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THESIS TEXTURE OPTIMIZATION OF FUNCTIONAL COOKIES WITH THE ADDITION OF CHIA (Salvia hispanica L.) FLOUR Written as partial fulfillment of the academic requirements to obtain the degree of Sarjana Teknologi Pertanian Strata Satu By : NAME : ANGGADA PUTRA NPM : 03420110004

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Page 1: Laporan Skripsi-revisi

THESIS

TEXTURE OPTIMIZATION OF FUNCTIONAL COOKIES

WITH THE ADDITION OF CHIA (Salvia hispanica L.) FLOUR

Written as partial fulfillment of the academic requirementsto obtain the degree of Sarjana Teknologi Pertanian Strata Satu

By :

NAME : ANGGADA PUTRANPM : 03420110004

FOOD TECHNOLOGY DEPARTMENTFACULTY OF SCIENCE AND TECHNOLOGY

UNIVERSITAS PELITA HARAPAN2015

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STATEMENT OF THESIS AUTHENTICITY

I, a student of Food Technology Department, Faculty of Science and Technology,

Universitas Pelita Harapan,

Name : Anggada Putra

Student Id. Number : 03420110004

Department : Food Technology

hereby declare that my thesis, entitled “TEXTURE OPTIMIZATION OF

FUNCTIONAL COOKIES WITH THE ADDITION OF CHIA (Salvia

hispanica L.) FLOUR” is:

1) An original piece of work, written and completed on my own, based on lecture

notes, data observation, reference books, journals, and other sources as listed

on the work cited section.

2) Not a duplication of other writings that have been published or used for

obtaining the degree of Sarjana in any Universities, except for passages that

include information on respective references.

3) Not a translation of other works.

I understand that if my statement above is proven untrue, this Thesis will be

cancelled.

Tangerang, July 14th 2015

(ANGGADA PUTRA)

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UNIVERSITAS PELITA HARAPAN

FACULTY OF SCIENCE AND TECHNOLOGY

APPROVAL BY THESIS SUPERVISORS

TEXTURE OPTIMIZATION OF FUNCTIONAL COOKIES WITH

THE ADDITION OF CHIA (Salvia hispanica L.) FLOUR

Written by :

Name : Anggada Putra

Student Id. Number : 03420110004

Department : Food Technology

has been examined in the thesis examination for obtaining the degree of Sarjana

Teknologi Pertanian Strata Satu in the Food Technology Department, Faculty of

Science and Technology, Universitas Pelita Harapan, Karawaci - Tangerang,

Banten, and has been approved by the thesis supervisors.

Tangerang, July 14th, 2015

Approved by:

Supervisor Co-Supervisor

(Prof. Dr. C. Hanny Wijaya) (Jeremia M. Halim, MP)

Acknowledged by:

Head of Department Dean

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(Julia Ratna Wijaya, MAppSc) (Prof. Dr. Manlian Ronald. A., ST,

MT.)

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UNIVERSITAS PELITA HARAPAN

FACULTY OF SCIENCE AND TECHNOLOGY

APPROVAL BY THESIS EXAMINATION COMMITTEE

We the undersigned, certify that a thesis defense has been held on June 30th, 2015,

as partial fulfillment of the academic requirements to obtain the degree of Sarjana

Teknologi Pertanian Strata Satu in Food Technology Department, Faculty of

Science and Technology, Universitas Pelita Harapan, for the student:

Name : Anggada Putra

Student Id. Number : 03420110004

Department : Food Technology

Faculty : Science and Technology

with the following title “TEXTURE OPTIMIZATION OF FUNCTIONAL

COOKIES WITH THE ADDITION OF CHIA (Salvia hispanica L.) Flour” and

that the thesis was successfully defended, henceforth approved by the examination

committee.

Examiners Signature

1. Dr. Hardoko Head of Examiners

2. Prof. Dr. C. Hanny Wijaya Member

3. Lisa A. Yakhin, M. Eng Member

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ABSTRACT

Anggada Putra (03420110004)

TEXTURE OPTIMIZATION OF FUNCTIONAL COOKIES WITH THE ADDITION OF CHIA (Salvia hispanica L.) FLOUR (xiii + 51 pages: 14 figures, 14 tables, and 24 appendices)

The addition of chia flour towards the formulation of baked products, including pound cake and bread shows that it can decrease the specific volume and texture parameter of these products, respectively. This research’s objective is to obtain the best formulation of chia flour and hydrogenated vegetable fat (HVF) to produce cookie with optimum texture quality based on sensory evaluation and physico-chemical analysis. Different contents of chia flour (0 - 30 g) and HVF (33 - 55 g) were added to the cookie mix using Response Surface Methodology (RSM) based on 22 central composite rotational design (CCRD). Chia flour and HVF significantly affects the acceptability of cookies produced in terms texture. Physicochemical parameters, including hardness, fracturability, spread ratio, and moisture content were also affected. The formula to obtain cookie with optimum texture is 20.45 g of chia flour and 55.00 g of HVF. The nutrition content of optimum chia cookie is 8.75 % protein, 27.81 % fat, 1.64 % omega-3 fatty acid, 1.18 % ash, 58.46 % carbohydrate, 9.16 % total dietary fiber, and 3.80 % moisture content. Based on the nutrition content, optimum chia cookie can be claimed as a good source of fiber and high source of α-linolenic acid (ALA) according to FDA.

Keyword: Chia, Fat, Cookie, Omega-3, Dietary Fiber, Texture.References: 47 (1992 - 2015)

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ACKNOWLEDGEMENTS

Praise the Lord for His blessing during the research and the making of

thesis report that this report can be finished well. The completion of thesis report

entitled “TEXTURE OPTIMIZATION OF FUNCTIONAL COOKIES

WITH THE ADDITION OF CHIA (Salvia hispanica L.) FLOUR” is one of

the requirements to achieve bachelor degree in Sarjana Strata Satu Teknologi

Pangan. Author realizes that the report could not be finished without the

guidance, assistance, prayer, and support from many parties. Hence, author would

like to express gratitude to those who help and support author during this time,

including:

1. Prof. Dr. C. Hanny Wijaya as the thesis supervisor for the guidance, time,

and support during research and thesis writing.

2. Mr. Jeremia Halim as thesis co-supervisor for the guidance, advice, and

support during the research and thesis report writing.

3. Ms. Julia Ratna Wijaya, MAppSc as the head of Food Technology

Department who gave chance to author to complete this thesis.

4. Beloved father and mother for the endless love, prayers, and supports for

author. And also for brothers who supports during the most difficult time.

5. Mr. Hendra, Mr. Aji, Mr. Darius and Mrs. Meri as laboratory assistant for

the help and support during research in laboratories.

6. Anastasia Stephanie, Nicholas Adams, Gabriel Eugenie, Amanda Inggita,

and Alvin Kusuma who accompanied, helped, and being cooperative with

the author during work in laboratories.

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7. Edison Sutiono, Marvin Setiawan, Natanael Leon, and Aditya Febrian for

constant support during the research and the completion of report.

8. All members of C Class of Food Technology 2011 Universitas Pelita

Harapan who are not be mentioned above.

9. All friends and close relatives that have not been mentioned but provided

help and support for author during internship and report completion.

Author realized author might have done mistakes during research and

report completion. Therefore, the author would welcome any critics and

suggestions upon this report. Finally, author hopes that this report would be useful

for the reader.

Tangerang, July 14th, 2015

Author

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TABLE OF CONTENTS

COVER page

STATEMENT OF THESIS AUTHENTICITY

APPROVAL BY THESIS SUPERVISORS

APPROVAL BY THESIS EXAMINATION COMMITTEE

ABSTRACT............................................................................................................v

ACKNOWLEDGEMENTS.................................................................................vi

TABLE OF CONTENTS...................................................................................viii

LIST OF TABLES................................................................................................xi

LIST OF FIGURES.............................................................................................xii

LIST OF APPENDICES....................................................................................xiii

CHAPTER I INTRODUCTION...........................................................................1

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

1.2 Research Problem..........................................................................................2

1.3 Objectives.......................................................................................................2

1.3.1 General Objectives..................................................................................2

1.3.2 Specific Objectives.................................................................................2

CHAPTER II LITERATURE REVIEW.............................................................4

2.1 Overview of Cookie.......................................................................................4

2.1.1 Pressed Cookies......................................................................................4

2.2 Cookie Ingredients.........................................................................................4

2.2.1 Flour........................................................................................................4

2.2.2 Sugar.......................................................................................................5

2.2.3 Fat...........................................................................................................5

2.2.4 Egg..........................................................................................................6

2.2.5 Leavening Agent.....................................................................................6

2.2.6 Water.......................................................................................................7

2.2.7 Additional Ingredients.............................................................................7

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2.3 Cookie Processing..........................................................................................8

2.4 Chia................................................................................................................9

2.4.1 Nutritional Value of Chia Seed.............................................................10

2.4.2 Utilization of Chia Seed in Food...........................................................12

2.5 Omega-3 Fatty Acid.....................................................................................13

2.6 Dietary Fiber................................................................................................15

2.7 Response Surface Methodology...................................................................16

2.7.1 Central Composite Design....................................................................16

CHAPTER III RESEARCH METHODOLOGY.............................................18

3.1 Materials and Equipments............................................................................18

3.2 Research Procedure......................................................................................18

3.2.1 Preliminary Research............................................................................18

3.2.2 Main Research.......................................................................................20

3.3 Experimental Design....................................................................................23

3.3.1 Preliminary Research............................................................................23

3.3.2 Main Research.......................................................................................23

3.4 Analysis Procedure......................................................................................24

3.4.1 Physico-chemical Analysis...................................................................24

3.4.2 Sensory Evaluation...............................................................................28

CHAPTER IV RESULT AND DISCUSSION...................................................30

4.1 Overview......................................................................................................30

4.2 Nutritional Content of Chia Flour................................................................30

4.3 Determination of Mixing Method................................................................31

4.4 Formula Optimization of Cookies................................................................33

4.4.1 Optimization of Sensory Evaluation Result..........................................34

4.4.2 Optimization of Physical Analysis Result............................................36

4.4.3 Optimal Formula Recommendation......................................................45

4.5 Product Verification.....................................................................................46

4.6 Product Comparison.....................................................................................47

4.6.1 Sensory Evaluation Result....................................................................47

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4.6.2 Physico-chemical Analysis...................................................................48

4.6.3 Nutrition Composition..........................................................................49

CHAPTER V CONCLUSION AND SUGGESTION.......................................51

5.1 Conclusion...................................................................................................51

5.2 Suggestion....................................................................................................51

BIBLIOGRAPHY................................................................................................52

APPENDICES......................................................................................................56

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LIST OF TABLES

page

Table 2.1 Composition of chia seed per 100 g......................................................11

Table 3.1 Basic formulation for cookies................................................................19

Table 3.2 Concentration composition of cookies formula.....................................22

Table 3.3 Formulation Combination Model..........................................................22

Table 3.4 Optimization cookies formula goal and importance..............................22

Table 4.1 Nutritional Content of Chia Flour..........................................................30

Table 4.2 Hardness Value of Cookie Made With Different Mixing Methods.......33

Table 4.3 Statistical Model for Each Responses....................................................34

Table 4.4 Criteria and Goals of Each Responses for Optimal Cookie Formulation

................................................................................................................................46

Table 4.5 The Optimal Formula of Cookie Formulated With Chia Flour.............46

Table 4.6 Comparison Between Prediction Value and The Actual Result............47

Table 4.7 Result of Sensory Evaluation Test.........................................................47

Table 4.8 Result of Physico-chemical Analysis.....................................................48

Table 4.9 Nutritional Content of Optimum Chia Cookie and Control Cookie......49

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LIST OF FIGURES

page

Figure 2.1 Salvia hispanica L................................................................................10

Figure 3.1 Flowchart of the cookies making..........................................................21

Figure 4.1 Result of Paired Comparison Test........................................................31

Figure 4.2 Result of Paired Preference Test..........................................................32

Figure 4.3 3-D Graph for Texture Response Based on Hedonic Test...................35

Figure 4.4 Contour Graph for Texture Response Based on Hedonic Test............36

Figure 4.5 3-D Graph for Hardness Value.............................................................37

Figure 4.6 Contour Graph for Hardness Value......................................................37

Figure 4.7 3-D Graph for Fracturability Value......................................................40

Figure 4.8 Contour Graph for Fracturability Value...............................................39

Figure 4.9 3-D Graph for Spread Ratio..................................................................41

Figure 4.10 Contour Graph for Spread Ratio.........................................................42

Figure 4.11 3-D Graph for Moisture Content........................................................45

Figure 4.12 Contour Graph for Moisture Content.................................................44

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LIST OF APPENDICES

page

Appendix A. Identification Result.......................................................................A-1

Appendix B. Questionnaire of Comparison Test.................................................B-1

Appendix C. Result of Comparison Test.............................................................C-1

Appendix D. Statistical Analysis of Comparison Test........................................D-1

Appendix E. Result of Texture Analysis in Preliminary Analysis.......................E-1

Appendix F. Questionnaire of Hedonic Test........................................................F-1

Appendix G. Result of Hedonic Test..................................................................G-1

Appendix H. Analysis of Texture Response........................................................H-1

Appendix I. Result of Hardness and Fracturability Analysis................................I-1

Appendix J. Analysis of Hardness Response........................................................J-1

Appendix K. Analysis of Fracturability Response..............................................K-1

Appendix L. Data of Spread Ratio.......................................................................L-1

Appendix M. Analysis of Spread Ratio Response..............................................M-1

Appendix N. Data of Moisture Content...............................................................N-1

Appendix O. Analysis of Moisture Content Response........................................O-1

Appendix P. Questionnaire for Verification Test.................................................P-1

Appendix Q. Result of Hedonic Test in Verification Test..................................Q-1

Appendix R. Result of Physicochemical Analysis in Verification Test..............R-1

Appendix S. Questionnaire for Product Comparison...........................................S-1

Appendix T. Result of Hedonic Test in Product Comparison..............................T-1

Appendix U. T-Test Analysis for Hedonic Test in Product Comparison............U-1

Appendix V. Physicochemical Analysis Result in Product Comparison............V-1

Appendix W. Analysis for Physicochemical Test in Product Comparison........W-1

Appendix X. Result of Proximate Analysis.........................................................X-1

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CHAPTER I

INTRODUCTION

1.1 Background

Biscuits and cookies are food products which have a very significant part

in the food industry in most countries (Manley, 2011). The reasons for this are due

to their relatively long shelf life, great convenience as food products, good value

for money, and human affinity, especially children, towards products which

contains sugar. However, according to Manley (2011), and Bassinello et al.

(2011) cookie lacks dietary fiber and essential fatty acids.

The interest on research, development and commercialization of functional

food ingredients, nutraceuticals and dietary supplements have been growing

around the globe (McManus et al., 2011). Chia (Salvia hispanica L.) is an annual

plant which grows mainly in South America, known to be rich in dietary fiber and

omega-3 fatty acid. For this reasons, it is expected that chia seeds can be utilized

as an ingredient for functional food, which in this case acts as a substitute of

wheat flour in formulation of cookie (Reyes Caudillo et al., 2007). Research done

by Pizarro et al. (2013) and Steffolani et al. (2015) shows that chia flour can be

added into the formulation of pound cake and bread, respectively. However, the

result of both experiments showed that the addition of chia can decrease the

specific volume of the final product and texture parameter based on sensory

evaluation result, but an increase in the amount of hydrogenated vegetable fat can

help overcome the problem. Fat is important for texture parameter, due to its

ability to prevent excessive gluten development by preventing water from reacting

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with glutenin and gliadin to form gluten. Optimization of the amount of chia flour

and hydrogenated vegetable fat added is expected to produce cookies with

acceptable texture comparable to most cookies. However, because of the usage of

new ingredient in the making of cookies, the method used to make the cookie

need to be adjusted (Novianty, 2015). Therefore it is important to determine the

best mixing method.

1.2 Research Problem

The addition of chia flour in wheat flour-based product such as cake and

bread is known to cause a decrease in its specific volume and lower texture

acceptability compared to the control. The mixing method of cookie have to be

adjusted as well, as new ingredient is incorporated in the formulation. The correct

amount of hydrogenated vegetable fat is known to be able to increase the specific

volume and texture characteristics of the wheat flour-based product. Hence,

finding the correct formulation of chia seeds flour and hydrogenated vegetable fat

for use in cookie making is expected to overcome this problem.

1.3 Objectives

1.3.1 General Objectives

The general objective of this research was to produce cookies with the

optimal texture using chia flour and hydrogenated vegetable fat.

1.3.2 Specific Objectives

The specific objectives of this research were:

1. To determine the best mixing method of cookie made with the addition of chia

flour.

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2. To study the effects of incorporating different amount of chia flour and

hydrogenated vegetable fat towards the texture characteristics of cookie.

3. To evaluate the acceptability of texture parameter of cookie made with the

addition of chia flour based on sensory evaluation.

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CHAPTER II

LITERATURE REVIEW

2.1 Overview of Cookie

Cookie is a name which originally comes from the dutch word Koekje,

which basically means a small cake. Most of the components found in cookie is

the same as cake, but it is different in that it contains lower water content and

higher sugar and fat content. Based on its dough or batter’s fluidity, cookies can

be classified into bar, dropped, pressed, molded, rolled, and icebox/refrigerator

cookie (Brown, 2011; Manning, 2011).

2.1.1 Pressed Cookies

Pressed cookies have a flour mixture which is viscous enough to be stuffed

into a pastry bag or cookie press. Examples of cookies of this type are ladyfingers

and coconut macaroons (Brown, 2011).

2.2 Cookie Ingredients

Main ingredients used in making cookies are flour, sugar, fat, egg,

leavening agent, and water. Additional ingredients might be added depending on

the desired final product (Sumnu and Sahin, 2008).

2.2.1 Flour

Wheat flour is the most used flour in cookie making. In cookie, gluten

formation is avoided, so soft wheat flour is generally preferred than heavy wheat

flour. The reason is because the desired texture for cookie is crispy and soft, and

heavy wheat flour with high protein content causes the the texture of the cookie to

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become hard and thick. Moreover, higher protein concentration have been

correlated with reduced diameter in cookie making as well, although other factors

are suspected to play a role as well. Rate of spreading of cookie dough is found to

be faster as well in cookies made from soft wheat flour. This is because the

amount of soluble starch in soft wheat flour is low, and causes the dough to be

less viscous which in turn increases its spreading rate (Brown, 2011; Sumnu and

Sahin, 2008).

2.2.2 Sugar

Sugar is added into cookie to add sweetness, acts as a tenderizing agent,

and affects spread. It was observed using a farinograph, that an increase in sugar

concentration reduces the consistency and cohesion of cookie dough. As a

hardening agent, sugar crystallizes as the cookie dough cools down after baking

and thereby makes the product crispy. However, it can act as softener in moderate

amounts, due to sugar’s ability to retain water. Sugar also makes the final product

to become fragile, because it controls hydration and tends to disperse starch and

protein molecules, which in turn prevents the formation of a continuous mass

(Sumnu and Sahin, 2008).

2.2.3 Fat

Fat is an essential ingredient in cookie, as its addition influences the

texture and taste of cookies, which makes the cookie crispier because this allows

the dough to spread as it cooks on the cookie sheet (Jacob and Leelavathi, 2007).

Fat has the function of preventing water from forming gluten network with

glutenin and gliadin protein from wheat flour, thereby making the dough less

resistant to mixing. Formation of gluten makes cookie dough more elastic and

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resistant to mixing, making the end product hard. Fat also entraps air particles in

the dough, thereby increasing the total volume and lower the density of cookie

produced. Additionally, during baking the fat melts and helps the cookie dough

spread in the cooking sheet. This makes cookie have its characteristic soft and

crispy texture (Jacob and Leelavathi, 2007).

The source of fat used for cookie varies, but vegetable fat is generally used

more compared to animal fat, due to the origin of these materials, their quality is

variable and can cause issues to the final product. Also, as manufacturers wanted

to sell their product to all consumers, including the vegetarians, vegetable fat

becomes preferrable (Sumnu and Sahin, 2008; Manley, 2011).

2.2.4 Egg

The addition of egg into cookie dough helps in puffing, emulsifying the

dough, due to the presence of lecithin, which is an emulsifier. Emulsifier helps

entrap air particles and allow water to mix with fat, preventing it from reacting

with glutenin and gliadin to form gluten (Jacob and Leelavathi, 2007). This results

in a creamier and smoother texture in cookies. Presence of fat in egg contributes

to the final taste and add the total fat in cookies as well. The egg white component

contributes toward the structure or shape of the cookie dough, due to the drying

effect it has (Sumnu and sahin, 2008; Manley, 2011).

2.2.5 Leavening Agent

The presence of leavening agent causes the cookie dough to rise, which in

turn causes the final product to have greater volume and superior texture.

Leavening agent may be of physical, biological, or chemical in nature (Sumnu and

Sahin, 2008). Physical leavening agents are air and steam, which is done through

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mechanical action, such as creaming, beating, or heating. Biological leavening

agents are yeasts and bacteria. Carbon dioxide produced by these microorganisms

through fermentation causes the dough to rise. Chemical leavening agents are

baking powder and baking soda, which yields carbon dioxide when it is heated or

mixed with acid. Sodium bicarbonate is the most commonly used chemical

leavening agent (Brown, 2011).

2.2.6 Water

Water is used in a very small amount in cookie making, usually only about

3 - 4 % of the whole cookie formulation. It’s purpose is generally to dissolve dry

ingredients and provide steam for leavening during baking. Too much water is

unfavorable, because it will induce the formation of gluten in the dough, causing

the texture of the cookie to be less crispy and more hard (Brown, 2011).

2.2.7 Additional Ingredients

Nonfat dry milk is sometimes added into cookies to give subtle flavor and

textural improvements and to aid surface coloring (Brown, 2011). Reducing agent

can also be added as an additive to increase cookie spread, by reducing disulfide

bonds to the sulfhydryl group, thereby decreasing dough stability. Cornstarch

sometimes is used in cookie as anticaking agent, drying agent, formulation aid,

processing aid, surface-finishing agent. Other food additives which is used in

cookies are potassium sorbate as preservative, soybean lecithin as emulsifier, and

whey as a binder ot extender to provide a uniform texture (Sumnu and Sahin,

2008).

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2.3 Cookie Processing

The processing of cookie is basically comprised of four steps, which are

dough making, processing and shaping, baking, cooling and packaging. The first

step of the process is dough making. In this step, all ingredients used to make

cookies are mixed together to form a dough. During mixing, the protein in flour

contacts with water and swell. If the mixing is continued, the protein containing

water will form a three-dimensional gluten network. Sugar should be dissolved by

the water in this process, as otherwise the sugar crystal will caramelize during

baking, causing brown spots. Dough temperature is also important in terms of the

fat used. At high temperatures, the fat will melt and the dough becomes fatty. The

dough should be maintained to have plastic-like texture (Sumnu and Sahin,

2008). Depending on the desired cookie characteristic, cookie processing can

categorized into one step and two step mixing (Hui, 2006). In two step mixing, the

fat and sugar are mixed first, followed by egg, and finally the flour and other dry

ingredients. Mixing cookie ingredients in two stages can minimize the

development of gluten in the flour, which is desirable in cookie dough. By

mixing the cookie ingredient in two stages, the fat will be more evenly dispersed

around the flour particles, and therefore rendering them less available to water and

preventing gluten development. In one-stage mixing, all the ingredients are mixed

at once. However, in this step the baker has less control over the mixing, and

therefore, the gluten development as well. However, it can be used when over-

mixing is not a serious problem, for example in the making of chewy cookies.

The second step is processing and shaping. In this step the doughs are

shaped to the desired form. The machines used for processing varies depending on

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the hardness of the dough. Very soft dough needs to be deposited directly onto the

steel oven band invariably. For soft and usually sticky dough, it needs to be

extruded and cut using wire-cut machine. Dough which are stiff should be

extruded on a bar machine or rout press machine (Sumnu and Sahin, 2008).

The third step is baking. In this process, the dough of the cookies should

be placed far enough apart on the baking sheet to prevent them from touching

together during baking. Cool cooking sheets should be places as well on the

baking sheet to prevent overspreading (Brown, 2011). Temperatures ranging

between 163 - 191 oC are usually used in baking of cookies. The next and last step

after baking is cooling and packaging. After baking, the cookies should be placed

on a cloth band and cooled down in room temperature. Placing the recently baked

cookie on a temperature which is too cold might cause cracking on the surface.

The cookies can be placed on the packaging after it is sufficiently cooled down

(Sumnu and Sahin, 2008).

2.4 Chia

Chia is a plant native to the central valleys of Mexico and northern

Guatemala. The word “chia” is a Spanish adaptation of the word chian or chien in

its plural form, meaning “oily”, which comes from Nahuatl, the language of Aztec

people. Chia plant, which name in latin is Salvia hispanica L., belongs to the

Lamiaceae family, which makes them a part of the mint family. It is

approximately a meter tall, with opposite, petiolate, and serrated leaves that are 4

to 8 cm long and 3 to 5 cm wide. The plant grows mainly in mountainous areas

and has little tolerance to abiotic phenomena, such as freezing and sunless

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locations, however it is semi-tolerant to acid soils and drought. It is an annual herb

and usually blooms suring the summer months (Munoz et al., 2013).

Seeds of chia plant are small (1.87± 0.1 mm length, 1.21 ± 0.08 mm width

and 0.88 ± 0.04 mm thickness) with an oval flattened shape and ranged in colour

from dark coffee to beige with small darker spots (Ixtaina, et al., 2008). Its seeds

was once used by the Aztecs as a food, and acquired importance as a staple crop

in central Mexico between 1500 and 900 BC. At the time, only corn and beans

surpassed chia in term of importance (Munoz et al., 2013).

Figure 2.1 Salvia hispanica L.Source: Munoz et al. (2013)

2.4.1 Nutritional Value of Chia Seed

Chia seed has been a subject of interest for food scientists and industries

due to the components found inside. It is rich in protein, fat, and dietary fiber

(Ayerza, 1995; Ayerza and Coates, 2005). Additionally, other components such as

vitamins, minerals, and antioxidant are also present in chia seed (Munoz et al.,

2013). Table 2.1 shows the composition of chia seed.

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Table 2.1 Composition of chia seed per 100 gComponent Content

Energy (Kcal.) 486Proteins (g) 9 - 23Total fat (g) 25 - 35Saturated fatty acid (g) 3.1 - 3.4Monounsaturated fatty acid (g) 2.309

Polyunsaturated fatty acid (g) 23.6 - 27.75Trans fatty acid (g) 0.14Omega-3 fatty acid (g) 17.83 gCarbohydrate (g) 42.12Total dietary fiber (g) 18 - 41Vitamin C (mg) 1.6Niacin (mg) 8.83Thiamin (mg) 0.62Riboflavin (mg) 0.17Calcium (mg) 631Potassium (mg) 407Phosphorus (mg) 860Iron (mg) 7.72Source: Munoz et al. (2013); Reyes-Caudillo et al. (2007); Ayerza and Coates (1996).

Dietary fiber is found in large amount in chia seeds, which is about 18 - 41

g/ 100 g seeds (Reyes-Caudillo et al., 2007). The recommended daily intake

(RDI) of dietary fiber for adult is generally in the range of 20 to 35 g/ day. This

means that consumption of about 100 g of chia seeds can fulfill the RDI of dietary

fiber in one day (Munoz et al., 2013).

One of the most important nutritional component found in chia seed is the

fat or lipid. Its content is approximately between 25 - 35 g/ 100 g of seeds (Ayerza

and Coates, 2011; Ixtaina et al., 2011). Total polyunsaturated fatty acids (PUFA)

found in the seed is more than 80.5 % of the total fats. However, the main

constituent of the fat content in chia seed is ω-3α-linolenic fatty acid, which

consists 56.9 - 64.8 % of the total fat, the highest compared to any known plant

source (Munoz et al., 2013).

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2.4.2 Utilization of Chia Seed in Food

Chia seed utilization as a food or ingredient of food began only recently. It

was approved as a Novel Food by the European Parliament and Council of Europe

in 2009. Some of the most important applications of the seeds include its use as a

nutritional supplement and as an ingredient in cereal bars, biscuits, pasta, bread,

snacks and yogurt. Also, due to abundance of essential fatty acids in the seed, it

can be used as an oil. Another application of chia seed is using its mucilage. This

component is composed mainly of polysaccharides in form of soluble fiber. A

recent study shows that the mucilage can be used as the new source of

polysaccharides, with the potential to generate different polymer blends to

produce films and coatings with improved properties. (Munoz et al., 2013).

Pizarro et al. (2013) studied the incorporation of whole chia flour (WCF)

in pound cake. In the research, different contents of WCF (0 - 30 g/ 100 g flour

mixture) and hydrogenated vegetable fat (HVF) (12 - 20 g/ 100 g flour mixture)

were added to the cake mix based on a 22 central composite rotational design

(CCRD). The result showed that WCF addition decreased the specific volume and

colour parameters of the cakes, however, variation of WCF and HVF content

contributed to maintenance of the moisture during storage. The best formulation

was found in cake containing up to 15 g WCF/100 g flour mixture and from 16 to

20 g HVF/100 g flour mixture. The cake was found to present higher protein,

lipid, and ash content than the control cake. The omega-3 fatty acid content also

increases considerably. The sensory test of the cake shown that it has good

sensory acceptance and a greater purchasing intention.

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Coelho and Salas-Mellado (2014) researched the effect of substituting chia

flour or seeds for wheat flour on the quality of bread. In the research, the HVF

content was reduced and chia seeds or flours were added to the formulations of

wheat flour based on a 22 CCRD. The best formulation was found on bread with

7.8 g chia flour/ 100 g flour mixture and 0.9 g HVF/ 100 g flour mixture and

bread with 11.0 g chia seeds/ 100 g flour mixture and 1.0 g HVF/ 100 g flour

mixture, which results in a reduction of 27% and 24% level of saturated fat

respectively, compared to the control bread. The ratio of PUFA and saturated fats

(PUFA:SAT) was increased to 3.1 and 3.9 respectively, compared to the control

bread (1.01). Dietary fiber content was increased to 2.0% and 5.7%, while the ω-

3α-linolenic fatty acid was increased to 1.21% and 1.85% respectively, a

significant increase compared to the control bread, which has a dietary fiber

content of 0.3% and ω-3α-linolenic fatty acid content of 0.03%. Based on the

sensory evaluation test, bread formulated with chia seeds or flour obtained high

level of acceptability test and purchase plans, with chia flour bread obtaining

higher index of purchase intent than the chia seed bread.

2.5 Omega-3 Fatty Acid

Omega-3 fatty acid is a type of polyunsaturated fatty acid. The term

omega-3 is in reference to the carbon molecule adjacent to a double bond

numbered from the methyl end of the molecule. An example of omega-3 fatty acid

is docosahexanoic fatty acid (DHA). It is a molecule with a backbone of 22

carbon chains and contains 6 double bonds, with the first double bond located on

carbon 3 from the methyl end. The other two commonly found omega-3 fatty acid

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in food are eicosapentaenoic acid (EPA) and alpha-linolenic acid (ALA)

(McManus et al., 2011).

Among the three commonly found omega-3 fatty acids in food, ALA is

the only one not naturally produced by human body, and so it is considered to be

an essential fatty acid. However, enzymes in human body can convert ALA into

EPA and DHA, which have long been associated with health promoting effects

(Larsen et al., 2011). According to McManus et al. (2011), consumption of

omega-3 fatty acids have been related to positive health outcomes, notably in the

areas of infant development, cardiovascular disease, platelet aggregation,

hypertension, hyperlipidemia, cancer, dementia, Alzheimer’s disease, depression

and inflammation.

According to Simopoulos and Cleland (2003), maintaining an

omega-6/omega-3 ratio of 4:1 or less is recommended. High ratio of

omega-6/omega-3 is detrimental to health and can lead to the development of

chronic disease. Improving the intake of omega-3 fatty acid is essential for brain

function and management of cardiovascular disease, arthritis, and cancer. Further

research by Gow and Hibbeln (2014) also shows that omega-3 and omega-6

intake needs to be balanced for optimal physical and mental health, and excessive

intake of one type of fatty acid may inhibit the conversion of the other.

Furthermore, supplementation of omega-3 towards children in the experiment

shows some improvement in terms of learning capacity and behavior, especially

in children who are underachieving, have ADHD-like symptoms, and/or have

severe misconduct.

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2.6 Dietary Fiber

According to Brown (2011), dietary fiber is defined as the undigested

portion of carbohydrates remaining in a food sample after exposure to digestive

enzymes. Dietary fibers are usually found in plant foods and includes

polysaccharides and lignin. More recently, however, the definition has been

expanded to include oligosaccharides, such as inulin and resistant starches.

Dietary fibers are usually classified based on its solubility, which are soluble and

insoluble fiber. Insoluble fiber cannot be dissolved in water, and usually acts as a

sponge in the intestine by soaking up water. Soluble fibers readily dissolves in

water, and may benefit health by lowering high blood cholesterol levels and

reducing high blood glucose. Example of soluble fibers are beta-glucans, pectins,

gums, and some hemicelluloses (Anderson et al., 2009). Foods containing soluble

fibers include dried beans, peas, lentils, oats, rice bran, barley, and oranges.

Insoluble fibers are found mostly in whole wheat (wheat bran) and rye products,

along with banana. Examples of insoluble fibers are cellulose, lignin, and some

hemicelluloses (Anderson et al., 2009; Brown, 2011).

High intake of dietary fibers have been associated with a lot of health

benefits. Its main effect is to regulate intestinal degradation and absorption of

nutrients as well as their transit along the gut (Taghipoor, et al., 2014). Lower

prevalence of coronary heart disease, stroke, peripheral vascular disease, diabetes,

obesity, and certain gastrointestinal diseases have been proven by consuming high

intake of dietary fiber (Anderson et al., 2009). One of the reason is because fibers

are found to be able to lower blood pressure and serum cholesterol levels.

Improved glycemia and insulin sensitivity is also caused by high intake of dietary

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fiber. Dietary fibers are also found to be able to significantly enhances weight loss

of obese individuals. Recent researches shows that intake of inulin and certain

soluble fibers might enhances immune function in humans, although further

research need to be done to prove it (Anderson et al., 2009).

2.7 Response Surface Methodology

Response Surface Methodology (RSM) is a collection of mathematical and

statistical techniques that are useful for the modeling and analysis of problems, in

which a response of interest is influenced by several variables and the objective is

to optimize this response (Montgomery, 2001). This method is able to process

responses based on precise maps using mathematical models to achieve one spot

that meet all of the required target. RSM is often used by industries to optimize a

certain factor in the process to achieve the best end product with minimal loss

(Montgomery, 2001).

2.7.1 Central Composite Design

Central Composite Design contains an imbedded factorial or fractional

factorial design with center points that is added with a group of “star points”

which allow estimation of a curvature (NIST, 2012). The distance from the central

to the factorial point is defined as +1, while the distance from the central point to

the star point is |α|>1. The value of α depends on the properties based on the

design and the numbers of factors involved. The star points represents the extreme

value for each of the factor involved in the design. The number of star points

always contains twice as there are factors in the design. There are three types of

central composite design, which are circumscribed, inscribed and face centered.

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Circumscribed designs are the original form of central composite design. This

design has circular, spherical or hyperspherical symmetry and requires 5 levels for

each factor. Inscribed type is usually used whereby the limits for each factor are

truly limits. It is basically a scaled down circumscribed design with each factor

level of the design divided by α to generate the inscribed design. Face centered

type’s star points is at the center of each face of the factorial space, so α = + 1

(NIST, 2012).

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CHAPTER III

RESEARCH METHODOLOGY

3.1 Materials and Equipments

Materials used in this experiment include chia (Salvia hispanica L.) seeds

obtained from SuperFood Indonesia in Jakarta, wheat flour with brand “Kunci

Biru”, margarine/hydrogenated vegetable fat (HVF) with brand “Blue Band”,

sugar, egg yolk, baking powder, and vanilla powder. For analysis, materials which

were used includes H2O2 ex.Merck, H2SO4 ex.Merck, K2SO4 ex.Merck, NaOH

ex.Merck, HCl ex.Merck, mixed indicator (100 mL of 0.1% methyl red with 200

mL of 0.2% bromocresol green) ex.Merck, Boric acid ex.Merck, Hexane PA

ex.Merck, Na3PO4 ex.Sigma-Aldrich, termamyl enzyme ex.Merck, pepsin enzyme

ex.Merck, pancreatin ex.Merck, ethanol ex.Merck, and acetone ex.Merck.

Equipments used in this experiment were dry blender, sifter, blender, oven,

mixer, stove, cookie cutter, balance “Mettler Toledo”, and pan. For the analysis,

equipments used were oven “Memmert”, kjeldahl system “VELP Scientifica UDK

127”, kjeldahl flask, desiccator “Duran”, muffle furnace “Thermoline 48000”,

tongs, texture analyzer “VELP Scientifica UDK 127”, evaporating dish, filter

paper, erlenmeyer, soxhlet equipment, and burette.

3.2 Research Procedure

3.2.1 Preliminary Research

3.2.1.1 Nutritional Content Analysis of Chia Flour

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Chia flour was analysed for its nutritional content by using proximate

analysis. The seeds was initially grounded using dry blender before sieving

through 20-mesh screen. Proximate analysis was used to determine the

carbohydrate, protein, fat, moisture, ash content, dietary fiber and omega-3 fatty

acid.

3.2.1.2 Determination of Mixing Method

This step was done to determine the method which gives the best texture

for the cookies. Two types of mixing method were used to make the cookies,

which are one stage mixing and two stages mixing. Basic formula shown in Table

3.1 was used for preliminary research.

Table 3.1 Basic formulation for cookiesIngredients Amount (g)Wheat flour 100Chia flour 15Margarine/HVF 55Sugar 70Egg 40Vanilla powder 0.2Baking powder 0.2

Source: Novianty (2015)

In one stage mixing, all ingredients were weighed, placed in the mixer, and

then mixed at low speed until the mixture becomes uniform. For two stages

mixing, all the ingredients were weighed and then placed separately. First, the fat,

sugar, and salt were put in the mixer and then mixed at low speed until the texture

is light and fluffy. Afterwards, eggs and other liquid ingredients were added and

blended at low speed. Then, the flour and leavening agent were added and mixed

until it becomes homogen. Sensory analysis and texture analyzer was used to

determine the best mixing method (Bassinello et al., 2011).

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3.2.2 Main Research

In the main research, the first activity done was making cookies with

different formulation of chia flour and hydrogenated vegetable fat (HVF), which

was determined according to a 22 Central Composite Rotational Design. Before

making the cookies, all chia seeds were grinded using dry blender and sieved

through a 20-mesh screen and packed in plastic containers. Afterwards, all

ingredients used in the formulation, which are wheat flour, chia flour, HVF, sugar,

egg, vanilla powder, and baking powder were weighed according to the

formulations, shown in Table 3.3. Next, all the ingredientes were mixed together

using the proper mixing method, which was determined in the preliminary

research. Using a cookie cutter, the dough was shaped and then placed into

margarine-smeared pan. After that, the dough was baked at 145 oC for

approximately 15 - 20 minutes. The cookies were cooled down after the baking

process is finished. Figure 3.1 shows the flowchart of cookie production.

The second activity was evaluating the physico-chemical characteristics of

the cookie produced, which includes the spread of the cookies, texture, color, and

moisture content. The third activity was sensory test to evaluate the preference of

panelists towards the cookie produced using hedonic test. After the result from the

physico-chemical analysis and sensory evaluation comes out, Response Surface

Method (RSM) was used to determine the recommended best composition.

Verification test was done afterwards towards the recommended composition.

After the optimum or best cookie formulation is determined, proximate analysis

was done to analyse the difference of the components inside the cookie between

cookies made with chia flour and the control cookie. The analysis includes

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carbohydrate content, protein content, fat content, ash content, fiber content, and

omega-3 content. The last activity was comparing the physical characteristics and

the result of the proximate analysis between the experimental cookies and control

cookies.

Grinding chia seeds into flour using dry blender and sieved through 20-mesh screen

Ingredient are weighted according to formulation (refer to Table 3.3)

Chia and wheat flour are mixed with HVF, sugar, egg, vanilla powder, and baking powder with the proper method determined from preliminary research

The dough is shaped using cookie cutter, and then placed into the margarine-smeared pan

The dough is baked at 150oC for 15 minutes

Let the cookies cool

Figure 3.1 Flowchart of the cookies makingSource: Novianty (2015), with modification

3.2.2.1 Determination of Chia Cookie Formulation

Detemination of formula used to produce chia cookies was conducted

using RSM with Design Expert 7.0®. This method was used to help the

optimization of composition of component used in the cookies, by recommending

the best formulation to be used based on responses to each formulation. There are

two factors used in this research, which are chia flour and HVF. Table 3.2 shows

the upper and lower level of chia flour and HVF used, and the cookies

formulation for optimization can be seen in Table 3.3. Table 3.4 shows the goal

and importance of each parameter. Texture parameter was set to the highest level,

which is 5, as it is the main objective of this research. Sensory evaluation result

was done to determine which cookie formulation have the highest acceptability in

texture parameter. Afterwards, physico-chemical analysis was done to determine

the effect of different compositions of chia flour and HVF towards the texture

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characteristics of cookie. The RSM recommended the optimal composition to

produce chia cookies.

Table 3.2 Concentration composition of cookies formulaFactor -α Level (g) -1 Level (g) 0 +1 Level (g) +α Level (g)

Chia Flour 0.00 4.39 15 25.61 30HVF 33.00 36.22 44.00 51.78 55

Table 3.3 Formulation Combination ModelNo Chia Flour (g) HVF (g)

1 4.39 36.222 15.00 44.003 4.39 51.784 25.61 51.785 25.61 36.226 15.00 44.007 15.00 44.008 15.00 55.009 30.00 44.0010 15.00 44.0011 15.00 33.0012 15.00 44.0013 0.00 44.0014 15.00 44.00

Table 3.4 Optimization cookies formula goal and importanceFactor Goal ImportanceOrganoleptic Texture Maximize 5Physico-chemical Hardness Is in range 3characteristics Fracturability Is in range 3

Cookies spread Is in range 3Moisture content Is in range 3

3.2.2.2 Verification Test

This test was done to verify the formula given by the RSM. It was done by

producing cookies based on the recommended formulation and then conduct

physico-chemical analysis and sensory evaluation towards the cookies. The result

of the tests was compared with the prediction value of RSM.

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3.2.2.3 Product Comparison

To observe the effects given by the addition of chia flour, comparison was

done by comparing the experimental cookies with control cookies. The nutritional

content, physico-chemical properties, and sensory evaluation result is compared

with control cookies.

3.3 Experimental Design

3.3.1 Preliminary Research

The treatment done in the preliminary research was to compare the effects

of different mixing method towards the physical characteristic of the cookies

produced. The data was analysed using binomial test with two factors, which was

one-stage and two-stage mixing method. The hypothesis are as follows:

H0 = There is no effect of different mixing method towards panelist preference.H1 = There is an effect of different mixing method toward panelist preference.

3.3.2 Main Research

3.3.2.1 Chia Cookies Formula Determination

The experimental design for this research was done to determine the best

formulation of cookies using the optimal concentration of chia flour and HVF

using RSM method. The Design Expert processed the result of the analysis and

recommend the best formulation. The statistical model of this research is written

below:

Y = β1X1 + β2X2

Y = Response functionβ = Linear coefficientX1 = Chia flour concentrationX2 = HVF concentration

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3.3.2.2 Product Comparison

Components and physical properties of experiment cookies and control

cookies were compared using independent sample t-test. Dependent sample t-test

was used when comparing the sensory parameters between experiment and

control cookies. The statistical model is as follows:

Yij = μ + Ai + εij

Yij = Observation value from experiment cookies at level 1 and repetition j.μ = Actual mean valueAi = Effect of formulation at level iεij = Error factorH0 = There is no difference between experiment cookies and control cookies H1 = There is a difference between experiment cookies and control cookies

3.4 Analysis Procedure

3.4.1 Physico-chemical Analysis

3.4.1.1 Cookies texture (Bourne, 2002)

Texture analyzer was used to determine the cookie texture. Hardness value

was considered as the maximum force obtain in the curve and fracturability as the

linear distance towards the maximum point. The studies was conducted using a 2

mm probe at a crosshead speed of 3 mms-1. Parameters measured were hardness

and fracturability.

3.4.1.2 Cookies spread (Sharif et al., 2009)

Spreading of cookie was observed manually using a ruler. The height and

diameter of the cookies before and after baking was observed as well. The height

was observed by placing six cookies horizontally (from edge to edge), and has its

height measured while the cookies are rotated 90o. Thickness was measured by

placing six cookies to one another.

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Spread factor = Weight

Thickness x Correction Factor x 10

3.4.1.3 Proximate Analysis

3.4.1.3.1 Moisture Content (AOAC, 2005)

Analysis of moisture content was done using oven method. First, 5 grams

of sample was transferred to the constant evaporating dish and placed in the oven

at 105 oC for 6 hours. After drying, the sample was moved into a desiccator to

cool down. Weighing process was done afterwards, and finished until the constant

weight is achieved.

Moisture Content (Wet Basis) = W 1−W 2

W 1 x 100

Where: W1 = weight (g) before dryingW2 = weight (g) after drying

3.4.1.3.2 Ash Content (AOAC, 2005)

Determination of ash content of cookies was done using dry ashing

method. Approximately 3 g of sample was weighed and put in the constant

crucible, which was digested until no smoke is formed. The crucible was then

placed in a muffle furnace, which afterwards was ignited at 550 oC until light gray

ash was obtained. The obtained ashes was then cooled in desiccator and weighed.

% Ash content (dry basis) = x− y

z × 100%

where: x = weight after ashing

y = weight of crucible

z = original sample weight

3.4.1.3.3 Protein Content (AOAC, 2005)

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Kjeldahl method was used to analyze the protein content. Fat free sample

weighing around 2 g was wrapped with a filter paper and placed in digestion

flask. The flask was then added with 7 g of K2SO4 and 0.05 g of Selenium. It was

then followed by the addition of 10 mL H2SO4 and 10 mL H2O2. The sample was

destructed until clear solution was obtained. Afterwards, the solution was cooled

down with the addition of 50 mL NaOH. The flask was then connected to a

distilling bulb on a condenser, in which the tip was immersed in a solution of

boric acid mixed with 3 drops of indicator. The distillation process was done for

about 5 minutes. Any excess acid in the distillate was then titrared using HCl

solution until pink color is achieved.

% Protein = ¿¿ x 100%

Where: A = Volume (ml) of titrationB = Volume (ml) of blankN = N HClW = weight (mg) of sample14.007 = atomic weight of nitrogen6.25 = protein conversion factor

3.4.1.3.4 Fat Content (AOAC, 2000)

Fat content analysis was done using soxhlet method. Approximately 5 g of

sample was wrapped in filter paper and put into extraction thimble. Hexane was

then added into the boiling flask. Afterwards, boiling flask, soxhlet flask, and

condenser was assembled. Fat was then extracted in a soxhlet extractor for 6

hours. Then the boiling flask with extracted fat was dried in oven at 105 oC until

constant. After drying, the sample was cooled down in the desiccator, and then

weighed.

% Fat content (dry basis) = weight of fat extracted (g) × 100%Weight of sample (g)

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3.4.1.3.5 Carbohydrate Content (AOAC, 2005)

Determination of carbohydrate content was done using difference method.

Carbohydrate content (%) = 100% - (% moisture + % ash + % protein + % fat)

3.4.1.4 Dietary Fiber Content

Approximately 1 g of dry fat free sample was placed in Erlenmeyer, and

0.1 M sodium phosphate is added. Afterwards, 0.1 ml of termamyl enzyme was

added into the mixture, and then covered with aluminium foil. The mixture was

then incubated in a water bath at 100 oC for 15 minutes. The mixture was then

cooled down, and afterwards 20 ml aquadest and 1 M HCl was added. The pH of

this mixture should be 1.5. Afterwards, 100 mg of pepsin enzyme was added, and

then the erlenmeyer flask was covered again and incubated in water bath at 40 oC

for 60 minutes. HCl addition was done to adjust the pH to 4.5. The mixture was

then filtered with a dry crucible which have been weighed and contains 0.5 g of

dry celite. The mixture was then washed twice with 10 ml of aquadest. The filtrate

was then used to determine the soluble fiber, while the precipitates were used to

determine the insoluble fibers. The precipitate was washed with 10 ml of 95%

ethanol and 10 ml acetone twice. Afterwards, the precipitate was dried in 105 oC

until it reaches constant weight. Then, the precipitate was ashed in furnace at 550

oC for 5 hours.

% Insoluble fiber = (A – B – C)/W x 100%

A = weight after dried (g)B = weight after ashed (g)C = weight of fat free blank (g)W = sample weight (g)

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The soluble fiber was determined by adding water into the resulting filtrate

until the volume reaches 100 mL. Afterwards, 400 ml of 95% ethanol was added

and the mixture was cooled for 1 hour. The mixture was then filtered with dry

crucible which have been weighed and contains 0.5 g of celite. The resulting

filtrate was washed twice with 10 ml of 78% ethanol, 10 ml 95% ethanol, and 10

ml acetone. Afterwards it was dried in 105 oC until constant weight was reached.

The filtrate was then ashed in furnace at 550 oC for 5 hours and cooled down in

desiccator before weighing.

% Soluble fiber = (A – B – C)/W x 100%

A = weight after dried (g)B = weight after ashed (g)C = weight of fat free blank (g)W = sample weight (g)Total dietary fiber = insoluble fiber + soluble fiber

3.4.1.5 Omega-3 Fatty Acid Content

Omega-3 analysis was done using gas chromatography. Initially, the

samples were dried and has its fat content extracted, using fat extraction method

from AOAC (2000). Afterwards, the fatty acid methyl esters (FAMEs) found in

the fat were obtained and the compositions determined via gas chromatography

with a flame ionisation detector (FID). Omega-3 fatty acid was determined and

has its content calculated, with the result expressed as g per 100 g of fat (AOCS,

2005).

3.4.2 Sensory Evaluation

Hedonic test was used in the sensory evaluation. Texture parameter is used

in this test. A total of 75 panelists was used. In the test, 1 indicates the least

preferred cookie, while 7 indicates the most preferred cookie. Panelists were

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asked to determine the score by eating each of the cookie sample. Mineral water

was provided and panelists must take a sip of water in between tasting each of the

samples. Afterwards panelists have to write the score in the form (Meilgaard et

al., 2007).

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CHAPTER IV

RESULT AND DISCUSSION

4.1 Overview

The cookies made were pressed cookies, with the addition of chia seed

flour. Proximate analysis of the chia seeds and determination of the best mixing

method were done first before the main experiment was commenced. The main

experiment was done to determine the optimal cookie formulation, the verification

of the formula, and characterization of the product.

4.2 Nutritional Content of Chia Flour

Chia flour is the main component in the making of the cookies. The

nutritional content of chia flour can be seen in Table 4.1. The identification result

is written in Appendix A.

Table 4.1 Nutritional Content of Chia FlourNutrition Chia SeedProtein (%) 17.24 ± 0.10Fat (%) 30.97 ± 0.25

Omega-3 ( %) 19.14Ash (%) 1.66 ± 0.13Carbohydrate (%) 41.88 ± 0.35Total Dietary Fiber (%) 42.60Moisture (%) 8.25 ± 0.38

The nutritional value of chia flour closely matches the value from USDA,

in which it is written as follows: 16.54 g protein/100 g, 30.74 g fat/100 g, 17.83 g

omega-3 fatty acids/100 g, and 42.12 g carbohydrate/100 g. However the total

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dietary fiber content of chia flour was significantly higher than the value from

USDA, which is written as 34.4 g dietary fiber / 100 g (Munoz et al., (2013).

4.3 Determination of Mixing Method

The mixing method of the cookies was determined based on the sensory

evaluation of the cookie’s texture. As fibers are found in large amount in chia

seeds, and it can affect the texture of the cookie produced, hence texture is the

parameter analyzed. Based on the result of the sensory evaluation, the best mixing

method is used. Two mixing method used in this experiment are one-stage and

two-stage mixing. Paired comparison and paired preference test were used in the

determination of mixing method. In paired comparison test, panelist were asked to

determine which cookie is more hard to bite, while in paired preference test, the

preferred cookie is chosen. Appendix B shows the questionnaire of both tests. The

result of the test is as shown in Figure 4.1 and 4.2.

96%

4%

One-stageTwo-stage

Figure 4.1 Result of Paired Comparison TestNote : One-stage = 72 panelists; Two-stage = 3 panelists

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16%

84%

One-stageTwo-stage

Figure 4.2 Result of Paired Preference TestNote : One-stage = 12 panelists; Two-stage = 63 panelists

The sensory evaluation data of both tests are found in Appendix C, while

the statistical analysis are found in Appendix D. The result from both the paired

comparison and paired preference test shows that there are significant differences

between cookies made with one-stage and two-stage mixing. In the paired

comparison test, cookie made with one-stage mixing is significantly harder than

cookie made with two-stage mixing. The paired preference test shows that cookie

made with two-stage mixing is more preferable than cookie made with one-stage

mixing. The result is backed by result from texture profile analysis, which can be

seen in Appendix E. Table 4.2 shows the average of hardness value of cookie

made with one-stage and two-stage mixing respectively. According to Hui (2006),

mixing cookie ingredients in two stages can minimize the development of gluten

in the flour, which is desirable in cookie dough. By mixing the cookie ingredient

in two stages, the fat will be more evenly dispersed around the flour particles, and

therefore rendering them less available to water and preventing gluten

development. High protein content, which causes gluten development in cookie

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dough is associated with harder cookies (Gaines, 1992). In one-stage mixing, the

baker has less control over the mixing, and therefore, the gluten development as

well. However, it can be used when over-mixing is not a serious problem, for

example in the making of chewy cookies (Hui, 2006).

Table 4.2 Hardness Value of Cookie Made With Different Mixing MethodsMixing Method Hardness (g)

One-stage mixing 2944,10 ± 156,54

Two-stage mixing 1864,33 ± 176,78

4.4 Formula Optimization of Cookies

This step was done to find the formula to made cookies from chia seeds

with the best texture based on the sensory evaluation. The sensory evaluation

questionnaire can be seen on Appendix F. Parameter evaluated is texture. The test

was done in the span of two weeks, in which the panelists must evaluate the

sensory attributes of 3 and 4 samples each week, with a total of 14 samples, which

was done to avoid sensory fatigue. According to Stone and Sidel (2004), sensory

fatigue can happen if panelists are asked to evaluate too many samples, and

consequently, the evaluation result becomes inaccurate. The result of the sensory

evaluation can be seen on Appendix G. Texture analysis, moisture content, and

spread rate were used to obtain objective data regarding the parameters of the

cookies.

The data obtained from the experiment were analyzed using Response

Surface Methodology (RSM). RSM is a mathematical and statistical method to

optimize responses from several variables (Montgomery, 2001). In this case, the

responses are all the parameters which was measured and the variables are the

chia flour and hydrogenated vegetable fat (HVF). Through RSM, the best

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combination of chia flour and HVF to obtain cookies with the optimal texture can

be found. The analysis result from RSM shows the appropriate statistical model

for each responses. Table 4.3 shows the appropriate statistical model of each

responses.

Table 4.3 Statistical Model for Each ResponsesResponse Model P-value model P-value Lack of fit

Texture Linear 0.0011 0.4712

Hardness Linear 0.0003 0.4558

Fracturability Quadratic 0.0003 0.2622

Spread ratio Quadratic 0.0001 0.0404

Moisture content Linear 0.0026 0.7306

In RSM, the P-value of the statistical model must be significant to show

that it is the most appropriate model (<0.05). While for the P-value in lack of fit

must be not significant to indicate that the chosen model is appropriate (>0.05)

(NIST, 2012). As shown in Table 4.3, all the responses has P-value less than 0.05,

which means all the selected models are significant, indicating that there are

significant differences found between the different compositions of chia flour and

HVF. However, in lack of fit, the P-value of spread ratio was found to be

significant, which means that the selected model does not accurately fit the data,

however, as the P-value model is significant, it means that although the different

composition of chia flour and HVF affected the spread ratio significantly, the

selected model does not represent the data accurately.

4.4.1 Optimization of Sensory Evaluation Result

Sensory evaluation was done to evaluate the preference of panelists in

terms if its texture. The texture of cookies is the most important parameter in

cookies. What differentiates cookies with the other bakery product is its

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crispiness. The interaction between fat and flour used is what made the

characteristic crispiness of the cookies. The resulting interaction between chia

flour, wheat flour, and HVF in this experiment were measured in terms of

desirability in the sensory evaluation test. Table 4.3 shows the P-value for model

and lack of fit in fit summary test, and linear model was found to be the most

appropriate model to represent the data. Figure 4.3 shows the 3-D graph for

texture response, while Figure 4.4 shows the contour graph. Appendix H shows

the statistical analysis of texture response. According to the analysis, chia flour

and HVF significantly affects the texture response. Shown below is the final

equation for texture response:

Y= 2.54849 - 0.033123 A + 0.066099 B

Note:Y = Hedonic score for textureA = Chia flourB = HVF

Figure 4.3 3-D Graph for Texture Response Based on Hedonic Test

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Figure 4.4 Contour Graph for Texture Response Based on Hedonic Test

The result of the sensory evaluation test shows that panelists prefer

cookies made with less chia flour and high amount of HVF. From the graph, it can

be concluded that high concentration of HVF can offset the undesirability of high

amount of chia flour. The result is similar to experiments done by Pizarro et al.

(2013) and Steffolani et al. (2015), whereby pound cake and bread added with

chia flour decreases its texture desirability respectively.

4.4.2 Optimization of Physical Analysis Result

4.4.2.1 Hardness

Hardness is considered to be the force needed to bite through the cookie in

a single bite (Bourne, 2002). Fit summary test from RSM in Table 4.2 shows that

linear model is suitable to represent the hardness response. The graph for hardness

response can be seen in Figure 4.5 and 4.6. Appendix I and Appendix J shows

result of hardness analysis and the statistical analysis of the hardness response

respectively. The statistical analysis result shows that both chia flour and HVF

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significantly affects the hardness response. The equation for hardness response is

as follows:

Y= 5754.73699 + 12.08214 A - 62.86553 B

Note:Y = Hardness valueA = Chia FlourB = HVF

Figure 4.5 3-D Graph for Hardness Value

Figure 4.6 Contour Graph for Hardness Value

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Based on the result shown in the graph and equation, it can be seen that

chia flour significantly increases the hardness of cookie, while HVF decreases it.

According to Pizarro et al. (2013), chia seed contains high amount of dietary

fibers, which in turn disturbs the fat and air distribution in the dough by exerting

physical impairment towards the dough.. Fat distribution is especially important in

cookie, as fat impedes gluten formation by breaking the long gluten strands in the

dough and help stabilize air cells. According to Gaines (1992), gluten formation is

associated with hard cookies, as the gluten structure . With the fat distribution

interrupted, gluten formation occurs, and consequently the cookies become harder

due to gluten’s tough and elastic nature. The result, compared with the sensory

evaluation result of texture parameter shows that cookies with hard texture is

undesirable according to panelists. Therefore, it can be concluded that the addition

of chia flour increase the hardness of cookie, and HVF can help decrease it.

4.4.2.2 Fracturability

According to Bourne (2002), fracturability is the force needed to shatter a

cookie in a single bite. Based on fit summary test, quadratic model fits the

fracturability response data. Figure 4.7 and 4.8 shows the graph for fracturability

response. Red color indicates high value and low value is indicated with blue

color. The result of fracturability analysis is shown in Appendix I. Appendix K

shows the statistical analysis of fracturability response. According to the analysis,

all the factors are significant, except for the quadratic HVF (B2) factor. This is

because the p-value is above 0.05, meaning that the factor does not significantly

affect the fracturability response and as a result, it is not put on the final equation.

Below is the equation for the fracturability response:

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Y= 11.70780 + 0.087422 A - 0.021202 B - 3.94545 x 10-3 AB + 1.61889 x 10-3 A2

Note:Y = Fracturability valueA = Chia FlourB = HVF

Figure 4.7 3-D Graph for Fracturability Value

Figure 4.8 Contour Graph for Fracturability Value

Based on the interaction term and the graph, it can be seen that the

addition of HVF significantly increases the fracturability of cookie in low amount

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of chia flour, but the effect is not significant if the chia flour is added in large

amount. Addition of HVF higher than used in this research might be needed to

maintain high fracturability value. Chia flour have a very small positive quadratic

effect towards the fracturability of cookie, whereby in small and high amount, the

value actually increases. Similar to the texture response, the change in

fracturability value is also affected due to the large amount of dietary fiber found

in the chia flour (Pizarro et al., 2013). As more chia flour is added, so does the

dietary fibers, therefore causing the fat to be unevenly distributed. This is because

fiber exerts physical impairment toward the dough, by displacing the fat

distribution around the dough. According to Jacob and Leelavathi (2006), fat

helps increases the crispiness of cookie, which is associated with high

fracturability. This is due to fat’s ability to break long gluten strains in the dough,

which consequently causes the dough to soft and less viscous. The resulting

dough after baking will be soft and crispy. Due to uneven distribution of fat, these

long gluten strains were not broken and the cookie becomes harder to fracture,

due to gluten’s tough and elastic nature. This is supported by research done by

Novianty (2015), whereby the incorporation of ingredient with high amount of

dietary fiber decreases the fracturability of cookies. The result, compared with the

result of sensory evaluation in texture parameter, shows that low fracturability

value of cookie is undesirable according to panelists. Therefore it can be

concluded that chia flour significantly decreases the fracturability of cookie, while

HVF can increase it in low amount of chia flour.

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4.4.2.2 Spread Ratio

Spread ratio is defined as the ratio between the diameter of cookies and its

thickness. The value is directly proportional of its diameter and inversely with its

thickness. Fit summary test from RSM shown in Table 4.3 shows that the

quadratic model fits the data for spread ratio. However, the P-value for lack of fit

was shown to be significant. The possible explanation for this is the high standard

deviation of the data. The result and statistical analysis for spread ratio response is

shown in Appendix L and Appendix M respectively. Result of the statistical

analysis shows that the quadratic HVF factor (B2) is not significant (p-value >

0.05), therefore it is not included in the final equation. Figure 4.9 shows the 3-D

graph for spread ratio response, with blue color indicating low spread ratio and

red color indicating the otherwise. The contour graph is shown in Figure 4.10.

Below is shown the equation for spread ratio response:

Y= -0.63690 + 0.12724 A + 1.37668 B - 0.023727 AB + 0.013871 A2

Note:Y = Spread ratio valueA = Chia FlourB = HVF

Figure 4.9 3-D Graph for Spread Ratio

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Figure 4.10 Contour Graph for Spread Ratio

From the result of the experiment represented on the graph, it can be seen

that HVF significantly increases the spread ratio of cookie in low amount of chia

flour, however the effect is not significant if the chia flour concentration is higher.

Chia flour have very small positive quadratic effect towards the spread ratio of

cookie, whereby in small and high amount, the value actually increases.

According to experiment done by Pizarro et al. (2013), high fiber content of chia

seed lowers the specific volume of cake formulated with the addition of chia flour.

The author concluded that the cause is the high amount of fiber found in chia

seed, which interferes the distribution of fat and air around the dough. As fat were

distributed unevenly, gluten formation occurs uncontrollably, thereby causing the

dough to be tough and elastic, making it harder to spread during baking. Another

experiment done by Saeed et al. (2012) which studies the effect of sweet potato

flour on the quality of cookie also reports that high content fiber decreases the

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width or diameter of the cookies produced. The journal mentions that high water

absorption capacity of sweet potato flour also contributes toward the decreasing

spread ratio of the final product, which decreases the amount of free water present

in the dough. The loss of free water creates viscous dough, which in turn

decreases the spread ratio in its final product. Based on manuscript written by

Munoz et al. (2013), chia seed is known to possess high water absorption capacity

as well, as the insoluble fibers has the ability to absorb high amount of water, and

as such, it further decreases the spread ratio of the final product. In this

experiment, spread ratio seems to be increased in low amount of chia flour by

increasing HVF content, as the fiber content is still relatively low, however when

the chia flour concentration is high, the fiber content becomes so high that

increasing HVF will not have any effect any longer. Increasing the amount of

HVF higher than used in present study might be beneficial to help increase spread

ratio in high amount of chia flour.

4.4.2.3 Moisture Content

According to the fit summary test, linear model fits the data for moisture

content response. Moisture content is one of the most important parameter of

cookie, as it influences the texture of the cookie formed. Low moisture content

increases the crispiness of cookie, while higher moisture content form soft cookie

(Hui, 2006). Appendix N shows the data of moisture content, while Appendix O

shows the statistical analysis for moisture content response. All factors in the

experiment significantly affects the moisture content response according to the

statistical analysis. The data for the moisture content response is represented in a

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3-D and contour graph in Figure 4.11 and 4.12 respectively. The resulting

equation for moisture content response is as follows:

Y= 6.16682 + 0.056443 A - 0.072952 B

Note:Y = Moisture contentA = Chia FlourB = HVF

Figure 4.11 3-D Graph for Moisture Content

Figure 4.12 Contour Graph for Moisture Content

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Chia flour was found to significantly increases the moisture content of

cookie. The possible explanation for this is the water absorption capability of chia

flour. According to Munoz et al. (2013), one of chia seed’s characteristic is its

ability to absorb large amount of water, due to its insoluble fiber content.

Experiment done by Novianty (2015) shows that the addition of ingredient with

high water absorption capability can increase the moisture content of cookie. The

insoluble fibers absorb free water, thereby making the dough more viscous. This

creates harder and less crispy cookies, which correlates with the result of hardness

and fracturability parameter.

4.4.3 Optimal Formula Recommendation

The optimal formula of chia flour and HVF in the cookie was determined

by Design Experiment via RSM, based on the data of the experiment. To

determine the optimal composition, goals were set for each responses and

variables, with particular focus on the texture parameter from the sensory

evaluation result, as the goal of this response is to obtain cookie with optimal

texture. To help this, the importance was set, with 5 as the highest priority and 1

as the lowest priority. The Design Expert optimized the formulation according to

goals with highest importance first, followed by the least important. Chia flour

and texture’s importance was set to 5, as the objective of this research is to obtain

cookie with highest amount of chia flour while having the best texture quality as

well. The criteria and goals for each response can be seen in Table 4.4.

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Table 4.4 Criteria and Goals of Each Responses for Optimal Cookie FormulationFactors Goal Lower Limit Upper Limit Importance

Chia Flour (g) Maximize 0 30 5

HVF (g) In range 33 55 3

Texture Maximize 3.95 5.84 5

Hardness (g) In range 2361.19 3930.77 3

Fracturability (mm) In range 12.028 13.637 3

Spread ratio In range 27.59 44.295 3

Moisture content (%) In range 2.65 6.01 3

Based on goals set previously, the Design Expert determined the optimal

composition of chia flour and HVF and gave the desirability value. The

desirability value is between 0 to 1, and the target is to achieve value as high as

possible, with 1 as the ideal response value (NIST, 2012). The optimal formula

recommended by the Design Expert can be seen in Table 4.5. Afterwards, the

optimal formula needs to be verified using sensory evaluation and physico-

chemical analysis and compared to the prediction value calculated by Design

Expert.

Table 4.5 The Optimal Formula of Cookie Formulated With Chia Flour

Formulation Chia Flour (g) HVF (g) Desirability

1 20.45 55.00 0.702

4.5 Product Verification

This step was done to verify the formulation recommended by the Design

Expert. In order to verify the formulation, sensory evaluation and physico-

chemical test was done. Appendix P and Appendix Q shows the questionnaire and

result of the sensory evaluation test respectively. Appendix R shows the

physicochemical analysis result. The comparison between the prediction value

and the actual result is shown in Table 4.6.

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Table 4.6 Comparison Between Prediction Value and The Actual Result

Response Predicted Actual 95% CI low

95% CI high

95% PI low

95% PI high

Texture 5.51 5.25 5.07 5.94 4.66 6.36Hardness 2544.11 2574.84 2242.85 2845.38 1955.12 3133.10

Fracturability 12.53 12.83 12.22 12.83 12.06 12.99Spread Ratio 31.39 30.16 28.55 34.23 27.08 35.70

Moisture content 3.31 3.80 2.66 3.95 2.05 4.57

Based on the result in the table, it can be seen that some value are larger

than the predicted value, and some are smaller. However, as the value is still

within the 95% confidence interval (CI) and prediction interval (PI), it is still

acceptable. The 95% CI is defined as the range in which the process average is

expected to fall into 95% of the time, while 95% PI is the range in which and

individual value is expected to fall into 95% of the time (NIST, 2012).

4.6 Product Comparison

4.6.1 Sensory Evaluation Result

Hedonic test was done to determine the panelists preference between

control cookie and optimal chia cookie. The parameters observed are color,

aroma, texture, and taste. Appendix S and Appendix T shows the questionnaire

and data from the sensory evaluation. The data was further analysed using

dependent sample t-test, and is shown in Appendix U. The result of the sensory

evaluation test can be seen in Table 4.7.

Table 4.7 Result of Sensory Evaluation TestParameter Optimum ControlAroma 5.56 ± 0.89 a 5.77 ± 0.92 aColor 5.32 ± 1.22 a 5.87 ± 0.70 bTaste 5.61 ± 0.84 a 6.09 ± 0.74 bTexture 5.25 ± 1.24 a 6.08 ± 0.88 b

Note: Score 1: Least Desirable 7: Most Desirable

According to t-test analysis, there is no significant difference in terms of

aroma between the control cookie and optimum chia cookie. However, for color,

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taste, and texture, the result significantly shows that panelist prefer the control

cookie compared to the optimum chia cookie. Color parameter of optimal chia

cookie was lower than control cookie due to greyish color formed in its texture,

which is similar to experiment done by Steffolani et al. (2015) regarding the

addition of chia flour into bread. The result for taste and texture also matches the

result of experiment done by Pizarro et al. (2013) about the addition of chia flour

into pound cake, which was lower compared to the control cake. Texture

parameter is lowered possibly due to higher hardness and lower fracturability of

optimum chia cookie compared to control cookie, caused by high content fiber of

chia seed which disrupts fat distribution, thereby allowing gluten to form in the

dough. The average scores for aroma, color, taste, and texture indicates that

optimum chia cookie is quite acceptable according to the panelists.

4.6.2 Physico-chemical Analysis

Parameters observed in physico-chemical analysis are hardness,

fracturability, spread ratio, and moisture content. Appendix V shows the data from

the physico-chemical analysis. Independent sample t-test analysis of the data

obtained can be seen on Appendix W. Table 4.8 shows the result of the physico-

chemical analysis.

Table 4.8 Result of Physico-chemical Analysis

Parameter Control OptimumHardness (g) 2017.13 ± 240.43 a 2574.84 ± 220.38 b

Fracturability (mm) 14.55 ± 0.34 a 12.83 ± 0.40 bSpread ratio 37.38 ± 1.13 a 30.16 ± 1.12 b

Moisture Content (%) 2.31 ± 0.24 a 3.80 ± 0.45 b

Based on t-test analysis, all the parameters tested between the control

cookie and optimum chia cookie differ significantly. Control cookie has

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significantly lower hardness and higher fracturability value compared to optimum

chia cookie. This is caused by high amount of fiber found in chia seed, which

impedes fat distribution, causing gluten to be formed which hardens the cookie

texture. Spread ratio of control cookie was also found to be significantly higher

than the optimum chia cookie, which is caused by high amount of fiber in chia

seed. The fiber impedes spread of fat, which is important in helping cookie dough

to spread as it cooks in the cooking sheet. Optimum chia cookie has significantly

higher moisture content compared to the control cookie, due to high water

absorption capacity of chia seed, which has high amount of unsoluble fiber.

4.6.3 Nutritional Composition

The nutritional value of optimum chia cookie is compared with control

cookie. This is done in order to know whether there are differences between the

nutritional value of optimum chia cookie and control cookie. The result of the

analysis is shown in Appendix X. Table 4.9 shows the data for nutritional content

of both optimum chia cookie and control cookie.

Table 4.9 Nutritional Content of Optimum Chia Cookie and Control CookieNutrition Optimum Control

Protein (%) 8.75 ± 0.01 7.21 ± 0.10Fat (%) 27.81 ± 0.05 28.10 ± 0.83

Omega-3 ( %) 1.64 0.09Ash (%) 1.18 ± 0.06 0.90 ± 0.01Carbohydrate (%) 58.46 ± 0.64 61.48 ± 1.21Total Dietary Fiber (%) 9.16 8.32Moisture (%) 3.80 ± 0.53 2.31 ± 0.29

As seen on Table 4.9, the nutrition content of optimum chia cookie and

control cookie is only slightly different. The protein, total dietary fiber, and

moisture content of optimum chia cookie is slightly higher compared to control

cookie. The carbohydrate content of control cookie is slightly higher than

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optimum chia cookie, while the fat content between the two cookies is very

similar. However, the most significant difference between optimum chia cookie

and control cookie is in its omega-3 fatty acid content, which was around 1.64 %

(1636.10 mg/100 g) compared to 0.09 % (87.45 mg/100 g) found in control

cookie.

According to standard set by FDA (2013), food is said to be a good source

of fiber if it contains 10 - 19 % or more of the daily value per reference amount

customarily consumed (RACC). The RACC of cookie is 30 g, and the daily value

for fiber is 25 g. The fiber content of optimum chia cookie is 9.16 %, which is

2.75 g. The amount is about 10.99 % of the daily value for fiber, meaning that it

can be claimed as a good source of fiber.

FDA (2014) allows food to be claimed high in α-linolenic acid (ALA) if it

contains ALA higher than 320 mg per RACC. Omega-3 fatty acid found in chia

seed is exclusively ALA, and so the standard can be used (Munoz et al., 2013).

The ALA content found in optimum chia cookie is 1636.10 mg/ 100 g, which

means the value per RACC is 490.83 mg. This value is significantly higher than

the minimal value, meaning that optimum chia cookie can be claimed to be a high

source of ALA.

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CHAPTER V

CONCLUSION AND SUGGESTION

5.1 Conclusion

The best mixing method to produce chia cookie with a better texture is

two-stage mixing method. Two-stage mixing produce softer cookies than one-

stage mixing method. High amount of chia flour lowers the spread ratio of the

cookie dough. It also formed hard and less crispy cookies, and increases its

moisture content, which makes the cookie less desirable in terms of texture. HVF

is important to maintain the cookie’s softness, crispiness, and decrease its

moisture content. Spread ratio of cookie dough was also increased in high amount

of HVF. The best formulation to produce chia cookie with the optimum texture is

20.45 g of chia flour and 55.00 g of HVF respectively. The texture parameter of

the cookie produced are as follows: moisture content 3.80%, hardness value

2574.84 g, fracturability value 12.83, spread ratio 30.16. It was well liked by

panelists in sensory evaluation test, obtaining the average score of 5.25 in the

texture parameter. The experimental cookie was found to have high amount of

omega-3 fatty acids and dietary fibers.

5.2 Suggestion

Further addition of HVF might be beneficial to further optimize the

texture, however consideration needs to be taken considering the amount of

saturated fatty acid in it. Addition of reducing agent might be beneficial to

increase spread ratio of dough and reducing hardness of cookie produced.

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NIST. 2012. “Process Modeling”. Home page on-line. Available from http://www.itl.nist.gov/div898/handbook/pmd/section4/pmd446.htm ; Internet, accessed 18 May 2015.

Novianty, Debby. “Optimization Composition of Wheat (Triticum spp.), Canna (Canna edulis), and Jack Bean (Canavalia ensiformis) Flour Towards Cookies Quality”. Sarjana Pertanian, Universitas Pelita Harapan, 2015.

Pizarro, Patricia Luna, Eveline Lopes Almeida, Norma Cristina Samman, and Yoon Kil Chang. “Evaluation of Whole Chia (Salvia hispanica L.) Flour and Hydrogenated Vegetable Fat in Pound Cake”. Food Science and Technology 54: 73 - 79, 2013.

Reyes-Caudillo, E., A. Tecante, and M.A. Valdivia-Lopez. “Dietary Fiber Content and Antioxidant Activity of Phenolic Compounds Present in Mexican Chia (Salvia hispanica L.) Seeds”. Food Chemistry 107: 656 - 663, 2008.

Saeed, Shazia, Muhammad Mushtaq Ahmad, Humaira Kausar, Saima Parveen, Sharoon Masih, and Abdus Salam. “Effect of Sweet Potato Flour on Quality of Cookies”. J. Agric. Res. 50 (4): 525 - 538, 2012.

Shahidi, Fereidoon. “Nutraceuticals and Functional Foods: Whole versus Processed Foods”. Trends in Food Science & Technology 20: 376 - 387, 2009.

Sharif, Mian K., Masood S. Butt, Faqir M. Anjum and Haq Nawaz. “Preparation of Fiber and Mineral Enriched Defatted Rice Bran Supplemented Cookies”. Pakistan Journal of Nutrition 8(5): 571-577, 2009.

Simopoulos, A.P., and L.G. Cleland. “Omega-6/Omega-3 Essential Fatty Acid Ratio: The Scientific Evidence”. World Review of Nutrition and Dietetics 92: 1-13, 2003.

Steffolani, Eugenia, Mario M. Martinez, Alberto E. Leon, and Manuel Gomez. “Effect of Pre-hydration of Chia (Salvia hispanica L.), Seeds and Flour on The Quality of Wheat Flour Breads”. Food Science and Technology 61: 401 - 405, 2015.

Stone, Herbert and Joel L. Sidel. Sensory Evaluation Practices 3rd ed. California: Elsevier, 2004.

Sumnu, Servet Gulum and Serpil Sahin. Food Engineering Aspects of Baking Sweet Goods. New York: Springer, 2006.

Taghipoor, M., G. Barles, C. Georgelin, J.R. Licois, P. Lescoat. “Digestion Modeling in the Small Intestine: Impact of Dietary Fiber”. Mathematical Biosciences 258: 101 - 112, 2014.

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APPENDICES

56

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Appendix A. Identification Result

ProteinSample mL HCl Weight (g) % Nitrogen % Protein Average

1 20,84 2,1251 2,75 17,17 17,242 20,16 2,0394 2,77 17,31

Calculation:% Protein = ¿¿ x 100%

= 20,84 mL x 0,2 N x 14,007 x 6,25 x 100%2125,1 mg

= 17,17%Fat

Sample Weight (g) Flask (g) Boiling Chip (g)

Final Weight

(g)% Fat Average

1 5,0051 105,9132 3,1861 1,5591 31,1530,97

2 5,0177 106,6245 1,5151 1,5449 30,79

Calculation:

% Fat = weight of fat extracted (g)

weight of sample (g) × 100%

= 1,5591 x 100% 5,0051 = 31,15%

Ash

SampleWeight

(g) Crucible (g) Final Weight (g) % Ash Average1 5,0345 20,9339 0,0790 1,57 1,662 5,0122 29,2951 0,0877 1,75

Calculation:

% Ash content = x− y

z × 100%

= (21,0129 - 20,9339) x 100% 5,0345

= 1,57%

Moisture Sample Weight Crucible (g) Final Weight (g) % Moisture Content Average

1 5,1224 39,0469 4,7136 7,98 8,252 5,1883 41,1139 4,7463 8,52

Calculation:

% Moisture content ¿ W 1−W 2W 1

X 100 %

= 5,1224 - 4,7136 x 100%5,1224

= 7,98 %Carbohydrate

NoCarbohydrate Content (%) Average (%)

1 42,13 41,88

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2 41,63

Calculation:% Carbohydrate = 100% - %Moisture - %Ash - %Fat - %Protein

= 100% - 8,25% - 1,66% - 30,97% - 17,24% = 41,88%

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Fiber and Omega-3 Fatty Acid Content of Chia Seed

A-3

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Appendix B. Questionnaire of Comparison Test

SIMPLE COMPARISON TEST

Product : CookiesName : Date :

Cicipi sampel dari kiri ke kanan. Jangan mencicipi ulang sampel. Tulis kode dari sampel yang lebih keras. Bilas mulut dengan air sebelum mencicipi sampel berikutnya.

Code

SIMPLE PAIRED PREFERENCE TEST

Product : CookiesName : Date:

Cicipi sampel dari kiri ke kanan. Jangan mencicipi ulang sampel. Tulis kode dari sampel yang lebih disukai. Bilas mulut dengan air sebelum mencicipi sampel berikutnya.

Code

B-1

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Appendix C. Result of Comparison Test

Simple Comparison Test

No Answer1 One-stage2 One-stage3 One-stage4 One-stage5 One-stage6 One-stage7 One-stage8 One-stage9 One-stage

10 One-stage11 One-stage12 One-stage13 One-stage14 One-stage15 One-stage16 One-stage17 One-stage18 One-stage19 One-stage20 One-stage21 One-stage22 One-stage23 One-stage24 One-stage25 One-stage26 One-stage27 One-stage28 One-stage29 One-stage30 One-stage31 One-stage32 One-stage33 One-stage34 One-stage35 One-stage36 One-stage37 One-stage38 One-stage39 One-stage

No Answer

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40 One-stage41 One-stage42 One-stage43 One-stage44 One-stage45 One-stage46 One-stage47 One-stage48 One-stage49 One-stage50 One-stage51 Two-stage52 One-stage53 One-stage54 One-stage55 One-stage56 One-stage57 One-stage58 One-stage59 One-stage60 One-stage61 One-stage62 One-stage63 Two-stage64 Two-stage65 One-stage66 One-stage67 One-stage68 One-stage69 One-stage70 One-stage71 One-stage72 One-stage73 One-stage74 One-stage75 One-stage

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Simple Paired Preference Test

No Answer

1 Two-stage2 One-stage3 Two-stage4 Two-stage5 Two-stage6 One-stage7 Two-stage8 Two-stage9 Two-stage

10 Two-stage11 One-stage12 Two-stage13 Two-stage14 Two-stage15 One-stage16 Two-stage17 Two-stage18 One-stage19 Two-stage20 One-stage21 Two-stage22 Two-stage23 One-stage24 Two-stage25 Two-stage26 Two-stage27 Two-stage28 Two-stage29 Two-stage30 Two-stage31 Two-stage32 One-stage33 Two-stage34 Two-stage35 Two-stage36 Two-stage37 Two-stage38 Two-stage39 Two-stage

No Answer40 Two-stage

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41 One-stage42 Two-stage43 Two-stage44 Two-stage45 Two-stage46 Two-stage47 Two-stage48 Two-stage49 Two-stage50 Two-stage51 Two-stage52 Two-stage53 Two-stage54 Two-stage55 Two-stage56 Two-stage57 Two-stage58 Two-stage59 Two-stage60 Two-stage61 Two-stage62 Two-stage63 Two-stage64 One-stage65 One-stage66 One-stage67 Two-stage68 Two-stage69 Two-stage70 Two-stage71 Two-stage72 Two-stage73 Two-stage74 Two-stage75 Two-stage

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Appendix D. Statistical Analysis of Comparison Test

Simple Comparison Test

Binomial Test

Category N Observed Prop.

Test Prop. Exact Sig. (2-tailed)

Simple Comparison

Group 1 One stage 72 ,96 ,50 ,000

Group 2 Two stage 3 ,04

Total 75 1,00

Simple Paired Preference Test

Binomial Test

Category N Observed Prop.

Test Prop. Exact Sig. (2-tailed)

Preference

Group 1 Two stage 63 ,84 ,50 ,000

Group 2 One stage 12 ,16

Total 75 1,00

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Appendix E. Result of Texture Analysis in Preliminary Analysis

Mixing Hardness

One Stage

2753,3 g3077,4 g2878,8 g3066,9 g

Two Stage

1828,5 g1687,0 g1832,5 g2109,3 g

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Appendix F. Questionnaire of Hedonic Test

UJI HEDONIK

Produk : CookiesNama : Tanggal :

Cicipi sampel dari kiri ke kanan, lalu nyatakan tingkat kesukaan masing-masing sampel berdasarkan parameter yang diuji dengan skala 1-7. Jangan membandingkan antar sampel. Bilas mulut dengan air sebelum mencicipi sampel berikutnya.

KodeTekstur

Keterangan:1 : Sangat tidak suka2 : Tidak suka3 : Agak tidak suka4 : Netral5 : Agak suka6 : Suka7 : Sangat suka

F-1

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Appendix G. Result of Hedonic Test

Week 1Texture

Formulation 1 Formulation 2 Formulation 33 5 75 4 62 5 75 4 57 5 66 6 76 5 76 4 56 6 64 4 77 7 76 5 67 6 75 5 56 6 66 7 75 3 53 4 45 4 65 5 66 6 74 6 53 6 63 6 65 5 67 6 77 5 75 5 53 3 37 6 55 5 54 1 65 7 76 7 72 5 52 5 25 5 67 5 64 5 56 6 6

G-1

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6 7 66 6 76 4 76 4 55 3 65 4 75 5 55 3 56 6 56 7 56 5 65 5 65 5 63 2 55 6 63 3 42 6 67 6 75 6 74 4 65 3 61 3 43 6 64 6 57 7 75 5 65 6 73 7 64 6 53 4 65 6 55 6 66 6 65 5 64 5 6

4,89 5,11 5,84Note : Formulation 1 : 4.39 g Chia Flour and 36.22 g HVF

Formulation 2 : 15.00 g Chia Flour and 44.00 g HVFFormulation 3 : 4.39 g Chia Flour and 51.78 g HVFScore 1 : Least Desirable 7 : Most Desirable

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Texture

G-3

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Formulation 4 Formulation 5 Formulation 6 Formulation 77 3 4 46 5 5 65 5 4 55 3 4 46 6 5 65 3 4 55 4 4 35 4 4 46 5 4 54 6 7 62 2 3 36 5 6 57 6 5 73 2 5 55 6 5 57 7 6 57 7 4 55 2 4 43 3 4 44 3 3 37 2 4 66 6 4 46 6 4 56 3 4 55 5 4 45 6 5 56 4 4 43 6 5 65 3 4 45 5 4 45 4 4 46 2 4 46 5 5 56 6 4 44 2 4 47 7 5 76 6 6 66 3 4 45 4 4 45 4 4 47 5 7 76 5 4 57 3 4 6

G-4

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5 5 5 56 3 5 65 3 4 55 6 5 36 5 5 54 4 6 66 3 4 57 5 5 66 6 6 77 7 4 46 5 5 66 5 5 45 4 3 47 2 4 56 7 4 66 3 4 56 5 5 56 3 3 46 4 5 54 5 4 56 6 4 65 5 5 67 6 6 76 6 5 65 4 5 56 4 5 55 3 5 55 3 5 56 3 5 56 6 5 56 5 5 43 4 5 6

5,52 4,45 4,56 4,95Note : Formulation 4 : 25.61 g Chia Flour and 51.78 g HVF

Formulation 5 : 25.61 g Chia Flour and 36.22 g HVFFormulation 6 : 15.00 g Chia Flour and 44.00 g HVFFormulation 7 : 15.00 g Chia Flour and 44.00 g HVFScore 1 : Least Desirable 7 : Most Desirable

G-5

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Week 2Texture

Formulation 8 Formulation 9 Formulation 105 4 36 4 46 4 55 2 34 5 54 3 47 3 36 2 33 3 27 4 56 3 57 7 77 5 67 7 77 7 77 7 77 7 73 3 36 5 56 5 66 5 66 5 42 2 26 5 37 5 66 3 63 3 55 5 66 6 67 3 33 2 34 3 53 6 53 2 56 6 65 5 75 1 74 2 34 4 46 3 67 4 36 3 6

G-6

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5 4 47 6 66 7 77 6 56 2 63 2 36 3 57 5 35 6 56 4 53 3 65 3 57 3 55 5 66 3 65 2 25 3 45 3 54 2 46 2 35 3 46 5 55 2 46 1 26 3 56 5 56 3 66 4 55 4 46 6 55 2 26 6 66 5 3

5,45 3,95 4,73Note : Formulation 8 : 15.00 g Chia Flour and 55.00 g HVF

Formulation 9 : 30.00 g Chia Flour and 44.00 g HVFFormulation 10 : 15.00 g Chia Flour and 44.00 g HVFScore 1 : Least Desirable 7 : Most Desirable

Texture

G-7

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Formulation 11 Formulation 12 Formulation 13 Formulation 142 5 5 55 5 5 45 5 5 45 4 5 55 4 6 45 4 4 45 4 5 53 4 5 45 4 5 53 5 5 32 7 5 73 4 4 32 6 2 24 7 6 53 6 5 52 6 4 23 6 4 66 7 7 63 6 7 63 6 7 65 5 6 55 6 6 54 6 5 63 6 5 64 3 3 34 3 3 32 6 3 52 6 3 53 6 5 73 6 5 74 7 6 44 7 7 46 6 6 66 6 6 64 4 6 64 4 6 65 6 6 56 6 6 63 6 7 63 5 5 55 7 6 66 6 6 73 6 6 7

G-8

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4 6 6 55 2 6 52 3 3 36 6 6 63 7 6 66 6 6 62 5 6 62 5 6 65 7 6 63 5 6 52 5 6 33 5 7 62 6 5 63 5 5 64 6 5 57 6 7 73 5 3 65 5 5 52 5 6 65 6 7 73 7 6 36 3 7 74 7 5 66 6 5 75 3 4 34 4 5 45 5 6 66 6 7 62 6 6 55 5 5 53 6 6 67 6 6 6

3,97 5,39 5,40 5,23Note : Formulation 11 : 15.00 g Chia Flour and 33.00 g HVF

Formulation 12 : 15.00 g Chia Flour and 44.00 g HVFFormulation 13 : 0.00 g Chia Flour and 44.00 g HVFFormulation 14 : 15.00 g Chia Flour and 44.00 g HVFScore 1 : Least Desirable 7 : Most Desirable

G-9

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Appendix H. Analysis of Texture Response

Source Sum of Squares df Mean Square F value p-value

Block 0,102857143 1 0,102857 Model 3,102074053 2 1,551037 14,42464 0.0011 A-Chia Flour 0,987440836 1 0,987441 9,1832 0.0127

B-HVF 2,114633217 1 2,114633 19,66609 0.0013Residual 1,075268804 10 0,107527

Lack of Fit 0,678135471 6 0,113023 1,138384 0.4712

Pure Error 0,397133333 4 0,099283

Cor Total 4,2802 13

Std. Dev. 0,327912916 R-Squared 0,742595Mean 4,96 Adj R-Squared 0,691114C.V. % 6,611147498 Pred R-Squared 0,516089PRESS 2,021463363 Adeq Precision 10,06393

Factor Coefficient Estimate df Standard

Error95% CI

Low95% CI High VIF

Intercept 4,96 10,08763

84,76472

95,15527

1

Week 10,08571428

6 1 Week 2 -0,08571429 A-Chia Flour -0,35132621 1

0,115935 -0,60964 -0,09301 1

B-HVF0,51412950

9 10,11593

50,25581

10,77244

8 1

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Appendix I. Result of Hardness and Fracturability Analysis

Formulation Hardness (g)Fracturability

1

2287,9 12,3692668,6 12,5922538,7 12,645

3316 12,135Average 2702,8 12,535

Formulation Hardness (g)Fracturability

2

2631,54 13,2952480,432 11,8483112,081 12,3473121,728 12,411

Average 2836,445 12,475

Formulation Hardness (g)Fracturability

3

2048,33 14,3372591,644 14,1473079,076 13,0263209,374 13,039

Average 2732,106 13,637

Formulation Hardness (g)Fracturability

4

2435,85 13,0872567,389 12,5872900,406 11,6992854,929 11,966

Average 2689,643 12,335

Formulation Hardness (g)Fracturability

5

3499,67 12,2453054,614 12,4334298,827 12,7463374,608 12,124

Average 3556,93 12,387

Formulation Hardness (g)Fracturability

6

2592,608 13,283112,357 13,153013,547 11,699

3299,64 12,291Average 3004,538 12,605

Formulation Hardness (g)Fracturability

7 3291,784 13,535

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2905,987 12,8153542,184 12,0343923,709 11,686

Average 3415,916 12,518

Formulation Hardness (g)Fracturability

8

2034,342 11,862314,578 13,122312,855 12,9592782,992 13,379

Average 2361,192 12,830

Formulation Hardness (g)Fracturability

9

3469,903 12,1063866,036 12,63163,553 11,8734799,488 11,534

Average 3824,745 12,028

Formulation Hardness (g)Fracturability

10

2958,217 12,0252793,19 12,473

2934,514 11,9123638,031 12,113

Average 3080,988 12,131

Formulation Hardness (g)Fracturability

11

3742,008 12,5673291,44 12,613

4359,394 11,9994330,247 11,419

Average 3930,772 12,150

Formulation Hardness (g)Fracturability

12

4351,814 12,7182620,928 12,9

2919,63 12,0262560,568 11,999

Average 3113,235 12,411

Formulation Hardness (g)Fracturability

13

2458,451 13,5314507,332 13,593

2597,57 13,1842715,81 13,147

Average 3069,791 13,364

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Formulation Hardness (g)Fracturability

14

2919,561 12,6274365,526 11,8872609,697 11,885

2925,9 12,125Average 3205,171 12,131

I-3

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Appendix J. Analysis of Hardness Response

Source Sum of Squares df Mean Square F value p-value

Block 44961,52464 1 44961,52 Model 2044184,212 2 1022092 19,80996 0.0003 A-Chia Flour 131380,1965 1 131380,2 2,546381 0.1416 B-HVF 1912804,016 1 1912804 37,07353 0.0001Residual 515948,7 10 51594,87 Lack of Fit 329886,2767 6 54981,05 1,181991 0.4558Pure Error 186062,4233 4 46515,61 Cor Total 2605094,437 13

Std. Dev. 227,1450418 R-Squared 0,798468Mean 3169,885857 Adj R-Squared 0,758162C.V. % 7,165716748 Pred R-Squared 0,56655PRESS 1109689,381 Adeq Precision 11,71191

Factor Coefficient Estimate df Standard

Error95% CI

Low95% CI High VIF

Intercept 3169,885857 1 60,70707 3034,622 3305,15 Week 1 -56,67042857 1 Week 2 56,67042857 A-Chia Flour 128,1503982 1 80,3079 -50,7868 307,0875 1B-HVF -488,9790404 1 80,3079 -667,916 -310,042 1

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Appendix K. Analysis of Fracturability Response

Source Sum of Squares df Mean Square F value p-value

Block 0,14955779 1 0,149558

Model 2,54347496 5 0,508695 31,44128 0.0001 A-Chia Flour 1,39394013 1 1,39394 86,15626 < 0.0001 B-HVF 0,50584962 1 0,50585 31,26541 0.0008 AB 0,332929 1 0,332929 20,57758 0.0027 A^2 0,27045704 1 0,270457 16,71633 0.0046 B^2 0,05767488 1 0,057675 3,564753 0.1010Residual 0,11325447 7 0,016179 Lack of Fit 0,05221513 3 0,017405 1,140579 0.4339Pure Error 0,06103933 4 0,01526 Cor Total 2,80628721 13

Std. Dev. 0,12719752 R-Squared 0,957371Mean 12,5383571 Adj R-Squared 0,926921C.V. % 1,0144672 Pred R-Squared 0,800375PRESS 0,53034912 Adeq Precision 18,36092

Factor Coefficient Estimate df Standard

Error95% CI

Low95% CI High VIF

Intercept 12,3785 1 0,051928 12,25571 12,50129 Week 1 0,10335714 1 Week 2 -0,10335714 A-Chia Flour -0,41742366 1 0,044971 -0,52376 -0,31108 1B-HVF 0,25145815 1 0,044971 0,145118 0,357798 1AB -0,2885 1 0,063599 -0,43889 -0,13811 1A^2 0,191375 1 0,046807 0,080693 0,302057 1,005952B^2 0,088375 1 0,046807 -0,02231 0,199057 1,005952

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Appendix L. Data of Spread Ratio

Formulation Result Average1 34,47 33,28 33,8752 33,26 34,39 33,8253 45,07 42,29 43,684 30,37 29,1 29,7355 27,22 27,96 27,596 35,5 33,49 34,4957 33,73 33,37 33,558 33,02 35,5 34,269 29,77 27,61 28,69

10 31,56 30,78 31,1711 29,4 31,5 30,4512 33,33 32,24 32,78513 44,41 44,18 44,29514 33,81 31,14 32,475

Calculation:

Spread ratio = Weight

ThicknessxCorrection Factor x 10

= 13.1 cm x 1 x 10 3.8 cm = 34.47

L-1

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Appendix M. Analysis of Spread Ratio Response

Source Sum of Squares df Mean Square F value p-value

Block 0,55004464 1 0,550045 Model 300,159447 5 60,03189 31,87087 0.0001 A-Chia Flour 225,556084 1 225,5561 119,7475 < 0.0001 B-HVF 38,3607135 1 38,36071 20,36567 0.0028 AB 15,327225 1 15,32723 8,137209 0.0246 A^2 17,983202 1 17,9832 9,547264 0.0176 B^2 1,90742316 1 1,907423 1,012649 0.3478Residual 13,1851816 7 1,883597 Lack of Fit 11,1967982 3 3,732266 7,508142 0.0404Pure Error 1,98838333 4 0,497096 Cor Total 313,894673 13

Std. Dev. 1,37244212 R-Squared 0,957921Mean 33,6446429 Adj R-Squared 0,927865C.V. % 4,07922927 Pred R-Squared 0,687408PRESS 97,9490679 Adeq Precision 15,75955

Factor Coefficient Estimate df Standard

Error95% CI

Low95% CI High VIF

Intercept 33,0433333 1 0,560297 31,71844 34,36823 Week 1 0,19821429 1 Week 2 -0,19821429 A-Chia Flour -5,30985033 1 0,485232 -6,45724 -4,16246 1B-HVF 2,18976921 1 0,485232 1,042379 3,33716 1AB -1,9575 1 0,686221 -3,58015 -0,33485 1A^2 1,56052083 1 0,505045 0,366279 2,754763 1,005952B^2 -0,50822917 1 0,505045 -1,70247 0,686013 1,005952

M-1

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Appendix N. Data of Moisture Content

Sample Weight Crucible (g)

Final Weight

(g) % Moisture Content Average

1

5,1541 40,5186 4,9624 3,72

3,974,9908 25,0334 4,7837 4,15

5,0603 41,3585 4,8655 3,85

5,1251 41,7284 4,9129 4,14

2

4,9860 39,7667 4,8299 3,13

3,745,0011 39,0762 4,8261 3,50

5,1132 41,7285 4,9036 4,10

4,9813 25,0343 4,7711 4,22

3

5,0235 19,7636 4,9080 2,30

2,885,0852 25,0343 4,9540 2,58

5,1104 19,2613 4,9438 3,26

5,0012 19,7390 4,8332 3,36

4

5,1263 41,1094 4,9187 4,05

4,305,0046 40,5186 4,7864 4,36

5,0021 19,2613 4,7890 4,26

4,8991 39,0724 4,6782 4,51

5

5,0535 20,0691 4,7584 5,84

6,015,0782 20,6811 4,7847 5,78

5,1332 39,0436 4,8175 6,15

5,0132 19,7636 4,6984 6,28

6 5,0417 39,0724 4,8506 3,79 3,75

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4,9514 19,2252 4,7583 3,90

4,9931 25,0343 4,8153 3,56

5,1104 41,1094 4,9198 3,73

7

5,0812 25,0343 4,9049 3,47

4,185,0292 41,7284 4,8416 3,73

5,0034 19,2239 4,7697 4,67

4,9879 19,7641 4,7465 4,84

8

4,9881 39,7655 4,8335 3,10

2,955,0877 41,3585 4,9142 3,41

5,0112 19,7390 4,8398 3,42

4,8991 20,0691 4,8080 1,86

9

5,0452 41,7284 4,8500 3,87

3,855,0008 39,0724 4,7923 4,17

4,9621 20,6811 4,7537 4,20

5,1012 19,2252 4,9405 3,15

10

5,0439 39,0436 4,8502 3,84

4,045,1116 40,5186 4,9010 4,12

5,0334 19,2613 4,8215 4,21

5,0122 25,0343 4,8127 3,98

11

4,9920 41,1094 4,7828 4,19

4,184,9873 19,7636 4,7649 4,46

5,0092 39,7655 4,7848 4,48

4,9903 41,3585 4,8116 3,58

12 5,1224 25,0343 4,9959 2,47 2,65

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5,0198 19,2613 4,8848 2,69

5,0032 41,7284 4,8651 2,76

5,0192 39,0724 4,8842 2,69

13

4,9684 19,2252 4,8273 2,84

2,914,9904 20,6811 4,8412 2,99

5,0120 40,5186 4,8551 3,13

4,9982 39,0436 4,8652 2,66

14

5,1149 20,0691 4,9287 3,64

3,845,0091 19,7390 4,8147 3,88

5,2093 19,7620 5,0014 3,99

5,0056 41,1095 4,8124 3,86

Calculation:

Moisture content % ¿ W 1−W 2W 1

X 100 %

= 5.0011 - 4.7962 x 100%5.0011

= 4.10 %

N-3

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Appendix O. Analysis of Moisture Content Response

Source Sum of Squares Df Mean Square F value p-value

Block 1,38915 1 1,38915 Model 5,44310992 2 2,721555 11,48015 0.0026 A-Chia Flour 2,86724705 1 2,867247 12,09471 0.0059 B-HVF 2,57586288 1 2,575863 10,86559 0.0081Residual 2,3706615 10 0,237066 Lack of Fit 1,1150615 6 0,185844 0,592047 0.7306Pure Error 1,2556 4 0,3139 Cor Total 9,20292143 13

Std. Dev. 0,48689439 R-Squared 0,696605Mean 3,80357143 Adj R-Squared 0,635926C.V. % 12,8009794 Pred R-Squared 0,421504PRESS 4,52023404 Adeq Precision 10,15444

Factor Coefficient Estimate df Standard

Error95% CI

Low95% CI High VIF

Intercept 3,80357143 10,13012

83,51362

84,09351

5 Week 1 0,315 1 Week 2 -0,315 A-Chia Flour 0,59867009 1

0,172143

0,215111

0,982229 1

B-HVF-

0,56743534 10,17214

3 -0,95099 -0,18388 1

O-1

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Appendix P. Questionnaire for Verification Test

UJI HEDONIK

Produk : CookiesNama : Tanggal :

Cicipi sampel dari kiri ke kanan, lalu nyatakan tingkat kesukaan masing-masing sampel berdasarkan parameter yang diuji dengan skala 1-7. Jangan membandingkan antar sampel. Bilas mulut dengan air sebelum mencicipi sampel berikutnya.

KodeTekstur

Keterangan:1 : Sangat tidak suka2 : Tidak suka3 : Agak tidak suka4 : Netral5 : Agak suka6 : Suka7 : Sangat suka

P-1

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Appendix Q. Result of Hedonic Test in Verification Test

TextureOptimum

Formulation3566647665652354776676557554563665556766

Q-1

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74573356645377436766436664455565556

5,25Note : Optimum Formulation : 20.45 g Chia Flour and 55.00 g HVF

Score 1 : Least Desirable 7 : Most Desirable

Q-2

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Appendix R. Result of Physicochemical Analysis in Verification Test

Hardness and Fracturability

Hardness (g)Fracturability

2558,721 -12,5812766,731 -13,1072271,113 -12,4152702,787 -13,2272574,838 -12,8325

Spread RatioSpread Ratio Average

29,37 30,1630,95

Spread ratio = Weight

ThicknessxCorrection Factor x 10

= 12.54 cm x 1 x 10 4.27cm = 29.37

Moisture Content

Sample Weight Crucible (g)Final Weight (g) % Moisture Content Average

Optimum

4,9902 41,1094 4,7871 4,07

3,85,0402 41,3585 4,8250 4,275,1103 41,7284 4,9289 3,554,9969 25,0343 4,8325 3,29

% Moisture content ¿ W 1−W 2W 1

X 100 %

= 5.0014 - 4.7979x 100%5.0014

= 4.07 %

R-1

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Appendix S. Questionnaire for Product Comparison

UJI HEDONIK

Produk : CookiesNama : Tanggal :

Cicipi sampel dari kiri ke kanan, lalu nyatakan tingkat kesukaan masing-masing sampel berdasarkan parameter yang diuji dengan skala 1-7. Jangan membandingkan antar sampel. Bilas mulut dengan air sebelum mencicipi sampel berikutnya.

KodeWarnaAromaTekstur Rasa

Keterangan:1 : Sangat tidak suka2 : Tidak suka3 : Agak tidak suka4 : Netral5 : Agak suka6 : Suka7 : Sangat suka

S-1

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Appendix T. Result of Hedonic Test in Product Comparison

Warna Aroma Tekstur RasaOptimu

m ControlOptimu

m ControlOptimu

m ControlOptimu

m Control5 6 4 5 3 6 6 65 6 5 6 5 5 5 63 6 5 6 6 5 6 64 6 4 6 6 6 5 66 6 7 5 6 7 6 76 5 6 5 4 5 6 66 6 6 5 7 6 7 54 6 6 7 6 7 5 73 7 6 6 6 7 5 74 5 6 7 5 7 7 66 5 6 7 6 7 5 66 6 5 6 5 6 5 67 6 6 5 2 5 3 66 6 6 4 3 5 7 57 6 4 7 5 6 4 67 6 7 7 4 6 7 67 6 4 6 7 7 5 76 6 4 6 7 7 5 77 5 5 3 6 3 5 66 4 4 7 6 7 6 57 6 4 5 7 6 4 66 6 5 5 6 6 5 66 7 6 6 5 7 6 65 6 5 6 5 5 6 67 5 6 5 7 5 7 64 6 6 5 5 6 7 64 6 7 6 5 7 6 76 6 6 6 4 7 7 75 6 7 6 5 7 6 76 7 6 6 6 6 6 66 5 6 4 3 4 4 65 5 6 6 6 6 6 66 7 6 7 6 7 6 76 7 6 6 5 6 6 56 5 6 6 5 6 5 56 7 6 6 5 6 5 77 6 6 6 6 6 6 66 6 5 6 7 6 6 66 6 5 5 6 6 5 74 6 4 6 6 6 5 6

T-1

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5 5 5 4 7 5 6 47 6 5 6 4 7 6 76 5 7 4 5 5 6 67 6 7 6 7 7 7 73 6 4 5 3 6 4 64 5 6 5 3 5 5 64 6 6 6 5 5 6 56 7 6 6 6 7 6 66 6 6 5 6 6 5 63 4 5 7 4 7 6 56 6 6 6 5 7 5 73 6 6 7 3 6 5 64 5 6 4 7 5 5 44 5 5 6 7 6 6 55 7 4 6 4 6 6 52 6 5 6 3 6 5 65 6 5 6 6 6 6 66 6 6 6 7 7 7 65 6 6 5 6 6 6 76 7 5 6 6 6 6 76 5 6 7 4 7 6 75 7 6 6 3 7 7 75 5 6 6 6 6 5 65 5 6 4 6 4 5 65 7 6 6 6 6 5 67 6 6 6 4 7 6 74 6 4 7 4 7 5 75 6 7 7 5 6 6 63 6 6 4 5 5 5 56 6 6 5 5 5 6 56 6 7 6 6 6 6 65 5 4 7 5 7 5 66 5 5 7 5 7 5 64 7 6 6 5 7 6 75 6 5 7 6 7 5 7

5,32 5,87 5,56 5,77 5,25 6,08 5,61 6,09Note : Optimum Formulation : 20.45 g Chia Flour and 55.00 g HVF

Control Formulation : 0.00 g Chia Flour and 55.00 g HVFScore 1 : Least Desirable 7 : Most Desirable

T-2

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Appendix U. T-Test Analysis for Hedonic Test in Product Comparison

Aroma

Paired Samples Statistics

Mean N Std. Deviation Std. Error Mean

Pair 1aroma_control 5,7733 75 ,92376 ,10667

aroma_optimum 5,5600 75 ,88897 ,10265

Paired Samples Correlations

N Correlation Sig.

Pair 1aroma_control &

aroma_optimum

75 -,107 ,363

Paired Samples Test

Paired Differences t df Sig. (2-tailed)

Mean Std. Deviation Std. Error Mean 95% Confidence Interval of the Difference

Lower Upper

Pair 1 aroma_control - aroma_optimum ,21333 1,34861 ,15572 -,09695 ,52362 1,370 74 ,175

U-1

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ColorPaired Samples Statistics

Mean N Std. Deviation Std. Error Mean

Pair 1color_control 5,8667 75 ,70391 ,08128

color_optimum 5,3200 75 1,22099 ,14099

Paired Samples Correlations

N Correlation Sig.

Pair 1 color_control & color_optimum 75 ,035 ,768

Paired Samples Test

Paired Differences t df Sig. (2-tailed)

Mean Std. Deviation Std. Error Mean 95% Confidence Interval of the Difference

Lower Upper

Pair 1 color_control - color_optimum ,54667 1,38811 ,16029 ,22729 ,86604 3,411 74 ,001

U-2

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Taste

Paired Samples Statistics

Mean N Std. Deviation Std. Error Mean

Pair 1taste_control 6,0933 75 ,73839 ,08526

taste_optimum 5,6133 75 ,83655 ,09660

Paired Samples Correlations

N Correlation Sig.

Pair 1 taste_control & taste_optimum 75 -,028 ,810

Paired Samples Test

Paired Differences t df Sig. (2-tailed)

Mean Std. Deviation Std. Error Mean 95% Confidence Interval of the Difference

Lower Upper

Pair 1 taste_control - taste_optimum ,48000 1,13137 ,13064 ,21970 ,74030 3,674 74 ,000

U-3

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Texture

Paired Samples Statistics

Mean N Std. Deviation Std. Error Mean

Pair 1texture_control 6,0800 75 ,88164 ,10180

texture_final 5,2533 75 1,24220 ,14344

Paired Samples Correlations

N Correlation Sig.

Pair 1 texture_control & texture_final 75 ,080 ,495

Paired Samples Test

Paired Differences t df Sig. (2-tailed)

Mean Std. Deviation Std. Error Mean 95% Confidence Interval of the

Difference

Lower Upper

Pair 1 texture_control - texture_final ,82667 1,46466 ,16912 ,48968 1,16365 4,888 74 ,000

U-4

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Appendix V. Physicochemical Analysis Result in Product Comparison

Hardness and FracturabilityHardness (g) Fracturability

Control Optimum Control Optimum

1933,006 2558,721 14,725 12,581

2337,385 2766,731 14,051 13,107

2033,047 2271,113 14,605 12,415

1765,08 2702,787 14,821 13,2272017,13 2574,84 14,55 12,83

Spread RatioFormulation Spread Ratio Average

Optimum29,37

30,1630,95

Control36,58

37,3838,18

Spread Ratio = Weight

ThicknessxCorrection Factor x 10

= 12.54 cm x 1 x 10 4.27 cm = 29.37

Moisture Content

Sample Weight Crucible (g)Final Weight (g) % Moisture Content Average

Optimum

4,9902 41,1094 4,9902 4,07

3,805,0402 41,3585 5,0402 4,275,1103 41,7284 5,1103 3,554,9969 25,0343 4,9969 3,29

Control

5,0335 39,0724 4,9258 2,14

2,315,1204 20,0691 5,0144 2,075,0008 20,6811 4,8748 2,525,0192 39,0436 4,8927 2,52

% Moisture content ¿ W 1−W 2W 1

X 100 %

= 5.0014 - 4.7979x 100%5.0014

= 4.07 %

V-1

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Appendix W. Analysis for Physicochemical Test in Product Comparison

Hardness

Group Statistics

Type N Mean Std. Deviation Std. Error Mean

HardnessControl 4 2017,1295 240,43202 120,21601

Optimal 4 2574,8380 220,38036 110,19018

Independent Samples Test

Levene's Test for Equality of Variances

t-test for Equality of Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Hardness

Equal variances assumed

,008 ,933 -3,420

6 ,014 -557,70850 163,07595 -956,74096 -158,67604

Equal variances not assumed

-3,420

5,955 ,014 -557,70850 163,07595 -957,47192 -157,94508

W-

1

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Fracturability

Group Statistics

Type N Mean Std. Deviation Std. Error Mean

FracturabilityControl 4 14,5505 ,34452 ,17226

Optimal 4 -12,8325 ,39520 ,19760

Independent Samples Test

Levene's Test for Equality of Variances

t-test for Equality of Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Fracturability

Equal variances assumed

,676 ,443 104,458 6 ,000 27,38300 ,26214 26,74156 28,02444

Equal variances not assumed

104,458 5,890 ,000 27,38300 ,26214 26,73866 28,02734

W-

2

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Spread Ratio

Group Statistics

Type N Mean Std. Deviation Std. Error Mean

Spread_ratioControl 2 37,3800 1,13137 ,80000

Optimal 2 30,1600 1,11723 ,79000

Independent Samples Test

Levene's Test for Equality of Variances

t-test for Equality of Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Spread_ratio

Equal variances assumed

32940614417348,785 ,000 6,422 2 ,023 7,22000 1,12432 2,38243 12,05757

Equal variances not assumed

6,422 2,000 ,023 7,22000 1,12432 2,38170 12,05830

W-

3

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Moisture Content

Group Statistics

Type N Mean Std. Deviation Std. Error Mean

Moisture_contentControl 4 2,3125 ,24130 ,12065

Optimal 4 3,7950 ,45325 ,22662

Independent Samples Test

Levene's Test for Equality of Variances

t-test for Equality of Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Moisture_content

Equal variances assumed

5,985 ,050 -5,774

6 ,001 -1,48250 ,25674 -2,11072 -,85428

Equal variances not assumed

-5,774

4,574 ,003 -1,48250 ,25674 -2,16138 -,80362

W-

4

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Appendix X. Result of Proximate Analysis

Fat Content

SampleWeight

(g) Flask (g) Boiling Chip (g)

Final Weight

(g) % Fat AverageOptimum 1 5,0442 105,9132 3,1861 1,4048 27,85

27,82Optimum 2 5,0958 106,6245 1,5151 1,4159 27,78

Control 1 5,0162 109,4990 1,1623 1,3799 27,5128,10

Control 2 5,0168 101,3740 1,5494 1,4393 28,69

Calculation:

% Fat = weight of fat extracted(g)

weight of sample (g) × 100%

= 1.4048 x 100% 5.0442 = 27.85%

Protein Content

SamplemL HCl Weight % Nitrogen % Protein Average

Optimum 1 10,24 2,0522 1,40 8,74 8,75Optimum 2 10,36 2,0740 1,40 8,75

Control 1 8,66 2,1251 1,14 7,14 7,21Control 2 8,42 2,0263 1,17 7,28

Calculation:% Protein = ¿¿ x 100%

= 10.24 mL x 0.2 N x 14.007 x 6.25 x 100%2052.2 mg

= 8.74 %

Ash Content

SampleWeight (g) Crucible (g) Final Weight (g) % Ash Average

Optimum 1 5,0061 20,9339 0,0790 1,23 1,19Optimum 2 5,0573 29,2951 0,0877 1,14

Control 1 5,0135 18,7396 0,0456 0,91 0,90Control 2 5,0585 21,4284 0,0450 0,89

Calculation:

% Ash content = x− y

z × 100%

= (20.9880 - 20.9339) x 100% 5.0061

= 1.13%

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Moisture Content

SampleWeight Crucible (g) Final Weight (g) % Moisture Content Average

Optimum 1 5,0442 39,0469 4,8339 4,17 3,80Optimum 2 5,0958 41,1139 4,9215 3,42

Control 1 5,0162 39,7879 4,9104 2,11 2,32Control 2 5,0168 41,3621 4,8904 2,52

Calculation:

% Moisture content ¿ W 1−W 2W 1

X 100 %

= 5.0367- 4.8267 x 100%5.0367

= 4.17 %

Carbohydrate Content

Formulation Carbohydrate Content (%)

Average (%)

Optimum58,01

58,4658,91

Control62,33

61,4860,62

Calculation:% Carbohydrate = 100% - %Moisture - %Ash - %Protein - %Fat

= 100% - 3.80% - 1.19% - 8.75% - 27.82% = 58.46%

X-2

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Fiber and Omega-3 Fatty Acid Content of Control Cookie

X-3

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Fiber and Omega-3 Fatty Acid Content of Chia Cookie

X-4