Optimization of antioxidant extraction from jackfruit (Artocarpus heterophyllus Lam.) seeds using response surface methodology
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Faculty of Bioscience Engineering
Academic year 2011 – 2012
Optimization of antioxidant extraction
from jackfruit (Artocarpus heterophyllus Lam.) seeds
using response surface methodology
Wahidu Zzaman
Promoter: Prof. dr. ir. Koen Dewettinck
Tutor: Mohammad Mozidul Islam
Master’s dissertation submitted in partial fulfillment of the requirements for the
degree of Master of Science in Nutrition and Rural Development,
main subject Human NutritionCopyright
“All rights reserved. The author, the promoter and the tutor permit the use of this Master’s
dissertation for consulting purposes and copying of parts for personal use. However, any other
use fall under the limitations of copyright regulations, particularly the stringent obligation to
explicitly mention the source when citing parts out of this Master’s dissertation”.
Ghent University, August, 2012
Promoter:…………………….. Tutor:..............................
Prof. dr. ir. Koen Dewettinck Mohammad Mozidul Islam
Author
Wahidu Zzaman
iACKNOWLEDGEMENTS
In the name of Allah, the most gracious, the most merciful, all praise is God Lord of all creation.
I would sincerely like to thank all those who helped and inspired me to complete this
dissertation.
I express my sincere gratitude, heartfelt respect, profound regards and indebtedness to my
respected promoter Prof. dr. ir. Koen Dewettinck, Head of the laboratory of Food Technology
and Engineering, Department of Food Safety and Food Quality, Faculty of Bioscience
Engineering, Ghent University, for his scholastic guidance, constructive valuable suggestions
and continuous encouragement during the dissertation period. I am deeply indebted to my tutor
Mr. Mohammad Mozidul Islam, Doctoral Student, Department of Food Safety and Food Quality,
Faculty of Bioscience Engineering, Ghent University for showing whole hearted interest during
this research. His supportive suggestions and intellectual perception helped me to carrying this
research work.
I am also grateful to Mrs. ir. Anne-Marie Remaut-Dewinter, Mrs. ir. Kathleen Anthierens, Mrs.
Marian Mareen and Mrs. Ruth Van den Driessche for their friendly assistance and generous help
on every occasion. To all members and staff of the Laboratory of Food Technology and
Engineering, I am grateful for their cooperation and warm friendship. Especially Benny Lewille,
Corine Loijson, and Beatrijs Vermeule for their valuable technical assistance.
I am very much grateful to VLIR-UOS (Flemish Interuniversity Council–University
Development Cooperation) for the financial and logistic support to pursue this master program,
without which this study work would have not been possible and wish to extend my sincere
thanks to the VLIR staff for their cordial concern about the international student.
I would like to express my special thanks to my beloved parents, family members and relatives,
who always blessed, inspired and sacrificed during my study. I am so indebted to Jesanuzzaman
Shuvo my beloved son and Mrs. Julekha Wahid who always shares with me love, happiness and
sorrow.
Wahidu Zzaman
Ghent, August, 2012
iiTABLE OF CONTENTS
ACKNOWLEDGEMENTS .......................................................................................................... II
TABLE OF CONTENTS ............................................................................................................ III
LIST OF TABLES ................................................................................................................... VII
LIST OF ABBREVIATIONS .......................................................................................................IX
LIST OF APPENDICES .............................................................................................................XI
ABSTRACT ........................................................................................................................... XII
CHAPTER I: INTRODUCTION ................................................................................................... 1
CHAPTER II: LITERATURE REVIEW ........................................................................................... 4
2.1. LIPID OXIDATION IN FOODS ......................................................................................................... 4
2.1.1. Mechanisms of Lipid Oxidation ..................................................................................... 5
2.1.2. Photo-oxidation............................................................................................................. 7
2.1.3. Enzyme-mediated Oxidation ......................................................................................... 7
2.2. ANTIOXIDANTS .......................................................................................................................... 8
2.2.1. Synthetic antioxidants................................................................................................... 8
2.2.2. Natural Antioxidants ..................................................................................................... 9
2.3. EXTRACTION OF POLYPHENOLS FROM PLANT MATERIALS .................................................................. 12
2.4. MEASURING ANTIOXIDANT ACTIVITY IN FOOD ................................................................................ 12
2.5. RESPONSE SURFACE METHODOLOGY (RSM) ................................................................................. 13
2.5.1. Screening ..................................................................................................................... 14
2.5.2. Factorial design ........................................................................................................... 14
2.5.3. Fractional factorial design .......................................................................................... 15
2.5.4. Addition of central point to factorial design ............................................................... 15
2.5.5. Blocking and randomization ....................................................................................... 15
2.5.6. Analysis for screening experiment .............................................................................. 16
2.5.7. Optimization ............................................................................................................... 16
CHAPTER III: MATERIALS AND METHODS ............................................................................. 19
3.1. CHEMICALS ............................................................................................................................ 19
3.2. PREPARATION OF MATERIALS ..................................................................................................... 19
3.3. EXTRACTION PROCEDURE .......................................................................................................... 19
3.4. DPPH RADICAL SCAVENGING ACTIVITY......................................................................................... 20
3.5. THE TOTAL PHENOLIC COMPOUNDS (FCR) .................................................................................... 21
iii3.6. FERRIC REDUCING ANTIOXIDANT POWER (FRAP) ........................................................................... 22
3.7. EXPERIMENTAL DESIGN ............................................................................................................. 23
3.7.1. Variable identification and screening ......................................................................... 24
3.7.2. Fitting a first-order model ........................................................................................... 25
3.7.3. Fitting second-order model ......................................................................................... 26
3.8. CORRELATION BETWEEN PHENOLIC CONTENT AND ANTIOXIDANT ACTIVITIES ........................................ 29
3.9. STATISTICAL ANALYSIS............................................................................................................... 29
CHAPTER IV: RESULTS AND DISCUSSION .............................................................................. 30
4.1. SAMPLE ................................................................................................................................. 30
4.2. STANDARD CURVES .................................................................................................................. 30
4.3. FACTORS SCREENING AND IDENTIFICATION .................................................................................... 30
4.4. FITTING MODELS ..................................................................................................................... 31
4.4.1. Response surface analysis of radical scavenging property (DPPH) ............................ 31
4.4.2. Response surface analysis of total phenol content (FCR) ........................................... 34
4.4.3. Response surface analysis of antioxidant activity (FRAP)........................................... 36
4.5. OPTIMIZATION AND VERIFICATION OF THE MODELS......................................................................... 38
4.6. ROLE OF POLYPHENOLS AS ANTIOXIDANT ...................................................................................... 40
CHAPTER V: CONCLUSION AND FURTHER RECOMMENDATION ............................................ 42
5.1. CONCLUSION .......................................................................................................................... 42
5.2. FURTHER RECOMMENDATION .................................................................................................... 43
REFERENCES ........................................................................................................................ 44
ivLIST OF FIGURES
Figure 1. Mechanism of auto-oxidation............................................................................... 6
Figure 2. Mechanism of photo-oxidation............................................................................. 7
Figure 3. Antioxidant (AH) reactions with free radicals generated during lipid oxidation. 8
Figure 4. Chemical structures of some common synthetic antioxidants.............................. 9
Figure 5. Chemical structures of common flavonoids found in plants................................ 11
Figure 6. The 22 factorial design.......................................................................................... 14
Figure 7. Blocking in design................................................................................................ 15
Figure 8. Box-Behnken design for three factors-(a) shows the geometric representation
and (b) shows the design...................................................................................... 17
Figure 9. Factor combinations for a central composite design............................................ 18
Figure 10. The standard curve by fitting the percentage of radical scavenging effect
versus its corresponding Trolox concentration..................................................... 20
Figure 11. The standard curve fitted by plotting absorbance versus the corresponding
concentration of Gallic acid solutions.................................................................. 21
Figure 12. The standard curve by fitting the absorbance versus its corresponding standard
ascorbic solutions.................................................................................................. 22
Figure 13. A flow diagram of the overall optimization of the process.................................. 23
Figure 14. Standard residual plots of the three linear fitted models, where responses are
(a) DPPH, (b) FCR and (c) FRAP...................................................................... 26
vFigure 15. Standard residual plots of the three quadratic models, where responses are (a)
DPPH (b) FCR and (c) FRAP.............................................................................. 28
Figure 16. Response surface plot showing the combined effect of (a) ethanol
concentration and temperature at fixed 55.01 ml/g DM liquid-to-solid ratio, (b)
liquid-to-solid ratio and temperature at fixed 72.19 % ethanol concentration,
(c) ethanol concentration and liquid-to-solid ratio at fixed 35 oC temperature
on radical scavenging activity measured by DPPH (mg TE/100 g DM).............. 32
Figure 17. Response surface plot showing the combined effect of (a) ethanol
concentration and temperature at fixed 55.01 ml/g DM liquid-to-solid ratio, (b)
liquid-to-solid ratio and temperature at fixed 72.19 % ethanol concentration,
(c) ethanol concentration and liquid-to-solid ratio at fixed 35 oC temperature
on phenolic content measured by FCR (mg GAE/100 g DM)............................. 35
Figure 18. Response surface plot showing the combined effect of (a) ethanol
concentration and temperature at fixed 55.01 ml/g DM liquid-to-solid ratio, (b)
liquid-to-solid ratio and temperature at fixed 72.19 % ethanol concentration,
(c) ethanol concentration and liquid-to-solid ratio at fixed 35 oC temperature
on phenolic content measured by FRAP (mg AA/100 g DM)............................. 37
Figure 19. Superimposed contour plots of responses DPPH and FRAP as a function of
liquid-to-solid ratio and ethanol concentration at temperature 35 oC................... 40
viLIST OF TABLES
Table 1. Regression coefficients and coefficient of determination of standard curves... 23
Table 2A. A full 24 factorial design experimental design and corresponding responses
for an ethanolic extraction with x1=ethanol concentration (%, v/v),
x2=temperature (oC), x3=liquid-to-solid ratio (ml/g DM), x4=time (minute);
DPPH=radical scavenging property (mg TE/100 g DM); FCR=total phenolic
content (mg GAE/100 g DM); FRAP=ferric reducing antioxidant property
(mg AA/100 g DM)........................................................................................... 24
Table 2B Experimental results of full factorial (24) screening design to identify most
influencing factors............................................................................................. 25
Table 3A. A full 23 factorial design experimental design with three replication at the
center and corresponding responses for an ethanolic extraction with
x1=ethanol concentration (%, v/v), x2=temperature (oC), x3=liquid-to-solid
ratio (ml/g DM); DPPH=radical scavenging property (mg TE/100 g DM);
FCR=total phenolic content (mg GAE/100 g DM); FRAP=ferric reducing
antioxidant property (mg AA/100 g DM).......................................................... 25
Table 3B Coefficient of determination (R2) and lack of fit values to evaluate the linear
fitted models with the experimental data of Table 3A; where DPPH=radical
scavenging property (mg TE/100 g DM); FCR=total phenolic content (mg
GAE/100 g DM); FRAP=ferric reducing antioxidant property (mg AA/100 g
DM)..................................................................................................................... 26
viiTable 4A Box-Behnken design and corresponding responses for an ethanolic extraction
with x1=ethanol concentration (%, v/v), x2=temperature (oC) and x3=liquid-to-
solid ratio (ml/ g DM); DPPH=radical scavenging property (mg TE/100 g
DM); FCR=total phenolic content (mg GAE/100 g DM); FRAP=ferric
reducing antioxidant property (mg AA/100 g DM)............................................ 27
Table 4B Regression coefficients, the coefficient of determination (R2), lack of fit
values for the second order fitted models. Predicted values are DPPH=radical
scavenging property (mg TE/100 g DM); FCR=total phenolic content (mg
GAE/100 g DM); FRAP=ferric reducing antioxidant property (mg AA/100 g
DM)..................................................................................................................... 28
Table 5. Maximum predicted values from the second order fitted models. Responses
are DPPH=radical scavenging property (mg TE/100 g DM); FCR=Total
phenolic content (mg GAE/100 g DM); FRAP=Ferric reducing antioxidant
property (mg AA/100 g DM).............................................................................. 39
Table 6. Experimental data for verification of the models predicted at optimal
condition with x1=ethanol concentration (v/v %), x2=temperature (oC),
x3=liquid-to-solid ratio (ml/g DM); Responses are DPPH=radical scavenging
property (mg TE/100 g DM); FCR=Total phenolic content (mg GAE/100 g
DM); FRAP=Ferric reducing antioxidant property (mg AA/100 g DM)........... 39
viiiLIST OF ABBREVIATIONS
ANOVA Analysis of Variance
AH Antioxidant
AA Ascorbic acid
BHA Butylated hydroxyanisole
BHT Butylated hydroxytoluene
CVD Cardiovascular disease
CCD Central composite design
CCRD Central composite rotatable design
CV Coefficient of variation
DOE Design of experiment
DPPH 2,2-diphenyl-1-picrylhydrazyl
DM Dry matter
ET Electron transfer
FRAP Ferric ion reducing antioxidant power
FCR Folin-Ciocalteu Phenol-Reagent
GA Gallic acid
GAE Gallic acid equivalent
HAT Hydrogen atom transfer
HN Hydroxynonenal
MDA Malondialdehyde
ORAC Oxygen radical absorbance capacity
pAV p-anisidine value
ixPV Peroxide value
PG Propyl gallate
RSM Response surface methodology
TBHQ Tert-butyl hydroquinone
TBARS Thiobarbituric acid reactive substances
TRAP Total radical trapping antioxidant parameters
TE Trolox equivalent
TEAC Trolox equivalence antioxidant capacity
xLIST OF APPENDICES
Appendix Table 1: Crude extracts yield calculation of jackfruit seeds 52
Appendix Table 2: ANOVA on screening test for DPPH without interaction 53
Appendix Table 3: Full factorial (24) screening test for DPPH with 2 factors interaction. 54
Appendix Table 4: Full factorial (24) screening test for FCR without interaction 55
Appendix Table 5: Full factorial (24) screening test for FCR with interaction 56
Appendix Table 6: Full factorial (24) screening test for FRAP withoutu interaction 57
Appendix Table 7: Full factorial (24) screening test for FRAP with interaction 58
Appendix Table 8: ANOVA on second order regreession model for DPPH 59
Appendix Table 9: ANOVA check for the fitness of the model for DPPH 60
Appendix Table 10: ANOVA on second order regreession model for FCR 61
Appendix Table 11: ANOVA check for the fitness of the model for FCR 62
Appendix Table 12: ANOVA on second order regreession model for FRAP 63
Appendix Table13: ANOVA check for the fitness of the model for FRAP 64
xiABSTRACT
Response surface methodology (RSM) in combination with Box-Behnken experimental design
was performed in this study to optimize the extraction parameters for assessing maximum yield
of antioxidant activity from jackfruit seeds. The RSM with a three level, three-factor mixture
design was used to optimize the extraction condition. The aqueous extraction of antioxidant
compounds from freeze-dried powder of jackfruit seeds were optimized by using the three
independent variables, namely ethanol concentration (%, v/v), temperature (oC) and liquid-to-
solid ratio (ml/g DM) were selected after factorial screening. The second order polynomial
models were found to be adequate to fit with the experimental data for radical scavenging
activity (R2=0.985), antioxidant activity (R2=0.968) and total phenolic content (R2=0.981). The
optimal conditions were determined by using desirability function approach, where both radical
scavenging activity measured by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and reducing activity
measured by ferric reducing antioxidant power (FRAP) were considered with equal importance.
Using this approach, the following optimal conditions can be recommended: ethanol 72.16%,
temperature 35oC and liquid-to-solid ratio 55.02ml/g DM. Under these conditions scavenging
activity of 1003.22mg Trolox eq./100g DW, reducing activity of 679.18mg Asc. Acid equ./100g
DM, and phenolic content of 1031.68mg GA/100g DM were obtained which was in close
conformity with predicted values, thus indicating the suitability of the models developed and the
success of RSM in optimizing the extraction setting. These methods could be utilized to prepare
crude extracts containing antioxidant from underutilized jackfruit seeds for industrial use as food
additives to protect the food products in retaining their sensorial quality, e.g. color, texture and
taste, as well as their nutritional quality.
xiiCHAPTER I: INTRODUCTION
Jackfruit is the largest tree born fruit in the world. Historically, the fruit is native to India, and
with time, the fruit has spread all over the world. Now jackfruit can be found in Bangladesh,
Malaysia, Myanmar, Sri-Lanka, Indonesia, USA (Florida, California ), Australia, West Africa,
the Caribbean, Brazil, Puerto Rico, Nauru, Samoa and many other countries (Bose, 1985;
Elevitch and Manner, 2006; Haq, 2006; Samaddar, 1985). Jackfruit is a very popular fruit in
India and Bangladesh (Bose, 1985; Morton, 1987), and in recent years the fruit is gaining
popularity in the USA as well (Campbell and El-Sawa, 1998; Schnell et al., 2001). In India,
jackfruit is the third largest harvested fruit ranked after mango and banana (Morton, 1987).
During the season, the fruit grows in plenty and is quite cheap where grown, but expensive in
the off-season. (Jagtap et al., 2010; Morton, 1987). Each year approximately 30-50% the total
harvested fruit, e.g. jackfruit, is spoiled because of the lack of post-harvest processing in India
and Bangladesh (Ali, 2003). The ripe sweet bulbs of the fruit can be processed into ice cream,
jam, jelly, alcoholic beverages, nectars or fruit powder (Elevitch and Manner, 2006; Morton,
1987). However, the industrial use of jackfruit seed has not been as diversified as pulp; apart
from the use as a substitute of wheat flour (Prakash et al., 2009) it is also processed in can.
Jackfruit seeds are mostly consumed after roasting in some local dishes (Samaddar, 1985).
Additionally, with comparison with others tropical fruits, such as orange, mango, banana,
pineapple, papaya, jack fruit contains higher protein, calcium, iron and thiamine levels and is
considered a good source of essential nutrients (Bhatia et al., 1955; Haq, 2006). Seeds are
reported as comparatively higher in phenolic and antioxidant components than bulb (Lu and
Foo, 1999; Meyer et al., 1998; Soong and Barlow, 2004).
In term of health benefits, epidemiological studies already have indicated that diet enriched
with phenolics probably play the protective role against different degenerative diseases
(Halliwell, 2008). According to Haleem et al. (2008) most of the beneficial properties of
phenolics are attributed due to their antioxidant activity. One of the possibilities is to increase
the consumption of antioxidants as a functional compound in daily diets (Wijngaard and
Brunton, 2010). However, consumers often reject food products that are enriched in with
synthetic antioxidants and prefer natural antioxidants (Wettasinghe and Shahidi, 1999).
1Besides playing the role as a functional component, antioxidants also help the food products in
retaining their sensorial quality, e.g. color, texture and taste, as well as their nutritional quality
through preventing the oxidation of essential fatty acids (Coda et al., 2012). Many researchers
have already illustrated that natural antioxidant compounds isolated from different sources, are
a good alternative for synthetic antioxidants in the retardation of fat oxidation (Saha et al.,
2011; Viuda-Martos et al., 2009).
Recently, a trend has been noticed for the search of newer antioxidants especially from the
plant origin (Singh and Rajini, 2004). According to Prasad et al. (2011) in recent years research
and development activities have especially focused on underutilized fruits. Moreover, in our
modern life waste valorization has become an important issue for food industries (Wijngaard
and Brunton, 2010). In (2004) Soong and Barlow emphasized on the importance of utilization
of jack fruit seeds as a source of natural food additives and ingredients. One of the possibilities,
is to use the seeds as a source of natural antioxidants (Bhushan et al., 2008). However before
extraction, the process should be optimized because factors like extraction time, temperature,
solvent concentration, pressure, solid-to-liquid ratio and pH can significantly influence the
extraction process (Prasad et al., 2011).
In a quest for natural antioxidant, Soong and Barlow (2004) used an identical method of
extraction process for jackfruit, avocado, longan, mango and tamarind for a respective
comparison of antioxidant activity between the edible portion and seeds. However according to
Liu et al. (2000), it would be difficult of establish an universally optimized extraction protocol
due to the complex internal matrix and diversity of the antioxidant compounds of natural
sources. Hence, the optimum extraction protocol is anticipated to be different according to the
type of fruits and between the edible portion and seeds.
In a traditional method of optimization, also known as “one factor at a time” optimization, an
individual factor is changed continuously while keeping all other remaining factors constant,
until the best value of response can be selected. This traditional technique is laborious and
could be erroneous, because it does not take into account the interactions between factors. This
limitation can easily be solved using specific design of experiment (DOE) (Box and Draper,
1987).
So far, no studies have reported the optimization of the antioxidant extraction from jackfruit
seeds. Hence, in this present study, the antioxidant activity of jackfruit seeds will be studied by
2using three different in vitro assay systems namely, radical scavenging activity (DPPH),
antioxidant reducing activity (FRAP), and phenolic content (FCR), in order to identify the
overall optimized antioxidant extraction protocol from jackfruit seeds. Considering the residual
toxicity of solvent, in the study, only ethanol and water are used for the extraction procedure. A
full factorial experimental design (24) will be carried out in the beginning for the variable
screening, followed by 23 full factorial and Box-Behnken designs for the further optimization.
The objectives of this study are:
To explore the effects of solvent concentration, extraction time, extraction temperature
and liquid-to-solid ratio on the extraction of antioxidant properties from jackfruit seeds;
To optimise the extraction conditions for antioxidant properties from jackfruit seeds;
To valorise of an under utilized product (jackfruit seeds).
3CHAPTER II: LITERATURE REVIEW
2.1. Lipid Oxidation in Foods
An antioxidant is a molecule that can prevent the oxidation of other molecules. Oxidation is the
interaction between oxygen molecules and all the different substances. It is chemical reaction
that transfers electrons or hydrogen atom from a substance to an oxidizing agent. Free radicals
are produced by oxidation reaction and the free radicals are extremely reactive and unstable
that prone to react with molecules, and these radicals can also start chain reactions.
Antioxidants can neutralize free radicals and stop these chain reactions by removing free
radical intermediates, and slow down other oxidation reactions. So antioxidants are often
reducing agents they do this by being oxidized themselves, such as polyphenols, ascorbic acid
or thiols.
Lipid oxidation is one of the major economic concerns in food industry as they may cause bad
effect on taste, flavour, colour, nutritional value and shelf life of foods (Juntachote et al.,
2006). Synthetic antioxidants such as butylated hydroxyanisole (BHA) and butylated
hydroxytoluene (BHT) are usually used to slow down the oxidative deterioration but due to
their possible toxic and carcinogenic effects there has been increasing worry over the use of
synthetic antioxidants to the fresh or processed foods (Arabshahi-Delouee and Urooj, 2006).
As a result, the use of natural and safe antioxidants, especially of tropical fruits and vegetables
has increased significantly in these recent years among consumer, institutionalists and food
scientists.
Lipids are one of the major components of many foods, and often need for the development of
flavor, texture and color characteristic. Nevertheless, lipids are highly unstable and are readily
reacted by oxygen, causing to a chain of chemical reactions that produce undesirable flavor and
odor compounds. These oxidative reactions can be speed up by metals (e.g., iron, copper),
light, temperature, and enzymes. Lipids are two main types as saturated or unsaturated fatty
acids. The term „saturated‟ referring to the fact that all carbon atoms are bound to as many
hydrogens as possible whereas unsaturated fatty acids have one (mono-unsaturated) or more
(poly-unsaturated) double bonds between carbon atoms. The food products contain high levels
of unsaturated fats such as meat and meat products, dairy, fish and oils that are particularly
susceptible to oxidative reactions as oxygen is able to attack those double bonds and yield the
4formation of free-radicals. The oxidations of lipids produce off-flavor and limiting the shelf-
life of lipids and lipid containing foods (Shahidi, 1997). The lipid oxidation is a major
economic problem in food industry because it makes products undesirable to consumer‟s
satisfaction. Food industries bear significant losses because of decreased product shelf-life
caused by lipid oxidation.
Oxidative rancidity is the lipid oxidation in which various kinds of fats produce oxidized
flavors in the presence of oxygen over time and can make a wide range of lipid-containing
products during storage period. It is the most important factor that decreases the shelf-life of
edible oils (Ryan et al., 2008). In addition, oxidative and hydrolytic rancidity are the major
reason of milk quality. Hydrolytic rancidity is the hydrolysis of triglycerides in the presence of
water and usually a catalyst such as lipoprotein lipase in milk and milk products. This lipase
releases the free fatty acids which contribute to the rancid, bitter and unpleasant taste in milk
and milk products (Gonzalez-Cordova and Vallejo-Cordoba, 2001). Lipid oxidations are not
only affecting off-lavor and odor development, but also have bad impact on food texture, color
and nutritive value of the products. The secondary products of lipid oxidation such as
malondialdehyde (MDA) and 4-hydroxynonenal (4-HN) are known to interact with amino
acids and proteins to produce undesirable products (Shahidi, 1997). In addition, textural
changes are caused by oxidized products to the oxidative induction of protein cross linking
(Kanner and Rosenthal, 1992). The oxidized products are also capable of destroying lipid-
soluble vitamins and essential fatty acids (Shahidi, 1997). Several key nutrients in milk are
destroyed by reason of light-induced lipid oxidation called photo-oxidation such as riboflavin
(Vitamin B2) and ascorbic acid (Vitamin C).
2.1.1. Mechanisms of Lipid Oxidation
The lipid oxidation can take place into three primary mechanisms: auto-oxidation,
photosensitized oxidation and enzyme catalyzed oxidation process. Auto-oxidation process is
extremely significance when it come contact to food. The auto-oxidation is a free-radical
mediated chain reaction whereby unsaturated fatty acids are attacked by molecular oxygen to
produce free radicals and a host of other oxidation products that negatively affect on texture,
taste, safety and nutritional quality of food products. The auto-oxidation happens into three
5stages: initiation that is the formation of free radicals, propagation making free-radical chain
reaction and termination cause formation of non radical products which is shown in Figure. 1.
2.1.1.1. Initiation
The initiation is the formation of free radicals via a hydrogen atom generalization by oxidizing
agents. The oxidizing agents are singlet oxygen free radicals and transition metals. The
formation of a hydrogen atom from an unsaturated fatty acid by an initiator makes to the
generation of a lipid free radical (L•) and the L• quickly reacts with molecular oxygen to form
the lipid peroxyl radical (LOO•) in the products.
2.1.1.2. Propagation
The stages of propagation include the fast acceleration of the chain reaction started in initiation
stage. In propagation stage, the peroxyl radical abstract a hydrogen atom from another
unsaturated fatty acid and a lipid hydroperoxide (LOOH) and another L• are produced. The
hydroperoxides are highly unstable primary products of oxidation, but do not contribute to the
undesirable flavors and odors commonly associated with rancid food products. But due to their
instability, peroxides can continue in the chain reaction and are further degraded into
secondary reaction products such as aldehydes, ketones and acids. These secondary products of
oxidation are mainly responsible for off-odor and off-flavor development in oxidized food
products.
2.1.1.3. Termination
The termination stage involves in which free radicals start to react to one another to make more
stable and nonradical products, thus completing one cycle. There can be reinitiating causing the
cycle to repeat as (Shahidi, 1997).
Initiation : LH →L•
Propagation : L• + O2 → LOO•
LOO• + LH → LOOH + L•
Termination : LOO• + LOO• → non-radical products
LOO• + L• → non-radical products
L• + L• → non-radical products
Figure 1. Mechanism of auto-oxidation (Shahidi, 1997).
62.1.2. Photo-oxidation
The photo-oxidation involves in which oxidation occurs due to the reaction of a
photosensitizing agent with molecular oxygen in the presence of light in food products shown
in Figure. 2. Common photosensitizers in food products are riboflavin chlorophyll and food
dyes. In photo-oxidation, a photosensitizer (1S) absorbs ultraviolet light (hν) and reaches an
excited state (3S*) and the excited sensitizer is then able to shift that energy to triplet oxygen
atom, e.g. ground state oxygen (3O2), thereby producing the more extremely reactive singlet
oxygen (1O2). The electrophilic nature of singlet oxygen permits it to directly attack
unsaturated fatty acids and photo-oxidation take place at a much quicker rate than auto-
oxidation. Transparent packaging and colorful foods make ideal conditions for the contact of
food to light, thus raising the likelihood of oxidative damage products (Kanner and Rosenthal,
1992). The photo-oxidation in food primarily happens through the following mechanism route
(Cuppett et al., 1997).
1S + hν →1S* →3S*
3S + 3O2→ 1O2 + 1S (energy transfer)
1O2 + LH→ LOOH
Figure. 2 Mechanism of photo-oxidation (Cuppett et al., 1997).
2.1.3. Enzyme-mediated Oxidation
Lipids oxidation can also be an enzyme-mediated way in which endogenous enzymes catalyze
reactions that make to the generation of free radical. These enzymatic reactions are occurred by
superoxide radical anion (O2•-) along with hydrogen peroxide (H2O2. For example, the enzyme
superoxide dismutase, catalyzes a reaction that converts O2•- to H2O2 and O2 molecules.
During the Fenton reaction (shown below), metal ions such as iron react with H2O2 to produce
the highly reactive hydroxyl (OH•) radical and the hydroxyl radical can directly attack the
double bond in lipids to begin the process of lipid oxidation (Cuppett et al., 1997).
Fenton Reaction: Fe2+ + H2O2 → Fe3+ + OH• + OH-
72.2. Antioxidants
Antioxidants slow down lipid oxidation in foods and prevent the cardiovascular disease (CVD)
and cancer in human. In order to slow down lipid oxidation food industry currently uses a
variety of synthetic antioxidants including butylated hydroxytoluene (BHT), butylated
hydroxyanisole (BHA), tert-butyl hydroquinone (TBHQ) and propyl gallate (PG) in food
products. Natural antioxidants, α-tocopherol, vitamin C and rosemary extracts are used by
industry.
The reactions shown in Figure 3 are suggesting that an appropriate antioxidant can totally stop
lipid oxidation in food products. An antioxidant, AH, reacts with free radicals and neutralizes
them in the following mechanism involved (Cuppett et al., 1997).
L• + AH → LH + A• (1)
LO• + AH → LOH + A• (2)
LOO• + AH → LOOH + A• (3)
LR• + A• → LA (4)
LO• + A• → LOA (5)
Figure 3. Antioxidant (AH) reactions with free radicals generated during lipid
oxidation (Cuppett et al., 1997).
2.2.1. Synthetic antioxidants
The synthetic antioxidants are widely employed to increase the shelf-life of various food
products. Commonly used synthetic antioxidants in the food industry are BHT, BHA and
TBHQ which is shown in Figure. 4. For undesirable color changes the use of PG are limited in
food industry. The BHT and BHA are hydrophobic phenolic antioxidants that hinder free-
radical initiated chain reactions in foods. The defense against lipid oxidation may occur for the
formation of a BHT radical, which have a lower reduction potential than that of lipid peroxyl
radicals in foods. The BHA is commonly used in combination with BHT or PG which generate
a synergistic effect in reaction. The TBHQ is less volatile than BHA and BHT but is stable at
8elevated temperatures also. For the stability of TBHQ at higher temperatures, it has established
to be more effective in polyunsaturated vegetable oil products (Patterson, 1989). Though
Synthetic antioxidants are extremely effective to slow down lipid oxidation, there have been
recent consumer concerns over possible adverse health effects associated with these products.
Many studies have showed that BHT and BHA cause a wide range of health trouble such as
enlarged liver, increased liver microsomal enzyme activity and make some ingested materials
into toxic and carcinogenic substances, especially if they are used in higher concentrations
(Rehman, 2003).
Figure 4. Chemical structures of some common synthetic antioxidants (Patterson, 1989)
2.2.2. Natural Antioxidants
Many researchers have been carried out to identify the sources of natural antioxidants that can
be used as an alternate of their synthetic antioxidants in recent years. The natural antioxidants
are recognized safe by consumers because they are naturally found in plant materials (Frankel,
1999). The natural antioxidants such as ascorbic acid, β-carotene and other carotenoids have
also been used in food products. The natural antioxidants not only decrease lipid oxidation in
food systems, but have also been shown to take part in a significant role in preventing a
number of chronic diseases including heart disease, Alzheimer‟s and Parkinson‟s diseases and
cancer (Chu et al., 2002; Tedesco et al., 2001; Weinreb et al., 2004; Youdim et al., 2002).
Antioxidant activity of plant extracts can be in large part credited to the existence of
polyphenolic compounds located within the plant tissue materials. The polyphenols are playing
a great deal of interest because their consumption in the diet may inhibit cancer, strokes and
9neurological disorders. It is estimated that we consume about 1g of polyphenols per day
because of the most abundant antioxidants in our diets (Scalbert and Williamson, 2000).
Almost several thousands of natural polyphenols have been well-known in plants and plant
food materials. The polyphenolic compounds are present in high concentrations in a variety of
fruits, vegetables and beverages such as tea and wine products. They are also found in
agricultural byproducts such as jackfruit seeds, peanut skins, hulls and roots, grape seeds and
skins and in a number of herbs and spice products. The polyphenols are vital to plant growth
and development and give a protective mechanism against injury and infection (Karakaya and
Taş, 2001). Various polyphenolic compounds have been found to have a much higher
antioxidant properties than vitamins C and E and β-carotene within the same food products
(Chu et al., 2002). The flavonoids are the major class of polyphenolic compounds and can be
divided into several sub-classes such as flavanols (catechin and catechin gallate esters),
anthocyanidins and flavonols (quercetin, myricetin, kaempferol), flavanones and flavones
(luteolin) shown in Figure. 5. Every flavonoids consist of a 15-carbon (C6C3C6)
diphenylpropane skeleton structure. As the 15-carbon backbone have the form of two benzene
rings (A and B) connected to a third heterocylic ring called the C ring in structure. The
differences in substitution on ring C help to distinguish the different classes of flavonoid
compounds. The flavonols, for example, lack a carbonyl at the carbon-4 (C-4) position on the
C ring and the C-4 position in flavonols is occupied instead, by a keto group in structure. Most
familiar of the flavanols are the flavan-3-ols, (+)-catechin and (-)-epicatechin that are
recognized to give green tea some of its antioxidant activities.
The number, existence, placement and degree of substitution of hydroxyl groups on the
benzene ring gives much of the structural variation found in flavonoid compounds (Bohm,
1998). The flavonoids can act as free radical scavengers, singlet oxygen quenchers or metal
chelators, depending on their chemical structure which is shown in Figure. 5 and there is much
discusses in the literature in regards to which structural configuration give the highest degree
of antioxidant properties. It is assumed that the antioxidant activity of flavonoids can be
attributed to the hydroxyl groups positioned at the 3‟,4‟-OH of ring B and the 2,3-double bond
of ring C, and the ability to stop free radical chain reactions increases with the number of OH
groups on rings A and B in structure. The flavonoids can act as metal chelators by binding
metals at two points: the orthodiphenol grouping in ring B and the ketol structure in the C ring
10of flavonol compounds. Therefore different metals show different properties with regard to
chelation by flavonoid compounds (Rice-Evans et al., 1996).
Figure 5. Chemical structures of common flavonoids found in plants (Bohm, 1998).
112.3. Extraction of polyphenols from plant materials
Naturally derived antioxidants to inhibit lipid oxidation in food products but standard
procedures for the extraction of these compounds from plant materials must be developed in
order to extend commercial uses. The researchers have developed a variety of extraction
procedures usually based on method. According to Waterman and Mole, 33 different extraction
procedures have been reported in recent plant biochemical literature review. Variation in these
procedures are extraction times ranging from 30 seconds to 96 hours and from 2 to 200 for
ratios of solvent volume to sample weight (Bohm, 1998). The main fact that one single plant
may contain up to several thousand secondary metabolites requires developing high
performance and rapid extraction methodology (Mandal et al., 2007). Optimization and
standardization of the extraction process is urgently needed to reduce time, energy and solvent
consumptions (Torres and Bobet, 2001).
2.4. Measuring antioxidant activity in food
In order to measure the antioxidant activity (AOA), there are a number of chemical assays that
have been developed. These assays are roughly divided into two main types depending on the
type of reaction that is involved: i) assays based on hydrogen atom transfer (HAT) and ii) assay
based on electron transfer (ET). The HAT-based assays are a competitive reaction scheme in
which the antioxidant and substrate compete for thermally generated peroxyl radicals (Huang
et al., 2005) and HAT-based assays include oxygen radical absorbance capacity (ORAC) and
total radical trapping antioxidant parameters (TRAP). Whereas ET-based assays is the capacity
of an antioxidant to reduce an oxidant and the oxidant changes color when reduced and the
degree of color change is correlated to the antioxidant concentration present in the sample
compounds. The ET-based assays are the Folin-Ciocalteu total phenols assay, Trolox
equivalence antioxidant capacity (TEAC), ferric ion reducing antioxidant power (FRAP) and
DPPH. The variety of the testing systems, methods and conditions employed for oxidation is a
major factor in the difficulty of interpreting the literature regarding antioxidant capacity of
natural antioxidants derived from plant extract materials (Frankel, 1999). The difficulty of the
topic of antioxidants coupled with the improper use of questionable methods has lead to a state
of confusion in the antioxidant research activities (Kinsella et al., 1993).
12The antioxidants activity is not only dependent upon the chemical reactivity (e.g., free radical
scavenging and chelating) of the antioxidant but also on factors including physical location,
interaction with other food components and environmental conditions in food systems (Decker
et al., 2005). Also the results derived these chemical assays are valid only for the specified
reaction conditions employed in the assay, and those conditions are usually not accurate
representations of real food systemic environments. However the current methods of
measuring AOA there are several methods that have been used as industry standards when it
comes to assessing oxidative deterioration in food products. These assessment methods are
thiobarbituric acid reactive substances (TBARS) assay, peroxide value (PV), p-anisidine value
(pAV), active oxygen method, Rancimat tests and sensory analysis. TBARS and PV are the
most frequently used although there are some restrictions to both tests. Recently, the use of the
ORAC assay to determine oxidation in food has increased in popularity in food system.
Nevertheless, sensory analysis play the most reliable method as the task of assessing the
acceptability and preference of products is best carried out by customers.
2.5. Response surface methodology (RSM)
Response surface methodology (RSM) is a statistical method in which quantitative data used to
determine and solve the multivariate equations from suitable experimental designs. To
determine the interrelationships among the test variables and to describe the combined effect of
all test variables on the response these equations were graphically represented as response
surfaces which are used to describe how the test variables affected the response. The use of
RSM in any experiments or optimization process, will save cost, energy time, and identify the
caused of defects and also eliminated waste during production process. It is reported that many
food researches and product developments such as in bread formulation design, cookies and
also in development and optimization of baked goods formulation such as cake are performed
using response surface methodology (RSM) (Myers and Montgomery, 1995).
An experimental design is a general step to be applied in any experiments and RSM study.
Firstly, the experiment is design to find out the purpose of the study and determined the
responses and factors. The independent variables included processing conditions or
ingredients. Dependent variables or Responses measured can be chemical constituents such as
percent antioxidants, physical measurements such as viscosity, sensory scores, shelf life of a
13product or microbiological stability results). Antioxidant extraction from plants or product
development is generally employed in two stages, namely screening and optimization process
(Dean and Voss, 1999).
2.5.1. Screening
Screening is the investigation of a great number of something looking for those with a
particular feature or problem. The aim of screening is to identify the critical control variables
from a collection of many potential variables so that the experiments will be more efficient and
fewer runs or tests required (Montgomery, 2005). It estimates the effect of each factor and
selects factors which produced a significant effect on the response variable for further testing.
For this purpose two level factorial and fractional factorial designs are employed (Myers et al.,
1989).
2.5.2. Factorial design
The factorial design is broadly employed in experiments involving several factors to examine
the interaction effects of the factors on a response or dependent variable by carry out all
possible combinations of levels and variable. During two level factorial designs, each variable
is studied at only two levels, called the (-) and (+) levels which is known as 2k factorial design
process. For 2k design; only two factors (A and B) are involved and each run at two levels and
this design is called a 22 (4 factor combinations) factorial design process (Montgomery, 2005).
A plot of the experimental region tested in a 22 factorial is shown in Figure 6.
Figure 6. The 22 factorial design (Montgomery, 2005)
142.5.3. Fractional factorial design
The fractional factorial design is employed to investigate only a fraction of the factor
combinations in a full factorial design process. In fractional factorial design it does not
determine the interaction effects between factors but used to test only a fraction of the factor
such as a one half fraction of a 23 design is designated as a ½ 23 or 23 – 1 which have only four
factor combinations compared to eight combinations in factorial design process (Dean and
Voss, 1999).
2.5.4. Addition of central point to factorial design
The addition of replicated centre points in a 2k factorial design is to give a protection against
curvature and to obtain an independent estimate of error in design (Montgomery, 2005).
2.5.5. Blocking and randomization
Protection against known enemies is called blocking. It makes sure that the blocking variable
is as orthogonal as possible to all the predictive variables. As for example, design to compare
paints from 4 suppliers shown in Figure 7.
1 2 3 4
A C C D
C B A B
D A D A
B D B C
Figure 7. Blocking in design (Dean and Voss, 1999)
Protecting against unknown enemies is called randomization. The response can be affected by
factors unknown at the time of designing the experiment and even unknown after the analysis
such as time temperature and concentration. One of these gets seriously confounded with a
variable of interest can be happened. The randomization is the best weapon to prevent this
error.
Therefore grouping together experiments is known as blocking, which helped in preventing
experimental error, while randomization reduced the correlation with time in experiment (Dean
15and Voss, 1999). As for example, when the 2k factorial design is replicated for n times then
each set of this design is considered as a block and each replicated of the design is run in a
separated block in design. Therefore the runs in each block were completed in random order
(Montgomery, 2005).
2.5.6. Analysis for screening experiment
During screening experiment, the first order model is constructed after evaluating the effects
and interactions as shown in Equation 2.1 in the case of two independent variables or factors
(Montgomery, 2005).
First order model: y = ß0 + ß1χ1 + ß2χ2 + e (2.1)
From the equation, y is the response, χ‟s represent factors, ß0 represents the y- intercept, ß‟s
are known as parameters and e is the residuals or error. After an analysis of residuals and
analysis of variance (ANOVA), when a model is built to evaluate how well the model
represented the data which consisted of percent of confidence, percent of variation and
coefficient of variation (CV) effect (Box et al., 2005).
2.5.7. Optimization
The aim of optimization is to determine the optimum levels of the factors studied. It included
both response surface methods and mixture experiments. Quantitative data is used to make an
empirical model that illustrated the relationship between the response and each factor
investigated.
During optimization experiments the model most often used was the full second order
polynomial model as shown in Equation (2.1) and (2.2) which including the interaction effects
between factors and curvature effects. Usually two or three the number of factors in response
surface method was used. Therefore, the model was used to evaluate the effects of each factor,
interactions between and among factors and curvature effects. Such as ß11χ12 is the Curvature
effect, produced parabolic shapes when the model was graphically represented. When two
different levels of the same factor produced similar values of response and higher or lower
responses at intermediate factor levels then these effects occurred (Box et al., 2005).
16Second order model:
y = ß0 + ß1χ1 + ß2χ2 + ß11χ12 + ß22χ22 + ß12χ1χ2 + e (2.2)
From the equation, y is the response, ß0 represents the y-intercept and ß‟s was the regression
coefficient, χ1 represents the first factor, χ2 represent the second factor and e represents the
usual random error.
Full response surface- second order design is a design that allows the estimation of a full
quadratic model (Box-Behnken, and Central composite design). For three level factors, Box
and Behnken (1960) introduced designs that are widely used in response surface methods to fit
second-order models to the response and the designs are known as Box-Behnken designs. The
combination of two level factorial designs with incomplete block designs used to develop the
designs shown in Figure 8, the Box-Behnken for three factors designs.
Figure 8. Box-Behnken design for three factors show the geometric representation
(Box et al., 2005).
By the combination of 22design with a balanced incomplete block design having three
treatments and three blocks the design is obtained. The benefit of Box-Behnken designs is the
fact that they are all spherical designs and need factors at only three levels to be run (Box et al.,
2005).
The Central composite design (CCD) consists of three types of points: Star points or axial
points, the axial points are created by a Screening Analysis, Factorial points or cube points, the
17cube points come from a Full Factorial design and Centre point, a single point in the center is
created by a nominal design shown in Figure 9 (Myers and Montgomery, 1995).
Figure 9. Factor combinations for a central composite design (Myers and
Montgomery, 1995)
The Central composite design (CCD) is widely used for fitting a second order method in
response surface method which consisted of four runs at the corners of the square, four axial
runs and four runs at the centre of this square that introduced by Box and William on 1957.
The model was established by the analysis of variance (ANOVA) to test the adequacy of the
model and the tests such as percent of variation, percent of confident, coefficient of variation
(CV), press and R2 value and „Root MSE‟ value. The model was described in a three
dimensional response surface plot and it represented a different response value and showed the
factors levels responsible for that response which provided an understanding of how the
experiment behaved when the factor levels were altered. A suitable model was selected when
R2 value was maximum and the „press‟ and „Root MSE‟ value was minimum. The coefficient
of variation (CV) value of the model should not exceeded than 10 % while the maximum R2
value was not less than 80 % which indicated that the confidence level of the chosen model
was not due to the experimental error and the model was significant (Montgomery, 2005).
18CHAPTER III: MATERIALS AND METHODS
3.1. Chemicals
2,2-diphenyl-1-picrylhydrazyl (DPPH) and ferric chloride (FeCl3) were purchased from Sigma-
Aldrich Chemical Co. (USA). Folin-Ciocalteu Phenol-Reagent (FCR), ethanol (C2H6O),
sodium carbonate (Na2CO3), di-sodium hydrogen phosphate (Na2HPO4) were purchased from
Chem-Lab (Belgium). Sodium phosphate, monobasic di-hydrate (NaH2PO4.2H2O),
Tricholoroacetic acid (C2HCl3O2), Potassium ferricyanide K3[Fe(CN)6] were supplied by
Acros Organics (USA).
3.2. Preparation of materials
According to Jagadeesh (2007) the chemical composition of jackfruit depends upon the type of
cultivar. Therefore, one specific jackfruit variety named Khaja (firm one) was included in this
study. Whole matured fruits were provided by the Bangladesh Agricultural University
(Mymensigh, Bangladesh). On arrival, fruits were stored in a dry place until ripening. Upon
ripening the seeds were separated from the pulp and were peeled off. Peeled seeds were
lyophilized and hermetically stored at -20oC.
3.3. Extraction procedure
The lyophilized samples were milled to a very fine power by using a planetary ball mill
(Retsch PM 400, Germany) and strained with 0.3 mm strainer, in order to get rid of bigger
chunks. The extraction was executed at three stages. Approximately, 0.23 g of sample (wet
powder) was used for each extraction. For the first extraction, 24 full factorial screening design
(Table 2A) was used, where x1 ethanol (% ,v/v), x2 temperature (oC), x3 liquid-to-solid ratio
(ml/g DM), and x4 time (minute) were independent variables. However, in the second and third
phases, only three independent variables of x1 ethanol (%, v/v), x2 temperature (°C), x3 liquid-
to-solid ratio (ml/g DM) were used, utilizing the design of experiment of 23 full factorial with
center points (Table 3A) and Box-Behnken (Table 4A), respectively. The samples were always
vortexed well before and after the extraction. During the extraction procedure the samples were
kept as airtight as possible, in order to prevent evaporation losses. At the end of each
extraction, the samples were immediately cooled with ice water, and the extracts were filtered
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