the wheat kernel are two parts
that are frequently removed. They are nevertheless preserved in whole wheat flour,
producing a more nutrient- and fiber-rich final product. The wheat kernel's embryo, or
germ, is a nutrient-rich component, it makes up about 14% of the kernel’s weight. It is a
tiny, oval-shaped structure that is situated near the kernel's base. Essential fatty acids,
vitamins, minerals (including zinc and iron), and phytonutrients are all present in the germ.
It is a strong source of protein and is high in unsaturated fats. Whole wheat flour contains
the germ, which imparts a nutty flavour, healthy natural oils, and essential nutrients. The
wetness and softness of baked foods can be enhanced by the lipids in the germ. However,
compared to refined white flour, the fat content of whole wheat flour may also make it
more prone to spoiling.
The bran is the wheat kernel's outer covering of defence, it makes up 2.5% of the kernel’s
weight. It is a fibrous component rich in dietary fibre, antioxidants, and many vitamins and
minerals, including vitamin B6 and folate, selenium, manganese, and phosphorus. Whole
wheat goods benefit from the texture and flavour of the bran, which gives them a somewhat
rougher texture and nutty flavour. The bran's fibre facilitates digestion and offers a number
8
of health advantages, including encouraging bowel regularity, managing blood sugar
levels, and maintaining heart health.
2.1.2 Processing of wheat
The broad range of procedures used to turn harvested wheat grains into a variety of wheatbased goods, such as flour, bran, and wheat germ, is referred to as "wheat processing." It
includes a number of procedures and methods that turn unprocessed wheat into finished
goods fit for human consumption or further industrial uses. The procedure is long and
difficult. After preparation, the wheat undergoes grading, inspection, and weighing.
Subsequently, the grains are sorted based on their weight, size, and shape. The steps
involved in wheat processing are given below (UDAWAT, 2020):
1. Harvesting: Harvesting mature wheat plants marks the start of the wheat milling
process. Combination harvesters are often used to chop and gather the wheat stalks
during the harvesting process.
2. Cleaning: After being harvested, wheat is cleaned to get rid of debris like dirt,
rocks, and other contaminants.
3. Conditioning: For the best milling qualities, the moisture level of the wheat is
adjusted by conditioning and tempering. The wheat is steeped in water at this point
to make the bran removal process simple. To guarantee that the grain's moisture
level is consistent throughout, conditioning is done before milling. During the
milling process, the moisture aids in keeping the bran from breaking.
4. Milling: The milling process starts by sending the conditioned wheat through a
series of rolls which rotate at different velocity. The rotating action of the rolls
cause the wheat grain to open causing the endosperm to be separated from the bran.
The method of using rolls to form wheat flour is known as roller milling. Other
milling methods such as stone milling, hammer milling, or impact milling can also
be used to separate endosperm from the bran. The bran and other outer layers of
the grains separate from the endosperm as they are crushed. The bran is the fibrous
outer layer that protects the wheat kernel. It has nutrients like minerals and dietary
fiber. The endosperm particles are smaller and lighter than the separated bran
particles.
5. Sifting and separation: Following milling, the flour is sieved or sifted to get rid of
any impurities and divide it into several classes or particle sizes. The crushed grains
go through sieves and screens that assist separating the bran from the finer
9
endosperm particles. The bran, being larger and coarser, is separated from the finer
flour particles by size and density. Air currents and gravity are frequently used to
facilitate this separation process.
6. Blending: In this case, ingredients are combined to create various flours. For
instance, whole wheat flour (crushed endosperm) is created by mixing white flour
with wheat bran.
7. Fortification and enrichment: Flour may occasionally go through fortification or
enrichment, which involves reintroducing specific components, including vitamins
and minerals, to the flour to improve its nutritional value. This process is frequently
used when using refined white flour.
8. Distribution and packaging: The processed wheat products, such as flour,
semolina, bran, and wheat germ, are distributed and packed in the proper containers
or bags. The products are better shielded from physical harm, pests, and moisture
thanks to packaging materials.
2.1.3 Advantages of wheat flour
Wheat is an essential part of the diets of billions of people worldwide. Therefore, it's
important to not undervalue the nutritional importance of wheat proteins, especially in less
developed countries where people may consume a large amount of bread, noodles, and
other wheat-based foods like bulgur and couscous on a regular basis. Wheat supplies
around 20% of the total dietary calories and about 55% of the carbohydrate content. Its
composition includes notable levels of vitamins (such thiamine and vitamin-B) and
minerals (including zinc and iron), as well as 78.10% carbs, 14.70% protein, 2.10% fat,
and 2.10% minerals (Kumar, 2011).
2.1.3.1 Benefits of Carbohydrate
Carbohydrates can be categorized in various ways, and one such classification is
determined by the number of simple sugar units present in the carbohydrate molecule.
Monosaccharides are single-unit sugars, while disaccharides are sugars with two units.
Galactose, fructose, and glucose are examples of monosaccharaides. However, lactose and
sucrose are examples of disaccharides. Simple carbohydrates typically refer to
carbohydrates with one or two simple sugar molecules. On the other hand, complex
carbohydrates encompass long-chain compounds, such as glycogen and fibers. (The
Nutrition Source, 2019).
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Carbohydrates are an essential part of our diets since they provide the body with glucose,
which is converted into energy to sustain biological processes and physical activities, such
as movement and cognitive functions. Glucose serves as the primary energy source for our
body, as different tissues, including muscles and the brain, directly utilize
monosaccharides for fuel. After monosaccharides are absorbed into the bloodstream
through the small intestine, they are transported to the cells that require them. Hormones
like insulin and glucagon play a crucial role in regulating blood sugar levels by adding or
removing glucose from the bloodstream as needed.
In addition to direct utilization, our body also indirectly utilizes glucose through glycogen,
a polysaccharide similar to starch. Glycogen is stored in the liver and muscles and acts as
an immediate reserve of energy. When needed, glycogen is converted back into glucose to
maintain stable blood sugar levels (European Food Information Council (EUFIC), 2020).
2.1.3.2 Benefits of Protein
Protein has a vital function in the formation and upkeep of all cells in our bodies. It
provides energy to our cells and fuels our overall body functions. Including protein in your
daily health routine is important for maintaining the well-being of your cells. Protein is
composed of amino acids, often referred to as building blocks, as they are linked together
in lengthy chains. It is categorized as a "macronutrient," which means that you require
significant quantities of it to sustain good health.
Protein fulfills various crucial roles in the body. It acts as a fundamental component for
the formation of bones, muscles, cartilage, and skin. Notably, a significant portion of your
hair and nails consists of protein. Additionally, protein is involved in the construction and
restoration of body tissues. It is found in the form of a protein compound within red blood
cells, facilitating the transportation of oxygen throughout the body and ensuring the supply
of necessary nutrients to all organs. Approximately half of the protein obtained from your
daily diet is utilized in producing enzymes, which aid in food digestion and the generation
of new cells and body chemicals. Moreover, protein plays a vital role in regulating
hormones, particularly during cell transformation and development in the pubescent stage
(Cooper, 2022).
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2.3.1.3 Benefits of Minerals and Vitamins
Wheat's mineral content varies according to its kind, the makeup of the soil, the climate,
and agricultural practices, including organic farming. Important elements included in
wheat flour, such as iron, magnesium, phosphorus, and zinc, are essential to many body
processes. Red blood cell production and oxygen delivery both depend on iron.
Magnesium supports healthy neuron and energy metabolism. Phosphorus aids in cell
growth and bone health. Among its many uses, zinc supports the immune system and the
healing of wounds.
B vitamins, beneficial to the human body, can be found in wheat flour. These
vitamins include thiamin (B1), riboflavin (B2), niacin (B3), and folate (B9). The creation
of energy, proper nerve operation, and the metabolism of carbs, proteins, and fats all
depend on B vitamins. Additionally, they help healthy brain function, good vision, and
nervous system maintenance. Wheat flour also has vitamin E, an antioxidant that protects
cells from oxidative damage brought on by free radicals. In addition to promoting skin
health and blood vessel health, vitamin E helps the immune system operate (Cooper,
2022).
2.1.4 Industrial application of wheat
Wheat is a highly adaptable plant that has diverse uses across various industries. It is a
cereal grain cultivated in temperate regions and has the potential to be utilized in the
production of a wide range of food products. Additionally, wheat has applications in
industries such as paper manufacturing, breweries, and biofuel production.
2.1.4.1 In the food industry
The food sector is the main consumer of wheat, which is processed into several varieties
of flour including all-purpose, bread, cake, and semolina. Wheat flour is an essential
component of baking and is used to make bread, cakes, muffins, and other baked items.
Wheat flour contains gluten, which adds to the dough's structure and elasticity and allows
it to rise and acquire a desired texture in the baked goods. When making pasta and noodles,
particularly using durum wheat flour, wheat flour and water are mixed to create a dough
that is moulded into different pasta and noodle shapes. Gluten in wheat flour gives pasta
and noodles the necessary strength and texture for proper formation. Wheat also finds
application in the manufacturing of diverse snack foods, and it also holds significance as
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a key ingredient in animal feed formulations. It serves as a valuable source of nutrition for
livestock, poultry, and other animals.
2.4.1.2 In the brewing industry
Wheat has a long history of being used as a primary ingredient in the manufacture of malt
and beer. Beer's flavor, body, and foam stability are all influenced by wheat malt, which
is made from malted wheat grains. It gives wheat beers a distinctive flavor and frequently
makes them smoother and hazier. Along with malted barley, wheat can be used as an
auxiliary in brewing. The flavor, texture, and appearance of the beer can be altered by
substituting wheat for a portion of the malted barley. Wheat can also be used in the brewing
process as a filtering aid. It helps clear the beer of unwanted particles and sediment by
acting as a clarifying agent or as a filter bed (Faltermaier, Waters, Becker, Arendt, & Gastl,
2014).
2.4.1.3 In the paper industry
Pulping refers to the transformation of raw materials, usually wood or other fibrous
substances, into a fibrous mass known as pulp. This pulp consists of individual fibers that
are well-suited for manufacturing paper, paperboard, and various other cellulose-based
products. The pulping process entails the mechanical or chemical breakdown of the raw
materials, enabling the separation of fibers from other constituents like lignin,
hemicellulose, and extractives. Wheat does not have significant direct applications in the
paper industry. Unlike other raw materials like wood, bamboo, or recycled paper, wheat is
not commonly used as a primary fiber source for paper production. However, wheat straw,
the byproduct of wheat harvesting, can be utilized as a potential source of fiber for
papermaking. Wheat straw pulp can be produced through a pulping process similar to
wood pulping.
Bleached wheat straw pulps offer a wide range of possibilities for producing diverse paper
and paperboard grades, such as lightweight printing paper, letterpress paper, typing paper,
writing paper, tissue and sanitary papers, and coated ivory board. This is due to their
favorable strength properties, reasonable brightness, and excellent printability. In certain
cases, a small proportion of bleached wood pulps or bamboo pulps may be blended with
wheat straw pulp to enhance pulp stock wet-web runability in paper machines. Moreover,
bleached wheat straw pulp finds application in the production of Bible paper products by
some paper factories (Fang & Shen, 2018).
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2.2 Overview of Extrusion Technology
In the extrusion process, material is continually transported through a barrel containing
one or more screws and driven through a die (shaped aperture) by combining several
activities quickly. Extrusion process utilizes pressure, heat, mechanical shear and moisture
to plasticize materials through a die. Examples of these materials include food and
polymers. The extrusion process combines a number of unit activities, including shearing,
heating, and shaping, to produce the final products. (Debomitra, Richter, Pichmony, BonJae, & Ganjyal, 2021); (Choton, Gupta, Bandral, Anjum, & Choudary, 2020).
The extrusion process is a high-temperature-high-pressure method in which raw material
is put under shear forces. The solid substance experiences physicochemical changes and as
a result, becomes a melt. Before reaching the final state, this viscous substance undergoes
additional changes in its physicochemical properties when it exits the system. This occurs
due to difference in extrudate's system conditions such as temperature and pressure
difference. In Extrusion, the parameters are split into inputs parameters for the extrusion
system, dependent parameters for the extrusion system, and output parameters for the
products. Examples of output parameters include water adsorption index, water solubility
index and bulk density (Debomitra, Richter, Pichmony, Bon-Jae, & Ganjyal, 2021).
2.2.1 Screw extruders
Extruders play a vital role in continuous process operations within extrusion processing
technology. They serve multiple functions, such as transporting and compressing
particulate components, melting polymers, mixing, cooking polymeric materials, and
texturizing and shaping products. The two primary equipment designs used in extrusion
processing are the single screw extruder and the twin screw extruder. Each design allows
for various engineering choices, depending on the equipment manufacturer or specific
processing requirements. This significant flexibility in processing settings is what grants
the extrusion process its remarkable versatility. (Debomitra, Richter, Pichmony, Bon-Jae,
& Ganjyal, 2021).
2.2.2 History of screw extruders
Since the 19th century, both single screw and intermeshing co-rotating twin screw
extruders have been in existence. The first single screw extruder for soap production was
described in a US patent granted to Sturges in 1871, while Gray developed a single screw
extruder for gutta-percha preparation and wire coating in 1879. The rubber industry was
14
among the early adopters of screw extrusion equipment for continuous rubber
compounding. Though there were no major industrial applications from 1880 to 1930,
significant mechanical engineering advancements improved the designs of single screw
extruders. Coignet received the first patent for a twin-screw extruder in 1869, known as a
malaxator, which processed synthetic stone paste. The intermeshing co-rotating twin screw
extruder design saw notable improvements in the late 1930s, with Colombo introducing
an innovative design produced by the Italian company Lavorazione Materie Plastiche in
1939. These machines gained wide usage in the polymer sector between 1940 and 1956.
The advent of thermoplastics in the 1930s accelerated the development of extrusion
processing technology. A significant step in automated extrusion technology came with
Paul Troester's creation of an electrically heated, air-cooled single screw extruder with
automated temperature control and variable screw speed in Germany in 1939.
As the polymer industry expanded and polymer compositions became more complex,
single screw extruders demonstrated limitations in properly mixing, compounding, and
pumping polymer melts with specific properties. In response to the plastics producers'
request after World War II, twin screw extrusion technology was adopted, greatly
enhancing the process.
Between 1940 and 1960, with global plastics production increasing from 300,000 to 12
million metric tonnes annually, screw extruders played a crucial role in the remarkable rise
of the polymer processing industry, including plastics and rubber manufacturing. The
sector's growth allowed for flexible and efficient processing at a competitive cost-toperformance ratio, fully realizing the processing potential of extrusion technology.
Today, extrusion technology finds application not only in the polymer processing industry
but also in the food processing industry, as it is one of the most cost-effective methods
available. (Bouvier & Campanella, 2014).
2.2.3 Components of the extruder
A schematic of an extruder's components is represented below in figure 2.1. It comprises
mostly of a barrel that extends from the hopper at the back of the extruder, through which
polymer is fed, to the die at the front of the extruder. The extruder's moving component,
the screw, is made to blend, compact, and transport the polymer as it transforms into a
viscous melt from solid granules. A motor driving a gear reducer powers the screw's
rotation within the barrel. The spinning screw is the extruder's main component. The axial
distance between one flight's edge and the equivalent edge on the following flight is known
15
as the pitch, and it is the thread of an extruder screw. The helix angle and pitch are related
terms that describe how coarse the thread is. The single screw extruder is currently the
most popular and adaptable extruder. Extruders are often identified by their barrel lengths,
which are expressed as the length-to-diameter ratio, L/D, and their bore diameters, D. For
laboratory equipment, diameters range from about 1 in. to around 8 in. for specialized
manufacturing equipment. Commercial extruders typically have L/D ratios between 20/1
and 34/1.
Figure 2.1: Schematics of an extruder with major parts
Source: (Bouvier & Campanella, 2014).
I.
Screw
The screw is the most essential part of the extruder, it is sometimes regarded to as
the heart of the extruder. The screw is a long, threaded shaft that rotates inside the
barrel. The material is pushed forward by the screw, which also mixes and
homogenizes the molten material once it has melted due to friction and heat
produced by the screw's rotation and heat from the heater bands. The feed portion,
the transition section, and the metering section are the three primary parts of the
screw. Each of these sections have a different channel depth
Feeding section: The material will be transported and melted in this portion. The
material travel from the hopper to the melting zone because of the feed
section's long flight depth and its decreasing channel depth throughout its length.
Transition section: By progressively lowering the flight depth and raising the
channel depth, the transition section aids in further melting and blending the
16
material. In order to prepare the material for final shape in the metering section and
to achieve a homogeneous melt, this part to compact the loosely packed feed and
remove air pockets in the process. It causes the resin to melt and condense into a
continuous flow of molten material. A major source of energy for melting the resin
is the frictional force created between the resin, the barrel wall, and the moving
screw. The transition section is also called the compression section
Metering section: The extrusion rate and pressure are precisely controlled by the
metering section. The material flows towards the die with a continuous flow and
pressure buildup thanks to its short flight depth and constant channel depth. A
constant flow rate is made guaranteed by the metering or pump section, which also
creates the pressure required to push the polymer melt through the remainder of the
extruder and out through the die.
II.
Barrel
The barrel is typically a cylindrical component of the extruder. In the barrel,
material to be extruded is melted, mixed, and transported. The raw material is often
heated using electric heaters or heating elements to melt it and keep it molten.
High-strength steel or other durable materials that can endure the high temperatures
and pressures are required for construction of the extruder's barrel. The material is
melted, mixed, and transported inside a cylindrical container called a barrel. The
raw material is often heated using electric heaters or heating elements to melt it
and keep it molten. High-strength steel or other durable materials that can endure
the high temperatures and pressures are required for construction of the
extruder's barrel. It is precisely machined to guarantee a uniformly smooth inner
surface. Heating components, such as electric heater bands are wrapped around the
barrel's outside. The heat from these heaters is essential to melt the material within
the extruder. In order to produce the best processing conditions for the particular
material being extruded, the barrel's temperature is carefully regulated.
III.
Heater bands
Heater bands are electric heating elements wrapped around the barrel using clamps
so as to ensure proper conduction of heat from the bands to the barrel. They supply
the heat required to melt the substance inside the barrel. To keep the best processing
conditions, the temperature of the heater bands may be accurately regulated. Heater
bands' major function is to keep the barrel at the ideal temperature so that the
17
material may be processed. Controlled heat is applied to the material as it passes
through the barrel, causing it to melt and become viscous for extrusion.
Stainless steel or ceramic are frequently used to make heater bands because they
can withstand high temperatures. They are made to securely round the extruder's
barrel and disperse heat uniformly along its length.
Electric heating components, such as resistance wires, are located inside the heater
bands and produce heat when an electrical current flows through them. The heating
components are placed precisely and created to heat the barrel's surface
uniformly. Temperature controller, used to monitor and control the barrel's
temperature, operate the heater bands. Based on the material being extruded, these
controllers enable operators to establish and maintain exact temperature required
for extrusion. Temperature sensors mounted on or inside the barrel provide
feedback that allows the heater bands' heat output to be changed to maintain the
required temperature.
IV.
Thermocouple
The thermocouple is the extruder’s temperature controller. It is used to monitor and
control the barrel's temperature, operate the heater bands. The thermocouple
provides real-time temperature feedback to ensure that the extrusion process
operates within the desired temperature range for the specific material being
extruded. Temperature sensors mounted on or inside the barrel provide feedback
that allows the heater bands' heat output to be changed to maintain the required
temperature.
Typically, a thermocouple is constructed from two distinct kinds of metal wires
that are linked at one end to create a junction. The barrel's internal position where
the temperature has to be monitored is where this connection is situated. The
opposite ends of the wires are attached to a temperature measurement equipment.
The thermoelectric effect, which is the phenomenon of creating an electric voltage
when there is a temperature gradient between the junction and the other end of the
wires, serves as the foundation for the operation of a thermocouple. It is possible
to measure this voltage in order to estimate the temperature because it is directly
proportional to the temperature differential.
V.
Feed throat
The raw material enters the extruder barrel through the feed throat. It offers a
regulated flow of material into the extruder and joins the hopper to the barrel. The
18
feed throat's main function is to deliver a steady and regulated flow of raw material
into the extruder barrel. Between the hopper and the barrel, it serves as a
transitional point, ensuring that the material is fed into and transported through the
extrusion system in the right manner. The design of the feed throat is influenced
by things like the kind of extruder and the properties of the substance being
extruded. The material is normally guided from the hopper and directed into the
barrel via an aperture with a funnel-like shape. The shape and dimensions of the
feed throat are optimized to promote efficient material flow and prevent bridging
or uneven feeding.
VI.
Hopper
The hopper is a big funnel-shaped container found at the top of the extruder. It
houses the raw materials that are fed into the extruder for processing, such as plastic
pellets or granules. The hopper's main function is to hold and provide the raw
material to the extruder. It delivers a stable feed rate and uninterrupted output by
supplying a regulated and continuous flow of material to the extrusion machine.
The top of the hopper is constructed with a large hole to make it simple to load the
raw material. It narrows to a smaller hole where it joins the feed throat, which
serves as the entrance to the extruder barrel. The hopper's shape and size can vary
depending on the specific requirements of the extrusion process and the
characteristics of the material being processed.
VII.
Thrust bearing
The thrust bearing's main objective is to withstand and control the axial forces
produced during the extrusion process. These forces are the consequence of the
pressure and resistance that the rotating screw must overcome as it advances the
material inside the extruder barrel. The screw's axial load is supported by the thrust
bearing, which enables the screw to revolve smoothly and keep its alignment within
the barrel. It aids in avoiding excessive wear and harm to the screw, barrel, and
gearbox, among other extruder parts. Typically, the thrust bearing is made as a
rolling-element bearing. Between the casing and the rotating portion of the
extruder, the rolling components are positioned to provide smooth rotation while
reducing wear. Ball thrust bearing and roller thrust bearing are the typical types of
thrust bearings used in extruders.
VIII.
Gear reducer
19
The gear reducer's primary function is to regulate and modify the extruder screw's
rotational speed and torque output. It provides the necessary power and torque for
plasticizing and forcing the material into the extruder barrel, enabling the
extruder to process materials efficiently. The gear reducer reduces speed by
utilizing a collection of gears in various sizes and arrangements. The ratio of the
motor speed to the speed of the extruder is known as the reduction ratio. The gear
reducer is made to improve torque while lowering speed since extruders often
need high torque and low rotating speeds. The gear reducer may employ spur
gears, helical gears, and planetary gears or a combination of these gears.
IX.
Motor
The motor's primary objective is to operate the extruder screw by converting
electrical energy into mechanical energy. It produces the rotating motion needed
to move the material within the extruder barrel and plasticize it.
Extruders can employ both AC (alternating current) and DC (direct current)
motors, among other types of motors.
2.2.4 Types of extrusion
The extrusion process involves subjecting raw materials to both high temperatures and
high pressures, causing them to undergo shear forces. This process leads to the
transformation of the solid substance into a molten state, accompanied by various
physicochemical changes. As the viscous substance moves through the system, it
experiences further alterations in its physicochemical properties before reaching its
ultimate form. These additional changes occur because of variations in temperature and
pressure within the extrudate system.
Extruded materials encompass a wide range of substances, including metals, polymers,
ceramics, concrete, modeling clay, and food items. The resulting products of the extrusion
process are commonly referred to as extrudates (Bouvier & Campanella, 2014).
2.2.4.1 Metal extrusion
Metal extrusion is a metal shaping technique that involves the application of force to push
metal or a workpiece through a die, reducing its cross-sectional area or giving it a desired
shape. This method finds extensive application in the manufacturing of pipes and steel
rods. Figure 2.1 illustrates the fundamental deformation concept of the extrusion process
and the tools utilized in extrusion, which include (1) the pressing stem, (2) the container
liner, (3) the container, (4) the dummy block, (5) the billet, (6) the extrusion, (7) the die
20
holder with the die, and (8) the die backer. The stem is a component that transmits the
main cylinder's power to the billet in the form of a column. Depending on the size of the
press, the stem must support a high pressure in order to work without bending or cracking
under high force. Before the metal billet is extruded, it is placed in a container or billet
sleeve, which has a protective lining within. It assists in preventing direct contact between
the container and the molten metal. This can lessen wear and tear brought on by the high
temperatures and pressures used in the extrusion process, which can avoid contamination
and increase the lifespan of the container. During the extrusion process, the metal billet is
held in a container. The metal billet, a cylindrical piece of metal, is positioned behind the
dummy block before the extrusion procedure starts. During the extrusion process, the
dummy block acts as a support and a barrier to stop the metal from flowing backward. A
cylindrical piece of metal known as a billet is used as the primary raw material in the
extrusion process. It is the initial substance that flows and deforms to take on the required
shape through the extrusion die. The die holder is a part that holds and supports the
extrusion die. It guarantees perfect alignment of the die throughout the extrusion process
and structural stability. The final extruded product's shape and dimensions are determined
by the extrusion die, it is made out of an aperture or hollow through which the metal flows
to take on the required profile (Guo & Yang, 2014).
Metal extrusion can be categorized into various types, depending on factors such as the
direction of extrusion flow, the force application medium, and the operating temperature.
These subdivisions include:
i.
Direct Extrusion
ii.
Indirect Extrusion
iii.
Hydrostatic Extrusion
iv.
Lateral or Vertical Extrusion
v.
Hot Extrusion
vi.
Cold Extrusion
vii.
Impact Extrusion
21
Figure 2.2: Schematic diagram of metal extrusion process
Source: (Guo & Yang, 2014)
Direct extrusion, also referred to as Forward Extrusion, starts with loading a heated
billet into a container within a press cavity, with a false block positioned behind it.
Subsequently, a mechanical or hydraulic ram forces the material through the die.
Figure 2.3: Direct extrusion
Source: (Engineering product design, 2019)
During the direct extrusion process, a portion of the extrusion load, which depends
on the billet's length, is employed to shear the inner materials away from the slowermoving peripheral region adjacent to the container wall. This action aims to
minimize friction between the billet and the wall, as the billet's surface slides along
the container wall. Frictional heat generation significantly impacts both the
extruding billet's temperature and the mechanical properties of the resulting extruded
products.When the materials tend to adhere to the container wall, the central region
22
of the billet flows more rapidly into the die than the periphery, primarily due to
friction. To mitigate this effect, molten glass or oil containing graphite particles can
be utilized as lubricants in direct extrusion. At higher temperatures, molten glass is
employed to reduce high friction, while at lower temperatures, lubricants containing
graphite powder are used to provide lubrication.
Indirect extrusion involves moving the die towards the billet inside the cavity using
a hydraulic ram located at the end of the device to force the material through the die.
Figure 2.4 illustrates this process. Due to the reduced friction on the billet caused by
the static billet container, this method requires less power. However, it becomes
challenging to control the extruded portion once it exits the die.
Figure 2.4: Indirect extrusion
Source: (Engineering product design, 2019)
Hydrostatic extrusion involves a chamber or cavity, smaller than the billet, which is
filled with hydraulic fluid to transfer force from the ram to the billet, as depicted in
figure 2.5. The pressure from the fluid applies triaxial forces, enhancing the billet's
formability. However, careful attention must be given to seal the fluid properly to
prevent leaks and minimize pressure-related issues. Despite the hydraulic fluid's
ability to reduce friction between the wall and billet, its use in the industry is limited
compared to other extrusion techniques due to the specialized equipment required,
lengthy setup process, and lower output rate.
23
Figure 2.5: Hydrostatic extrusion
Source: (Engineering product design, 2019)
Lateral extrusion: Lateral extrusion, often referred to as sideways extrusion or cross
extrusion, forces the material to flow perpendicular to the extrusion axis. Contrary
to conventional direct extrusion, which uses axial material flow, lateral extrusion
enables the production of intricate structures with characteristics that are difficult to
achieve using other extrusion techniques.
A metal billet is inserted into a container or die assembly for lateral extrusion that
contains an aperture or cavity with the necessary cross-sectional form. The material
flows sideways and fills the cavity as a result of a force that is provided perpendicular
to the extrusion direction.
Figure 2.6: Lateral extrusion
Source: (Engineering product design, 2019)
24
Impact extrusion is an alternative method for producing extruded shapes from
metals. Unlike traditional extrusion, which requires high temperatures to soften the
material, impact extrusion uses cold metal billets. This process employs high
efficiency and pressure to extrude these billets. In a standard impact extrusion
procedure, a lubricated slug is placed in a die cavity and struck once by a punch.
The punch creates a gap between itself and the die, causing the metal to flow
around the punch. Impact extrusion works well with somewhat softer materials like
lead, aluminum, or tin. There are three main categories of impact extrusion:
forward, backward, and mixed impact extrusions, as illustrated in figure 2.7.
Figure 2.7: Three types of impact extrusion
Source: (Guo & Yang, 2014)
2.2.4.2 Polymer Extrusion
A thermoplastic substance is homogeneously melted during the high-volume production
process of plastic extrusion. Pellets, powder, or granules might be produced from this
melted substance. The melted material then exits the shaping die hole with enough
pressure.
The shape of the die hole is imprinted on the molten plastic as it exits the shaping die
through the extruder. Many different items, including pipe/tubing, window frames,
weather stripping and wire insulation may be produced using this technology. The first
step in the plastic extrusion process is to add additives to the plastic substance. Colorants
or UV inhibitors might be used as additives, depending on the needs of the production
process. The next step involved in polymer extrusion is melting the plastic in the extruder’s
barrel. The temperature of the barrel is set as the melting point of the plastic to be extruded.
The molten material is forced through a die using a rotating screw. This causes molten
plastic to take a desired shape. The procedure then proceeds to cooling after going through
the die. Several cooling rolls or a water spray might do this. The goal of cooling is to
25
prevent any modification to the shape of the extruded plastic (Wayken rapid
manufacturing, 2022).
Types of polymer extrusion are tubing extrusion, blow-film extrusion, sheet film extrusion
and over-jacketing extrusion.
Tubing extrusion: At the die section, tubing extrusion is different from typical polymer
extrusion. When working with hollow objects and tubes, such as pipes and long tubes, this
method is perfect. Additionally, it is perfect for making medical tubing and drinking
straws. In tubing extrusion, a mandrel or pin is placed within the die, after which positive
pressure is applied to the interior cavities through the pin. Manufacturers insert more than
one pin at the die's center when there are several holes required. The intended number of
holes determines how many pins are needed. Additionally, the air pressure for the pins in
this situation often comes from a distinct source, which makes it simple to change the size
of each hole.
Blow-film extrusion: Blown-film extrusion is ideal for producing products like shopping
bags. The main distinction between blown-film extrusion and conventional
polymer extrusion is the die. An upright cylinder with a circular hole that can be anything
with 3-4 meter diameter is the blown-film extrusion die. To employ the molten plastic in
this procedure, a pair of nip rollers draw it up from the die. The nip rollers are frequently
between 4-20 meters away from the die and elevated above it. The quantity of cooling
required determines the precise height of the nip roll. The wall thickness or gauge of the
film is also determined by the nip rollers' speed.
Figure 2.8: Blow film extrusion
Source: (Wayken rapid manufacturing, 2022).
Sheet film extrusion: The main need for achieving the appropriate form in this extrusion
type is a pulling and rolling operation. This involves figuring out the sheet's thickness and
26
surface roughness. The product is given the proper form and is helped to cool and
permanently solidify during the rolling process. The difference between this procedure and
blow-film extrusion is how the required form is produced.
Over-jacketing extrusion: Making insulation wires is a perfect application for this kind of
plastic extrusion. For coating wires, pressure and jacketing are the two main extrusion
plastic tools. Both tooling kinds have their applications, but which one you choose to coat
wires with will depend on how closely the plastic material must adhere to the wire.
Pressure tooling is the best option when close contact or adhesion between the wire and
the material is required. But jacketing tooling is preferable if closeness and interaction are
unnecessary. The location of the pin in relation to the die is the main distinction between
different types of tooling.
2.3 Food Extrusion
Food extrusion is employed in the food industry to create a variety of food products with
a particular form, texture, and structure. In order to create continuous, uniform forms, it
entails carefully controlling the flow of a combination of components through a die. A
variety of foods, including snacks, breakfast cereals, pasta, and pet food, are produced via
food extrusion.
Piston and ram-type extruders for processing meats and sausages were the first extruders
used in the food industry. Piston extruders have not advanced much over the years,
although they are still helpful in some applications. To switch from the previous batch
process to a continuous one, pistons were replaced in the 1930s with a single screw. The
single screws were applied to pasta manufacturing and transformed the food sector with
the speed and usefulness a screw extruder offered. Twin-screw extruders were developed
later in the 1960s. Due to the greater possibilities of a twin-screw system, food extrusion
choices diversified, resulting in a wide range of innovative cereal and snack products in
the 1980s. Extruders of the present day are incredibly versatile and functional (Gu,
Kowalski, & Ganjyal, 2017).
Extruders are well-liked because they enable the production of a number of food products,
including pre-gelatinized flours, breakfast cereals, snacks, pet foods, and pellet products,
among others, in a quick and continuous manner. It is a system that integrates several unit
processes such as mixing, kneading, cooking, shaping, and cutting all into a single piece
of equipment. Due to this, the procedure is very straightforward, highly effective, and
inexpensive in comparison to other processing techniques.
27
Food ingredients are exposed to high shear, temperature, and pressure for a brief period of
time during extrusion. As a result, the ingredients are converted inside the extruder from a
solid
powder
state
to
a
melt
state. The
melted
components
subsequently
exit the extruder through the die to form a desired shape. A sudden reduction in pressure
causes a rapid expansion and a drop in temperature in the melt as it exits the extruder,
assisting in the transformation of the melt into a cooked product. Figure 2.9 shows a
schematic of the transformation.
Figure 2.9: Simple food extrusion process
Source: (Gu, Kowalski, & Ganjyal, 2017)
2.3.1 Instrumentation for extrusion processing
The food extruder's instrumentation plays a crucial role in measuring variables related to
the process and delivering precise and timely data to the operator. This information is
essential for making informed decisions about adjusting the process. Data provided by
instrumentation can either be basic i.e. temperature, pressure and speed, or advanced i.e.
specific energy input, and intensity of mix.
In order for operators to make well-informed decisions, it is crucial for instrumentation to
have sufficient precision, and consistency. Accuracy refers to the proximity of the
measured value to the actual value, while precision pertains to the consistency of
measurements taken at different instances. Ideally, both accuracy and precision should be
high. Nevertheless, in certain situations, achieving good precision becomes more crucial
than high accuracy, especially when making comparisons over time. If it is possible to
attain precise measurements at the expense of absolute accuracy, it is often preferred
(Strahm, 2020).
2.3.2 Measuring and controlling fundamental variables
The instrumentation utilized to measure critical variables serves as the basis for controlling
the food extrusion process, whether it's achieved manually at a basic level or through
28
advanced automation. These essential variables provide valuable information to the control
system, allowing them to make informed decisions regarding process control.
2.3.2.1Temperature
One of the main goals in food extrusion cooking processes is to raise the temperature of
the raw materials to achieve cookingThis temperature elevation is necessary for starch
cooking, protein denaturation and texturization, and reaching temperatures above 100°C
to induce the flash vaporization of water into steam, causing the product to expand upon
exiting the extruder die (Rangira, Gu, Ek, & Ganjya, 2020).
In the extrusion process, direct control of the extrudate temperature is not possible. Instead,
it is influenced by several factors, such as the input of mechanical energy, injection of
steam, and heating or cooling of the extruder barrel (Lipar, Noga, & Hulk, 2013). The
temperature of the extruder barrel sections does not directly impact the extrudate
temperature. However, it is crucial to precisely measure the temperature of the barrel
sections during process startup and to pre-heat the extruder using external heating. Cooling
of the entrance part of the extruder is also necessary during processing, particularly when
receiving hot material from a preconditioner, to prevent early steam generation and
blowback that may hinder material intake. Additionally, temperature measurement is
essential for this cooling procedure (Vera-Sorroche, et al., 2013).
Prior to initiating the material flow and generating heat through mechanical energy input,
it is advisable to pre-heat the extruder barrel and screws from room temperature to the
predetermined process temperature. It is essential to accurately measure the temperature
of the metal barrel sections to effectively control this pre-startup heating process.
Thermocouples (TC) or resistance thermometer detectors (RTD) are frequently used to
measure temperature in extruders. Thermocouples function based on the Seebeck effect,
generating a millivolt voltage proportional to the temperature at the junction of two
dissimilar metals. This millivolt signal is translated into temperature using suitable
equipment. On the other hand, resistance thermometer detectors (RTDs) utilize materials
with electrical resistance varying with temperature. The resistance is measured and
converted to temperature through the appropriate equipment.
Thermocouples have a broader temperature range and are more cost-effective, although
they offer lower precision. RTDs, in contrast, are more accurate but come with a higher
price tag. Both technologies can be utilized in food extruders.
29
Infra-red (IR) sensors is an alternative method for temperature measurement in extruders,
relying on the detection of IR radiation, which correlates with temperature. However, the
effectiveness of IR sensors is contingent upon the melt's emissivity and the depth of
penetration, which, in turn, relies on the clarity of the melt. In the majority of food
extrusion processes, the melt clarity is low, limiting the advantages of using IR sensors
over traditional melt-bolt temperature probes for production extrusion. Consequently, IR
sensors are not extensively employed in this context (Leonard, Zhang, Ying, & Fang,
2020).
2.3.2.2 Pressure
In most food extrusion processes, the maximum process pressure is observed at the
discharge end of the extruder screws. The pressure can vary depending on the specific
process and the type of product being produced, ranging from negligible to as high as
17,000 kN/m2. Higher pressure results in a more significant transfer of mechanical energy
into the extrudate, while lower pressure leads to a lesser transfer of mechanical energy.
This is due to the extrusion process being responsive to the pressure at the screw's end
(Strahm, 2020).
Maintaining a stable pressure at the end of the screw is a crucial indicator of process
stability and steady-state conditions. Properly containing the high pressure within the
extruder is essential, and this responsibility falls on the extruder die and the attachment
mechanism between the die and the extruder discharge. Additionally, the high end pressure
of the extruder screws exerts a force that pushes the screw back toward the gearbox,
generating a thrust load that requires robust bearings in the extruder gearbox to counteract
it. If the pressure exceeds the extruder's design limits, it can overload the gearbox or the
die, leading to potential mechanical failures that may occur suddenly or gradually. To
monitor pressure during the extrusion process, a pressure gauge is often attached to an
entrance in the extruder or die. This gauge may be a manual bourdon-tube pressure gauge
or an electronic sensor that utilizes strain gauges for electronic force measurement.
However, due to the hot, sticky, and abrasive nature of the materials used in extruders, it
is often challenging to directly transfer pressure from the material to the pressure
measuring instrument. In such cases, finding a suitable method to transfer pressure
becomes crucial as using traditional bourdon tube pressure gauges may lead to clogging
and damage, while delicate electronics of strain gauge measurement devices could be
compromised. (Scherschligt, Olson, Driver, & Yang, 2016).
30
A method for transferring pressure that entails attaching a thin metal diaphragm to the end
of a tube that makes contact with the extrudate. A rod or fluid column is then forced by
the diaphragm, effectively communicating the pressure to a strain gauge that is placed far
from the extrudate. The strain gauge sensor is positioned at the top of the column, and it
receives the pressure acting on the diaphragm as it travels up the stem. As long as the
diaphragm is still in place, this approach has the benefit of a totally sealed pressure sensor.
However, with systems that use a rod, the rod's length extends and contracts in response
to temperature changes, which may affect how accurate these devices are. Furthermore, in
both types of devices, the diaphragm located at the end of the tube that makes contact with
the extrudate is susceptible to abrasion and wear, which can diminish the lifespan of the
costly sensor.
Another often used technique in food extrusion systems involves employing a grease-filled
tube (known as a grease stem) to convey the extruder's internal pressure to the
measurement tool. By pumping additional grease through a grease fitting placed close to
the sensor, this design also enables the elimination of any extrudate that might enter into
the stem. It is expected that with this system, during processing, some grease will leak
from the stem and mix with the extrudate. A food-grade grease that is suitable for
accidental contact with food is used to assure food safety. However, it's crucial to
remember that there is very little fat that might really contact the food.
2.3.2.3 Speed
To effectively monitor and control a food extrusion system, precise measurement of
rotational speed is vital. These measurements are typically conducted on various
components, including screw feeders, preconditioner shafts, rotary cutters, and the
extruder screw itself, as they directly influence the final product. Modern extrusion
systems often employ an alternating current (AC) induction motor, which can be powered
by three phases of electricity, to provide rotational motion. The frequency of the alternating
current supplied to the motor is directly proportional to its rotational speed (Ekielski,
Żelaziński, & Durczak, 2017).
Modern food extrusion systems utilize a variable frequency drive (VFD) along with a
three-phase AC motor to control the rotating speed. Typically, the motor is connected to a
gearbox to achieve speed reduction, which drives the shafts of various components such
as the screw feeder, preconditioner, extruder, or cutter. The VFD serves as an electrical
device that converts the incoming electricity into AC three-phase power with a variable
31
frequency, which is then supplied to the motor. The rotational speed of an AC motor is
determined by the frequency of the output power it receives. The VFD readily provides an
instrumentation signal closely related to its frequency output, which can be used to obtain
a signal indicative of the rotational speed. This signal can be suitably scaled to represent
the velocity of the rotating shaft.
In some cases, variable speed rotating devices may not utilize the VFD system, opting
instead for a mechanical variable speed mechanism, which requires a different method to
determine rotational speed. In such situations, a small generator tachometer powered by
the rotating shaft can be employed. This tachometer generates a voltage proportional to
the rotational speed, providing a speed signal that can be used for metering or control
purposes. Even in systems with simple manual controls, a handheld tachometer can be
used to assess speed. To operate this handheld instrument, the tachometer shaft can be
placed against the end of a shaft, or it can use non-contact detection of a reflective strip of
self-adhesive tape affixed to the shaft. (Strahm, 2020).
2.3.3 Measurement of extrudate product variables
The preceding section highlighted the significance of monitoring and managing the inputs
of the extrusion system, such as process temperature and pressure. However, it is equally
important to consider the characteristics of the final product. This aspect presents a
promising opportunity for optimizing food extrusion. This section focuses on the
properties of extrudate products, as well as the methods used for their measurement.
Measurements can be performed either at the line or in line. At-line measurements involve
sampling the product, either through automated or manual methods, and then conducting
the examination on samples. In contrast, in-line measurements examine the product stream
as it flows past a sensor, without changing or interrupting the product flow.
2.3.3.1 Expansion ratio
The increase in volume or size of a material during the extrusion process is referred to as
the expansion ratio of an extrudate. The ratio of the extrudate's final cross-sectional area
or diameter to its beginning cross-sectional area or diameter is a common way to express
it. The qualities of the material being extruded, the extrusion process parameters, and the
extrusion die design all affect the expansion ratio. Different expansion ratios may be the
result of various materials and processing methods. For instance, the expansion ratio is a
crucial factor in foam extrusion since it affects the product's density and cellular structure.
32
Generally speaking, lower densities and larger cell sizes are produced by higher expansion
ratios while lower expansion ratios lead to higher densities and smaller cell sizes.
Expansion ratio is calculated as the ratio of the extruded product diameter to the opening
diameter of the die. A vernier caliper is typically used to find diameter of the extrudate
(Singh, Majumdar, & Venkateshwarlu, 2012).
Expansion ratio =
Extruded product diameter
Die diameter
2.3.3.2 Bulk density
The bulk density of an extrudate refers to the mass of a material per unit volume, including
both the solid material and any void spaces within it. It is a measure of how tightly the
particles of the extrudate are packed together. The degree of cooking, texture, and
eventually how it fills the final package are all closely related to other crucial features of
items made through the food extrusion process. Although there are several automated
technologies for measuring bulk density, this measurement is often done manually. Both
methods would qualify as at-line measurements (Strahm, 2020).
When measuring bulk density using manual systems, the sample is placed in a container
with a known volume, and the mass of the material inside is calculated. The container
needs to have the right size for the product being produced, ideally at a size that makes it
simple to convert between using bulk density units. More often than not, volume of a
known mass of extrudate is calculated by measuring the dimension of the extruded
products using a vernier caliper (Sahua, Patel, & Tripathi, 2022).
Bulk density is then given as
Bulk density =
4 × mass of extrudate
π × (extrudate diameter)! × extrudate length
2.3.3.3 Hardness
The hardness of an extrudate refers to its resistance to deformation or indentation. It is a
measure of the extrudate's mechanical strength or rigidity. Hardness can be influenced by
various factors, including the composition of the material, processing conditions, and any
post-processing treatments.
There are different methods to measure the hardness of an extrudate, and the choice of
method depends on the specific material and its properties. Here are two commonly used
methods:
33
i.
Shore Hardness: This method is commonly used for elastomeric materials. It
measures the resistance of the extrudate to indentation using a durometer. The
Shore hardness is expressed as a numerical value on different scales, such as Shore
A, Shore D, etc. The higher the Shore hardness value, the harder the material.
ii.
Rockwell Hardness: This method is widely used for metals and other rigid
materials. It measures the depth of penetration of an indenter under a specific load.
The Rockwell hardness is expressed as a numerical value followed by a scale
indicator, such as HRC (Rockwell C scale) or HRB (Rockwell B scale). Higher
Rockwell hardness values indicate greater hardness.
2.3.3.4 Water adsorption index and water solubility index
Water solubility index calculates a substance's capacity to dissolve in water. It often takes
the form of a percentage and describes how much of a material can dissolve in water under
certain conditions. The more soluble a compound is in water, the higher the WSI value.
The amount of soluble components released from a substance following extrusion is
measured by the water solubility index, which is frequently employed as a gauge for
molecular component degradation. Extruded products frequently swell when combined
with water, some of which will dissolve. Water solubility measures how many tiny
molecules are dissolved in water to prevent molecular damage, whereas water absorption
index measures how much water is immobilized by the extrudate. Water adsorption index
measures the ability of a substance to retain water. It is a measure of the capacity of the
ingredient to attract and retain water molecules. The WAI is typically expressed as a
percentage and indicates the amount of water absorbed by the substance relative to its
initial weight.
To calculate water adsorption index, centrifuge, evaporating dish and weighing balance
were obtained. Some of the extruded wheat flour from the first run was collected and
crushed. The crushed extrudate was sieved with a 60-mesh sieve. 2.5 gram of the sieved
extrudate was taken and suspended in 30 ml of water at 30℃ in a centrifuge tube. The
suspended extrudate was stirred intermittently for about 5-30 minutes until the extrudate
dissolved. Next, centrifugation was performed by placing the centrifuge tube in the
centrifuge and spinning it at 3000 rpm for 15 minutes. Once the centrifugation process was
complete, the supernatant liquor was carefully poured into a pre-weighed evaporating dish.
The remaining gel was then weighed, and the water absorption index was calculated based
on its weight.
34
WAI (g/g) =
!"#$%& () *"+#,"-&*
2.1
!"#$%& () +./ *(0#+
Water solubility index was calculated from the dissolved extrudate in the supernatant
liquor. The amount of dried solids recovered by evaporating the supernatant was measured.
Water solubility index was given as
WSI (%) =
!"#$%& () +#**(01"+ *(0#+* #- *23".-4&4-&
2.2
!"#$%& () +./ *(0#+
2.4 Effects of Extrusion Parameters on Extrudate variables
Extrusion process is fundamentally a straightforward technological procedure,
however, quality control of extrudate is challenging because it is influenced by specific
process variables. The system's independent and dependent factors influence the
extrudate's quality. The independent variables are controllable and include amount of
moisture in the feed, screw speed, and temperature in the extruder's barrel. The dependent
variables are those whose value depends on how much an independent variable is present.
These include extrudate characteristics like viscosity, flow rate, residence time, and
product color, as well as others like water absorption index, expansion index, and density
(Ruiz-Gutiérrez, Sánchez-Madrigal, & Quintero-Ramos, 2017).
Small variations in these factors can have a big impact on the final product's qualities and
features. Temperature, screw speed, and moisture content have the most influence on
extrusion operations. Moisture content of the mixes affects the physical qualities of
extrudates or energy consumption by influencing factors like viscosity of the melt fluid,
residence time of the material in the extruder, and shear stress given to the meal. The
mixture's moisture content and extrusion temperature also affect expansion index
of extrudate. Extrudates expand more readily at low temperatures as feed moisture content
rises. Nevertheless, even with high moisture content, a rise in temperature limits the
expansion.
2.4.1 Bulk density
Bulk density refers to the mass of a bulk material divided by its volume. It is a measure of
how densely packed or compacted a material is when it is in a bulk or loose state, rather
than in a confined or compacted form. Bulk density is typically expressed in units of mass
per unit volume, such as kilograms per cubic meter (kg/m³) or pounds per cubic foot
35
(lb/ft³). The feed moisture has the biggest impact on the extrudate density. The density of
the extrudate is also significantly influenced by screw speed and temperature. The
extrudate density may significantly increase as feed moisture increases. However, greater
barrel and screw temperatures result in a modest reduction in extrudate density.
Studies by Sahua, Patel, & Tripathi, (2022) showed the effect of temperature, screw speed
and feed moisture on physical and functional quality of soy protein enriched maize. Their
study developed a regression equation that predicted the effect of temperature, screw speed
and feed moisture on bulk density of the extrudate. The coefficient of the feed moisture in
the regression equation was found to be positive while the other variables had negative
coefficients. This indicates that an increase in feed moisture yields a corresponding
increase in the extrudate’s bulk density. A possible justification for this phenomenon is
that during extrusion cooking, increasing moisture availability causes variations in the
molecular structure of starch, which reduces the melt's elasticity and, in turn, the melt's
capability for puffing or expanding. As temperature rises, moisture evaporates more
quickly during the extrusion process, consequently reducing moisture availability and bulk
density. Reduction in bulk density as temperature rises can further be attributed to greater
difference in vapour pressure between the water vapour pressure within the extruder and
the ambient pressure at the die's exit point. Difference in vapour pressure causes the liquid
to evaporate more. Additionally, the increased screw speed tends to decrease the melt
viscosity of the mixture, which in turn enhances the dough's elasticity and lowers extrudate
density. Studies by Hoyos-Concha, Villada-Castillo, Roa-Acosta, Fernández-Quintero, &
Ortega-Toro, (2023) also show that feed moisture significantly affects density of extrudate.
As feed moisture increase with constant temperature, density of the product increases
consequently.
2.4.2 Expansion
Products that have been cooled and are dimensionally stable can be characterized
by expansion. Both the growth of the extrudate to its greatest size and its subsequent
shrinking are used to calculate the expansion parameters. An essential characteristic of the
food extrusion cooking process is extrudate expansion. It is useful for describing product
quality and is connected to cook level. The product's precise extrudate expansion
determines how acceptable it is. Thus, for the extrusion cooking process, an understanding
of how process factors affect extrudate expansion is essential.
36
Study by Sahua et al., (2022) showed that temperature, screw speed and feed moisture
content affect expansion ratio at 0.1% level. The study showed that temperature and screw
speed significantly affect the expansion ratio of the extrudate product whereas feed
moisture content affected expansion ratio insignificantly. A regression equation for the
effect of the process variables was developed in the study. The model showed that barrel
temperature had the highest positive coefficient followed by screw speed. This means
barrel temperature positively affects expansion ratio to a higher degree compared to screw
speed. Increased bubble production when water is heated and screw speed is increased is
what's responsible for the rise in expansion ratio. In a sense, the bubble that develops
during extrusion serves as a blueprint for the cellular structure. In order to fill the space
left by the expanding material around the bubble, an enlarged extrudate is produced. While
the negative coefficient of feed moisture shows that a less expansive extruded product was
created when feed moisture was higher. Due to the material's decreased elasticity at higher
moisture levels and lower gelatinization, bubble formation and stability were negatively
impacted.
2.4.3 Hardness
An extrudate's resistance to deformation is referred to as hardness. It gauges the extrudate's
tensile strength and is impacted by a number of variables, including the material's
composition, the processing environment, and the extrusion die's shape. Typically,
hardness testing techniques like the Shore durometer test or the Rockwell hardness test are
used to assess the hardness of an extrudate. In these tests, the extrudate's surface is
subjected to a known force and the resulting indentation's depth or size is measured. Study
by Seth, Badwaik, & Ganapathy, (2013) showed that barrel temperature, screw speed and
feed moisture content all affect the extrudate’s hardness to a high degree. A regression
equation was developed to show how each factor affects hardness. The regression equation
had a high determination coefficient of R2 = 0.92 which suggests the equation’s prediction
on how each variable affects hardness is quite adequate. From the regression equation,
feed moisture content had a high positive coefficient. Consequently, increased moisture
content in feed yields increased hardness. As the feed moisture increases, it becomes
evident that the plasticization of the melt leads to reduced elasticity of the extrudate and
an increase in its compact or less porous structure. Consequently, this diminishes the
gelatinization of starch, negatively affecting product expansion and moisture retention. On
the other hand, the negative correlation between barrel temperature and screw speed and
37
hardness indicates that both factors have an adverse effect. This is likely due to a reduction
in melt viscosity and the generation of superheated steam with increasing temperature and
screw speed. As a result, more bubbles are formed, leading to a more porous extrudate.
This phenomenon is corroborated in the study by Sahua et al., (2022) on the effect of
independent variables on extrudate characteristics of yam like snack food, their
investigation showed that as feed moisture content is increased, hardness of extrudate
increases while as barrel temperature increases, hardness decreases.
2.4.4 Water adsorption index (WAI) and water solubility index (WSI)
Water solubility index calculates a substance's capacity to dissolve in water. It often takes
the form of a percentage and describes how much of a material can dissolve in water under
certain conditions. The more soluble a compound is in water, the higher the WSI value.
The amount of soluble components released from a substance following extrusion is
measured by the water solubility index, which is frequently employed as a gauge for
molecular component degradation. Extruded products frequently swell when combined
with water, some of which will dissolve. Water solubility measures how many tiny
molecules are dissolved in water to prevent molecular damage, whereas water absorption
index measures how much water is immobilized by the extrudate. Water adsorption index
measures the ability of a substance to retain water. It is a measure of the capacity of the
ingredient to attract and retain water molecules. The WAI is typically expressed as a
percentage and indicates the amount of water absorbed by the substance relative to its
initial weight.
Study by Sahua et al., (2022) measured the effect of screw speed, temperature and feed
moisture content on water adsorption index and water solubility index of soy protein
enriched extruded maize snack. A measured mass of ground extruded maize snack was
taken and suspended in water at 30℃ in a centrifuge. The samples were centrifuged at
3000 rpm for 10 minutes. Water solubility index was calculated from the supernatant liquid
and water adsorption index from residual gel.
Investigations by Seth, Badwaik, & Ganapathy, (2013) developed a second order
regression equation to determine the effect of screw speed, temperature and feed moisture
content on water adsorption index of the extrudate material. The regression equation had
a high coefficient of determination (R2 = 0.90) which indicates close adequacy. From the
regression equation, it is determined that feed moisture content had the greatest positive
impact on water adsorption index followed by screw speed. Increase in water adsorption
38
index as feed moisture content increases is attributed to decrease in melt viscosity of starch
as moisture content increases. Increase in melt viscosity enhances movement of molecules
in the extrudate which consequently causes a greater penetration of heat and ultimately
increased gelatinization. Screw speed positively affect gelatinization because as screw
speed increases, shearing action also increases and this ultimately enhances gelatinization.
However, the effect of screw speed is insignificant compared to that of feed moisture
content. Similar effect of screw speed and feed moisture content was reported by Sahua et
al., (2022). Barrel temperature unlike other studied parameters had a negative effect on
water adsorption index showing that WAI decreased with the increase in barrel
temperature. This phenomenon was attributed to a possible degradation of starch
component of the extruded snack. Similar result was also reported by Wani & Kumar,
(2016).
Study by Sahua et al., (2022) also developed a second order regression equation to
determine the effect of screw speed, temperature and feed moisture content on water
solubility index of the extrudate material. The regression equation had a high coefficient
of determination (R2 = 0.82) which indicates close correlation. Based on the regression
equation, it was found that screw speed had the most significant positive influence on the
water adsorption index, followed by barrel temperature. However, the feed moisture
content had a negative impact on the water solubility index. The increase in specific
mechanical energy due to higher screw speed during extrusion leads to excessive shearing
of the melt. This excessive shearing causes the degradation of macromolecules and results
in a decrease in the molecular mass of starch particles. As a result, the surface area of the
starch particles increases, thus exposing more hydrophilic sites. The increased surface area
and exposure of hydrophilic sites enable better interaction between starch and water
molecules. Also, at higher temperature, macromolecules of starch degrade during
extrusion causing increased water solubility index. Sahua et al., (2022) study further
indicates water solubility index increases initially with feed moisture content, however,
further rise in moisture content of the feed decreases the WSI. Kothakota, Jindal, &
Thimmaiah, (2013) found that the effect of feed moisture on WSI was die to appropriate
gelatinization and reduced tangential expansion owing to melt plasticization respectively.
2.5 Optimization of Food Extrusion Process
The construction and improvement of production processes for various products are
included in process design and optimization.
39
The main goal in process design is to create a safe, affordable process that can reliably
generate high-quality products with a sizable yield. Optimization however, entails
analyzing and improving current processes to raise their effectiveness, economy, and
environmental sustainability.
Process optimization is the methodical approach of enhancing a process to efficiently and
effectively achieve desired results. It entails locating, evaluating, and changing different
characteristics or elements inside a process in order to maximize output, cut costs,
eradicate errors, or improve overall performance (Magnússon, Al, & Sin, 2020).
The process optimization methodology typically involves the following steps:
1. Objectives: Declare in detail the aims and goals of the process optimization
endeavor. This can entail enhancing quality, speeding up the process, or
minimizing waste.
2. Process variables: Determine the essential elements or variables that have a major
influence on the process's result. These characteristics might have to do with raw
ingredients, operational practices, or equipment settings.
3. Design experiments: Create tests to gather information on how the process
performs in various environments or circumstances. To effectively investigate the
parameter space, experimental design techniques like factorial designs or response
surface methods may be used.
4. Collect and analyze data: Conduct the experiments and collect data on the process
output/response. Perform statistical analysis to understand the relationships
between the process parameters and the desired outcome. Tools like regression
analysis, ANOVA (Analysis of Variance), or statistical software packages can aid
in data analysis.
5. Develop statistical models: Develop mathematical or statistical models that
represent the relationship between the process parameters and the response. These
models can be used to predict and optimize the process performance.
6. Process optimization: Utilize optimization algorithms and techniques to find the
best combination of process parameters that maximize the desired outcome or
minimize the cost. Optimization methods such as gradient-based algorithms,
genetic algorithms, or response surface optimization can be employed.
7. Validate and Implement: Validate the optimized process settings through further
experimentation or pilot studies. Implement the optimized process in the actual
production environment and continuously monitor its performance.
40
8. Continuous Improvement: Establish a process monitoring system and regularly
review the process performance to identify further improvement opportunities.
This involves ongoing measurement, analysis, and adjustment of process
parameters to maintain or enhance the optimized process.
2.5.1 Optimization using response surface
Response Surface Methodology (RSM), when two or more quantitative components are
present, is a strategy to maximize the response(s). In the response surface methodology,
the independent variables or factors are commonly referred to as the predictor variables,
while the dependent variables are known as responses.
RSM offers improved process optimization and result reproducibility together with a clear
perspective for developing predictive models. Response surfaces are a type of graphical
representation used in RSM to explain the combined impact or influence of two or more
factors on the response or outcome of a process. The interactive effect process focuses on
studying the interactions among the factors and their impact on the response variable. The
two main factorial designs used to evaluate the quadratic response surface are the Central
Composite Design (CCD) and the Box-Behnken Design (BBD) (Kumari & Gupta, 2019).
2.5.2 Composite design (CCD)
For modeling and process optimization, Central Composite Designs (CCD) are especially
helpful when there are continuous or categorical input variables (factors) and a continuous
response variable (Beg & Rahman, 2021).
To effectively explore the factor space and determine the curvature of the response surface,
CCD designs combine factorial designs with center points and axial points. Three different
point kinds are used in the design:
1. Multifactor Points: The calculation of main effects and two-factor interactions is
possible using these points, which are produced from a factorial design. They stand
for different assemblages of factor levels.
2. Center Points: The replicated measurements at the factor space's center are known
as center points. They assist evaluate the model's poor fit and offer an estimate of
the pure error.
3. Axial Points: Axial points are additional runs performed at the factor's extreme
levels, typically at a distance that is ±𝛼 times the standard deviation from the
center point. In addition to capturing any nonlinearity in the relationship between
41
the components and the response, they also aid in estimating the curvature of the
response surface.
The positioning of these dots in a CCD is determined by the level of precision that is
wanted as well as a variety of other parameters. Because the design is rotatable, the same
statistical properties can be obtained regardless of how it is oriented. Second-order
response surface models can be fitted with CCD designs to help with process optimization
by discovering the best factor values to maximize the response variable. The primary
impacts, interactions, and curvature of the response surface can all be better understood
with the help of the models
2.5.3 Box-Behnken design (BBD)
Box-Behnken Design (BBD) is form of design employed in RSM to investigate and model
the relationship between input factors and a response variable. When there are only a few
elements to be explored, BBD designs are especially helpful.
In contrast to Central Composite Designs (CCD), BBD designs are based on a three-level
factorial design and do not have axial or center points. The three-level factorial design is
made up of various combinations of factor levels. Usually, the factors are adjusted to low
(-1), medium (0), and high (+1) values. A balanced and effective experimental design is
maintained while ensuring that the factors are explored at various depths.
The main attributes of Box-Behnken Designs are as follows:
1. Reduced Number of Runs: When compared to CCD designs, BBD designs require
fewer experimental runs. The quantity of factors under investigation determines
the number of runs.
2. Efficiency in Estimating Main Effects and Two-Factor Interactions: BBD designs
are effective at determining the main effects of factors and the interactions between
two factors, enabling a more in-depth examination of these effects.
3. Inability to Rotate: Unlike CCD designs, Box-Behnken Designs are not rotatable
by nature. They are made to be roughly rotatable, though, within a specific area of
the experimental space.
By determining the factor values that maximize or minimize the response variable, BBD
designs are frequently used for fitting second-order response surface models and process
optimization. The design allows for efficient exploration of the factor space and estimation
of the response surface curvature.
42
2.6 Review of Past Works
Investigating the impacts of extrusion process parameters on the physical and functional
properties of extruded food products holds significant importance. This research provides
valuable insights and expertise regarding process optimization, resource efficiency, and
waste reduction. By systematically analyzing and adjusting factors like temperature, feed
moisture content, and extruder screw speed, one can determine the ideal conditions that
result in the desired product characteristics. This optimization process can lead to enhanced
production efficiency, reduced energy consumption, and minimized waste generation,
aligning with the goals of SDG 9: Industry, Innovation, and Infrastructure. Numerous
studies have been conducted on this subject, and below are some of the relevant studies
that are highlighted in this project.
Ratankumar, Ranendra, & Venkateshwarlu (2014) established the impact of extruder
parameters and feed composition on the expansion ratio and bulk density of the fish cereal
extrudates. They utilized RSM in this study. They found that change in barrel temperature,
screw speed, moisture and fish flour had significant effect on the expansion ratio and bulk
density of extruded fish cereal. However, their study did not consider the effect of
extrusion parameters on water adsorption index and water solubility index of the extrudate
product.
Dibyakanta Laxmikant & Vijayalakshmi (2013) extruded yam-based snack food to
determine influence of extruder parameters and feed moisture content on extrudate
characteristics. They determined how the extrusion parameters affected expansion ratio,
water adsorption index, water solubility index and hardness of the extrudate products. In
their study, they did not consider the effect of using a single screw extruder and change in
screw speed on the response variables (water adsorption index, water solubility index and
softening time) of extrudates.
Yogesh and Laxmi (2013) determined effect of feed moisture, die temperature and screw
speed on physicochemical properties of extruded pregelatinized rice flour. They
discovered that higher temperature decreased expansion ratio while increasing extrudate
density and WSI. Increased feed moisture content produced extrudates with lower
expansion ratio and water adsorption index but higher bulk density, water adsorption
index, and hardness. Extrudates' expansion and hardness were found to be unaffected by
screw speed, but it was determined that increasing screw speed increased the extrudates'
water adsorption index.
43
CHAPTER THREE
METHODOLGY
3.1 Materials
1. Wheat flour
Plate 3.1: Wheat flour
3.2 Equipment and Apparatus
3.2.1 Equipment
i.
Single screw extruder
ii.
Electronic Weighing Balance (HH-12/XMTE-205)
iii.
Digital Photo Contact Tachometer (DT6235B)
iv.
Digital stopwatch (Samsung S6 SM-T865)
v.
Centrifuge (PRP Centrifuge LC-04C Plus)
vi.
Air oven (Scientific Japan, hot air oven, 300℃ maximum)
44
Plate 3.3: Weighing balance
Plate 3.2: Centrifuge
Plate 3.4: Single screw extruder
45
Plate 3.5: Measuring cylinder
Plate 3.6: Spatula
Plate 3.7: Mortar and pestle
46
3.2.2 Apparatus
i.
Spatula (1)
ii.
Beaker 500 ml (3)
iii.
Measuring cylinder 500 ml (2)
iv.
Mortar and pestle
v.
Vernier calliper
3.3 Procedure
3.3.1 Changes to the existing single screw extruder
The two significant changes to the existing single screw extruder design were changes to
the the heating elements and welding of the thrust bearing.
Three heating elements were changed from 800 W (3) to 1500 W (3) to increase the
attainable temperature of the extruder. Due to the short barrel length, increasing the speed
without increasing the temperature will not give the wheat flour sufficient time to melt.
Thus, the heating capacity of the extruder machine also needed to be improved. Installation
of heating elements allows us to measure the effect of temperature change on extrudate
properties.
The thrust bearing of the extruder was reinforced by welding. The thrust bearing's main
objective is to withstand and control the axial forces produced during the extrusion
process. These forces are the consequence of the pressure and resistance that the rotating
screw must overcome as it advances the material inside the extruder barrel. The screw's
axial load is supported by the thrust bearing, which enables the screw to revolve smoothly
and keep its alignment within the barrel. It aids in avoiding excessive wear and harm to
the screw, barrel, and gearbox, among other extruder parts. Typically, the thrust bearing is
made as a rolling-element bearing. Between the casing and the rotating portion of the
extruder, the rolling components are positioned to provide smooth rotation while reducing
wear.
3.3.2 Design of experiment
Minitab Statistical Software (Version 20.3) was used to carry out the design of experiment.
A Multilevel Factorial Design was created with three factors: Extruder Temperature,
Screw Speed and moisture content. The software determined that twelve (12) runs of the
experiment needed to be performed to accomplish the design objectives.
47
3.3.3 Extrusion process
The extrusion process is described as follows with each sentence representing a step in the
process. 250g of wheat flour feed sample was measured using the weighing balance. 107ml
of water was added to measured wheat flour to obtain a moisture content of 27% using
equation 3.1.
Moisture content (%) =
!"#$%& () *(#+&,-"
(!"& /"#$%& () *0&"-#01)
3.1
The extrusion machine was turned on, the heating elements were switched on, and the
thermostat was set to 40℃, with the analogue reader displaying the instantaneous heating
temperature applied to the barrel via the heating elements.
While the barrel was being heated up, the screw speed was set to 60 rpm by varying the
gear of the electric motor and measuring the speed of the larger sprocket gear using the
tachometer. When the thermostat read 40℃ the feed sample was systematically fed into
the hopper. The rotation of the screw conveyed the wet wheat flour along the barrel.
Extrudate rate was calculated using equation 3.2. It is given as the mass of extruded wheat
flour divided by time taken for extrudate to leave the extruder.
Extrusion rate =
,4** (2&
3.2
&#," &45"- )(. "6&.2+4&" &( "6#& "6&.2+".
The extruded wheat flour was dried at 100℃ in a dryer until constant mass was attained.
The final weight of the extruded wheat flour was measured and recorded.
Twelve runs were carried out by varying screw speed (60-80 rpm), extrusion temperature
(40-80℃), and feed moisture content (27-33.33 %). Details of the runs were generated
using multilevel factorial design on Minitab software and they are given in the table 3.1
below. On completion of the runs, the motor was powered down, the heating elements
were switched off, and the extrusion machine was turned off.
48
Table 3.1: Design of experiment
Runs
Temperature
(℃)
Screw Speed
(rpm)
Feed moisture content
(moisture/wet feed)
1
40
60
0.27
2
80
60
0.3333
3
80
80
0.27
4
60
80
0.27
5
40
60
0.3333
6
80
80
0.3333
7
60
60
0.3333
8
60
60
0.27
9
40
80
0.27
10
80
60
0.27
11
60
80
0.3333
12
40
80
0.3333
3.3.4 Bulk density test
To carry out the density test a vernier caliper, beaker and weighing balance were obtained.
Some of the extruded wheat flour from the first run was collected and divided into three
parts. The weights of three beakers were measured and recorded using the electronic
weighing scale. The samples were placed into the respective beakers, and the weights of
the samples and the beakers were measured and recorded.
Diameter of each extrudate sample was taken using a vernier caliper and their respective
length were measured and recorded. (Sahua, Patel, & Tripathi, 2022).
Bulk density was calculated using equation 3.3
Bulk density =
4 × mass of extrudate
π × (extrudate diameter)! × extrudate length
49
3.3
3.3.5 Water adsorption index (WAI) and water solubility index (WSI)
To calculate water adsorption index, centrifuge, evaporating dish and weighing balance
were obtained. Some of the extruded wheat flour from the first run was collected and
crushed. The crushed extrudate was sieved with a 60-mesh sieve. 2.5 gram of the sieved
extrudate was taken and suspended in 30 ml of water at 30℃ in a centrifuge tube. The
suspended extrudate was stirred intermittently for about 5-30 minutes until the extrudate
dissolved. Centrifugation was performed by centrifuge at 3000 rpm for 15 min.
After centrifugation was complete, the supernatant liquor was poured carefully into a tared
evaporating dish. The remaining gel was weighed water absorption index calculated from
equation 3.4
WAI (g/g) =
!"#$%& () *"+#,"-&*
3.4
!"#$%& () +./ *(0#+
Water solubility index was calculated from the dissolved extrudate in the supernatant
liquor. The amount of dried solids recovered by evaporating the supernatant was measured.
Water solubility index was calculated using equation 3.5
WSI (%) =
!"#$%& () +#**(01"+ *(0#+* #- *23".-4&4-&
3.5
!"#$%& () +./ *(0#+
3.3.6 Softening time
Softening time is calculated as the time taken to for extruded flour to soften in hot water.
In this experiment softening time of extruded product was found in 60℃, 80℃ and 100℃
water.
3.3.7 Response models and optimization
Values for all the response variables were recorded. The response data was used to
generate surface models on Minitab software. Response variables were optimized using
response optimizer feature in Minitab. It was indicated in the response optimizer what
response variables to minimize and maximize. Water absorption index and extrusion rate
were maximized while bulk density, softening time, and water solubility index were
minimized
3.4 Precaution Taken
i.
Extruder was properly insulated to avoid energy waste
ii.
Gloves were worn when collecting the hot extruded wheat flour from the extruder
and dryer.
50
iii.
Parallax error and zero error were avoided in reading the beakers and measuring
cylinders
iv.
All equipment was turned off after use
v.
All apparatus was washed and cleaned before and after use.
51
CHAPTER FOUR
RESULTS AND DISCUSSION
4.1 Results
Table 4.1: Values of multi-level independent variables
Parameters
Values
Moisture content, % (MC)
27
30
Screw speed, rpm (SS)
60
80
Extrusion temperature, ℃ (ET)
40
60
52
33
Table 4.2: Values of response variables
Run
order
MC
(%)
SS
(rpm)
ET
(℃)
Extrusion rate
(g/s)
Bulk density WAI
(g/cm3)
(g/g)
WSI (%)
Softening
time at 60℃
(min)
Softening
Softening
time at 80℃ time at 90℃
(min)
(min)
1
2
3
4
5
6
7
8
9
10
11
12
Average
27
27
27
27
30
30
30
30
33
33
33
33
30
60
60
80
80
60
60
80
80
60
60
80
80
70
40
60
40
60
40
60
40
60
40
60
40
60
50
1.341
1.590
1.841
2.632
1.379
1.645
1.923
2.650
1.586
1.739
1.935
2.792
1.921
0.667
0.674
0.854
0.989
0.845
0.771
0.749
0.760
0.880
0.700
0.709
0.710
0.776
17.000
8.740
20.220
10.200
12.160
5.840
6.260
12.360
12.080
11.680
13.240
10.820
11.717
7.200
6.880
7.120
6.340
7.120
7.600
7.520
7.330
8.030
8.120
7.890
8.330
7.457
4.230
4.190
4.200
4.150
4.570
4.230
4.400
4.140
5.200
4.980
4.700
4.780
4.481
2.325
2.621
2.121
2.714
2.337
3.046
3.015
2.762
3.308
4.142
2.568
3.442
2.867
3.160
2.900
3.010
3.120
3.330
3.040
3.120
2.980
3.520
3.010
3.310
2.900
3.117
MC- Feed moisture content, SS – screw speed, ET- extrusion temperature, WAI- water absorption index, WSI- water solubility index.
53
Table 4.3: Coded regression coefficients for independent variables and product responses
Independent
Extrusion
variables
rate (g/s)
Bulk
density
(g/cm3)
Softening
Softening
Softening
WAI
WSI
time at
time at
time at
(g/g)
(%)
60℃
80℃
90℃
(min)
(min)
(min)
Constant
1.8993
0.7813
2.79
9.15
7.393
4.335
3.1175
MC - Feed moisture
0.081
-0.0232
0.46
-1.04
0.6037
0.3613
0.0687
SS - Screw speed
0.3743
0.0195
-0.096
0.47
-0.035
-0.0858
-0.0433
ET - Temperature
0.2535
-0.0082
0.254
-1.78
-0.0233
-0.0692
-0.125
MC2
0.0327
-0.0085
0.115
3.84
0.096
0.2188
-0.0013
MC*SS
-0.0173
-0.0827
-0.166
-0.55
0.0863
-0.0787
-0.0487
MC*ET
-0.0039
-0.0401
0.102
1.93
0.2038
-0.0063
-0.0963
SS*ET
0.1423
0.0328
-0.052
0.72
-0.065
0.0308
0.0517
Model F-value
179.600
3.630
2.970
1.380
8.550
14.450
13.610
P-Value
0.000
0.115
0.154
0.397
0.028
0.011
0.012
R2 (%)
99.680
86.390
83.880
70.760
93.740
96.200
95.970
Adjusted R2 (%)
99.130
62.560
55.680
19.590
82.770
89.540
88.920
4.1.1 Results on extrusion rate
Table 4.4: Coded regression coefficients for independent variables for extrusion rate
Independent
Extrusion
variables
rate (g/s)
F - Value
P - Value
Constant
1.8993
MC - Feed moisture
0.081
23.980
0.008
SS - Screw speed
0.3743
767.690
0.000
ET - Temperature
0.2535
352.130
0.000
2
MC
0.0327
1.090
0.355
MC*SS
-0.0173
0.060
0.825
MC*ET
-0.0039
110.910
0.000
SS*ET
0.1423
1.300
0.317
2
R
99.680
Adjusted R2
99.130
54
Figure 4.1: Surface plot of extrusion rate vs moisture content, screw speed
Figure 4.2: Surface plot of extrusion rate vs moisture content, extrusion temperature
Figure 4.3: Pareto chart of standardized effects for extrusion rate
55
4.1.2 Results on bulk density
Table 4.5: Coded regression coefficients for independent variables for bulk density
Independent
Bulk density
variables
(g/cm3)
F - Value
P - Value
Constant
0.7813
MC - Feed moisture
-0.0232
1.200
0.334
SS - Screw speed
0.0195
1.280
0.321
ET - Temperature
-0.0082
0.230
0.657
2
MC
-0.0085
0.050
0.827
MC*SS
-0.0827
15.380
0.017
MC*ET
-0.0401
3.620
0.130
SS*ET
0.0328
3.620
0.130
2
R
86.390
Adjusted R2
62.560
Figure 4.4: Surface plot of bulk density vs moisture content, screw speed
56
Figure 4.5: Surface plot of bulk density vs moisture content, extrusion temperature
Figure 4.6: Pareto chart of standardized effects for bulk density
57
4.1.3 Results on water adsorption index
Table 4.6: Coded regression coefficients for independent variables for water adsorption
index (WAI)
Independent
variables
WAI (g/g)
F - Value
P - Value
Constant
2.79
MC - Feed moisture
0.46
11.920
0.026
SS - Screw speed
-0.096
0.790
0.425
ET - Temperature
0.254
5.480
0.079
MC2
0.115
1.560
0.280
MC*SS
-0.166
0.590
0.485
MC*ET
0.102
0.230
0.656
SS*ET
-0.052
0.250
0.644
R2
83.880
2
Adjusted R
55.680
Figure 4.7: Surface plot of WAI vs moisture content, extrusion temperature
58
Figure 4.8: Surface plot of WAI vs screw speed, extrusion temperature
Figure 4.9: Pareto chart of standardized effects for WAI
59
4.1.4 Results on water solubility index
Table 4.7: Coded regression coefficients for independent variables for water solubility
index (WSI)
Independent
variables
WSI (%)
F - Value
P - Value
Constant
9.15
MC - Feed moisture
-1.04
0.660
0.461
SS - Screw speed
0.47
0.200
0.679
ET - Temperature
-1.78
2.890
0.165
MC2
3.84
0.180
0.691
MC*SS
-0.55
2.280
0.206
MC*ET
1.93
0.470
0.529
SS*ET
0.72
3.000
0.158
R2
70.760
2
Adjusted R
19.590
Figure 4.10: Surface plot of WSI vs moisture content, screw speed
60
Figure 4.11: Surface plot of WSI vs moisture content, extrusion temperature
Figure 4.12: Pareto chart of standardized effects for WSI
61
4.1.5 Results on softening time at different temperature
Table 4.8: Coded regression coefficients for independent variables for softening time at
60℃
Independent
variables
Softening
time at
F - Value
P - Value
60℃ (min)
Constant
7.393
MC - Feed moisture
0.6037
51.27
0.002
SS - Screw speed
-0.035
0.26
0.638
ET - Temperature
-0.0233
0.11
0.752
2
MC
0.096
1.05
0.364
MC*SS
0.0863
5.84
0.073
MC*ET
0.2038
0.89
0.399
SS*ET
-0.065
0.43
0.546
2
R
93.74
2
Adjusted R
82.77
Figure 4.13: Surface plot of softening time at 60℃ vs moisture content, screw speed
62
Figure 4.14: Surface plot of softening time at 60℃ vs moisture content, extrusion
temperature
Figure 4.15: Pareto chart of standardized effects softening time at 60℃
63
Table 4.9: Coded regression coefficients for independent variables for softening time at
80℃
Independent
variables
Softening
time at
F - Value
P - Value
80℃ (min)
Constant
4.335
MC - Feed moisture
0.3613
76.59
0.001
SS - Screw speed
-0.0858
6.49
0.064
ET - Temperature
-0.0692
4.21
0.109
2
MC
0.2188
3.64
0.129
MC*SS
-0.0787
0.02
0.887
MC*ET
-0.0063
0.84
0.412
SS*ET
0.0308
9.36
0.038
R2
96.2
2
Adjusted R
89.54
Figure 4.16: Surface plot of softening time at 80℃ vs moisture content, screw speed
64
Figure 4.17: Surface plot of softening time at 80℃ vs moisture content, extrusion
temperature
Figure 4.18: Pareto chart of standardized effects softening time at 80℃
65
Table 4.10: Coded regression coefficients for Independent variables for softening time at
90℃
Independent
variables
Softening
time at
F - Value
P - Value
90℃ (min)
Constant
3.1175
MC - Feed moisture
0.0687
9.66
0.036
SS - Screw speed
-0.0433
5.76
0.074
ET - Temperature
-0.125
47.9
0.002
MC2
-0.0013
4.86
0.092
MC*SS
-0.0487
18.93
0.012
MC*ET
-0.0963
8.18
0.046
SS*ET
0.0517
0
0.976
2
R
95.97
Adjusted R2
88.92
Figure 4.19: Surface plot of softening time at 90℃ vs moisture content, screw speed
66
Figure 4.20: Surface plot of softening time at 90℃ vs moisture content, screw speed
Figure 4.21: Pareto chart of standardized effects softening time at 90℃
Table 4.11: Optimized extrusion parameters
Independent variables
Value
Feed moisture content (%wb)
30.48
Extruder screw speed (rpm)
80
Extrusion Temperature (℃)
60
67
Table 4.12: Optimized response variables
Response variables
Value
Extrusion rate (g/s)
2.68
Bulk density (g/cm3)
0.8
Water adsorption index (g/g)
2.96
Water solubility index (%)
8.72
Softening time at 60 (min)
7.42
Softening time at 80 (min)
4.26
Softening time at 90 (min)
2.99
Table 4.13: Quadratic models developed for each response variables
Parameters
Models
R2
Extrusion
4.05 - 0.144 MC - 0.0164 SS - 0.0703 ET + 0.00363 (MC)2 -
rate (g/s)
0.000576 MC*SS - 0.000130 MC*ET + 0.001423 SS*ET
Bulk density
- 6.58 + 0.309 MC + 0.0683 SS + 0.0163 ET - 0.00095
(g/cm3)
(MC)2 - 0.002757 MC*SS - 0.001337 MC*ET + 0.000328
99.68
86.39
SS*ET
WAI (g/g)
0.8 - 0.40 MC + 0.183 SS - 0.040 ET + 0.0128 (MC)2 -
83.88
0.00554 MC*SS + 0.00341 MC*ET - 0.00052 SS*ET
WSI (%)
493 - 27.9 MC + 0.23 SS - 2.61 ET + 0.427 (MC)2 - 0.0183
70.76
MC*SS + 0.0644 MC*ET + 0.0072 SS*ET
Softening
25.3 - 0.98 MC - 0.0572 SS - 0.1606 ET + 0.0107 (MC)2 +
time at 60℃
0.00287 MC*SS + 0.00679 MC*ET - 0.000650 SS*ET
93.74
(min)
Softening
18.80 - 1.144 MC + 0.0547 SS - 0.0222 ET + 0.02431 (MC)2
time at 80℃
- 0.00262 MC*SS - 0.00021 MC*ET + 0.000308 SS*ET
96.2
(min)
Softening
-3.18 + 0.305 MC + 0.0186 SS + 0.0476 ET - 0.00014 (MC)2
time at 90℃
- 0.001625 MC*SS - 0.003208 MC*ET + 0.000517 SS*ET
(min)
68
88.92
4.2 Discussion of Results
This project aims to study the effect of temperature, screw speed and moisture content of
feed on extrusion rate, bulk density, water adsorption index, water solubility index, and
softening time of extruded wheat flour. Variations of temperature, screw speed and
moisture content in this experiment were developed using a 3-level multilevel factorial
design on Minitab Statistical Software (Version 20.3) and the values were recorded in
Table 4.1.
Effect of feed moisture content, screw speed and extrusion temperature on temperature,
screw speed and moisture content of feed on extrudate characteristics are presented in 3D
surface plots which showed significant effect.
4.2.1 Extrusion rate
Extrusion rate obtained for this study was recorded in Table 4.2. Extrusion rate values were
obtained by dividing the mass of extruded wheat flour in grams by time taken for that mass
of extruded flour to exit the extruder. The extrusion rate of extruded wheat flour measured
for all the runs varied from 1.34 to 2.79 g/s as seen from Table 4.2.
A quadratic model was obtained by inputting the data of extrusion rate response in Minitab
statistical software. The coefficient of the model, model F-value, P-value, along with R2
values are presented in Table 4.3. It is seen from Table 4.3 that the developed quadratic
model has a high F-value (179.60) and a low P-value (0.00), which suggests that the model
is significant. The high F-value and low P-value is evidence to suggest that the variability
explained by the quadratic model is larger than what would be expected by random chance.
Table 4.3 also shows that the developed model is highly adequate to describe the
relationship between extrusion rate and the independent variables (feed moisture content,
extrusion temperature and screw speed). The high coefficient of determination (R2 = 0.99)
indicates the model’s close adequacy. The predicted R2 (0.96) was in close agreement with
adjusted R2 (0.99) which further shows the model’s adequacy to describe the relationship
between extrusion rate response and the independent variables (feed moisture content,
screw speed and extrusion temperature).
Figures 4.1 and 4.2 are three-dimensional surface plots of this regression equation. Figure
4.1 depicts the functional relationship between a dependent variable/response value
(extrusion rate) and two independent variables/continuous factors (feed moisture content
and screw speed) while Figure 4.2 depicts the functional relationship between extrusion
rate and two independent variables/continuous factors (feed moisture content and
69
extrusion temperature). Figures 4.1 and 4.2 show that the highest extrusion rate
corresponds to high screw speed, extrusion temperature and moisture content values. In
contrast, the lowest extrusion rate corresponds to the low extrusion temperature, screw
speed and moisture content values.
Figure 4.3 depicts the pareto chart of standardized effects for extrusion rate. The chart
shows the absolute values of the standardized effects of the terms of the extrusion rate
model equation on extrusion rate response from the largest to the smallest, it also plots a
reference line (2.78) dependent on the significance level (α = 0.05) to indicate which of
the terms in the regression equation is statistically significant. From Figure 4.3, it is seen
that screw speed, extrusion temperature, moisture content and the product of screw speed
and extrusion temperature are the only terms that are statistically significant on a 0.05
level. It is also seen that screw speed has the most effect on extrusion rate followed by
extrusion temperature. The Pareto chart is significant for showing the factors' impact on
the extrusion rate, however, it does not account for the magnitude and direction of the said
effects.
Table 4.4 shows the coded regression coefficients for independent variables in the
regression equation for extrusion rate. Coded coefficients were obtained by normalizing
the values of the independent variables, coded coefficients are useful for identifying the
impact and direction of each independent variable in the regression equation. From Table
4.4, it is observed that screw speed has the highest positive coefficient (0.374) followed
by extrusion temperature (0.253) then moisture content (0.081), this suggests that screw
speed has the highest positive influence in extrusion rate followed by temperature of
extrusion. The screw is a part of the extruder responsible for conveying materials to the
extruder’s exit by rotation, so the faster the screw rotates, the lesser the residence time of
material in the extruder which consequently increases extrusion rate. The positive
influence of temperature on extrusion rate occurs because an increase in temperature
causes a decrease in extrudate viscosity and lower viscosity allows the material to flow
more easily through the extruder, leading to faster extrusion rates. Also, increase in
moisture content increases gelatinization, the rupturing of starch granules. This causes the
extrudate to become more gel like, leading to a smoother and easier flow of the extrudate
through the extruder and faster extrusion rate. These findings were well supported by
Elmiawan, Saryanto, & Sebayang (2017) and Ditudompo, Takhar, Ganjyal, & Hanna
(2013). Elmiawan, Saryanto, & Sebayang (2017) found that increasing screw speed
significantly increases extrusion rate while Ditudompo, Takhar, Ganjyal, & Hanna (2013)
70
observed from investigation that an increase in feed moisture content and extrusion
temperature yields higher extrusion rate.
4.2.2 Bulk density
Bulk density obtained for this study was recorded in Table 4.2. Bulk density values were
obtained by dividing a mass of extruded wheat flour in grams by volume of the measured
mass of extrudate. Bulk density of extruded wheat flour measured for all the runs varied
from 0.667 to 0.989 g/cm3 as seen from Table 4.2.
A quadratic model was obtained by inputting the data of bulk density response in Minitab
statistical software. The coefficient of the model, model F-value, P-value, along with R2
values are presented in Table 4.3. It is seen from Table 4.3 that the developed quadratic
model has a low F-value (3.630) and a high P-value (0.1150), which suggests that obtained
results are not statistically significant. However, the high R2 value (0.86) suggests that the
independent variables in the regression model are responsible for the variation of bulk
density.
Figures 4.4 and 4.5 are three-dimensional surface plots of this regression equation. Figures
4.4 and 4.5 depicts the functional relationship between bulk density, feed moisture content,
and screw speed. Figures 4.4 and 4.5 show that the highest bulk density corresponds to
high screw speed, high extrusion temperature and low moisture content values.
Figure 4.6 depicts the pareto chart of standardized effects for bulk density. The chart shows
the absolute values of the standardized effects of the terms in the bulk density model
equation on bulk density response from the largest to the smallest, it also plots a reference
line (2.776) dependent on the significance level (α = 0.05) to indicate which of the terms
in the regression equation is statistically significant. From Figure 4.6, it is seen that the
product of moisture content and screw speed is the only term that is statistically significant
on a 0.05 level. This means moisture content and screw speed impact bulk density the
most.
Table 4.5 shows the coded regression coefficients for independent variables in the
regression equation for extrusion rate. From Table 4.5, it is observed that screw speed has
the only positive coefficient (0.0195) while extrusion temperature and moisture content
have negative coefficients, this suggests that an increase in screw speed will cause an
increase in bulk density while increasing extrusion temperature and moisture content will
cause a decrease in bulk density. Although figure 4.5 suggests that the highest bulk density
71
corresponds to a high temperature, the pareto chart of standardized effects for bulk density
depicted by figure 4.6 confirms that temperature has no significant effect on bulk density.
Figure 4.4 and A possible explanation could be, as screw speed increases, the extruder
applies greater mechanical force on the wheat extrudate causing an increase in compaction
force, resulting in higher bulk density. Temperature rise in the extruder evaporates the
moisture at a faster rate. The steam generated from evaporation generates pressure in the
extruder which leads to expansion of extrudate, in the same vein, an increase in feed
moisture content will lead to greater expansion during extrusion. When moisture is
subjected to heat and pressure in the extruder, it turns to steam. This steam generates
pressure within the extrudate, leading to its expansion, thereby reducing the bulk density.
Similar results were also gotten by Sahua, Patel, & Tripathi (2022) for effect of extrusion
parameters on quality of maize based extruded snack
4.2.3 Water adsorption index
Water adsorption index obtained for this study was recorded in Table 4.2. Water adsorption
index of extruded wheat flour measured for all the runs varied from 2.121 to 4.142 g/g as
seen from Table 4.2.
A quadratic model was obtained by inputting the data of water adsorption index response
in Minitab statistical software. The coefficient of the model, model F-value, P-value, along
with R2 values are presented in Table 4.3. It is seen from Table 4.3 that the developed
quadratic model has a low F-value (2.970) and a high P-value (0.154), which suggests that
obtained results are not statistically significant. However, the high R2 value (0.84) suggests
that the independent variables in the regression model are responsible for the variation of
water adsorption index.
Figures 4.7 and 4.8 are three-dimensional surface plots of this regression equation. Figures
4.7 and 4.8 depicts the functional relationship between water adsorption index, feed
moisture content, and screw speed. Figures 4.7 and 4.8 show that the highest water
adsorption index corresponds to high moisture content, high extrusion temperature and
low screw speed values
Figure 4.9 depicts the pareto chart of standardized effects for water adsorption index. The
chart shows the absolute values of the standardized effects of the terms in the water
adsorption index equation on water adsorption index response from the largest to the
smallest, it also plots a reference line (2.776) dependent on the significance level (α = 0.05)
to indicate which of the terms in the regression equation is statistically significant. From
72
Figure 4.9, it is seen that moisture content is the only term that is statistically significant
on a 0.05 level. This means moisture content impacts water adsorption index the most.
Table 4.6 shows the coded regression coefficients for independent variables in the
regression equation for water adsorption index. From Table 4.6, it is observed that feed
moisture content and extrusion temperature have positive coefficients of 0.46 and 0.254
respectively while screw speed has a negative coefficient. This suggests that an increase
in feed moisture content and extrusion temperature will cause an increase in water
adsorption index while an increase in screw speed will cause a decrease in water adsorption
index. A possible explanation could be, rise in moisture content and temperature during
extrusion cause gelatinization of starch present in wheat flour. Gelatinization, which is the
rupturing of starch, increases the porosity of extruded wheat flour which in turn yields
greater water absorption and retention capacity. Similar results were gotten in the study by
Rweyemamu, Yusuph, & Mrema (2015) for physical properties of extruded snacks
enriched with soybean and moringa leaf powder. Increasing in extruder screw speed results
in a shorter residence time for the wheat flour within the extruder barrel. A shorter
residence time limits the effect of moisture and temperature thus impeding gelatinization
and reducing water adsorption capacity.
4.2.4 Water solubility index
Water solubility index obtained for this study was recorded in Table 4.2. Water solubility
index of extruded wheat flour measured for all the runs varied from 5.84 to 20.22% as seen
from Table 4.2.
A quadratic model was obtained by inputting the data of water solubility index response
in Minitab statistical software. The coefficient of the model, model F-value, P-value, along
with R2 values are presented in Table 4.3. It is seen from Table 4.3 that the developed
quadratic model has a low F-value (1.38) and a high P-value (0.397), which suggests that
obtained results are not statistically significant. However, the high R2 value (0.71) suggests
that the independent variables in the regression model are responsible for the variation of
water solubility index.
Figures 4.10 and 4.11 are three-dimensional surface plots of this regression equation.
Figures 4.10 and 4.11 depicts the functional relationship between water solubility index,
feed moisture content, and screw speed. Figures 4.10 and 4.11 show that the highest water
adsorption index corresponds to low moisture content, low extrusion temperature and high
screw speed values.
73
Figure 4.12 depicts the pareto chart of standardized effects for water adsorption index. The
chart shows the absolute values of the standardized effects of the terms in the water
solubility index equation on water solubility index response from the largest to the
smallest, it also plots a reference line (2.776) dependent on the significance level (α = 0.05)
to indicate which of the terms in the regression equation is statistically significant. From
Figure 4.12, it is seen that none of the terms are statistically significant on a 0.05 level.
This means moisture content impacts water adsorption index the most.
Table 4.7 shows the coded regression coefficients for independent variables in the
regression equation for water solubility index. From Table 4.7, it is observed that screw
speed has positive coefficients of 0.47 while feed moisture content and extrusion
temperature have negative coefficients of -1.04 and -1.78 respectively. This suggests that
an increase in screw speed will cause an increase in water solubility index while an
increase in feed moisture content and extrusion temperature will cause a decrease in water
solubility index. Rise in screw speed increases shear forces and specific mechanical energy
causing excessive shearing of the melt resulting into decreased molecular mass of starch
particles in wheat flour. As a result, water solubility index increases. Also, increase in
extrusion temperature and moisture content can lead to increased protein aggregation.
High heat and moisture can cause protein aggregation, leading to reduced solubility in
water. Similar results were obtained by Hongyuan, Hao, Shifeng, & Min (2022) for
development of a water solubility model of extruded feeds.
4.2.5 Softening time at different temperature
Softening time obtained for this study was recorded in Table 4.2. Softening time of
extruded wheat flour at 60℃, 80℃ and 90℃ measured for all the runs varied from 2.9 to
8.3 minutes as seen from Table 4.2.
Quadratic models for softening time at 60℃, 80℃ and 90℃ were obtained by inputting the
data of softening time response in Minitab statistical software. The coefficient of the
model, F-value, P-value, along with R2 values for each temperature are presented in Table
4.3. It is seen from Table 4.3 that the developed quadratic model at 60℃, 80℃ and 90℃
have high F-value and P-values of 8.550 and 0.028, 14.450 and 0.011, 13.610 and 0.012
respectively. This suggests that obtained results are statistically significant on a 5% level.
The models developed at 60℃, 80℃ and 90℃ for softening time all have high R2 value of
0.937, 0.962 and 0.96 which suggest that the independent variables in the regression model
are responsible for the variation of softening time.
74
Figures 4.13, 4.14, 4.16, 4.17 4.19 and 4.20 are three-dimensional surface plots of this
regression equation. Figures 4.13 4.14, 4.16, 4.17 4.19 and 4.20 depict the functional
relationship between softening time at 60℃, 80℃ and 90℃ with feed moisture content,
and screw speed respectively. These figures show that the highest softening time at any of
these temperature values corresponds to high moisture content, low extrusion temperature
and low screw speed values.
Figure 4.15, 4.18 and 4.21 depict the pareto chart of standardized effects for softening time
at 60℃, 80℃ and 90℃ respectively. The chart shows the absolute values of the
standardized effects of the terms in the softening time model equation for each temperature
on the softening time response from the largest to the smallest. They plot a reference line
(2.776) dependent on the significance level (α = 0.05) to indicate which of the terms in the
regression equations are statistically significant. Figure 4.15 and 4.18 show that moisture
content is statistically significant on moisture content at 60℃ and 80℃ and as result impact
softening time the greatest at these temperatures. Figure 4.21 shows however, that
extrusion temperature and moisture content affect softening time at 90℃. Figure 4.21
further shows that extrusion temperature has the greatest impact on softening time at 90℃
followed by moisture content.
Table 4.8-4.10 shows the coded regression coefficients for independent variables in the
regression equation for softening time at 60℃, 80℃ and 90℃. From the Tables 4.8-4.10,
it is observed that moisture content has a positive coefficient while screw speed and
extrusion temperature have negative coefficients. This suggests that an increase in
moisture content will cause an increase in softening time at 60℃, 80℃ and 90℃ while an
increase in feed moisture content and extrusion temperature will cause a decrease in
softening time. Wheat flour's plasticity and elasticity in the extruder are influenced by the
moisture level of the feed. Elasticity is the capacity of a material to deform under stress
and then return to its former shape, whereas plasticization is the softening and increased
flexibility of a material when treated to heat and moisture. Wheat flour becomes more
plasticized and the elasticity of the dough decreases as feed moisture content rises. The
extrudate becomes more compact or less porous as a result of the dough's enhanced
plasticization and lower elasticity, which also reduces the extrudate's capacity to expand
and create air pockets or bubbles. The extruded product has a denser and harder
structure as a result. Similar results were obtained by Seth, Badwaik, & Ganapathy (2013)
for effect of extrusion parameters on extrudate characteristics of yam-corn- rice based
75
snack food. On the other hand, melt viscosity of the material being extruded tends to
decrease as the temperature and screw speed in the extruder rise. Lower melt viscosity
increase the capacity of the material to capture and retain air bubbles during the extrusion
process. Also, moisture in the feed material will evaporate at high barrel temperature and
produce steam in the extruder causing bubbles to develop in the extrudate. Similar results
were obtained by Sahua, Patel, & Tripathi (2022) for effect of extrusion parameters on
quality of maize based extruded snack.
Tables 4.11 and 4.12 depicted the optimized extrusion parameters and their corresponding
response variable. The values were gotten by regression surface model on Minitab
statistical software by minimizing bulk density, water solubility index and softenig time
while maximizing water adsorption index and extrusion rate. Table 4.13 showed the
uncoded regression models developed for each response variable.
76
CHAPTER FIVE
CONCLUSION AND RECOMMENDATION
Food extrusion via a single screw extruder is a relatively cheap food processing technique,
with a high adaptability, which enables it to process various food products and valorize
food wastes. This research investigates the effect of extrusion parameters on wheat flour
product quality. Effect of varying moisture content, extrusion temperature and extruder
screw speed on the properties (extrusion rate, bulk density, water adsorption index, water
solubility index, and softening time at different temperatures) of wheat flour extrudate was
observed. This data was used to generate regression models that predict the response of
extrudate properties to the variation of extrusion parameters.
5.1 Conclusion
At the end of this experiment, the following conclusions were arrived at. Response surface
design on Minitab statistical software depicted the effect of extrusion parameters on wheat
flour extrudate properties. Extrusion parameters have significant effect on properties of
extruded wheat flour. Increase in extruder screw speed, extrusion temperature and
moisture content caused an increase in extrusion rate. Increase in screw speed caused the
greatest increase in extrusion rate. Increase in screw speed yielded an increase in extrudate
bulk density while extrusion temperature and moisture content decrease bulk density. Feed
moisture content and extrusion temperature increased water adsorption index of extruded
flour. Moisture content increase water adsorption to a greater degree relative to extrusion
temperature. Water solubility index of extrudate product was increased by screw speed
while feed moisture content and extrusion temperature had decrease water solubility.
Moisture content reduced water solubility to a greater degree relative to extrusion
temperature. Softening time at 60℃, 80℃ and 90℃ was increased by moisture content
while screw speed and extrusion temperature had negative effect on softening time.
Extruder screw speed increased extrusion rate, bulk density and water solubility index but
reduced softening time and water adsorption index of extrudate wheat flour. Extrusion
temperature increases extrusion rate and water adsorption index but reduce bulk density,
water solubility index and softening time. Feed moisture content increases extrusion rate,
water adsorption index and softening time but reduced bulk density and water solubility
index of extrudate product. Optimized extrusion parameters were found to be 60°C
extrusion temperature, 80 rpm screw speed and 30.48 % (wb) moisture content with
2.68g/s extrusion rate, 0.80 g/cm3 bulk density, 2.96 g/g WAI, 8.72% WSI, and softening
77
time of 7.416 minutes, 4.261 minutes, 2.9885 minutes in 60, 80 and 90°C water
respectively of extruded wheat flour.
5.2 Contribution to Knowledge
By carrying out this project, regression quadratic models that give a relationship between
independent extrusion parameters and response variables were developed. Developed
models include:
1. Quadratic model relating extrusion rate of extruded wheat flour with extrusion
temperature, screw speed and moisture content
2. Quadratic model relating bulk density of extruded wheat flour with extrusion
temperature, screw speed and moisture content
3. Quadratic model relating WAI of extruded wheat flour with extrusion temperature,
screw speed and moisture content
4. Quadratic model relating WSI of extruded wheat flour with extrusion temperature,
screw speed and moisture content
5. Quadratic model relating softening time of extruded wheat flour in 60℃ hot water
with extrusion temperature, screw speed and moisture content
6. Quadratic model relating softening time of extruded wheat flour in 80℃ hot water
with extrusion temperature, screw speed and moisture content
7. Quadratic model relating softening time of extruded wheat flour in 90℃ hot water
with extrusion temperature, screw speed and moisture content
5.3 Recommendation
The following can be implemented to augment the results of this research project:
1. Better insulation of extruder barrel to improve heat retention in the system and
minimise heat loss to the environment.
2. Independent variables should be varied across a wider range to generate more data.
This will increase the statistical significance and accuracy of each model
3. The extruder’s thrust bearing should be further strengthened to avoid damage to the
extruder from excessive pressure.
4. The extruder’s motor should be changed to allow the use of higher pressure in study.
78
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83
APPENDICES
Appendix A: Extrusion Process
Extrusion rate =
Run
No
!"## %&'
A-1
'(!) '"*)+ ,%- ).'-&/"') '% ).(' ).'-&/)-
Table A-1: Extrusion Process Raw Data
Screw
Time taken
Feed moisture
Temperature
speed
to exit
content (%wb)
(℃)
(rpm)
extruder (s)
Mass
out (g)
Extrusion
rate (g/s)
1
2
3
4
27
27
27
27
60
60
80
80
40
60
40
60
29.100
31.000
33.140
28.120
38.900
49.300
61.000
74.000
1.341
1.590
1.841
2.632
Run
No
Feed moisture
content (%wb)
Speed
(rpm)
Tempature
(℃)
Time taken
to exit
extruder (s)
Mass
out (g)
Extrusion
rate (g/s)
5
6
7
8
30
30
30
30
60
60
80
80
40
60
40
60
29.000
31.000
28.090
20.000
40.000
51.000
54.000
53.000
1.379
1.645
1.923
2.650
Run
No
Feed moisture
content (%wb)
Speed
(rpm)
Tempature
(℃)
Time taken
to exit
extruder (s)
Mass
out (g)
Extrusion
rate (g/s)
9
10
11
12
30
30
30
30
60
60
80
80
40
60
40
60
29.000
31.000
28.090
20.000
40.000
51.000
54.000
53.000
1.379
1.645
1.923
2.650
84
Appendix B: Bulk Density Test
Bulk density =
4 × mass of extrudate
π × (extrudate diameter)! × extrudate length
B-1
Table B-1: Bulk density test raw data
Run No
1
2
3
4
Run No
5
6
7
8
Run No
9
10
11
12
Feed
moisture
Content
(%wb)
27
27
27
27
Feed
moisture
Content
(%wb)
30
30
30
30
Feed
moisture
Content
(%wb)
30
30
30
30
Screw
speed
(rpm)
60
60
80
80
Speed
(rpm)
60
60
80
80
Speed
(rpm)
60
60
80
80
Temperature Diameter
(℃)
(cm)
40
29.100
60
31.000
40
33.140
60
28.120
Tempature
(℃)
40
60
40
60
Tempature
(℃)
40
60
40
60
85
Diameter
(cm)
29.000
31.000
28.090
20.000
Diameter
(cm)
29.000
31.000
28.090
20.000
Mass
(g)
38.900
49.300
61.000
74.000
Mass
out (g)
40.000
51.000
54.000
53.000
Mass
out (g)
40.000
51.000
54.000
53.000
Length
(cm)
1.341
1.590
1.841
2.632
Bulk
density
(g/cm3)
0.0436
0.0411
0.0384
0.0453
Extrusion
rate
1.379
1.645
1.923
2.650
Bulk
density
(g/cm3)
0.0439
0.0411
0.0453
0.0636
Extrusion
rate
1.379
1.645
1.923
2.650
Bulk
density
(g/cm3)
0.0439
0.0411
0.0453
0.0636
Appendix C: Water Adsorption Index Test
WAI (g/g) =
!"#$%& () *"+#,"-&*
C-1
!"#$%& () +./ *(0#+
Table C-1: Water adsorption index raw data
Run No
1
2
3
4
Run No
5
6
7
8
Run No
9
10
11
12
Feed
moisture
Content
(%wb)
27
27
27
27
Feed
moisture
Content
(%wb)
30
30
30
30
Feed
moisture
Content
(%wb)
33
33
33
33
Screw
speed
(rpm)
60
60
80
80
Empty
Tube +
centrifuge sediments
tube (g)
(g)
4.917
6.080
4.815
6.126
5.551
6.612
4.938
6.295
Screw
speed
(rpm)
60
60
80
80
Empty
Tube +
centrifuge sediments
tube (g)
(g)
5.110
6.278
5.574
7.097
5.005
6.512
5.650
7.031
Screw
speed
(rpm)
60
60
80
80
Empty
Tube +
centrifuge sediments
tube (g)
(g)
5.094
6.748
4.840
6.911
4.912
6.196
5.619
7.340
86
Sediment
(g)
1.163
1.311
1.061
1.357
Initial
dry
mass(g)
0.500
0.500
0.500
0.500
WAI (g)
2.325
2.6212
2.1214
2.7144
Sediment
(g)
1.169
1.523
1.507
1.381
Initial
dry
mass(g)
0.500
0.500
0.500
0.500
WAI (g)
2.3372
3.0464
3.0148
2.7618
Sediment
(g)
1.654
2.071
1.284
1.721
Initial
dry
mass(g)
0.500
0.500
0.500
0.500
WAI (g)
3.3076
4.14182
2.5678
3.4416
Appendix D: Water Solubility Index Test
WSI (%) =
Run
No
1
2
3
4
Run
No
5
6
7
8
Run
No
9
10
11
12
!"#$%& () +#**(01"+ *(0#+* #- *23".-4&4-&
Feed
moisture
Content
(%wb)
27
27
27
27
Feed
moisture
Content
(%wb)
30
30
30
30
Feed
moisture
Content
(%wb)
33
33
33
33
D-1
!"#$%& () +./ *(0#+
Table D-1: Water solubility index raw data
Crucible +
Screw
Empty
dissolved Dissolved
speed
crucible
extrudate extrudate
(rpm)
(g)
(g)
(g)
60
35.095
35.18
1.163
60
36.129
36.1727
1.311
80
26.719
26.8201
1.061
80
33.451
33.502
1.357
Screw
speed
(rpm)
60
60
80
80
Empty
crucible
(g)
29.9272
31.0148
33.2657
33.1602
Screw
speed
(rpm)
60
60
80
80
Empty
crucible
(g)
29.926
31.013
33.264
33.159
Crucible +
dissolved Dissolved
extrudate extrudate
(g)
(g)
29.988
1.169
31.044
1.523
33.297
1.507
33.222
1.381
Crucible +
dissolved Dissolved
extrudate extrudate
(g)
(g)
29.9864
1.654
31.0714
2.071
33.3302
1.284
33.2131
1.721
87
Initial
dry
mass(g)
0.500
0.500
0.500
0.500
WSI
(%)
17
8.74
20.22
10.2
Initial
dry
mass(g)
0.500
0.500
0.500
0.500
WSI
(%)
12.16
5.84
6.26
12.36
Initial
dry
mass(g)
0.500
0.500
0.500
0.500
WSI
(%)
12.08
11.68
13.24
10.82