University of the Philippines Los Baos
COLLEGE OF AGRICULTURE
BACHELOR OF SCIENCE IN FOOD TECHNOLOGY
JAYME PAOLO DUGAY LACISTE Name of Student
OPTIMIZATION OF FORMULATION FOR BREAKFAST CEREAL
SNACK USING ADLAI (Coix lacryma-jobi L.) PINEAPPLE (Anonas comosus L.), AND CARROTS (Daucus carota S.)
Thesis Title
DR. LERJUN M. PEAFLOR Thesis Adviser
___________________
Date of Submission
Permission is given to the following people to access to this thesis:
Available to the general public NO
Available only after consultation with author/thesis adviser YES
Available only those to bound by confidentiality agreement YES
Students Signature: _____________
Signature of thesis adviser: ____________
OPTIMIZATION OF FORMULATION FOR BREAKFAST CEREAL SNACK
USING ADLAI (Coix lacryma-jobi L.), PINEAPPLE (Anonas comosus L.), AND
CARROTS (Daucus carota S.)
JAYME PAOLO DUGAY LACISTE
SUBMITTED TO THE FACULTY OF THE COLLEGE OF AGRICULTURE
UNIVERSITY OF THE PHILIPPINES LOS BANOS IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS FOR
GRADUATION WITH THE DEGREE OF
BACHELOR OF SCIENCE IN FOOD TECHNOLOGY
AUGUST 2015
UPLBCA Form No. 30
Revised 2003
UNIVERSITY OF THE PHILIPPINES LOS BAOS
College, Laguna
UNDERGRADUATE THESIS MANUSCRIPT
FST 200
Name of Student: JAYME PAOLO DUGAY LACISTE
Degree Program: BACHELOR OF SCIENCE IN FOOD TECHNOLOGY
Thesis Title: OPTIMIZATION OF FORMULATION FOR BREAKFAST
CEREAL SNACK USING ADLAI (Coix lacryma-jobi L.)
PINEAPPLE (Anonas comosus L.) AND CARROTS (Daucus
carota S.)
APPROVED DR. LERJUN M. PEAFLOR____ __________________, 2015
Thesis Adviser
APPROVED DR. LOTIS E. MOPERA________ ___________________, 2015
Director, FSC
APPROVED DR. ENRICO P. SUPANGCO____ ___________________, 2015 College Dean
RECORDED DR. MARIA CYNTHIA R. OLIVEROS ________________,2015
College Secretary
iv
BIOGRAPHICAL SKETCH
The author was born on July 23, 1989 in Metro Manila. He is the second child
among three children of Engr. Jaime B. Laciste Jr. and Rosario D. Laciste. He started his
pre-school education in Christ Child School. He obtained his primary education in Saints
Peter and Paul Early Childhood Center. He obtained his secondary education in Santa
Rosa Science and Technology High School. He entered the university 2nd semester of
2006-2007.
The author has an innate liking for mechanical things and has trained in TESDA
for welding and fabrication and automotive troubleshooting.
The author hopes that all of his knowledge obtained from different disciplines of
learning like the technical aspects of vocational courses and the theoretical aspects of a
college education may be used and merge in order to accomplish his tasks in the open
world.
JAYME PAOLO LACISTE
v
ACKNOWLEDGEMENT
The author would like to give thanks to the following for the completion of this
thesis manuscript;
To the Lord Almighty for giving me the fuel to continue despite all the
disappointments, hardships and struggles.
For my family, my mother and my father for providing me financial, emotional
and moral support to finish this course. My sisters Angelica and Regina for supporting
me and being able to help me to finish this thesis. For my Tita Divina Russo for the
financial aid and egging me to dream despite hard times.
For my thesis adviser. Ser Lerjun for pushing me to finish this manuscript and for personally overseeing the development of this manuscript and keeping an eye not
only for the accomplishment of my results but on the technical inputs to make my thesis
much easier.
For the Food Science Cluster Faculty and Staff. Special thanks to mam Ara
Algar for letting me use the equipment for analysis. Tita Dory and Tita Fe for letting me
use the laboratory for analysis. Special thanks to Mang Emong, Mang Buns, Mang Jun
and Kuya Viven for their technical knowledge and expertise in guiding me to use the
different equipment while doing my thesis.
For AMDP for letting me fabricate my tools for the experiment. Special thanks to
Kuya Eugene for being there to fabricate things that I needed in the experiment and
happily doing so.
For Tita Odette, Tita Wena and the staff of the directors office for all the help in formatting this manuscript.
The author would also like to thank the following for a fruitful college life;
Special thanks to Samahang Room 111 and its constituents. Datu, Oliver,
Alexis, Jet, Rudolph, Xavier, Jem, Kennedy Pogi, Jem pwet, Edzel, Marlon etc. The Friendship that was developed inside our home, the New Dorm for keeping me company
in times of need, trials or just simply there because Im bored.
Special thanks to Allan and Kim, Pola, Iane for keeping me company, The former VegaSoc which shared my hobbies, sentiments and my interests.
For my thesis mates and others, Fonzy, Bart, Mikee etc. for keeping me
company in the laboratory to fight the lonesomeness I sometimes feel while doing tests.
And again, for Our Father, God Almighty for everything
vi
TABLE OF CONTENTS
Page
LIBRARY FORM i
UPLB CA Form No. 30 ii
TITLE PAGE iii
BIOGRAPHICAL SKETCH iv
ACKNOWLEDGMENT v
TABLE OF CONTENTS vi
LIST OF TABLES viii
LIST OF FIGURES ix
LIST OF APPENDICES xi
ABSTRACT xii
INTRODUCTION 1
Objectives of the study 3
Scope and limitations of the study. 3
REVIEW OF RELATED LITERATURE 4
Adlai: Biographical description, proximate analysis 4
and cultivation
Nutritional components of pineapple and carrots by-products 6
Micronutrient malnutrition 8
Recommended nutritional intake and
upper level intake of commercial cereals 9
Extrusion 10
Effect of extrusion to different food components 13
Breakfast cereals snacks 17
MATERIALS AND METHODS 20
Materials 20
Methods 20
Preparation of sample powders 20
Preparation of the breakfast cereal snack 20
Preparation of samples 21
Mixing 22
Extrusion 23
Physical attributes 25
Chemical analysis 25
Sensory evaluation 25
Statistical Analysis 26
Experimental analysis 27
Optimization of formulation for breakfast cereal snack 28
Verification 30
vii
RESULTS AND DISCUSSION 31
Moisture content of raw materials 31
Effect of independent variables on the formulation 31
of pineapple-carrot-adlai cereals
Physical Properties 33
Bulk Density 33
Extruded cereal moisture content 35
Water Absorptivity Index 36
Chemical Analysis 38
Breakfast cereal final moisture content 38
Crude fat 40
Ash content 41
Crude protein 43
Carbohydrate content 47
Sensory Evaluation 48
Appearance 48
Flavor 50
Aftertaste 51
Texture 53
General acceptability
Optimization 59
Verification 59
SUMMARY AND CONCLUSION 61
RECOMMENDATIONS 62
REFERENCES 64
APPENDICES 68
viii
LIST OF TABLES
Table Title Page
Number
1 Proximate analysis of polished adlai and adlai flour 5
2 Proximate analysis of pineapple, pineapple (air-oven dried) 7 and carrots
3 Dietary reference intakes (DRIs): Tolerable upper 10
intake levels
4 Nutritional effects of dietary fiber extrusion 15
5 Sales of breakfast cereals by category: volume 18
2007-2012.
6 Design matrix of a full factorial, two factor-three level 28
experimental design
7 Independent variables used in acceptability test 28
8 Moisture content of raw materials 31
9 Effect of independent variables on the physico-chemical 32
composition of the sample.
10 Effect of independent variables on the sensory score 33
11 Predicted and experimental responses at optimum 57
combination
ix
Figure LIST OF FIGURES Page
number
1 Adlai crop 5
2 Varieties of adlai 6
3 Changes in raw materials in an extrusion 11
cooking process
4 Process flowchart for breakfast cereals 21
5 Powdered samples 22
6 Mixed powder 22
7 Piston-type extruder 23
8 Cabinet dryer 24
9 Breakfast cereal snack final product 24
10 Contour plot of bulk density as a function of mixture 34
moisture content against adlai:pineapple-carrots ratio
11 Contour plot of extruded cereal moisture content 36
as a function of mixture moisture content against
adlai:pineapple-carrots ratio
12 Contour plot of water absorptivity index as a 38
function of mixture moisture content against
adlai:pineapple-carrots ratio
13 Contour plot of breakfast cereal final moisture content 39
as a function of mixture moisture content against
adlai:pineapple-carrots ratio
14 Contour plot of crude fat as a function of 41
mixture moisture content against
adlai:pineapple-carrots ratio
15 Contour plot of ash content as a function of 42
mixture moisture content against
adlai:pineapple-carrots ratio
16 Contour plot of crude protein as a function of 44
x
mixture moisture content against
adlai:pineapple-carrots ratio
17 Contour plot of crude fiber as a function of 46
mixture moisture content against
adlai:pineapple-carrots ratio
18 Contour plot of carbohydrate as a function of 48
mixture moisture content against
adlai:pineapple-carrots ratio
19 Contour plot of appearance as a function of 49
mixture moisture content against
adlai:pineapple-carrots ratio
20 Contour plot of flavor as a function of 51
mixture moisture content against
adlai:pineapple-carrots ratio
21 Contour plot of aftertaste as a function of 52
mixture moisture content against
adlai:pineapple-carrots ratio
22 Contour plot of texture as a function of 54
mixture moisture content against
adlai:pineapple-carrots ratio
23 Contour plot of overall acceptability as a function of 55
mixture moisture content against
adlai:pineapple-carrots ratio
xi
LIST OF APPENDICES
Appendices Appendices Page
Table
A Sensory scoresheet for extruded pineapple-carrots 68
adlai cereals
1 Model summary statistics for breakfast cereal final 69
moisture content
2 Sequential model of sum of squares for breakfast 69
cereal final moisture content
3 Model summary statistics for crude fat 69
4 Sequential model of sum of squares for crude fat 70
5 Model summary statistics for ash content 70
6 Sequential model of sum of squares for ash content 70
7 Model summary statistics for crude protein 70
8 Sequential model of sum of squares for crude protein 70
9 Model summary statistics for crude fiber 70
10 Sequential model of sum of squares for crude fiber 71
11 Model summary statistics for carbohydrates 71
12 Sequential model of sum of squares for carbohydrates 71
13 Model summary statistics for appearance 71
14 Sequential model of sum of squares for appearance 71
15 Model summary statistics for flavor 72
16 Sequential model of sum of squares for flavor 72
17 Model summary statistics for aftertaste 72
18 Sequential model of sum of squares for aftertaste 72
19 Model summary statistics for texture 72
xii
20 Sequential model of sum of squares for texture 73
21 Model summary statistics for overall acceptability 73
22 Sequential model of sum of squares for 73
overall acceptability
23 Model summary statistics for bulk density 73
24 Sequential model of sum of squares for bulk density 73
25 Model summary statistics for feed moisture content 74
26 Sequential model of sum of squares for feed 74
moisture content
27 Model summary statistics for water solubility index 74
28 Sequential model of sum of squares for water 74
solubility index
29 Post analysis coefficients table 75
OPTIMIZATION OF FORMULATION FOR BREAKFAST CEREAL SNACK
USING ADLAI (Coix lacryma-jobi L.), PINEAPPLE (Anonas comosus L) AND
CARROTS (Daucus carota S.)
JAYME PAOLO DUGAY LACISTE
ABSTRACT
Adlai or Jobs tears is one of the common crops in Southeast Asia. In the
Philippines, it is considered as an underutilized product. In this study, Adlai powder mixed
with pineapple and carrots powder were used to optimize the formulation of breakfast
cereals snacks. The independent variables are mixture moisture content (35, 40 and 45%)
and adlai:pineapple-carrots ratio (60:40, 70:30 and 80:20). Physical, Chemical, and
Sensory attributes were analyzed in order to optimize the product. A predicted value was
obtained which has ash content of 2.18%, Crude Protein of 7.60%, Carbohydrate content
of 74.10%, bulk density of 0.73 g/ml, extrudate moisture content of 37.13 % and water
absorption index of 2.60 g gel/g solids was attained. The predicted value was compared
with an actual experimental value attained through the same series of test. The results were
reasonably close and therefore the optimum formulation (38.38% mixture moisture content
and 69.40: 30.60 adlai:pineapple-carrots ratio) is suitable for making breakfast cereal
snacks.
OPTIMIZATION OF FORMULATION FOR BREAKFAST CEREAL SNACK
USING ADLAI (Coix lacryma jobi L.)1, PINEAPPLE (Ananas comosus L.) AND
CARROTS (Daucus carrota S.)
JAYME PAOLO DUGAY LACISTE
INTRODUCTION
Adlai or Jobs tears is one of the most common crops in Southeast Asia. Adlai is
historically being utilized as food by peasants. The grain was discovered in the 17th century
by naturalist Georg Eberhard Rumphius which stated that in his day Job's tears were
planted in Java and Celebes on the margins of rice fields. Aldai is closely related to rice
and corn or maize (Zea mays). Both species both belong to the grass tribe Tripsacea. The
grain is known to have higher protein content than most cereals in which adlai can be
utilized to be a good substitute against staples such as corn, rice, wheat and barley.
One of the major concerns of adlai in the Philippines is the underutilization of the
produce. In the Philippines, the grain is largely consumed as an alternative to rice in
Zamboanga del sur. The Department of Agriculture is pushing for the increased
consumption and trade of adlai as an alternative food staple to lessen pressure on rice
production. The Department of Agriculture has announced a central task for the
propagation of the grain.
1 A Food and Science Technology Thesis manuscript submitted in partial fulfillment of the requirements
for graduation with a degree of Bachelor of Science in Food Technology, Food Science Cluster, College of
Agriculture, University of the Philippines Los Baos, prepared under the supervision of Dr. Lerjun M.
Peaflor.
2
In relation to this, the study is aimed to help at least satisfy the requirement to
encourage the increased consumption of the cereal in various product forms.
Among the most nutritive foods is a breakfast cereal snack. A breakfast cereal snack
is an important food especially with the rising demand for a convenient and healthy food.
Lifestyle changes in modern times have changed the trends in foods. In connection with
adlai, most corn and rice based cereal have less of the nutritive value. However, most
Breakfast cereal snacks are fortified to include micronutrients such as minerals and fiber.
One of the ingredients of the experiment is powdered carrots. Carrots is rich in fiber
and is a good source of minerals and vitamins.
Pineapple is also a major fruit produce particularly in Southeast Asia. Among the
largest product from pineapple is pineapple juice. The production of pineapple juice
produces a lot of solid waste by canned industries every year. A good amount of cellulose,
hemicelluloses and other carbohydrates found in the by-products of pineapple juice
processing are lost (Abdullah, 2008).
By combining these three products, there should be a room for improvement and
innovation as these products were never mixed previously into a single snack. Also, the
resulting product should be nutritious similar to the food programs developed by the
Department Of Health in the early 90s. The main purpose of this study is to develop a
formulation of a breakfast cereal snack that is nutritious, cheap and enjoyable to the
younger generation and supplement the nutrients and fiber content of commercial breakfast
cereals snacks.
3
OBJECTIVES
The general objective of the study is to provide a formulation for breakfast cereal
snacks and explore the potential of adlai, pineapple and carrots. Specifically, this study
aims to:
1. Determine the operating parameters that can be controlled and modelled for
formulating a breakfast cereal snack;
2. Determine the optimum combinations of the operating parameters for
formulation of breakfast cereal snack;
3. Establish appropriate formulation for breakfast snack using powdered carrots,
powdered pineapple and adlai powder;
4. To determine the physico-chemical properties of the breakfast cereal snack and;
5. To evaluate the acceptability of the formulated breakfast cereal snack.
SCOPE AND LIMITATIONS OF THE STUDY
The study is only limited to adlai powder extruded with pineapple powder and
carrots powder using a piston-type extruder.
All preparations, processing and experiments were conducted at the Institute of
Food Science and Technology, University of the Philippines Los Baos. Adlai flour was
sieved in the Pilot Plant of the facility. Cooking and preparation was done at the L1 room
and Pilot Plant of the facility. Physico-chemical testing was done at the Food Engineering
Laboratory. Proximate Analysis was done in the Student Labortory and Instrument Room.
The sensory evaluation was done in the University of the Philippines Los Baos campus.
The study was conducted from January 2015 to July 2015.
4
REVIEW OF RELATED LITERATURE
Adlai: Biographical description, proximate analysis and cultivation
Adlai (Coix lacryma-jobi L), is also known as Chinese barley, or Jobs tears (Figure
1). It is an annual crop in a temperate zone but a perennial crop where winter is absent or
mild. The branching of this crop is upright or ascending herb which grows 1-2m tall. The
cordate clasping leaf blades of adlai measures 20-50 cm long, 1-5 cm broad. The grains
are colored white to bluish white, or black, globular orvoid, 6-12 mm long. The crop is a
native to Southeast Asia, but now rather pantropical as cultigen and weed. It is considered
a serious weed in Polynesia, a principle weed in Italy and Korea and a common weed in
parts of South America, China, India, Nepal, and Southeast Asia. The ecological condition
of the Philippines can be contributed to adlais propagation. The optimum range of annual
precipitation is from 6.1 to 42.9 dm, an annual temperature of 9.6 to 27.8 oC and a soil pH
of 4.5 to 8.4. The yield varies as to strains cultivated in different countries. In the
Philippines, yield of unhusked grains is about 3.5 T /ha and loss in hulling is about 30-
40%.
Adlai is generally vulnerable to fungi attack. List of fungi that attacks adlai includes
Cladosporium herbarum, various Fusarium species such as F. equiseti, F. graminearum,
F. monolifrome, F. semitectum, T. taiana, Uredo operta and Ustilago coicis. It is also
vulnerable to Leaf-gall virus and nematode (Meloidogyne incognita acrita). Among others
that attack the plant are rodents and parrots (Duke, 1983). The proximate analysis of adlai
grains and flour is listed in Table 1.
5
Figure 1. Adlai crop (Peaflor, 2013).
Table 1. Proximate analysis of polished adlai grains and adlai flour (Vilbar,
2014).
In the Philippines, adlai is harvested 5-6 months after planting. Most of the process
operation is similar to rice. The grains are dehusked, milled and air dried to 13% moisture
content in a cool and dry place. The adlai is milled through rice and corn mills with up to
6
50% milling recovery depending on varieties. In the Philippines, 4 varieties are commonly
seen (Figure 2).
Figure 2. Varieties of adlai. (A) ginampay, (B) kibua, (C) gulian and (D) tapol
(Vilbar, 2014).
Nutritional components of pineapple and carrot juice
processing by-products
Among the most available by-products available in the canning industry are
pineapple waste pulp and carrot pomace. Pineapple (Ananas comoscus L.) also called as
King of Fruits is one of the most popular non-citrus tropical and subtropical fruit.
Pineapple is processed into various food products such as jam, jelly, beverage and
concentrate. These processes produce large amount of solid wastes such as skin and core.
In perspective, the production of canned pineapple was estimated at about 48 million
standard cases as against 41 million standard case tones in 1996, an increase of almost 16%
7
in the year 2008-2011 (Kothakota, 2013). In the by-products, a good amount of cellulose,
hemicelluloses and carbohydrates are available. These components should increase the
fiber content of a food material once it is added on a product. The chemical composition
of the processed pineapple in Table 2 shows 29.86% crude fiber and 20.4% ascorbic acid
are available which is adequate when incorporated with other foods.
Table 2. Proximate analysis of pineapple, pineapple (air-oven dried) and carrots
powder. (Ackom 2012, and Gazzali, 2014).
Meanwhile, carrot pomace is also an underutilized produce. Carrot (Daucus carota S.) is a
root vegetable, usually orange, purple red, white or yellow in color with a crisp texture
when fresh. The total production of carrot and turnips was estimated as 27.386 million tons
in the world during year 2008. It is a rich source of beta carotene and contains other
vitamins, like thiamine, riboflavin, vitamin B-complex and minerals. Carrot pomace is a
by-product of carrot juice processing. The juice yield in carrots is only 60-70% and even
up to 80%. Carrots has good amount of vitamins, minerals and dietary fiber. However, left-
over pomace produced after juice extraction of carrots does not find proper utilization.
Moreover, carrot pomace is quite perishable as it contains about 88 % of moisture.
However, processing carrot pomace into powder may prolong the shelf life of these
products. Dried carrot pomace has beta-carotene and ascorbic acid in the range of 9.87 to
8
11.57 mg and 13.53 to 22.95 mg per 100 g, respectively (Upadhyay, 2008). A promising
way to utilize the by-products of pineapple and carrot juice processing is to make them in
dried, powdered form and incorporate them into extrudates.
Micronutrient malnutrition
Micronutrient malnutrition is widespread in the industrialized nations. Young
children and women of reproductive age tend to be among those most at risk of developing
the deficiency but can affect all age groups. Worldwide, the three most common forms of
micronutrient malnutrition are iron, vitamin A and iodine deficiency. Throughout the
world, iron deficiency is the most prevalent and an estimate of 2 billion people are affected
at it and 254 million preschool-aged children are vitamin A deficient.
Food fortification. Food fortification refers to the addition of micronutrients to
processed foods. In many situations, this strategy can lead to relatively rapid improvements
at very reasonable costs. In fortifying foods, there must be an adequate amount of
consumption from the target population. Trials conducted in the Philippines revealed that
fortification of monosodium glutamate with vitamin A produces a positive effect on
mortality, improved growth and hemoglobin level in children. Later studies with preschool-
aged children, who consumed 27 g of vitamin A- fortified margarine per day for a period
of 6 months, reported a reduction in the prevalence of low serum retinol concentrations
from 10-26%. Wheat flour fortified with vitamin A and fed as buns to Filipino school
children for 30 weeks had the effect of halving the number that had low liver stores of the
vitamin.
9
Recommended nutritional intake and upper
level intake of commercial cereals
Dietary fiber. Dietary fibers have important physiologic properties. The dietary
reference intakes and dietary guidelines recommend a daily fiber intake of 14 g/1000
calories consumed. Despite the broad range of potential health applications attributed to
dietary fiber, including the treatment of colonic disorders, lower risk of heart disease,
diabetes and colon cancer, the proportions in which they should be fed is not yet optimized.
An increase in fiber in the diet has shown different effects on the body mainly fecal weight
which has increased from 2.8 g to 5.4 g. Another effect of dietary fiber consumption are
increase in H2 production in breath and increase in feeling of bloating and flatulence as an
indication of fermentation activity of bacteria (Vuskan 2008).
Vitamins and minerals. The cereal snack fortified with vitamins and minerals
provide at least 25% of daily requirements for essential vitamins and 17% for iron.
Commercially fortified breakfast cereals is an excellent source of folic acid which
contributes 15% of the daily intake. It also includes vitamin B1 with providing 14% of
overall daily intake. Riboflavin and niacin of breakfast cereals are 15% and 10% of daily
intake respectively and vitamin B6 which is 13% of average daily intake (Gregory, 2004).
Tolerable upper intake levels. Upper Intake Level (UL) is the highest level of daily
nutrient intake that is likely to pose no risk of adverse health effects to almost all individuals
in the general population. Unless otherwise specified, the UL represents total intake from
food, water, and supplements. In the absence of a UL, extra caution may be warranted in
consuming levels above recommended intakes. Members of the general population should
be advised not to routinely exceed the UL. The UL is not meant to apply to individuals
10
who are treated with the nutrient under medical supervision or to individuals with
predisposing conditions that modify their sensitivity to the nutrient.
According to Table 3, the UL of vitamin A and fiber as per se is not defined.
Table 3. Dietary Reference Intakes (DRIs): Tolerable Upper Intake Levels, (Vitamins
Food and Nutrition Board, Institute of Medicine, National Academies) (1998).
Extrusion
Extrusion technologies are efficient manufacturing processes in food industries.
Their main role was developed for conveying and shaping fluid forms of processed raw
materials, such as dough and pastries. Today, their processing factions may include
conveying, mixing shearing separation, heating or cooling, shaping, co extrusion, venting
volatiles and moisture, flavor generation, encapsulation and sterilization.
11
Figure 3. Changes in raw materials in an extrusion cooking process (Guy, 2000).
Principles. The principles of operation in all types of extruders are: raw materials are
fed into the extruder barrel and the screw(s) or piston then convey food along barrels.
Further down the barrel, smaller flights restrict the volume and increase the resistance to
movement of food. As a result, food material fills the barrel and the spaces between screw
flights and becomes compressed resulting into a semi-solid, plasticized mass.
Classification of extruders. Extruders are classified into two types according to
operation: hot and cold extruders.
Based on type of construction extruders are classified into: Single screw and twin
screw extruder
Hot and cold extrusion. Two processes may be done in an extruder. In hot
extrusion, frictional heat and any additional heating that is used cause the temperature to
rise rapidly. The food is then passed to the section of the barrel having smaller flights,
where pressure and shearing is further increased. Food material is then forced through a
die at the end of the barrel as the food emerges under pressure from the die; it expands to
the final shape and cools rapidly as moisture is flashed off as steam.
Cold extrusion otherwise remains at ambient temperature and is used to mix and
shape foods such as pasta and meat products. Low pressure extrusion at temperatures below
100oC is used for products such as, liquorice, fish pastes, surimi and pet foods.
12
Single or double-barrel extruder: Segmented screw/barrel single-screw wet
extruders consists of a live bin, feeding screw, preconditioning cylinder, extruder barrel,
die and knife. Single-screw extruders have relatively poor mixing ability and are usually
supplied with preconditioned material with added steam or water.
Recent years have seen increasing prospects for new products with intricate shapes
and small sizes that are beyond the capabilities of single-screw systems. Twin screw
extruders are developed to fill its inadequacies. The term twin-screw applies to extruder
with two screws of equal length placed inside the same barrel. Twin screw extruders are
more complicated but provide much more flexibility and better control. Twin extruders are
categorized as counter rotating and co rotating twin screw. In the counter rotating position
the extruder screw rotates in the opposite direction while the co rotating acts otherwise.
Co-rotating self-wiping types of extruders are most commonly used in the food industry.
The limitations for single and twin-screw machines are respectively 4% and 20%
fat, 10% and 40% sugar, and 40 and 65% moisture. There is therefore flexibility using
different raw materials when using twin screw against single screw extruders.
Hydraulic-type piston extruder. Most piston extruders are used in foodstuffs in
making pastas and in other industries such as shaping aluminum. These extruders operating
in batch-type extrusions and are advantageous for their economical operation, maximum
product yield and minimal feed accumulation. Another advantage of these extruders are
their high pressure forces which are beneficial for products with very low moisture content.
This type of extruder is typically used for pilot processing and for experimental purposes
due to their ability to produce smaller batches and the easy interchangeability of the die.
The parts of the piston type extruder are; hydraulic piston, base frame and press frame and
the press ram. The hydraulic piston can be water-charged or oil charged. The base frame
13
design relies on the weight and the design of the whole piston assembly. The press ram is
sheathed inside a barrel in which applied force is concentrated inside the barrel thus forcing
the product material into a die.
Physical properties that affect extrusion. The specific gravity is used to calculate
volumetric flow and degree of fill of the screws. The thermal properties are specific heat,
melting point, the enthalpy of fusion and thermal conductivity. Specific heat of foodstuffs
varies from 1500 to 2500 J/kg-K depending on nature and state of material. Additive rule
is used if a material is mixed with different materials. Thermal conductivity lies between
0.1 and 0.5 W/m-K.
Effect of extrusion to different food components
Carbohydrates. Carbohydrates are involved in numerous chemical reactions when
undergoing extrusion. Extrusion cooking is unique due to gelatinization of carbohydrates
occurring in much lower moisture levels (12-22%). Gelatinization may occur but it may
not be complete. The presence of other food compounds such as lipids, sucrose, dietary
fiber and salts affect gelatinization. An increase in temperature, shear and pressure
increases the rate of gelatinization. Starch is predigested when it undergoes extrusion where
amylopectin molecules are easily sheared off in the barrel. In a study, fiber values more
than doubled when 7.5% citric acid was mixed with cornmeal. 30% high-amylose
cornstarch with 5-7.5% citric acid resulted in values of 14% which is 2% more against
100% cornmeal when extruded. The authors of the study speculated that polydextrose may
have been formed inside the extruder. Yield of polymers increased with temperature in
which 93.7% yield was observed at 200oC. (Kumari, 2006).
14
Proteins. Extrusion improves protein digestibility via denaturation which exposes
enzymes-access sites. Denaturation is more pronounced under high shear extrusion
conditions although mass temperature and moisture are also important influences. Since
most extruded products are not high in protein, nutritional evaluation of extruded feeds,
weaning foods and other specialized products have been emphasized. High barrel
temperatures and low moistures promote Maillard reactions. Some studies show that
reducing sugars can also react to lysine thereby lowering protein nutritional value (Kumari,
2006).
Lipids. Foodstuffs that contain less than 10% lipids are extruded because greater
quantities reduce slip within the extruder barrel making extrusion difficult particularly for
expanded products. Lipid oxidation is a major cause of nutritional and sensory qualities in
foods and feeds. However, lipid oxidation does not occur during extrusion due to brief
residence time and occurs more during storage time. Screw wear results in formation of
oxidative rancidity. This is due to the metal shavings from the barrels being incorporated
into the food and acts as a catalyst for oxidation of lipids in foodstuffs.
Dietary fiber. Dietary fiber is the edible part of plants and analogous carbohydrates
that are resistant to digestion and absorption in the human small intestine with complete or
partial fermentation in the large intestine. Dietary fiber includes polysaccharides,
oligosaccharides, lignin, and associated plant substances. Extrusion did not affect uronic
acids (components of pectin) but insoluble non-starch polysaccharides (NSP) increased in
oatmeal and potato peels. Soluble NSP was higher in extruded oatmeals and potato peels,
and corn meal fiber was unaffected by extrusion. Beans which are hard-to-cook, were
extruded under various conditions in order to make them more functional.
Table 4. Nutritional effects of dietary fiber extrusion (Guy, 2000).
15
Total fiber values were unaffected by extrusion but insoluble fiber decreased when
extruded at 25% moisture content. Soluble fibers increased especially in a sample
processed at 30% moisture and 180oC. Increased levels of soluble fiber in citrus peels after
extrusion were correlated with increased in vitro viscosity. However, starch digestion and
diffusion of glucose were not affected by extrusion. Extrusion reduced sugar beet pectin
and hemi-cellulose molecular weight and viscosity. But water solubility increased 16.6%
to 47.5% (Kumari, 2006).
Vitamins. Fortification of extruded foods with micronutrients is popular. The
concern for post process loss of vitamins is aided through spraying of vitamins in the
extruded products. Studies for current vitamins in extruded products focuses more on
stability post process especially folic acid which is typically needed by pregnant women.
Vitamins D and K are fairly stable during food processing, and they are not commonly
used in extruded human foods. In some studies, tocopherols and retinyl palmitate decreased
in puffed snacks containing either fish or partially defatted peanut flour. Rice bran
tocopherol decreased with increasing extrusion temperature, and bran extruded at 120-
140oC lost more tocopherols over a years storage than did bran extruded at 110oC (Shin
et al., 1997). Ascorbic acid is lost in the presence of heat and oxidation. Ascrobic acid
16
decreased in wheat flour when extruded in higher barrel temperatures at low moistures at
around 10%. When ascorbic acid was added to cassava starch to increase starch conversion,
retention of over 50% occurred at levels of 0.4-1.0 % addition. Vitamin A is destroyed by
oxygen and heat. Beta-carotene is added to make foods more orange in color but it is
unstable when heated. Increasing barrel temperatures from 125 200oC resulted in more
than 50% destruction of all trans beta carotene in wheat flour (Kumari, 2006).
Minerals. High fiber foods may abrade the interior of extruder barrel and screws,
resulting in increased mineral content. Previous studies resulted in iron content in extruded
potato flakes increased with barrel temperature. Screw wear iron had high bioavailability
in rats fed with extruded corn and potato. Extrusion and any resulting changes in mineral
content did not reduce utilization of iron and zinc from wheat bran and wheat in adult
human volunteers. Another study shows that extrusion did not compromise the zinc
bioavailability of 85:15 blends of semolina and soy protein concentrate.
Breakfast cereal snacks
Preprocessed cereal-based products, like ready-to-eat cereals to be eaten directly
out of the packaging are relatively new. Since they were first introduced by W.K. Kellog
in the United States, cornflakes have initiated a vigorous development of the breakfast
cereal industry. The world consumption of cereal snacks amount to about 3 million tons.
However, there is an unequal distribution of production throughout the world. The main
cause of this discrepancy is depending upon the population food culture and degree of
development. Breakfast cereal manufacturers aim to supply products for children and pay
attention to taste (sweet flavorings), texture (crispiness), and nutrition (vitamins and
minerals, in particular).
17
Market analysis in the Philippines by Euromonitor was made in 2013 (Table 5).
According to the report, the breakfast cereals market volume sales are set to increase 4%
in 2012 with a compound growth annual interest of 4% from 2012-2017. Convenience is
the key driver of breakfast cereal growth. The childrens breakfast cereals was expected to
see fastest current value growth of 8% in 2012. With more young adults joining workforce
and an increase in the expansion of business process outsourcing in the Philippines,
demand for convenience plays an essential role in changing consumer habits. More adults
continue to consume breakfast cereals in morning as a quick meal. Hot cereals as of the
moment is expected to account for 52% of the breakfast cereals value in 2012. However,
growth of hot cereals has been slower compared to RTE (ready-to-eat) cereals which are
marketed to be fortified with multivitamins and are usually marketed as complete
breakfast meal that would cover all ones nutritional needs. These products tend to target
the middle income segment in the Philippines. The popularity of breakfast cereals stems
from nutritional content mainly energy (350-400 kcal/100 g), nutrients (vitamins, minerals)
and health oriented components (dietary fiber).
Table 5. Sales of Breakfast Cereals by Category: Volume 2007-2012 (Euromonitor, 2013).
Types of
breakfast
cereals
2007 2008 2009 2010 2011 2012
(ton) (ton) (ton) (ton) (ton) (ton)
Hot cereals 9130.00 9449.60 9,733.00 10,054.20 10,406.10 10,780.70
RTE Cereals 3,171.60 3,349.50 3,451.20 3,573.00 3,706.80 3,850.90
-Childrens 2,521.90 2,698.40 2,806.40 2,924.20 3,040.00 3,184.20
-Family 649.70 651.00 644.80 648.80 656.90 666.70
-General 12,301.60 12,799.00 13,184.20 13,627.30 14,133.00 14,631.60
18
Breakfast cereal snacks and extrusion cooking. Over the years, extrusion
cooking has played an important role in developing breakfast products. It is made through
a new cooking concept thermomechanical high temperature short time (HTST) cooking
against the traditional hydrothermal cooking. Currently, there are 2 types of extrusion-
cooked breakfast cereals can be found on the market which are;
Directly expanded extrusion cooking which uses cereals with very low moisture
content (usually 20% below) and relies on highly mechanical cooking. The process relies
more in the mechanical forces which cooks the cereals.
Pellet-to-flakes extrusion cooking which uses cereals on higher moisture in the
range of 22-26% which relies more on thermal components against mechanical forces.
Generally, breakfast cereal extrusion cooking processes involve low moisture
contents (below 25-26%) and high temperatures (above 130-140oC). In such conditions,
starch granules undergo not only gelatinization but also melting due to shear forces. In
extrusion cooking, much parameters of concern as independent variables include screw
speed, moisture content, screw configuration, die temperature etc. while dependent
variables or product outcome parameters include Water Absorption Index, WAI; Water
Solubility Index, WSI; expansion index, bulk density, hardness and sensory characteristics.
(Kothakota, 2013).
Drying and toasting of breakfast cereals. Drying is an essential part of breakfast
cereal processing apart from water removal. It aims to finalize the crispy and crunchy
texture of products by reducing moisture content to the level at which cereal polymers are
in the glassy state. By combining drying with toasting generates blistering and specific
brown color which gives good sensory characteristics. Sensory characteristics such as
19
blistering and a specific brown color gives a bakery taste in breakfast cereal snacks (Guy,
2000).
20
MATERIALS AND METHODS
Materials
Milled Adlai grains was obtained from Southern Tagalog Region Integrated
Agricultural Research Center (STIARC) in Lipa City, Batangas. The carrots was purchased
in a local market in Binan, Laguna and the pineapples was purchased in a local market in
Tagaytay City.
Methods
Preparation of sample powders. Adlai grains was ground using a pin mill. The
powder was passed through mesh 80. The other samples that did not pass through the mesh
had undergone size reduction repeatedly until most of the powder can pass through the
mesh.
The pineapples were washed, peeled, and was processed through a pulper. The pulp
was collected and separated from its juice through the use of a strainer. The pulp was then
dried at 50oC overnight then was grinded to a powder that can pass through a sieve with 80
mesh.
The carrots were washed, peeled and was processed through a pulper. The pulp that
were collected had undergone separation from its juice through the use of a cheesecloth.
The pulp were then dried at 50oC overnight. The resulting product was run through a pin
mill with a mesh 80 sieve. The resulting product was collected as carrot powder.
The adlai, pineapple and carrots powder was subjected to moisture content analysis
using an Ohaus moisture meter.
Preparation of the breakfast cereal snacks. The three components mainly; adlai
powder, dried pineapple powder and dried carrot powder were mixed into different ratios.
21
The prepared mixtures were adjusted with different moisture contents. The samples were
steamed to obtain a semi-gelatinized texture, cooled and was extruded through a piston
extruder with a 13 mm circular diameter die. The samples are then sliced with a blade and
was dried at 50oC overnight. Figure 4 shows the flowchart for making the breakfast cereal
snacks.
Figure 4. Process flowchart for breakfast cereal snacks.
Preparation of samples. Three sample powders were prepared in the study
namely; adlai, pineapple and carrots are shown in figure 5.
Piston
Extrusion
1. Adlai
2. Pineapple
3. Carrots
Mixing
Gelatinization
Water
Cutting Drying
Breakfast
Cereal Snack
22
Figure 5. Powdered samples: (A) Adlai powder; (B) Carrots powder; (C)
Pineapple powder.
Mixing. The three powders were mixed to their respective ratios weight/weight
with a fixed ratio of 50:50 for pineapple and carrots powder. Then, water was added to
adjust the mixture moisture content into three levels. Figure 6 shows the mixed powder.
Figure 6. Mixed powder
23
Extrusion. After achieving a semi-gelatinized mixture, the mixture was extruded
through a piston-type extruder with a die measuring 13mm diameter (Figure 7) and cut into
desired shape.
Figure 7. Piston-type extruder.
Drying. The extruded cereals are dried using a cabinet dryer (Figure 8) for 24 hours
at 50 oC temperature. This was set in order to prevent case hardening of the samples which
might affect different attributes of the product. After drying, the final product was obtained
(Figure 9). The cereals are then subjected into different tests to acquire the following;
24
Figure 8. Cabinet dryer.
Figure 9. Breakfast cereal snack final product
25
Physical attributes
Bulk Density. Bulk density is obtained by using a standard measuring cup where
the cup was filled with the samples until it overflowed. The samples are then scraped and
weighed on a tared measuring cup. The volume of the measuring cup and the weight of the
samples were obtained.
Extruded cereal moisture content. The samples were analyzed before dried. 5
grams of sample was weighed per treatment and were analyzed using an Ohaus moisture
meter.
Water Absorption Index. The Water Absorption Index (WSI) was obtained by
submerging the samples in a beaker for 30 minutes and was centrifuged to 3000 g for 15
minutes. The supernatant was removed. The initial weight of the powdered final product
and the gel produced was recorded.
Chemical analysis
The AOAC method for proximate analysis was followed in order to obtain
numerical values for chemical components such as the final moisture content of breakfast
cereal, crude fat, ash, crude protein, crude fiber and carbohydrate content. The results from
chemical analysis are compared with the values from Composition of foods: Breakfast
cereals: raw, processed, prepared (Douglas, 1982).
Sensory evaluation
Twenty (20) panelists were asked to score samples in terms of appearance, flavor,
aftertaste, texture and general acceptability using a 9-point hedonic scale. Quality scoring
was used in order to numerically categorize the samples. The scores were evaluated using
a scoresheet prepared.
26
Statistical Analysis
In formulating of the adlai :pineapple-carrots breakfast cereal snacks, the
independent variables are coded as X1 (adlai-carrots-pineapple mixture, g/g) and X2
(moisture content of the mixture, %). The dependent variables are coded as Yx. The
responses include; Y1 (extruded cereal moisture content), Y2 (bulk density), Y3 (water
absorption index), Y4 (final breakfast cereal moisture content), Y5 (crude fat), Y6 (ash
content), Y7 (crude protein), Y8 (crude fiber), Y9 (carbohydrate content), Y10 (appearance),
Y11, (flavor), Y12 (aftertaste) and Y13 (texture) and Y14 (general acceptability).
The independent variables were the following: (1) Mixture moisture content, %.
defined as the amount of moisture present in the mixture of adlai, pineapples and carrot
powders. This variable was held at three levels depending on the results of preliminary test
runs; (2) Adlai:pineapple-carrots ratio, g/g. defined as the combination of adlai, pineapple
and carrots that were present in the sample. The ratio between pineapples and carrots were
held at 50:50 while being varied with adlai. This variable was held at three levels
depending on the results of preliminary test runs.
The dependent variables were the following (1) Bulk density, g / ml. the bulk
density is used to check the actual, ungrounded density of the product; (2) Extruded cereal
moisture content, %. the moisture content of the extruded breakfast cereals before drying;
(3) Water solubility index, g gel/ g solids. the water solubility index is the ratio of the
weight of the gel produced when powdered final product was submerged in liquid and the
weight of the powdered final product; (4) Final Breakfast Cereal Moisture Content, Dry
Basis, %. defined as the moisture content of the final product; (5) Crude Fat, %. defined
as the amount of fat that can be extracted in the sample; (6) Ash Content, %. defined as the
amount of incombustible material left after ignition of sample. It is also a rough estimate
27
of mineral content of the samples; (7) Crude Protein, %. defined as the amount of titratable
nitrogen in the sample; (8) Crude Fiber, %. Defined as the amount of indigestible starches
in the sample; (9) Carbohydrates, %. defined as Nitrogen Free Extract. It is the amount of
carbohydrates available in the sample; (10) Appearance. defined as the visual appeal of the
product. Involves the colors, pore development and curvature of samples; (11) Flavor.
defined as the total appeal of the product involving taste and aroma; (12) Aftertaste. defined
as the tartness of the product; (13) Texture. defined as the crunchiness of the sample when
eaten. A balance between cohesiveness and crumbness was explained to be a desirable
measure of the cereals in presence of bite pressure which may be considered as crunchiness;
(14) General acceptability. defined as the overall experience felt by the judge after
ingestion of sample.
Experimental Analysis
In the analysis for optimization of formulation of adlai-pineapple-carrots breakfast
cereal snacks, a full factorial, two-factor, three-level experiment was used to obtain
optimum combinations for the product. The design has produced 9 runs using a face
centered option. Independent variables coded as X has corresponding levels as -1, 0 and
1+ with 0 as center point. Mixture moisture content is coded as X1 and adlai:pineapple-
carrots ratio as X2. Table 6 shows the experimental design using central composite design
that was used in the experiment for formulation of adlai-pineapple-carrots breakfast cereal
snacks. Table 6 also presents the independent variables as they are coded in the
optimization study. Corresponding values of L1, L2 and L3 was based on the results of the
preliminary test runs.
28
Table 6. Design matrix of a full factorial, two-factor, three-level experimental design.
Table 7. Independent variable used in acceptability test.
Optimization of formulation for breakfast cereal snack
Response Surface Methodology (RSM) was used in order to optimize the results
obtained. This was carried out by Design Expert software. Using the optimization function
of the software, an optimum point was established. This optimum point represents the
processing conditions wherein all set physical, chemical and sensory properties overlaps.
Formulating breakfast cereal from adlai, pineapple and carrots using the optimum
combination would deliver product with superior qualities.
Central Composite Design
Run Numbers X1 X2
1 -1 -1
2 1 -1
3 -1 1
4 1 1
5 -1 0
6 1 0
7 0 -1
8 0 1
9 0 0
INDEPENDENT
VARIABLES
SYMBOL
CODED VARIABLE LEVELS
Coded Uncoded -1 0 1
Adlai : Pineapple-
carrot and ratio (kg/kg) X1 PCAR 60:40 70:30 80:20
Moisture content (%) X2 MC 35% 40% 45%
29
In the optimization process, the results from available literatures, preliminary
testing results, and on-point observation served as a basis for setting the acceptable
boundaries or target values of each response in the formulation of breakfast cereal snacks.
The criteria set for acquiring the optimum combination were:
1. Bulk density, the target value was set 0.65 g/ml based on the index by
FAO/INFOODS density database.
2. Extruded cereal moisture content, the target value was set at 40% in order for the
product to gel and aid in the cutting of the extrudate.
3. Water Absorptivity Index, the target value was set at 2.5g gel/g solids in order for
the cereals to absorb more moisture by mixing it to liquid material (i.e milk) without
changing its properties and produce a soggy texture.
4. Breakfast cereal final moisture content, the target value was set at 10% for good
balance between having good sensory characteristics and adequate storage time of
the product.
5. Crude fat, the target value was set at of 2% which is a good fat content value for
consumer preference based on low fat food. It is also advantageous for storage
conditions as it prevents early onset of oxidative rancidity.
6. Ash content, the target value was set at 5% which is identical to commercial
breakfast cereal snacks.
7. Crude protein, the target value was set at 6%. It is identical to commercially
available cereals and lessens the risk of proteolytic degradation during storage
conditions.
8. Crude fiber, the target value was 5% as compared to commercial breakfast cereals.
30
9. Carbohydrate content, the target value was set at 65-70% which is the carbohydrate
content of most cereals snacks and most of the grains.
10. Appearance, the target value was set above 4 based on the scale of commercial
breakfast cereal.
11. Flavor, the target value was set above 4 based on the scale of commercial breakfast
cereal.
12. Aftertaste, the target value was set above 4 in order to quantify the slight tartness
of the cereal as produced from addition of the pineapple powder in the sample.
13. Texture, the target value was set above 4 to score the crunchiness of the sample.
14. General acceptability, the target value was set above 4 as a good measure for the
overall mouthfeel of the sample.
Verification
Verification of the response models was made in order to test the precision of the
generated values against experimental values. The resulting values of the independent
variables that were obtained through Design Expert were used in formulating breakfast
cereals. The breakfast cereals that were made with optimum mixture moisture content and
ratio was subjected to physical, chemical tests and sensory evaluation. The resulting
values obtained from these tests were compared with the predicted data that was generated
and the percent difference was computed.
% = 100/
31
RESULTS AND DISCUSSION
Moisture content of raw materials
The moisture content of the raw materials is very essential to the study. The initial
moisture content of the raw materials were listed in Table 8. Pineapple powder has the
highest moisture content of 15.42 % wet basis while adlai had the least moisture content
at 8.54%. The pineapple had the highest moisture content due to being processed from a
fresh product. This is in contrast with adlai which has a relatively low moisture content
due to the grains being dried prior to storage.
Table 8. Moisture content of the powdered treatments.
Powdered
Treatments
Moisture Content
Wet basis (%) Dry basis (%)
Adlai 8.54 9.33
Pineapple 15.42 18.23
Carrot 9.56 10.57
Effect of Independent variables on the formulation
of the adlai :pineapple-carrots cereal
The effect of independent variables on the optimization of formulation for adlai-
:pineapple-carrots was achieved using Response Surface Methodology. The results from
the experimental data gathered from the formulation of adlai-pineapple-carrots breakfast
cereal snacks are shown in Table 9 and Table 10.
32
Table 9. Effect of independent variables on the physico-chemical composition of the sample.
Legend = Highest Lowest
Sample
Run
Independent Variables Dependent Variables (physicochemical analysis)
Mixture
Moisture
Content adlai:pineapple-
carrots ratio
Bulk
Density
Extruded
Cereal
MC
Water
Absorptivity
Index
Breakfast
Cereal
Final
MC
Crude
Fat
Ash
Content
Crude
Protein
Crude
Fiber
Carbohydrate
content
(%) g/ml (%) g gel/ g
solids (%) (%) (%) (%) (%) (%)
1 30 60:40 0.56 37.13 3.00 8.08 4.07 5.81 10.29 6.04 65.71
2 45 60:40 0.67 35.56 2.40 9.60 1.57 3.65 8.25 2.17 74.76
3 30 80:20 0.79 33.23 2.60 11.68 3.05 2.44 6.93 2.63 73.27
4 45 80:20 0.81 41.76 2.15 13.62 1.29 1.22 4.37 1.67 77.83
5 30 70:30 0.76 35.18 2.65 10.07 3.85 4.97 9.67 4.77 66.67
6 45 70:30 0.78 37.50 2.28 11.36 1.41 2.38 7.07 1.68 76.1
7 35 60:40 0.65 36.35 2.59 9.59 2.89 4.97 7.80 2.52 72.23
8 35 80:20 0.77 38.66 2.40 13.49 2.00 2.91 7.07 2.39 72.14
9 35 70:30 0.79 37.76 2.59 11.23 2.07 2.93 7.46 2.51 73.8
33
Table 10. Effect of independent variables on the sensory scores of the sample
Legend = Highest Lowest
Physical Properties
Bulk Density. Bulk density is a property of powders, granules and other divided
solids. It is the mass of the foodstuffs in a given volume and increases with compaction.
The density also provides a rough estimate of the air spaces developed from processing
foods. Treatment 4 with with 0.81 g/ml which has a combination of 45% mixture moisture
content and 60:40 adlai:pineapple carrots ratio has achieved the highest bulk density of the
treatments. The least dense of all treatments is treatment 1 with 0.56 g/ml which has a 30%
mixture moisture content and 60:40 adlai:pineapple-carrots ratio. The rest of the results are
shown in Table 9. Proper gelatinization and higher expansion is attributed to lower mixture
moisture content. Whereas further increase in bulk density can be attributed to the
reduction in elasticity of dough and lower expansion available for it. However, it is also
noted that increase in bulk density may also be attributed with the water binding capacity
of non-starch polysaccharides (Kothakota, 2013). It must also be noted that an inversely
proportional relationship of bulk density and lateral expansion has been observed with the
Independent Variables Dependent Variables (Quality Scoring)
Sample
Run
Moisture
Content
(%)
Combination Appearance Flavor Aftertaste Texture General
acceptability
1 30 60:40 5.93 3.73 3.67 4.44 5.60
2 45 60:40 6.20 5.53 5.07 3.93 6.27
3 30 80:20 4.80 5.80 6.47 5.13 4.47
4 45 80:20 4.57 4.80 4.73 6.46 3.87
5 30 70:30 5.20 4.60 4.00 4.07 5.73
6 45 70:30 4.80 5.40 5.27 5.27 4.53
7 35 60:40 5.03 5.67 4.73 4.67 4.80
8 35 80:20 4.40 6.07 5.13 5.07 4.47
9 35 70:30 5.10 4.86 4.73 4.73 5.34
34
change in process variables. The bulk density initially increased as the carrot powder was
also increased. However, further addition of fibrous material against carbohydrate content
saw a decrease in bulk density due to the light mass of fibrous carrot powder against other
constituents. Analysis of variance suggests that the adlai:pineapple-carrots ratio is the
significant term (p
35
Figure 10. Contour plot of bulk density as a function of mixture moisture content
and adlai:pineapple carrots ratio.
The high bulk density in junction with a low pineapple-carrots content was achieved due
to the effect of the fibers from carrots and pineapple having less mass against the adlai
powder.
Extruded Cereal Moisture Content. The extruded cereal moisture content is the
actual moisture of the treatments before the products are dried. Previous study by Peaflor
(2013) suggests that a directly proportional relationship was observed between mixture
moisture content and extruded cereal moisture content. The extruded cereal moisture
content is affected by colligative properties of species like carbohydrates, proteins and
other undissolved ingredients in junction with water binding, dissociation of water,
solubility of solutes. These phenomena can be a controlling factor usually from the state of
prevailing conditions (glassy or rubbery state).
The highest extruded cereal moisture is treatment 4 with 41.76% which has a
combination of 45% mixture moisture content and an 80:20 adlai:pineapple-carrots ratio.
The least extruded cereal moisture content is treatment 3 with 33.23% which has a
combination of 30% mixture moisture content and 80:20 adlai:pineapple-carrots ratio. The
rest of the results are shown in Table 9. Analysis of variance states that the mixture
moisture content (P< 0.01), adlai:pineapple-carrots ratio (P< 0.10) and the interaction
between the variables (P< 0.01) are affecting extruded cereal moisture content.
Response surface regression yielded the following equation:
= 112.27139 2.150441 1.185582 + 0.03366712
36
The R-squared value is 0.9378 which is a good fit. Linear term was non-significant while
the quadratic term (P< 0.05) and two-function interaction (P< 0.01) was significant. The
contour plot analysis of extruded cereal moisture content as a function of mixture moisture
content and adlai:pineapple-carrots ratio in Figure 11 shows that the a high extruded cereal
moisture content is achieved by having a high adlai content and a high mixture moisture
content. This phenomena can be explained by the directly proportional relationship
between the addition of water and the increase in extruded cereals moisture content.
Figure 11. Contour plot for the extruded cereal moisture content as a function of
mixture moisture content and adlai:pineapple-carrots ratio.
Water Absorptivity Index. The values of water absorption index obtained from
the treatments were very close with each other. Water absorption index is a measuring
index of gelatinization. The highest water absorption index was that of treatment 1 with
3.00 g gel/g solids with a combination of 45% mixture moisture content and 60:40
37
adlai:pineapple-carrots ratio. The lowest water absorptivity index is treatment 4 with a
combination of 45% moisture content and a 80:20 adlai:pineapple-carrots ratio. A study
by Dorsey-Redding (1990) modelled the function of mixture moisture content against
water absorption index. The study concluded that an inversely proportional relationship
exists. The rest of the results are shown on Table 9. Studies made by Altan (2008) observed
that an increase in moisture content decreases the water adsorption index. The study
explained that the decrease in WAI is attributed to the competition of absorption of water
between pineapple pulp and the available starch. Analysis of variance shows mixture
moisture content (P< 0.01) and adlai:pineapple-carrots ratio (P< 0.01) are affecting the
water absorptivity index.
Response surface equation yielded the following equation:
= 5.99 0.06651 0.03282 + 5.010412
The R-squared value is 0.9436 which is a good fit. Linear (P< 0.01), quadratic (P< 0.05)
and twofactor interaction (P< 0.01) terms are significant. Contour plot analysis of water
absorptivity index as a function of mixture moisture content against adlai:pineapple-
carrots ratio on Figure 12 shows that the maximum water absorptivity index is achieved
with a low adlai content against pineapple-carrots content and a low mixture moisture
content. The study of Altan observed that there is a direct relationship between adlai
content against pineapple-carrots content exists until a critical point was reached. The
phenomena observed is due to the increase in the adlai in the sample consuming the
moisture. In effect, the adlai powder uses the excess moisture to create a paste until the
excess moisture is not accommodated anymore.
38
Figure 12. Water Absorptivity Index as a function of mixture moisture content
against adlai:pineapple-carrots ratio.
Chemical Analysis
Breakfast Cereal Final Moisture Content. The highest breakfast cereal final
moisture content was treatment 4 with 13.62% which has a combination of 45% mixture
moisture content and 80:20 adlai: carrots-pineapple ratio. The lowest final breakfast cereal
moisture content was achieved by treatment 1 with 8.08% which has a combination of
30% mixture moisture content and a 60:40 adlai: carrots-pineapple combination. The rest
of the results are shown on Table 9. Low moisture content will give the product a long
shelf life (Aremu, 2014). However, a more reliable measure of a long shelf life is water
activity but most cases, water activity and moisture content has a directly proportional
relationship. Analysis of variance suggests that mixture moisture content (P< 0.01) and
adlai:pineapple-carrots ratio (P< 0.01) are affecting the breakfast cereal final moisture
39
content. Response surface regression yielded the equation for breakfast cereal final
moisture content:
= 2.757 + 7.621031 + 0.13952 + 1.410312
The R-squared value is 0.9587 which is a good fit. The model is also significant
using linear (P< 0.01), quadratic (P< 0.01) and two-function interaction (P< 0.01) terms.
Contour plot analysis of breakfast cereal final moisture content as a function of the mixture
moisture content against adlai:pineapple-carrots ratio in Figure 13 shows that the
breakfast cereal final moisture content increases as the moisture content of the mixture has
been increased and the adlai content is increased against the pineapples-carrots powder
content.
Figure 13. Contour plot of breakfast cereal final moisture content as a function of
mixture moisture content and adlai:pineapple-carrots ratio.
40
The breakfast cereal final moisture content has a directly proportional relationship with the
amount of water added in the sample. The addition of adlai is also affecting the moisture
content by trapping the water as it is being used for gelatinization.
Crude Fat. The sample that was analyzed with the highest crude fat content is
treatment 1 with 4.06% with a combination of 30% mixture moisture content and a 60:40
adlai:pineapple-carrots ratio. The sample with the lowest crude fat is treatment 4 with
1.29% with a combination of 45% mixture moisture content and 80:20 adlai:pineapple-
carrots ratio. The rest of the data for fat content are shown on Table 9. Contour plot analysis
reveals that minimal water content and less adlai content against pineapple-carrots content
is needed to achieve a high fat content of sample. This increase may be caused by a
blending effect which affects the distribution of fat through the sample. A low fat content
is desirable for the product. Chemically, lipid oxidation is avoided due to rancidity of the
sample when stored especially that the treatments are in contact with metals in the extruder
barrel. Metals shavings are proved to accelerate oxidative rancidity. (Guy, 2000). Analysis
of variance revealed that mixture moisture content (P< 0.01) and adlai:pineapple-carrots
ratio (P< 0.05) affects the crude fat. This may be caused by the interaction of water
molecules available to the fat content particularly in adlai grains.
The response surface regression yielded the equation for crude fat:
= 17.001 0.31991 .128012 + 2.43310312
The R squared value is 0.9692 which is a good fit. The linear (P< 0.01), quadratic (P<
0.01) and two-function interaction (P< 0.01) are significant. Contour plot analysis of the
crude fat as a function of mixture moisture content against adlai:pineapple-carrots ratio
in Figure 14 shows that the less adlai:pineapple-carrots used in the sample and a lower
41
moisture content yields high fat content. Figure 14 states that a sample with the highest fat
can be obtained by combining a low moisture with a low adlai content against a high
pineapple-carrots content. A reason for a low crude fat may be due to the blending effect
of fat in the sample as explained by Kothakota (2013).
Figure 14. Contour plot for the crude fat as a function of mixture moisture content
against adlai:pineapple-carrots ratio.
Ash content. Ash content is the measure of all the matter left after ignition. It is
also a gross estimate of the mineral content that is available in the sample. The sample with
the highest ash content is treatment 1 with 5.81% which has a mixture moisture content of
30% and 60:40 adlai:pineapple-carrots ratio. The sample with the least ash content is
treatment 4 with an ash content of 1.22% which has a mixture moisture content of 45% and
80:20 adlai:pineapple-carrots ratio. The rest of the results are shown on Table 9. From the
study of Razzaq (2012). The extrusion cooking outcome is significant for nutrients like
42
calcium, iron and zinc. In this case, water dissolves the minerals that were carried by adlai,
pineapples and carrots thus reducing the ash content of the sample. Ash content may have
a direct relationship as pineapple and carrots are added. The proximate analysis of
pineapple and carrots shows significant values of nutrients against adlai and therefore may
be attributed in the increase in minerals as pineapples and carrots when coextruded with
adlai.
Response surface regression yielded the equation for ash content:
= 25.846 0.35201 0.24850 + 3.153310312
Figure 15. Contour plot for the ash content as a function of mixture moisture
content and adlai:pineapple-carrots ratio.
Analysis of variance reveals that mixture moisture content (P< 0.01) and adlai:pineapple-
carrots ratio (P< 0.01) affects the ash content. The R-squared value is 0.9182 which is a
good fit. The linear (P< 0.01) and two-function interaction (P< 0.01) terms are significant.
43
However the quadratic term is non-significant. Contour plot analysis of ash content as a
function of mixture moisture content against adlai:pineapple-carrots ratio in Figure 15
shows that the ash content yields maximum when the adlai:pineapple-carrots is decreased
and the mixture moisture content is increased. This phenomena can be explained by the
innate chemical build-up of pineapple-carrots against adlai content and a dilution effect of
the minerals available in the samples (Kothakota, 2013).
Crude protein. In the study, the protein content of the selected grain is significantly
needed to be studied. The inherent crude protein of the adlai grain is higher than standard,
conventional grains. The sample with the highest protein content is treatment 1 with
10.29% which has 30% mixture moisture content and a 60:40 adlai:pineapple-carrot ratio.
The least crude protein content with treatment 4 which has a 45% mixture moisture content
and 80:20 adlai:pineapple-carrots ratio. The rest of the results are shown on Table 9. Upon
looking at the results of protein content on Table 9 and the proximate analysis of adlai on
Table 2, there is a slight discrepancy of protein content between the raw powders against
that of the prepared breakfast cereals. This phenomena could be attributed to the cooking
technique. Prolonged cooking time under high temperature tends to lead to protein
denaturation and deamination reactions thus yielding a lower protein content. Mixture
moisture content also has an effect in the protein yield. According to Anuonye (2012), there
is a dilution effect of protein if a high moisture environment is present in the treatments.
Thus, a low moisture content tends to dilute much less protein against a higher mixture
moisture content. The moisture content also aids in cooking through convection by
affecting the protein content through protein denaturation. Another source of variances in
protein content is the innate chemical composition of the raw materials especially adlai
44
which has a relatively high amount of protein content against the pineapple-carrots powder
combination. This supports a directly proportional relationship exists between adlai
content and crude protein content. Analysis of variance revealed that the mixture moisture
content (P< 0.05) and adlai:pineapple-carrots ratio (P< 0.05) significantly affects the crude
protein content.
Response surface regression yielded the equation for crude protein:
= 18.40 0.03861 00678332 1.733010312
.
Figure 16. Contour plot of crude protein as a function of mixture moisture content
against adlai:pineapple-carrots ratio.
The R-squared value is 0.8240 which is a moderate fit. The linear term (P< 0.05) and two
function interaction (P< 0.05) significant. Quadratic process term is non-significant.
Contour plot analysis of crude protein as a function of mixture moisture content against
45
adlai:pineapple-carrots ratio in Figure 16 shows that a high crude protein is achieved by
having a low moisture content and having a low adlai content against a high amount of
pineapple-carrots powder. The results of the moisture content is consistent with the
findings of Anuonye which shows a higher yield of protein when less water is added in the
mixture.
Crude Fiber. Crude fiber is the rough estimate of insoluble starches such as
celluloses and hemicelluloses in the treatments. Crude fiber is one of the crucial
components of a breakfast cereal snack. Being a functional food, the benefit of having a
high fiber content is to increase fecal weight due to its indigestibility and to lessen the
contact time between intestines and fecal matter. In recent studies, residence time of feces
in the intestines may cause severe ailments particularly intestinal cancer. The sample with
the highest crude fiber content is that of treatment 1 with 6.04% which has a combination
of 30% mixture moisture content and 60:40 adlai:pineapple-carrots ratio. The lowest crude
fiber content is that of treatment 4 with 4.37% which has a combination of 45% mixture
moisture content and 80:20 adlai:pineapple-carrots ratio. The rest of the results are shown
on Table 9. Crude fiber is affected by the addition of the pineapple and carrots. The
proximate analysis of carrots and pineapple from Table 2 shows a relatively high amount
of fiber present in them. This explains the directly proportional relationship in the fiber
content of treatments with a higher pineapple-carrots content. Moisture also affects the
fiber content by diluting the treatments overall. This has an inversely proportional
relationship on the amount of fiber weight per weight in the sample. Analysis of variance
reveals that mixture moisture content (P< 0.01) and adlai:pineapple-carrots ratio (P< 0.10)
affects the crude fiber content.
46
Response surface expression yielded an expression for the crude protein.
= 39.707 0.85501 0.43102 + 9.7010312
The R-squared value is 0.8239 which is a moderate fit. Linear term (P
47
Carbohydrate content. The carbohydrate content using proximate analysis is a
function of the difference between the summations of previous chemical components. It is
also known as the Nitrogen Free Extract. This directly affects the carbohydrate content of
the samples relative to the other components included. The sample with the highest
carbohydrate content is treatment 4 with 77.83% which has 45% mixture moisture content
and a 80:20 adlai:pineapple-carrots ratio. The sample with the least carbohydrate content
is treatment 4 with 65.71% which has a 45% mixture moisture content and a 60:40
adlai:pineapple-carrots ratio. The rest of the data are shown in Table 9. In most of the study
by Anuonye (2012) and Kothakotha (2013), there has been no significant effect in the
carbohydrate content of the sample. Analysis of variance suggests the mixture moisture
content (P< 0.01) and adlai:pineapple-carrots ratio (P< 0.10) affects the carbohydrate
content.
Response surface regression yielded the equation for carbohydrate:
= 3.138 + 2.12011 + 0.81392 0.02316712
The Rsquared value is 0.8681 which is a moderate fit. Linear term (P< 0.01) and two-
function interaction (P< 0.05) are significant while the quadratic process term is not-
significant. Contour plot analysis of carbohydrates as a function of mixture moisture
content and adlai:pineapple-carrots ratio in Figure 18 shows an increase in adlai content
against pineapple-carrots content and a high mixture moisture content yields the highest
carbohydrate content. This is due to the increase in adlai which has a high total
carbohydrate content (Vilbar, 2014). However, the moisture also affects by aiding
molecular dispersion and gel formation which converts some starches into carbohydrates
(Fennema, 2014).
48
Figure 18. Contour plot of carbohydrates as a function of mixture moisture
content against adlai:pineapple-carrots ratio.
Sensory Evaluation
Sensory evaluation of the prepared breakfast cereal snacks was conducted at the
Food Science Cluster. Twenty (20) panelist determine the eating quality of the product.
Based on quality scoring, the attributes such as: appearance, taste, aftertaste, texture and
General acceptability were evaluated.
Appearance. The sample with the highest score in appearance was treatment 2
with a score of 6.20 which has a moisture content of 45% and an 60:40 adlai:pineapple-
carrots ratio. The least score for appearance was treatment 8 with a score of 4.4 which has
a 35% mixture moisture content and 80:20 adlai:pineapple-carrots ratio. The rest of the
results are shown on Table 10. Upon looking at the appearance of the treatments, a trend
has been observed in the different treatments. A browning effect has been observed with
49
less adlai in the mixture and more of the pineapple-carrots mixture. This may be attributed
as oxidative browning or maillard reaction of the carrots mixture and the pineapple powder
components. A mixture with more adlai in the sample tends to be whiter. Adlai components
tends to dominate the appearance of the sample upon gelatinization. Analysis of variance
revealed that adlai:pineapple-carrots ratio (P< 0.05) affects the appearance of the samples.
Figure 19. Contour plot of appearance as a function of mixture moisture content
against adlai:pineapple-carrots ratio
.
Response surface regression yielded the following equation:
= 10.38633 0.252441 0.093332 + 4.1333310312.
The R-squared value is 0.7153 which is a moderate fit. Linear, two-factor interaction and
quadratic terms shows that the terms are not significant. Contour plot analysis of
appearance as a function of mixture moisture content against adlai:pineapple-carrots ratio
on Figure 19 shows that a higher pineapple-carrots content against adlai content is
generally preferred by judges due to a more brownish color of the final product. This is in
agreement with the results of Guy which prefer a brownish color. The brownish color of
50
the samples signify that the samples are well dried, and near the appearance of
commercially prepared breakfast cereal snacks. Moisture content affects the appearance
through plastization which lubricates and fully separates and solvate amylose chains thus,
showing more air packets in the sample which is formed through drying of the extrudates
which may have been increased the quality score of products with high moisture content.
(Fennema, 2014).
Flavor. The treatments with the highest score is treatment 1 which has a 30%
moisture content and a combination of 60:40 adlai:pineapple-carrots ratio. The lowest
score is treatment 8 which has 35% moisture and 80:20 adlai:pineapple-carrots ratio. The
rest of the results are shown on Table 10. A trend has been observed in the samples.
Treatments with more carrots-pineapple in their composition tends to bring a hint of
sourness on it. This is due to the powdering process of pineapple which tends to crystallize
the sugars in the sample. However, acids in pineapple are also concentrated which explains
the perceived sourness on the samples. Analysis of variance reveals that the interaction of
moisture and adlai:pineapple-carrots ratio (P< 0.05) affects flavor of the product.
Response surface regression yielded the following equation:
() = 22.696 + 0.688971 + 0.378932 9.334410312
The R-squared value is 0.6794 which is a moderate fit. There were no significant
terms. The contour plot analysis of flavor as a function of mixture moisture content against
adlai:pineapple carrots in Figure 20 shows that the highest scores in flavor were achieved
using a high mixture moisture content and a high adlai content, and that of a high mixture
moisture content and a low adlai ratio. In this case, mixture moisture content, have affected
the flavor of the product. From observation of the contour plot, the highest scores were
51
achieved with both a high mixture moisture content with a low pineapple-carrots content
against adlai and a high adlai content with a low moisture content. This result may be due
to the trend of the judges as to perceive the tartness as an off-taste.
Figure 20: Contour plot of flavor as a function of mixture moisture content against
adlai:pineapple-carrots ratio.
An increase in adlai content neutralizes the taste of such a high concentrate product as the
pineapple. This is also the same as increasing the moisture content to dilute the sugars and
acids brought by the pineapple in the treatments.
Aftertaste. The sample with the best score for aftertaste is treatment 6 with 5.27
which has a 45% moisture and a 70:30 adlai:pineapple-carrots. The sample with the least
score for aftertaste was treatment 1 with 30% mixture moisture content and 60:40
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