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STABILISATION AND CHARACTERISATION OF A PEANUT BASED 
READY-TO-USE SUPPLEMENTARY FOOD (RUSF) 
 
 
 
 
A THESIS SUBMITTED TO THE DEPARTMENT OF NUTRITION AND 
FOOD SCIENCE OF THE UNIVERSITY OF GHANA, LEGON 
 
 
BY 
 
AGARTHA ADWOA KRAH 
(10230034) 
 
 
 
 
 
 
IN PARTIAL FULFILMENT OF THE REQUIREMENT FOR THE 
AWARD OF MASTERS IN THE PHILOSOPHY OF FOOD SCIENCE 
 
 
 
MARCH 2014 
 
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DECLARATION 
This is to certify that this thesis is the result of research undertaken by Agartha Adwoa Krah 
towards the award of the MPhil Food Science in the Department of Nutrition and Food Science, 
University of Ghana, Legon. 
 
 
  ……………………………………….                 ……………………………. 
                    Agartha Adwoa Krah        Date 
                       (Student) 
  
 
 
        ………………….....…………..                               …………………………. 
                         Prof. F. K. Saalia     Date 
                           (Supervisor) 
 
 
 
        …………………..…………..                                    ………………………….. 
                 Prof. E. Sakyi-Dawson                                                    Date 
                          (Supervisor) 
 
 
 
 
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ABSTRACT 
The prevalence of under nutrition in many communities requires the need for the availability of 
nutrient dense affordable food supplements such as Ready-to-use supplementary foods. An 
energy dense, drinkable ready to use supplementary food produced by  enzyme hydrolysis of 
cooked mixture of peanuts, cowpeas and rice with added vitamin mineral mix was both 
acceptable to consumers and showed promise of efficacy in improving the nutritional status of 
women of child bearing age through nutritional intervention studies. However the product was 
physically, chemically and microbiologically unstable, and did not store for long at ambient 
temperatures. This work was done to improve the physical and microbiological stability of the 
drinkable peanut based ready-to-use supplementary food. 
 Roasted peanut, cooked cowpeas and rice were mixed in a ratio of 3:3:4 (dmb) and slurried in a 
colloid mill, hydrolysed with alpha-amylase and bromelain enzymes at 50˚C and 43˚C 
respectively to obtain a liquefied product of about 20% solids. Calculated amounts of vitamin 
and mineral mix were added to meet the requirements of the target population for the 
supplement. The product was thermally processed by either pasteurizing (10, 20 and 30 minutes) 
at 95˚C or retorting at 119˚C for 10 minutes. The effectiveness of the thermal processes on the 
microbial and chemical stability of the product was monitored at 25, 35 and 45˚C for five weeks. 
The flow behaviour of the product and viscosity were characterised using the Brookfield digital 
viscometer.  The effects of particle size on product separation rate were determined, and the 
application of stabilizers (CMC, carrageenan and Xanthan gum) to modify product viscosity 
examined.  The shelf life of the product was calculated based on chemical deterioration rate by 
modelling free fatty acids data on Arrhenius kinetics.  
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 The finer particles in the product (≤106µ) had faster settling rates than the larger ones (≥300 and 
500µ). The apparent viscosity of the product was 440cP, and generally increased by the use of 
stabilizers. Addition of Xanthan gum at 1% level gave the greatest increase in apparent viscosity 
(1111.0 cP), and its subsequent application in the product formulation substantially reduced the 
settling rate of particles, and provided some measure of physical stability to the product.   
 Optimal starch hydrolysis was achieved after 1 hour incubation with alpha amylase at 50˚C-
55˚C. Protein hydrolysis by bromelain was highest at 43˚C, and SDS-PAGE zymograms showed 
extensive hydrolysis of all proteins within I hour of incubation with bromelain. Prolonged 
incubation times led to reformation of peptides as was noticeable on the zymograms of 3 hour 
hydrolysates, suggesting that plastein-like reactions probably occurred under the conditions of 
incubation with bromelain. 
Microbiological stabilization of the product by thermal processing proved inadequate as was 
evidenced by high microbial counts in all treatments. Heat penetration data from both 
pasteurization and sterilization processes showed that thermal processing was inadequate to 
assure microbial stability of the product. Accelerated shelf life studies (based on lipid oxidation 
data) showed the product to be chemically stable at room temperature (25˚C) for 22 days. 
Practically however, the product shelf stability did not go beyond three days at ambient 
conditions due to microbial spoilage.  
While it was possible to improve the physical stability of the product, microbiological stability 
was not attainable using physical treatments, and other options need to be explored. It is essential 
to improve the shelf life of the product at ambient temperature storage, in order to enhance its 
distribution and usage among the rural poor and undernourished who need it the most. 
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DEDICATION 
I dedicate this work to the Almighty God; my banner. To the two wonderful ladies in my life; my 
mother Agnes and my sister Christiana for believing in me, nurturing my dreams and sacrificing 
so much for me to come this far.  
 
 
 
 
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ACKNOWLEDGEMENT 
All praise and thanks to God for His love and faithfulness that made this work possible. 
I am most grateful to my dear mother Agnes, sisters Christiana, Matilda and Rita for your 
constant love, prayers and support.  
I am deeply indebted Dr F. K. Saalia and Prof. E. Sakyi-Dawson for not just supervising my 
work but accepting me and shaping my dream. I am also grateful to all lecturers at the 
Department of Nutrition and Food Science for their contributions during the period of study. 
Benard, Nana Kwame, Nelson and all my MPhil colleagues, you were always there for me. I 
really appreciate your constant help. I am also grateful to all technicians of the Department of 
Nutrition and Food Science. 
To the staff of the Cocoa Research Institute of Ghana especially Mr. Osae Awuku, Dr. Takrama, 
Rafiatu, Clement and Mrs Kumi, I am so grateful. 
To all the sweet ladies I call sisters and wonderful gentlemen I call friends especially Evelyn, 
Darlene, Forgive, Maame Kyerewaa, Enock, Asiamah and my dear Richmond; I cannot 
overemphasise the love you have shown me, God bless you. 
 
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TABLE OF CONTENTS 
Content                   Page 
DECLARATION .......................................................................................................................................... ii 
ABSTRACT ................................................................................................................................................ iii 
DEDICATION .............................................................................................................................................. v 
ACKNOWLEDGEMENT ........................................................................................................................... vi 
TABLE OF CONTENTS ........................................................................................................................... vii 
LIST OF TABLES ....................................................................................................................................... xi 
LIST OF FIGURES .................................................................................................................................... xii 
LIST OF PLATES ..................................................................................................................................... xiv 
LIST OF APPENDICES ............................................................................................................................. xv 
CHAPTER ONE ........................................................................................................................................... 1 
1.0  INTRODUCTION ............................................................................................................... 1 
1.1  Background ........................................................................................................................... 1 
1.2  Rationale .............................................................................................................................. 3 
1.3  Objectives ............................................................................................................................ 4 
CHAPTER TWO .......................................................................................................................................... 5 
2.0 LITERATURE REVIEW ..................................................................................................... 5 
2.1 Malnutrition .......................................................................................................................... 5 
2.2 Ready-to-use Therapeutic Foods (RUTFs) ........................................................................... 6 
2.3 The Concept of Food Supplementation ................................................................................ 7 
2.4 Recommended Dietary Allowances (RDAs) for Vulnerable Groups ................................... 8 
2.5    The Application of Enzymes in Food Processing .................................................................. 10 
2.5.1 Amylases in Food Processing ..................................................................................... 11 
2.5.2 Cysteine Proteases ...................................................................................................... 13 
2.5.3 Plastein Reactions ....................................................................................................... 14 
2.6 Rheological Behaviour of Fluids ........................................................................................ 15 
2.7 Emulsifiers and Stabilizers ................................................................................................. 16 
2.8 Causes of Food Spoilage..................................................................................................... 19 
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2.8.1 Physical ....................................................................................................................... 19 
2.8.2 Chemical ..................................................................................................................... 20 
2.8.3 Biological .................................................................................................................... 21 
2.9 Thermal Processing ............................................................................................................ 22 
2.9.1    Microbial Destruction Kinetics ....................................................................................... 23 
2.9.2 Blanching .................................................................................................................... 24 
2.9.3 Pasteurisation .............................................................................................................. 25 
2.9.4 Sterilisation ................................................................................................................. 27 
2.9.5 Quality Deterioration of Food during Thermal Processing ........................................ 28 
2.10   Food Spoilage Due to Lipid Hydrolysis and Oxidation .................................................................... 29 
2.10.1 Hydrolytic Rancidity................................................................................................... 30 
2.10.2   Oxidative Rancidity ....................................................................................................... 30 
2.11 Shelf-Life Testing ............................................................................................................... 31 
2.11.1 Indirect Methods ......................................................................................................... 32 
2.11.1.1 Predictive Modelling ................................................................................................... 32 
2.11.1.2 Application of Q10 Concept in Predicting Shelf Life .................................................. 33 
2.11.1.3 Application of the Arrhenius Theorem in Predicting Product Shelf Life ................... 34 
CHAPTER THREE .................................................................................................................................... 36 
3.0  MATERIAL AND METHODS ........................................................................................ 36 
3.1 Raw Materials ..................................................................................................................... 36 
3.2 Sample Preparation ............................................................................................................. 36 
3.2.1 Roasting ...................................................................................................................... 36 
3.2.2 Soaking ....................................................................................................................... 36 
3.2.3 Cooking ....................................................................................................................... 37 
3.2.4  Homogenisation ......................................................................................................... 37 
3.2.5 Thermal Processing..................................................................................................... 37 
3.3 Process Flow Chart for RUSF Production .......................................................................... 38 
3.4 Chemical Determinations ................................................................................................... 39 
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3.4.1 Proximate Analysis ..................................................................................................... 39 
3.4.2 Mineral Analysis ......................................................................................................... 39 
3.4.2.1  Determination of Na and K ............................................................................................ 39 
3.4.2.2   Determination of Phosphorus ....................................................................................... 40 
3.4.2.3  Determination of Ca, Cr, Cu, Fe, Mg, Mn, Zn, Ni and Pb .......................................... 40 
3.5 Determination of the Degree of Hydrolysis of the Macromolecule by Enzymes ............... 41 
3.5.1 Starch .......................................................................................................................... 41 
3.5.2 Protein Hydrolysis by (Bromelain) Protease Enzymes ............................................... 41 
3.5.2.1 Preparation of Samples ................................................................................................... 41 
3.5.2.2  Trinitrobenzene Sulphonic Acid (TNBSA) Method ................................................... 42 
3.5.2.3 SDS-PAGE ......................................................................................................................... 42 
3.6 Effect of Particle Size Distribution on Product Separation. ............................................... 43 
3.7   Effects of Stabilizers on Physical Stability and Flow Behaviour of Product. ......................... 43 
3.7.1 Apparent Viscosity ..................................................................................................... 44 
3.8 Storage Stability and Shelf-life Studies .............................................................................. 44 
3.8.1 Microbial Analysis ...................................................................................................... 44 
3.8.2 pH and Titratable Acidity ........................................................................................... 45 
3.8.3 Free fatty Acids and Peroxide Value Test .................................................................. 45 
CHAPTER FOUR ...................................................................................................................................... 47 
4.0  RESULTS AND DISCUSSIONS ..................................................................................... 47 
4.1 Nutrient Composition of Drinkable RUSF ......................................................................... 47 
4.2  Degree of Hydrolysis of Macromolecules ......................................................................... 48 
4.2.1 Hydrolysis of Starches in the Product Formulation .................................................... 49 
4.2.2 Trinitrobenzene Sulphonic Acid Determination of –NH2 groups (as a Measure of Protein 
Hydrolysis) ................................................................................................................. 51 
4.2.3 Sodium Dodecyl Sulphate Polyacrylamide Gel Electrophoresis (SDS-PAGE) of Protein 
Hydrolysates. .............................................................................................................. 56 
4.3 Physical Stability of the Product (RUSF). .......................................................................... 57 
4.3.1 The Effect of Particle Size on the Rate of Separation................................................. 58 
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4.3.2 Effects of Stabilizer on Sedimentation Rates of Particles in the drinkable RUSF ...... 63 
4.4 The Effect of Pasteurisation Time, Storage Temperature and Storage Time on Microbial 
Growth, and Physico-Chemical Properties of the RUSF ................................................................ 65 
4.4.1 Comparison between Retorted RUSF (119°C) and Pasteurised (95°C) RUSF Samples69 
4.5 Product Stability and Shelf-life Estimation ........................................................................ 72 
4.5.1 Microbial Growth as Indices for Product Stability ..................................................... 74 
4.5.2 pH and Titratable Acidity ........................................................................................... 75 
4.5.3 Free Fatty Acids and Peroxide Value as Indices of Product Stability ............................... 78 
4.6 Estimation of Product Shelf-life ............................................................................................... 81 
5.1 Conclusions............................................................................................................................... 87 
5.2 Recommendations ..................................................................................................................... 88 
REFERENCES ........................................................................................................................................... 89 
APPENDICES .......................................................................................................................................... 106 
 
 
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LIST OF TABLES 
 
Table 2.1: RDAs of Children within the Age Range of 0-12 and 12-24 Months................ 10 
Table 4.1: Nutrient Composition of RUSF and the Percentage of RDAs of WRA                                              
to be Met........................................................................................................... 48 
 
Table 4.2: Degradation Rate Values Showing the Rate of Sedimentation of RUSF Samples with 
Different Particle Sizes....................................................................................................... 60 
 
Table 4.3: Effects of Stabilizers on some Rheological Characteristics of the  
Drinkable RUSF.................................................................................................................. 62 
 
Degradation Rate Values Showing the Effects of Stabilizers on the Rate of Sedimentation of the 
drinkable RUSF.............................................................................................. 66 
 
Table 4.5: Anova Summay (P-Values) Showing the Effects of Different Processing and Storage 
Variables on Microbial Parameters of RUSF Samples...................................... 69 
 
Table 4.6: Anova Summay (P-Values) Showing the Effects of Different Processing and Storage 
Variables on Physico-Chemical Parameters of RUSF Samples.......................... 70 
Table 4.7 Experimental Design for Shelf Life Studies on the Drinkable RUSF.................. 83 
Table 4.8 Degradation Rate Models for RUSF at Different Storage Temperatures............. 85 
Table 4.9: Predicted Shelf Life of RUSF as a Function of Temperature.............................. 86 
 
 
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LIST OF FIGURES 
 
Figure 3.1: Process Flow Chart for RUSF Production......................................................... 38 
Figure 3.2 Reaction of TNBSA with amino groups............................................................ 42 
Figure 4.1: Effects of temperature on the degree of hydrolysis of starches of the drinkable     
       RUSF.................................................................................................................. 50 
 
Figure 4.2: Effects of time on the degree of hydrolysis of the starches of the drinkable 
                  RUSF.................................................................................................................. 51 
 
Figure 4.2: Combined effects of temperature and time on the degree of hydrolysis of the starches           
         of the drinkable RUSF..................................................................................... 52 
 
Figure 4.4: Effects of temperature on the degree of hydrolysis of the RUSF proteins......... 53 
Figure 4.5: Effects of time on the degree of hydrolysis of the drinkable RUSF          
       proteins................................................................................................................ 54 
 
Figure 4.6: Combined effects of temperature and incubation time on the degree of hydrolysis of 
the drinkable RUSF proteins............................................................................. 55 
Figure 4.7: Combined effects of temperature and concentration of the enzyme on the degree of           
        hydrolysis of the drinkable RUSF proteins........................................................ 56 
 
Figure 4.8: Effects of product particle size on the settling rate of RUSF samples with different    
        particle sizes..................................................................................................... 59 
 
Figure 4.9: Effects of three different stabilizers on the sedimentation of RUSF.................   65 
Figure 4.10: Heat penetration curve of pasteurised RUSF samples 
          (at 95°C for 10,20 &30min)............................................................................ 67 
 
Figure 4.11: Heat penetration curve of retorted RUSF samples  
                  (sterilised at 119°C for 10min)........................................................................... 68 
 
Figure 4.12: Effects of heat treatment on microbial loads (TVC) of RUSF samples .........  71 
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Figure 4.13: Effects of heat treatment on free fatty acids of RUSF samples........................ 72 
Figure 4.14: Effects of heat treatment on peroxide value of RUSF Samples.....................    73 
Figure 4.15: Bacteria growth (TVC) in RUSF samples during 5 weeks of storage at 25°C, 35°C       
           and 45°C....................................................................................................... 74 
 
Figure 4.16: Changes in pH of RUSF samples during 5 weeks of storage at 25°C, 35°C 
and 45°C............................................................................................................................ 77 
 
Figure 4.17: Figure 4.17: Changes in titratable acidity of RUSF samples during 5 weeks of     
         storage at 25°C, 35°C and 45°C................................................................... 78 
Figure 4.18: Changes in the growth of Yeasts and Moulds Growth in RUSF samples during 5        
          weeks of storage at 25°C, 35°C and 45°C....................................................... 79 
Figure 4.19: Changes in free fatty acids values of RUSF samples during 5 weeks of storage at             
          25°C, 35°C and 45°C..................................................................................... 81 
Figure 4.20: Changes in peroxide values of RUSF samples during 5 weeks of storage  
                      at 25°C, 35°C and 45°C................................................................................. 82 
Figure 4.21: Effect of storage time on the rate of deterioration of fat (log FFA)................ 85 
Figure 4.22: Predictive shelf life of RUSF as a function of storage temperature based on the 
Arrhenius model................................................................................................ 86 
 
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LIST OF PLATES 
 
Plate 4.1: SDS PAGE zymogram showing the effect of bromelain hydrolysis on RUSF 
 Proteins .............................................................................................../................................58 
 
 
 
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LIST OF APPENDICES 
 
Appendix 1: Analysis of Variance (ANOVA) Table for Degree of Starch Hydrolysis..... 107 
Appendix 2: ANOVA Table for Degree of Protein Hydrolysis.......................................... 107 
Appendix 3: ANOVA Table for Particle size……………………………………............. 107 
Appendix 4: Viscosities of Samples Using Different Stabilizers ………………………...   108 
Appendix 5: ANOVA Table for Stabilizer Treated Samples…………………………….. 108 
Appendix 6: Values for Microbial Growth, pH and Titratable Acidity at Different                
Pasteurisation Time, Storage temperature and Storage Time……………… 109 
Appendix 7: ANOVA Table for pH………………………………………………………. 112 
Appendix 8: ANOVA Table for Titratable Acidity………………………………………. 112 
Appendix 9: ANOVA Table for TVC.................................................................................. 113 
Appendix 10: ANOVA Table for E. Coli…………………………………………………. 113 
Appendix 11: ANOVA Table for Yeast and Mould............................................................. 113 
Appendix 12: Values of FFA PV at Different Pasteurisation Time, Storage temperature and Storage 
Time………………………………………………………………………………………………………………………………….………… 114 
Appendix 13: ANOVA Table for FFA................................................................................ 117 
Appendix 14: ANOVA Table for PV.................................................................................. 117 
Appendix 15: L-leucine Standards for TNBSA .................................................................. 118 
 
  
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CHAPTER ONE 
 
1.0  INTRODUCTION 
1.1  Background 
Under nutrition is a prevalent condition in many African communities and a pre-disposing factor 
to various forms of diseases. This to a large extent has been a result of poverty which makes it 
very difficult for vulnerable groups to afford nutritionally adequate food. As a result they are 
heavily dependent on high carbohydrate foods with little or inadequate supplies of proteins and 
essential vitamins. In poor and deprived communities, children, the aged, pregnant women and 
the sick are particularly vulnerable to under nutrition (Van Der Kam et al., 2012; Stratton et al., 
2003). For the short term it is frequently an emergency that requires immediate nutritional 
intervention with foods that are nutritionally potent enough to either prevent or correct the 
conditions of under nutrition.  Such foods should also be able to provide enough energy to meet 
or supplement the daily requirements of the consumer.    
 
 Ready to use therapeutic foods (RUTF) is a generic term referring to different types of foods 
such as spreads or compressed products useful for feeding children and adults who are seriously 
malnourished or chronically sick (Manary, 2006). Due to the high energy density of RUTFs 
(about 5.5kcal/g), severely malnourished and chronically sick individuals can consume just a few 
spoonfuls  several times a day and obtain sufficient nutrients for complete restoration of health. 
RUTFs are formulated and processed such that they need no further processing before eating. 
They also have a reasonably long shelf life and are very palatable and acceptable to the consumer 
(Annan, 2014). Formulation of RUTFs to provide the calories, and nutritional profile needed to 
meet the requirements of specific vulnerable groups can be challenging depending upon the 
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recommended daily allowances (RDA) of the target group. In the case of meeting the 
requirements of adult vulnerable groups, rather than provide RUTF, it is a lot easier to 
supplement their food with better sources of nu 
3trition, or formulate a product that can be used as ready to use supplementary food (UNICEF, 
2008).  Asante (2009) described the development of a ready to use supplementary food by 
formulating cowpeas, peanuts and rice using constrained mixture designs (Cornell, 1995). The 
three commodities were chosen in part because they are easily available locally and also because 
when mixed in the right proportions they provided the needed nutritional energy necessary for a 
supplementary food.  A pre-hydrolyzed mixture of roasted peanuts (0.35-0.45), cooked cowpea 
(0.2-0.25) and rice (0.35-0.4) was drum dried and evaluated for its energy and protein content 
among other properties. The product had nutritional properties which met the recommended 
dietary allowances of energy, macro- and micronutrients for vulnerable groups (children, 
pregnant and lactating mothers).  The formulation was further modified into protease and 
amylase pre-hydrolyzed liquefied drinkable product to contain 15% solids, such that it would 
have the following attributes: 
1. Sufficiently liquid enough to be swallowed by consumers who may be so malnourished or 
severely ill that consuming solid food might be difficult.  
2. Highly digestible. 
3. Pleasant nutty flavour with some sweetness deriving from the process of amylase hydrolysis of 
the starches and the addition of sugar.  
4. Nutrient dense with high levels of protein to promote recovery.  Vitamins and minerals were 
added at pre-determined amounts. 
5. No detectable levels of aflatoxins. 
 
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Product quality and shelf life are critical to its success and acceptability by consumers, no matter 
its nutritional quality (NZFSA, 2005). For a liquid product, some quality characteristics may 
include physical attributes (i.e. colour, appearance, flow properties, structural degradation), 
microbiological stability, chemical characteristics (including degradation of some vitamins, and 
lipid oxidation) as well as sensory acceptability. 
 
1.2  Rationale 
The peanut based ready to use supplementary food (RUSF) formulation under consideration is a 
drinkable beverage that was designed to be readily digestible when ingested and to release 
needed energy to the consumer as quickly as possible. Initial tests have shown the product to be 
quite acceptable to consumers (Anim-Fofie, 2011). Its efficacy was tested in a nutritional 
intervention study among women of childbearing age (Agbemefle, 2013; under review) in a 
community from which previous baseline studies showed the cohort group to be grossly 
undernourished (Anim-Fofie, 2011). However, the product was microbiologically and physically 
unstable as it easily separated (i.e. sedimentation of particles) upon standing, and did not store 
longer than one week even after pasteurization. To extend the shelf life, the product was usually 
kept in refrigerated storage after pasteurization. The target consumers may not have access to 
house hold refrigeration facilities, or even afford electrical energy to keep them refrigerated. The 
physical separation of the product also needs to be addressed, by reducing the mean particle size 
or varying the medium viscosity in order to minimize the rate of particle sedimentation. A 
reduced mean particle size will improve product mouth feel and probably increase consumer 
acceptance. 
 
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1.3  Objectives  
The objective of the study was to improve the physical and microbiological stability of the 
peanut based drinkable RUSF. 
The specific objectives were to: 
 Investigate the effects of product particle size distribution on separation rate during storage.  
 Investigate the effects of stabilizers in minimizing product separation and characterize the 
flow behaviour of the drinkable RUSF.  
 Determine the degree of hydrolysis of the macromolecules (proteins and starches). 
 Conduct shelf life studies and microbial stability under different temperature storage 
conditions. 
 
 
 
 
 
 
 
 
 
 
 
 
  
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CHAPTER TWO 
 
2.0 LITERATURE REVIEW 
2.1 Malnutrition 
Malnutrition or abnormal nutrition occurs in human beings as a result of nutritional imbalance 
and could mean an excess or a deficit of nutrients depending on the physiological requirements 
of the body. Based on the requirements of normal nutrition, the body mass index (BMI) is used 
as an indicator of the risk of an individual being over or under-nourished (Stratton et al., 2003). 
Though malnutrition can imply inappropriate intake of any of the essential nutrients, protein-
energy malnutrition (PEM) which is due to an inappropriate intake of the macro-nutrients 
especially protein and fats is the commonest form of malnutrition (Stratton et al., 2003).  
 
In developing countries where living conditions of majority of the people are characterised by 
poverty, lack of resources and skills with its accompanying food insecurity, protein-energy 
under-nutrition is very common and children under the age of five (5) years are the most 
vulnerable (Wardlaw, 1993). It is reported (Defourny et al., 2009) that about 146 million 
children under five in developing countries are under weight whiles in sub-Saharan Africa about 
38.6% of the children are stunted, 28.4% underweight, and 7.2% wasted (Olwedo et al., 2008) 
with 3% suffering from severe acute malnutrition (Briend and Collins, 2010) at any point in 
time. According to Huybregts et al. (2012), from analysis based on 139 countries, about 10.2% 
of deaths were attributed to wasting, which was mainly as a result of malnutrition. Black et al., 
(2010) asserted that wasted children are three times more likely to die than their well nourished 
counterparts. Additionally malnutrition has a profound effect on the health and cognitive 
performance of these children as child nutrition is known to be vital in brain development (Pollitt 
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and Brown, 1996). Under-nutrition has also been implicated in child mortality, morbidity (Gera, 
2010) and disability-adjusted life years together with intrauterine growth restriction (PLoS 
Medicine Editors, 2008). 
 
Furthermore, under nutrition affects immune function leading to compromised immune defences 
and increased susceptibility to all forms of diseases (Heikens et al, 2008). It is also known to 
cause mortality through its potentiating effect on diseases (Pelletier, 1995) such as malaria (Van 
Der Kam et al., 2012) and  HIV/AIDS (Ndekha, 2009) as well as aging etc. which could be a 
result of inefficient absorption of nutrients (Olwedo et al., 2009). Under-nutrition is also known 
to have a synergistic effect with these co-morbidities as well as parental characteristics such as 
poor health and nutritional status (Grantham-McGregor, 1995). The long term effect of this is a 
reduction in the human resource base as a result of deaths or a diminishing of intellectual ability 
of victims thus perpetuating the poverty cycle (Huybregts et al., 2012). There is therefore the 
need for an urgent remedy if the cycle should be broken (Pelletier, 1995). 
 
2.2 Ready-to-use Therapeutic Foods (RUTFs) 
Malnutrition in children with its accompanying effects such as wasting, stunting, morbidity and 
mortality has for a long time been a public health issue worldwide (Van der Kam et al., 2012).  
Food security is one of the leading causes of malnutrition and hence makes children and other 
vulnerable groups targets of interest (Amsel and Hirsch, 2009).  
Interventions in the form of food aid programs have normally been centred on the provision of 
cereal legume blends distributed in areas facing food security problems but these have been 
reported to be too low in energy density for the problems of malnutrition (Karakochuks et al., 
2012; Bahwere, Sadler and Collins, 2009) as compared to a more energy dense formulation 
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intended for feeding of severe acute malnourished (SAM) patients (Manary, 2006). Ready-to-use 
therapeutic foods (RUTFs) belong to the group of lipid rich nutrition supplements (LNS). They 
are energy-dense, protein-rich fortified with micronutrient and formulated to have similar 
nutrients composition with UNICEP’s F-100 formula. RUTFs have been used at the 
rehabilitation stage of treating SAM and have been proven successful in the implementation of 
community based therapeutic care (CTC) (Briend and Collins, 2010; Ndekha et al., 2009). This 
concept was developed as an alternative to the in-patient therapeutic care system which has been 
relatively ineffective in curtailing the effect of SAM (Defourny et al., 2009), due to cost  
(Defourny et al., 2009), the availability of facilities (Beesabathuni and Natchu, 2010) and their 
effect on the number of people reached (Karakochuks et al., 2012) by these interventions.  
 
The first RUFT plumpy nutR by Nutriset is basically made up of peanuts, sugar, oil and milk but 
is quite expensive because it has to be imported. Also in the case of local production, milk 
powder which is imported is used as protein source, not making it any less expensive. 
Researchers have therefore been concentrating on the use of locally available raw material for a 
formulation that will provide nutrient composition very similar to the proven plumpy nutR 
(Karakochuks et al., 2012; Briend and Collins, 2010).  
 
2.3 The Concept of Food Supplementation 
Food supplementation or dietary supplementation is a practice in which people are provided with 
a product to complement their daily dietary intake with the intention to improve the nutritional 
value of their diet (http://www.fda.gov/AboutFDA/Transparency/Basics/ucm195635.htm). 
 Food supplementation is normally done in the form of food aids in areas of food shortages 
where nutritious foods such as cereal soy blend (CSB) are distributed to people (Nackers et al., 
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2010). In children with SAM this may come as RUTF whereas in those with moderate acute 
malnutrition (MAM) it has been described as ready to use supplementary food (RUSF) 
(Defourny et al, 2009). There have been a number of studies on the efficacy of RUSF in 
enhancing the rate of recovery from MAM and SAM or even preventing them. Defourny et al. 
(2009) found that adding child-targeted RUSF supplementation to a general food distribution 
resulted in increased haemoglobin status and linear growth. In a similar study Karakochuks et al. 
(2012), realized that the treatment of moderate acute malnutrition with RUSF resulted in higher 
recovery rates in children, despite the higher amount and energy content cereal soya blend 
(CSB).  RUTF supplementation has been found to improve the rate of weight gain and 
improvement of appetite, a shorter period of convalescence as well as a higher rate of recovery 
from cough in children after an episode of acute uncomplicated Plasmodium falciparum malaria 
(Van der Kam et al., 2012). In addition RUSF in a research to determine the efficacy of two 
different food supplements on body mass index (BMI) in wasted Malawian adults with HIV, 
supplementary feeding with fortified spread was proved (Ndekha et al., 2009) to result in a 
greater increase in BMI and lean body mass than feeding with corn-soy blend yet proving the 
fact that food supplementation can be employed to enhance the health status of sick adults. 
 
2.4 Recommended Dietary Allowances (RDAs) for Vulnerable Groups 
For normal growth and healthy life people need a well balanced diet having the nutrient 
composition that is needed to fully satisfy the metabolic requirements of the body. There are 
different requirement of nutrients for different groups of people with different characteristics 
age, gender, health status etc (Naicker, 2004). Child nutrition is vital for proper growth and 
development (Campos et al., 2010) and as the sick and aged they are considered vulnerable 
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because they have special nutritional requirement (RDAs) to achieve the required rate of growth 
for a period (Hermoso et al., 2010). When these needs are not met these people are exposed to 
malnutrition and its accompanying complications (Brown and Pollitt, 1996). Naicker, (2004) 
stated the RDA for nutrient intake of children between 0-12months and 12-24months (Table 2.1) 
and indicated based on a 24 hour dietary recall, that children from 0-24months in Umbumbulu 
(South Africa) met only about 70% and 75% of their protein and energy RDA respectively. 
Marin (2004) stated that there could be up to 33% increase in energy requirements hence 
frequent under nutrition cases in patients with cystic fibrosis. WHO has recommended that apart 
from proteins and vitamins and minerals the daily energy intake of HIV and AIDS patients 
should be increased by half the requirements of an active HIV negative adult of 2430 Kcal for 
male and 2170 kcal for female (Bahwere, Sadler and Collins, 2012). Among institutionalized old 
women in India, Reddy and Syeda (2011) found that the women’s carbohydrate and fat was not 
significantly different from RDAs whereas protein, fibre and micro nutrients were lower than 
their respective RDAs.  
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Table 2.1: RDAs of Children within the Age Range of 0-12 and 12-24 Months 
Nutrient RDA 
0-12months 12-24months 
Energy  2869 5440 
Proteins  13.5 14 
Vitamin C 30 40 
Vitamin E 3 6 
Riboflavin 0.4 0.8 
Niacin 5 9 
Vitamin B6 0.3 1 
Vitamin B12 0.3 0.7 
Phosphorus  300 800 
Magnesium  40 80 
Selenium  10 20 
                    Source: Naicker, 2004 
2.5    The Application of Enzymes in Food Processing 
Enzymes are often referred to as biological catalysts which enhance the rates of reactions in 
biological systems. They  are predominantly made up of proteins and are very specific in terms 
of the reaction they catalyze, the conditions required for optimum activity (temperature, pH and 
other chemical) etc. Enzymes are naturally occurring in biological organisms and are involved in 
different activities; for example they perform different functions in food crops from cultivation 
to post harvest periods in the supply chain of food (Tawil et al., 2012). In the food processing 
industry, various endogenous enzymes have been employed to enhance the quality of food, 
bioavailability of nutrients, increase energy density foods etc. (Songré-Ouattara, 2009).  
One way in which enzyme hydrolysis has been utilized in the food processing industry is in 
alcoholic beverage production. In beer production, endogenous cereal enzymes (amylases and 
proteases) developed during germination breakdown storage starches and proteins into soluble 
forms to be fermented by yeasts into alcohol (Sim and Berry 1996). In addition to malt enzymes, 
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various works have been done on isolating enzymes from micro-organisms. Amylases for 
instance have been isolated from various micro-organisms such as Bacillus licheniformis ATCC 
9945a (Nataˇsa Boˇzi et al.,2011 Sodhi et al., (2005) lactic acid bacteria (Songré-Ouattara, 
2009), Bacillus amyloliquefacien (Yook and Robyt, 2002) etc. Amylases have also been isolated 
from animals; an example of which is the porcine pancreas (Yook and Robyt, 2002). 
 
The primary concern of most researches using enzymes has been on the efficiency in yielding the 
desired end product. To validate the enzyme activity, appropriate substrates have been used to 
explore the conditions of optimum hydrolysis.  Usually the conditions of interest for enzyme 
activity have frequently been the temperature, pH, moisture content, the state of the substrate. 
 
2.5.1 Amylases in Food Processing 
Amylases are hydrolases that act on long chain polysaccharides such as starches to break them 
down into oligosaccharides and monosaccharides such as maltose and glucose by hydrolysing 
the α-1,4 and α-1,6 glycosidic linkages of the polysaccharides (Aiyer, 2005). Amylases can be 
obtained from animal, micro-organism and plant sources.  
 
Amylases are classified into endo-amylases or exo-amylases based on how the glycosidic bond is 
attacked. α-amylase is an endo-amylase attacking the randomly breaking the inner α-1, 4 
glycosidic linkages of the starch structure (Konsula and Liakopoulou-Kyriakides, 2004) while 
beta-amylase and gluco-amylase are examples of exo-enzymes which hydrolyse from the non-
reducing end of the chain producing short chain product (Gupta et al., 2003). Glucoamylases are 
debranching enzymes thus able to hydrolyse the α-1, 6 glycosidic linkages leading to complete 
hydrolysis of starch together with alpha and/beta amylases (Aiyer, 2005). These amylases have 
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been used in the production of dextrose, syrups, dextrins and their products also used as sources 
of sweetness in various food products (Aiyer, 2005). 
 
Alpha and beta amylases have been isolated from organisms of varying sources including plant 
and microbial and have been used in foods for various outcomes (Matsuo et al., 2012; Bozic et 
al., 2011; Sanni et al., 2002). Alpha and beta amylases have also been used to produce 
hydrolysates of starchy foods in order to improve upon their digestibility, nutritional quality and 
enhance their taste (L´opez, 2005; Traore, 2004). These enzymes have been used extensively in 
the brewing industry especially in the malting process in which they are used to produce 
fermentable sugars (Sim and Berry, 1996). 
  
The effects of processing conditions on enzyme hydrolysis have been investigated (Mousia et al., 
2004; Eneje, 2001; Warparla and Pandiella, 2000). Gebremariam et al. (2013) found that alpha 
and beta amylases were deactivated at temperatures higher than 50°C whilst Sim and Berry 
(1996) obtained 65°C for alpha amylase hydrolysis. Using different concentrations of α- amylase 
at different temperatures, Yook and Robyt  (2002) also found that the rate constant of α-amylase 
hydrolysis  increased  with temperature from 40 to 70°C with 500C giving the optimum degree of 
hydrolysis.  In a similar study, Sodhi et al., (2005) indicated that alpha amylase from Bacillus sp. 
PS-7 showed maximum activity at 60oC though activity was observed within a range of 40-80oC. 
The rate of enzyme activity depended on nature of the solid substrate, the moistening agent, level 
of moisture content, incubation temperature, presence or absence of surfactant, carbon, nitrogen, 
mineral, amino acid and vitamin supplements.  
 
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2.5.2 Cysteine Proteases 
Cysteine proteases also known as thiol proteases refer to a class of proteases in which the 
nucleophilic cysteine residue of the protease forms a covalent bond with the carbonyl group of 
the scissile peptide bond in substrates (Bromme, 2000). They can be derived from a wide range 
of organisms including plants, and even micro-organisms. The papain family proteases such as 
papain, bromelain and ficin are the most predominant cysteine proteases of plant sources and 
have various applications in the textile, pharmaceutical and food industries (González-Rábade et 
al., 2011). Papain has a popular use in the tenderisation of meat (Minh et al., 2012) and protein 
coagulation (Zhong, et al., 2005) whereas ficin is known (González-Rábade et al., 2011) to have 
casein hydrolysing properties thus ability to function as a milk clotting protease. These proteases 
also used for the treatment and reduction of many illnesses including tumours, diarrhoea, 
digestion enhancers among others (González-Rábade et al., 2011). 
Bromelain is a cysteine protease from the family of bromeliaceae obtained from pineapple plant 
mainly from the stem or fruit extract of pineapple (Crude bromelain). The crude extract is 
constituted by a complex mixture of different thiol-endopeptidases (González-Rábade et al., 
2011). Bromelain can be obtained from cooled pineapple pulp or juice as well as the stem though 
the stem bromelain for economic reason is preferred for commercial purposes since it is not 
consumed (Leite et al., 2012). Bromelain has been found to have numerous important health 
benefits apart from acting as a digestive enzyme; a property that is employed in food processing 
(Bharttacharyya, 2008). Bromelain has also been used extensively in foods for meat 
tenderization (Calkins and Sallivans, 2007), milk clotting, brewing and functional protein pre-
digestion (Corzo et al., 2012). It is believed to have a wide range of activities, and acts on 
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specific bonds in the subtrates and also has specific conditions under which it acts (González-
Rábade et al., 2011). 
 
Researches on the activity of bromelain indicated that the conditions required for optimum 
activity depends on the source of the enzyme and the conditions of incubation (Gautam et al., 
2010; Jutamongkon and Charoenrein, 2010). Tochi et al., (2008) stated that bromelain is stable 
over a wide range of pH range from 2-9. Work done by Corzo, (2012) showed that fruit 
bromelain showed optimum activity at 55 °C azoalbumin for azocasein, 59 °C for sodium 
caseinate and 37°C for haemoglobin all at different pHs. For stem bromelain, Gautam et al., 
(2010) indicated that the optimum temperature for activity was within 50°C-60°C. Yet 
Jutamongkon and Charoenrein, (2010) established from their work on the thermal stability of 
fruit bromelain that the enzyme is stable at 40°C, above which 40°C, loss of activity begins, and 
the rate of activity loss increasing with temperature.  
 
2.5.3 Plastein Reactions 
When a protein hydrolysate is incubated with a protease, the plastein reaction may occur in 
which small molecular polypeptides may undergo rearrangements, into new protein-like 
substance.   In the plastein reaction, peptide fragments of a protein hydrolysate are enzymatically 
joined through peptide bonds (Belitz, et al., 2009). Madzlan et al., (2006) reported that 
electrophoresis analysis of plastein synthesised by papain showed the presence of one major 
band with molecular weight of 2.8 KDalton while, synthesis with bromelain showed the presence 
of two bands with a molecular weight of less than 6.5 KDalton and 3.5 KDalton.  The 
mechanisms of the reaction have been suggested to involve condensation (Yamashita, et al., 
1976a), transpeptidation (Combes and Lozano, 1994) and physical forces (Andrews and 
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Alichanidis, 1990). These may occur separately or simultaneously (Stevenson et al., 1998). The 
plastein reaction has been applied in debittering protein hydrolysates (Stevenson et al., 1998), 
fortifying food proteins deficient in some essential amino acids (e.g., methionine), reducing the 
content of some undesirable amino acids (e.g., phenylalanine) for special dietetic applications 
(Yamashita et al., 1976b) or improving functional properties of food proteins (Andrews and 
Alichanidis, 1990).  
 
2.6 Rheological Behaviour of Fluids 
Rheologically fluids are categorized into (a) Newtonian flow in which shear rate (γ) is directly 
proportional to shear stress (σ) and (b) and non-newtonian which requires additional parameters 
in describing their flow behaviour because the relationship between γ and σ is inadequate in 
describing the relationship (Steffe, 1996). Non- Newtonian fluids could be shear thinning 
(pseudoplastic), shear thickening (dilatants), time dependent and time independent (Steffe,1996). 
A lot of fluid foods have been found to be non-Newtonian, pseudoplastic and the power law 
model has been used to describe their rheological behaviour. Examples of these include fruit 
juices (Dak et al., 2008), molasses (Kaur, 2008), etc. 
The Power Law Model 
σ = K (γ) n 
where; 
σ is the shear stress which is the force applied on the fluid for example the revolutions per 
minutes (RPM) applied for the determination of viscosity. 
 
γ is the shear strain; the effect of the shear stress on the viscosity of the fluid. 
K is the consistency index which is a measure of the apparent viscosity 
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n is the power law index; an indicator of the flow properties of the fluid. 
 
The consistency co-efficient of power law fluids has been found to increase with increase in the 
concentration of solids contents of fluid foods (Shamsudin et al., 2005; Zainal et al., 2000). In 
the same way gums such as dextran (Kaur, 2008) xanthan gum (Ahmed and Ramaswamy, 2004), 
carboxymethyl cellulose (CMC), carrageenan (Steffe, 1996) etc when they are used in food 
systems cause viscosity increments with increase in concentration which forms the basis for their 
use as thickeners and stabilizers (Kaur, 2009).  
 
2.7 Emulsifiers and Stabilizers 
Apart from safety and quality considerations in food processing, the structure and appearance of 
a food product is important for consumer acceptability. The structure and texture of food well 
depends on its composition which in turn has an effect on sensorial characteristics of the food 
(Dalgleish, 2006). Emulsions are a group of foods in which various components which otherwise 
are immiscible are made by dispersing one component in the other.  To facilitate the dispersion 
process the surface tension is reduced through the use of surfactants (as emulsifiers) and/or by 
increasing the interfacial viscosity (Charcosset, 1998). Examples of food emulsions include dairy 
products, salad dressing, etc.   
 
Emulsifiers are small surface active molecules which have both hydrophilic and hydrophobic 
sites, and they include compounds such as mono and diglycerides, polysorbates, phospholipids 
etc. Proteins such as those derived from milk and eggs are also frequently used as emulsifying 
agents in a number of food products.  
 
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The properties of a protein stabilized food emulsions such as dairy product and beverages depend 
both on the surfactant used and the nature of the continuous layer (Charcosset, 1998) meanwhile, 
the nature and composition of the interfacial layer is dependent on the interactions between the 
proteins and the surfactants  (Dickinson, 1992). For these reasons surface properties such as 
viscosity, surface adsorbed layer composition and interfacial tension which are responsible for 
emulsion stability could be changed as a result of an alteration of the protein-surfactant 
composition (Xu et al., 2005). This means that the composition of the emulsion should be taken 
into consideration when deciding the type of stabilizing agent used in any food system. 
Jayasundera et al., (2009), concluded that small amounts of surfactants do not enhance the 
stability of a protein stabilized emulsion.   
 
The choice of an emulsifying agent therefore depends greatly on the food system and the 
behaviour and mechanism of particular stabilizers and emulsifiers as well as the type of food, its 
components and the structure desired (Thakur et al., 2006). The stability of an emulsion is 
influenced by the size of the emulsion droplets; the smaller the droplets the smaller the 
interfacial tension and hence the higher the stability (Chung et al., 2013). Surfactants are 
generally known for reducing the interfacial tension and enhancing the formation of smaller 
droplets. The type and concentration of the surfactants used in emulsions therefore have a very 
significant effect on the droplet formation and stability.   
 
Stabilizers are hydrocolloids which are large molecular polymers predominantly polysaccharides 
that act in food products normally as gelling agents, thickening agents, stabilizing agents etc. 
They can also act in emulsions as stabilizing agents or to a lesser extent emulsifying agents (Dolz 
et al., 2008).  
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The ability of hydrocolloids to modify the properties of an emulsion depends on its molecular 
characteristics (molar mass, conformation, charge etc.) as well as their impact on the physico-
chemical properties of the food system (Philips and Williams, 2009). For example gum arabic is 
a highly compact, branched hydrocolloid with a protein covalently bound to it and is normally 
used as a stabilizer. However its effectiveness remains an issue since so much of it is needed and 
the effectiveness of an emulsifying agent is related to the amount of it that is required to create 
and stabilize an emulsion. 
 
The ability of food colloids to thicken aqueous solution is utilized in emulsions to prevent 
creaming and hence enhance stability when fat level is low and hence close packing of fat 
globules is impossible (Chung et al., 2013). The stabilizing action of hydrocolloids such as 
xanthan, carboxymethycellose and carrageenan in emulsions is normally attributed to the 
structuring, thickening and gelation of the aqueous continuous phase depending on their 
properties and concentration. The addition of hydrocolloids to emulsions can disturb stability 
through phase separation due to thermodynamic incompatibility with the emulsion droplets 
(Dalgleish, 2006).  
 
Emulsifiers and stabilizers have been used in various researchers for the attainment of emulsion 
stability. For instance, using a mixed system of Tween 80 and locust bean gum, Chung et al., 
(2013) found that beyond a certain concentration, the particle size of droplets increased with 
increased concentration of locust bean gum as the samples increased in consistency and 
pseudoplasticity. It has also been hypothesized (Aryanti, Hou and Williams, 2009) that the 
viscosity of the continuous phase (aqueous phase) in oil in water emulsions affect the droplets 
size and stability.  In their work (Hellerbach et al., 2013) proved that at a given concentration of 
emulsifier, an increase in the concentration of xanthan gum increases the viscosity of the 
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continuous phase. However there was an observed increase in the droplets size which was 
suspected to be a result of the shear thinning nature of xanthan.  William and Philips (2009) 
explained that the high viscosity at low concentration helps prevent sedimentation and the shear 
thinning enhance easy flow from bottle upon shaking. 
 
2.8 Causes of Food Spoilage. 
Food is obtained from biological organisms within which various biochemical reactions occur. 
The termination or continuation of these processes after the conversion of these living organisms 
into food could be a cause of spoilage. Processing techniques that are applied to food may 
enhance its quality and/or induce spoilage by changing some of their properties. Furthermore 
with storage depending on the nature of the food it gets exposed to other organisms and 
environmental conditions which could lead to their deterioration. Based on the factors involved 
food spoilage and/or deterioration could be classified as physical, chemical or biological. 
 
2.8.1 Physical 
The physical quality of food is related to attributes such as texture, colour, appearance, 
mouthfeel, consistency and therefore the deterioration of physical quality is the alteration or 
deviation of the characteristics of food from the consumers’ expectation. The effect of the heat 
treatment on sensory and nutritional attributes as a result of some chemical reactions during food 
processing can lead to changes in the physical properties of some foods. (Miri et al., 2008). 
Enzymatic and non enzymatic browning can lead to changes in colour due to the changes in 
natural pigments for example in foods containing green vegetables during thermal processing 
(Shin and Bhowmik, 1995). Change in the texture (softening) of foods such as fruits and 
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vegetables (Sun, Tang and Powers, 2007), change in viscosity of fluids such as milk products 
(Mussa and Ramaswamy, 1997) and fruit juices, alteration of the colour of milk, meat and fruit 
juices (Durance 1997), changes in organoleptic properties of foods as a result of the destruction 
of some nutrients (Awuah, Ramaswamy and Economides, 2007) may also be undesirable 
changes that can occur in foods. In food products in which structure and texture are vital such as 
in emulsions, the physical quality is paramount as small deviations in the form of flocculation, 
creaming, phase separation and ultimately serum separation are completely unacceptable (Philips 
and Williams, 2009). 
 
2.8.2 Chemical 
A number of chemical reactions occur in food during processing and storage which can lead to 
changes in physical characteristics and loss of important nutrients (Lindley, 1998). In thermally 
processed foods, thermal degradation reactions, such as maillard reactions, lipid oxidation etc., 
occur to a varying extent depending on the type of food and the prevailing conditions. Maillard 
reactions for instance between carbohydrates, free amino acids and proteins can lead to 
discolouration or browning of food (non-enzymatic browning). Enzymatic browning in fruits has 
been linked to the presence of oxygen, a reason for which they are de-aerated before 
pasteurization (Awuah et al., 2007). Also vitamin degradation of heat treated food is a very 
significant phenomenon in thermal processing and has been used extensively in optimization of 
heat processes as an indicator of quality retention (Leskova, 2006; Abakarov and Nunez, 2013). 
Loss of vitamins is dependent on a number of factors such as oxygen, heat and processing 
conditions as well as on the constituents and formulation (Awuah et al., 2007). Additionally, 
exposure of proteins to heat leads to the destruction of most of the tertiary and quaternary 
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structure. This leads to changes in the protein conformation which in most cases leads to an 
increased digestibility as a result of the exposure of peptide bonds which may be the active sites 
of digestive enzymes (Thomas et al., 2007).  
 
Lipid oxidation is a very common cause of food deterioration and contributes to the development 
of undesirable flavours in foods that are rich in fats or oils.  The rancidity development in high 
lipid foods is due to the formation of numerous aliphatic aldehydes, and alcohols, which are 
expressed as off-flavours (Farhoosh et al., 2009). For example, peanuts contain approximately 
50–55% oil with 30% of the oil being linoleic acid, which becomes susceptible to development 
of rancid and off-flavours through lipid oxidation (Grosso et al., 2008). The rate of oxidation is 
affected by factors such as water activity, storage conditions; temperature, light, and mineral 
contaminant etc.  
 
2.8.3 Biological 
Biological substances like enzymes and micro-organisms are very important in food 
deterioration and spoilage. This is because most enzymes are present in food in their natural form 
and micro-organisms are present in natural bodies such as soil, water, air etc, with which food 
stuffs are in constant contact. Apart from microbial spoilage of fresh and high moisture foods, 
food crops undergo changes induced by respiration, transpiration and other metabolic activities, 
mediated by enzymes (Paull and Chen, 1997). Also storage related parameters such as water 
activity, temperature, oxygen content, light etc can also have adverse effect on the keeping 
quality of some foods (Ahvenainen, 1996). 
 
Microbial spoilage and pathogenicity have been the major factors in food processing 
considerations and have been the goal of most food processing techniques. Most enzymes in 
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foods are destroyed at temperatures lower than those needed for microbial sterility (Negi and. 
Roy, 2000). Enzymes such as polymethylesterase, polyphenol oxidase, galacturonase and 
peroxidase are normally present in fruits and are inactivated using pasteurization temperatures 
which are generally lower than 100oC (Awuah et al.,   2007).  
 
Lipolytic micro-organisms can also cause lipid hydrolysis by the release of extracellular lipolytic 
enzymes that can be active even after the destruction of the cells that produced them.  These 
microbial lipases degrade lipids in foods resulting in the production of undesirable characteristics 
such as excessive foaming during churning in butter making and the development of rancidity in 
the finished product and the production off-flavours and rancidity in pasteurized milk 
(Ledenbach and Marshall, 2009). In addition some psychrotropic bacteria can produce 
proteinases which have been found to cause off-flavours, for example bitter flavours resulting 
from the production of bitter peptides (Ledenbach and Marshall, 2009).  
 
2.9 Thermal Processing 
The use of heat in treating food is a very old and common practice often intended to enhance the 
quality of food by destroying micro-organisms, reducing or removing anti-nutritional substances, 
enhance the digestibility, availability of nutrients, the flavour of foods (Wandsnider, 1997; De 
Corcuera et al, 2003).  Food preservation is the main aim of thermal processing and is mostly 
based on the control of micro-organisms which are destroyed by heat based on their nature, 
environmental conditions and consequently their response to the heat treatment. On this basis 
there are different techniques in thermal processing including blanching, pasteurization and 
sterilization that can be applied based on the purpose of the thermal treatment. 
 
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2.9.1    Microbial Destruction Kinetics 
Attaining an optimum thermal process requires that the heat resistance of the micro-organism of 
interest at a given temperature for a given time is known (Miri et al., 2008). Microbial 
destruction by lethal agents such as heat has been reported to be a first order reaction and can be 
obtained from the survivors curve expressed as: 
 
 Loge (N/NO) = –kt where 
N = number of surviving microorganisms after a treatment with lethal agent for time t (min),  
NO = initial number of microorganisms  
k = reaction rate constant in min–1 (Mussa and Ramaswamy, 1997). 
 
The treatment time (constant lethal agent) that will destroy 90% of the existing microbial 
population is normally expressed in thermal processing as the decimal reduction time (D value) 
and can be obtained as the negative reciprocal slope of the log10 (NO/N) vs. time curve and is 
therefore reciprocally related to k as; D = 2.303/k. The z value which measures the sensitivity of 
the organism to change in temperature is defined as the temperature required to cause a change in 
D-value by a factor of 10 and can be obtained from a plot of the log of D-value against 
temperature (Mussa and Ramaswamy, 1997). Depending on the target micro-organism and food 
formulation there are different D and z values for different products. Heat labile micro-organisms 
generally have lower D and z values than heat resistant micro-organisms. For this reason the 
thermal process of any food system is set using the most heat resistant micro-organisms present 
(Silva and Gibbs, 2010). 
 
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2.9.2 Blanching  
Blanching is a form of heat treatment  normally applied to fruits and vegetables with the 
intention of deactivating enzymes, modifying texture, flavour (Kidmose and Martens, 1999) 
colour (Genovese et al.,1997) and in some cases removing trapped air (Reyes De Corcuera, et 
al., 2004). Blanching can also be used in destroying surface microorganisms or reducing 
microbial load in food (Forsythe, 2011). 
 
In spite of the need for utilisation of legumes such as soya beans and cowpeas as sources of 
protein, they contain anti-nutritional component such as tannins, trypsin inhibitors and Phytates 
that have to be removed to enhance the nutritional quality of the proteins (Wang et al., 1997). 
Because these anti-nutritional factors are heat labile, they can be removed by traditional 
preparation procedures such as cooking and blanching that also allows for the absorption of 
water and heat to enhance digestibility of the legumes (Gowen et al., 2007). Blanching of 
legumes also stops the action of enzymes as well as leads to a reduction in the microbial load of 
the food (Gowen et al., 2007).  
 
Being a thermal process, blanching can have negative effects on the desirable characteristics of 
blanched foods. For instance blanching is said (Prestamo, Fuster and Risueno, 1998) to have an 
effect on the texture of treated carrots intended for frozen storage, which they attributed to 
changes in pectic substances when exposed to heat. Blanching of some fruits and vegetables may 
also lead to loss of nutritional substances such as vitamins (Kidmose and Martens, 1999) colour 
and (Negi and. Roy, 2000). Similarly blanching of legumes can lead to the loss of important 
nutrients such as vitamins, sugars etc (song et al., 2003). 
 
However some methods of blanching lead to a better retention of this quality attributes. 
Microwave blanching has been proved to result in better texture of carrots as a result of a lower 
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extent of cell destruction and the removal of water leading to an increase in mechanical strength 
and also that steam blanching and microwave blanching are better in terms of nutrients retention 
since there is no tendency of nutrients leaching into the water as in the case of water blanching 
(Kidmose and Martens, 1999). Peroxidase inactivation which is said to occur faster at higher 
temperature is often used to assess the efficiency of blanching (Negi and. Roy, 2000) which is 
normally done at temperature from 90oc to 110oc (Forsythe, 2011) although the optimum time 
and temperature appropriate for a particular food item depends on the quality expectation of the 
end product (Reyes De Corcuera, Cavalieri and Powers, 2004). The negative effects of blanching 
can be reduced by optimising the thermal process (Shi et al., 2004) or by using other alternative 
methods of blanching such as steam blanching instead of water blanching (Wang et al., 1997). 
 
2.9.3 Pasteurisation 
Pasteurisation is a food preservation method aimed at reducing food micro-organisms to levels 
that will make the food safe to the consumer in the state in which it is presented, for a specified 
time within which it should be consumed (Kalchayanand et al., 1998). Traditionally 
pasteurisation is a thermal process that is based on the elimination of pathogenic organisms and 
reducing spoilage organisms to acceptable levels. During pasteurisation temperatures are 
controlled such that the effect on microbial destruction is obtained and yet the loss of desirable 
properties of the food for instance the colour and flavour of milk is minimised (Franco et al., 
2008).  
 
The process of pasteurisation is widely applied to milk and milk products and the effectiveness 
of the pasteurisation is normally determined by the inactivation of the enzyme alkaline 
phosphatase or peroxidases (Mussa and Ramaswamy, 1997) which can be destroyed by 
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temperatures within 62°C and 80°C depending on the time used. Meat and meat and meat 
products are also pasteurised at similar temperature to destroy surface micro-organisms. In fruits 
juices such as orange juice the target of pasteurisation is the destruction of the enzyme pectin 
methylesterase which require higher heat of about 95-98°C (Vervoort et al., 2011).  
 
Generally due to the low temperatures involved in pasteurisation (65-95°C), products obtained 
after pasteurisation are not stable other means of preservation such as refrigeration, modified 
atmosphere packaging or storage, vacuum packaging, addition of antimicrobial additives etc 
must be employed to enhance shelf stability (Silva and Gibbs, 2010).  
 
Traditionally, pasteurisation can be classified either as low temperature-long time (63.5°C for 
30min) or high temperature-short time (71.7 for 15s) pasteurisation (Van Brandt et al., 2011). 
Apart from these however, ultra high temperature pasteurization (UHT) is an improvement upon 
the high temperature short time (HTST) treatment, where a more sever temperature is used at an 
extremely short time. A temperature range of 135-150°C (for 1-10s) has been used in milk 
processing to yield products with extended shelf life (Heilig et al., 2008). Additionally, 
temperatures around 145°C for as low as 25milli seconds have been used in surface 
pasteurisation of meat and poultry to reduce pathogenic microbes on the surfaces (Morgan et al., 
1996; Cygnarowicz-Provost et al., 1994). UHT pasteurisation (though occurs at a higher 
temperature) has been considered a relatively milder heat treatment intended for microbial 
sterility whilst minimising the effects of heat on the properties of foods that determine their 
quality (Newstead et al., 2006). 
 
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2.9.4 Sterilisation 
The primary aim of thermal sterilisation has been the achievement commercial sterility: a state in 
which most of the microorganisms are destroyed and yet nutritive and organoleptic properties are 
as much as possible maintained (Awuah et al., 2007). This is because an attempt to render food 
completely free of micro-organisms will render food unsuitable for consumption because it will 
not meet the consumers’ expectation of quality (Simpson et al., 2008).  A number of food 
processing techniques intended to preserve the more natural colour and flavour, and yet assure 
safer, more convenient, more nutritious foods to the consumer are available. These include high-
pressure processing ( Mussa and Ramaswamy,1997), pulsed electric field (Zhang, Barbosa-
Canovas and Swanson, 1995), ohmic heating, radio frequency, microwave (Sun, Tang and 
Powers, 2007), pulsed light , ionizing radiation, ultra violet light, ozone treatment (Ozen and 
Floros, 2001), soft electron processor (Baba et al., 2004).  
 
Like all the other processing techniques the success of a thermal process depends on a number of 
factors. Different food systems require different temperatures and times at which they attain 
sterility which depend on factors such as the composition of the food, the processing technique 
used, the type and size of container (Kannan and Sandaka, 2008; Abdul Ghani et al, 2001). For 
instance solid foods are heated by conduction whilst liquids heat by natural convection and a 
mixture of solids and liquids mix by both mechanisms (Abdul Ghani and Farid, 2006), yet some 
processing techniques are more suited to liquid foods of low viscosity whilst others will be best 
for highly viscous liquids (Awuah et al.,  2007).  In addition, foods that contain heat labile 
nutrients or other quality parameters are less thermally processed than those that are rather 
enhanced or less affected by the application of heat (Choi et al., 2006). This is also because the 
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heat resistance of micro-organisms changes in different environment due to different factors 
including pH, water activity, chemical composition etc (Miri et al., 2008). 
 
Retorting has been used to refer to thermal sterilization and has gained a lot of research attention 
in enhancing the safety and quality of sterilized food. The type of retort used has been implicated 
in the efficiency of sterilization due to its effects on heat penetration, lethality and the loss of 
food quality (Berry and Bradshaw, 1982). Agitated retorts have been found to be better in terms 
of effectiveness and efficiency of sterilization as the time and temperature of microbial 
destruction is concerned product quality retention for that matter (Ansar Ali et al., 2006).    
 
Many researchers have worked on thermal sterilisation and various process parameters have been 
established based on the properties of the food and especially the organisms relevant to food 
safety and public health concern. For low acid canned foods the sterilization value is based on 
the destruction of the spores of Clostridium botulinum. The spores of Clostridium botulinum 
which is an anaerobic heat resistant organism of public health concern have been found not to 
germinate in a pH below 4.8 based on which a pH of 4.6 has been set as the standard for acidity 
in foods (Awuah et al., 2007). Generally a D-value of 0.21 min. at 121oc has been established 
based on the 12D reduction required for minimum sterility, which has become a basis for the 
calculation of the integrated lethality value Fo.  The Fo value for minimum sterility has been 
calculated to be 2.52min based on the spores of clostridium (Forsythe, 2011).  
 
2.9.5 Quality Deterioration of Food during Thermal Processing 
Quality concerns during thermal processing are mostly on the change in physico-chemical 
properties of foods. The application of heat has deteriorative effects on food quality due to the 
potential loss of nutrients, change in colour, flavour, texture and consistency (Sun et al., 2007). 
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Just as in microbial destruction, the sensitivity of these desirable characteristics to heat follows 
the first order reaction kinetics (Durance, 1997). For instance Shin and Bhowmik (1995) used the 
thermal reduction of the colour in green pea puree as the indicator of the extent of heat damage 
to quality during thermal processing obtained 31.10 min and 42.87 as D and z values 
respectively based on (-La/b) for their product. Simpson et al., (2008), indicated that temperature 
uniformity is very vital to quality retention in thermal processing and hence efforts should be 
made to integrate temperature over the volume of container and time. Although both microbial 
destruction kinetics and quality deterioration kinetics of food are first order reactions, the 
increase of the rate of microbial destruction with increase in temperature is higher than that of 
loss of quality; a reason for the usefulness of high temperature short time operations in quality 
retention (Durance, 1997). This has been confirmed in the degradation rates of nutrients, colour 
and texture of asparagus which were found (Sun et al., 2007) to increase at a lower rate than 
microbial spores at 121oC with time. Based on that, the Optimum temperature of sterilization 
with minimum quality loss has been found to be a function of the z of the quality attribute and 
the specific location of the quality loss within the container (Durance, 1997). 
 
2.10   Food Spoilage Due to Lipid Hydrolysis and Oxidation 
Oily foods are normally unstable mainly due to the presence of triacylglycerides which are 
hydrolysed in the presence of water to form free fatty acids resulting in the hydrolytic rancidity 
of the fatty foods. The free fatty acids if unsaturated are prone to oxidation, leading to the 
production of short chain acids and carbonyl compounds that cause the undesirable flavours 
characteristic of oxidative rancidity. 
 
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2.10.1 Hydrolytic Rancidity 
Hydrolytic rancidity is a fat degradation reaction in which the fatty acids of the triglyceride 
bonds are cleaved to release the free fatty acids with their characteristic odours. This occurs 
either through the action of lipase enzymes, or very high temperatures. Foods containing high 
levels of polyunsaturated fatty acids such as linoleic acid and linolenic acid have been found 
(Sewald and DeVries, 2012) to be much more susceptible to rancidity than moderately saturated 
compounds such as oleic acid because they can form many  different off-flavour molecules (Cesa 
et al., 2012). Apart from those naturally present in food some lipolytic micro-organisms are 
known (Ledenbach and Marshall, 2009) to produce microbial lipases that cause rancidity in food 
during storage. Because the presence of free fatty acids (FFA) in oily products exposure to high 
storage temperatures can cause off-flavours and it is important to reduce the rate of deterioration 
of oil due to rancidity (Chotimarkorn and Silalai, 2008) by maintaining low levels of FFAs 
throughout storage. 
 
2.10.2   Oxidative Rancidity 
The enzymes peroxidase and lipoxygenase act on the double bonds of free fatty acids and begin a 
chain of reactions with various undesirable products reducing the quality of food and is one of 
the routes of oxidation in fats. Another route which the oxidation reaction could take is the free 
radical route which requires the presence of a catalyst such as light, high energy radiation or the 
presence of metal ions which is propagated by the formation of free radicals (Sewald and 
DeVries, 2012). The photo-oxidation route is the third one and is driven by the absorption of 
light and oxygen. The oxidation process brings about intermediate products such as 
hydroperoxides which are further broken down to form low molecular weight products such as 
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alcohols, aldehydes, and ketones, ultimately leading to oxidative rancidity (Farhoosh et al., 
2009).    
 
Oxidation reactions take place in the presence of light, heat, energy etc. Beltran et al., (2003) 
found that, oxidation of minced chicken depended on the amount of pressure treatment. Also 
working on Jameed, a milk product, Al-Isma et al., (2007), found that both oxidation and 
hydrolytic rancidity increased with air drying and also with storage at room temperature. Similar 
results were obtained by Nieto et al. (2011) on their work on cooked lamb as they realized that 
volatiles from lipid oxidation increased with increase storage time and the exposure for retail.  
 
2.11 Shelf-Life Testing 
      The shelf life of processed foods is very vital for quality retention and economic 
considerations of the processed foods. This is because the aim of food processor is to deliver safe 
foods that retain their quality over a stipulated period of time which is termed as the shelf-life of 
the food (Fu and Labuza 1991). The shelf-life of a particular food product depends on factors 
such as product formulation, processing technique used, storage and distribution (Kilcast and 
Subramaniam, 2000). The shelf-life of a product may be determined by the growth of micro-
organisms with time based on safety concerns whereas in other cases it may be the loss of quality 
which have no harmful effects but indicates that the food no longer conforms to its consumers’ 
acceptability standards (NZFSA, 2005). Shelf-life studies require knowledge of the quality 
reduction parameters which could be microbial, chemical or physical and shelf life studies could 
be indirect or direct.  
 
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2.11.1 Indirect Methods 
Indirect methods of shelf-life estimation can be done by the use of accelerated shelf-life studies 
(ASLS) involving the use of elevated temperatures to increase the rate of deterioration of food 
with the intention of hastening spoilage. The rate of spoilage at actual storage temperature can be 
deduced by extrapolating (NZFSA, 2005). To do this the principles of predictive modelling using 
appropriate models such as the Arrhenius theorem, Q10 concept or (FSAI, 2011) may be used. 
2.11.1.1 Predictive Modelling  
Predictive modelling is a means of estimation of the shelf-life of a product based on changes in 
the various factors affecting spoilage and their interaction with each other (Kilcast and 
Subramaniam, 2000). The deterioration can be due to the effects environmental conditions such 
as temperature, water activity, presence or absence of oxygen and their resultant changes in 
biochemical reactions and physiological activities (Ahvenainen, 1996). Predictive modelling is 
used widely to study microbial behaviour in specific environment, their control in particular food 
systems and the estimation of shelf life of foods (Podolak et al., 2010). The use of microbial 
models in the prediction of shelf life is common in the fish and fish product (Taoukis et al., 
1999), minimally processed fruits and vegetables (Corbo et al., 2006), milk and milk products 
(Duyvesteyn et al., 2001) where microbial spoilage is the main mode of deterioration. In the use 
of microbial growth models in the prediction of shelf life, the specific spoilage organisms which 
are normally the most important organisms to the spoilage of the food are used. This is done by 
isolating the most predominant of the micro flora present in natural storage conditions of the 
product and studying its growth pattern in model substrates through which the shelf life is 
predicted (Dalgaard, 1995). The obtained shelf life is normally validated by the use of real data 
from normal storage conditions or information derived from sensory data (Dalgaard et al., 1997). 
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Shelf life estimation based on Predictive models can be done by evaluating the effects of the 
mechanism of spoilage such as temperature on spoilage using such as the Arrhenius equation, 
Q10 concept and other kinetic models depending on the mechanism(Taoukis et al., 1999; 
Dalgaard, 1995). 
2.11.1.2 Application of Q10 Concept in Predicting Shelf Life 
The Q10 concept of shelf life prediction is based on the increase in the rate of reaction 
corresponding to a 10° increase in the temperature (Berges et al., 2002). Normally the shelf life 
estimation based on a criteria which could be sensory, lipid stability, microbial degradation etc 
(Dalgaard and Jørgensen, 2002). Based on any such criteria Q10 can be calculated as the shelf life 
at T°C/shelf life at T+10°C and the figure is used to predict the shelf life of the product (Al-
Kadamany et al., 2002). The Q10 model has been applied in modelling microbial behaviour 
(Davidson et al., 2006), respiration of rate in plants (Gifford, 2003) and other biological and 
biochemical phenomena. In food processing, the Q10 concept can be used in modelling the 
temperature sensitivity of food spoilage reactions to the mechanisms of spoilage such as 
temperature and water activity.  For instance Evranuz, (1993) calculated the Q10 value of 
unblanched salted and roasted peanuts based on the rate of peroxidation. The shelf life of Hass 
avocado was also predicted at 7 and 25°C based on Q10 of data obtained at 10 and 20°C (Perez et 
al., 2004). Additionally based on the effect of temperature, the Q10 of guava fruits was calculated 
as a measure of the rate of change in respiration and ripening behaviour to help in optimising 
storage and retail conditions and reduce quality losses (Bron et al., 2005). The Q10 concept can 
be related to the Arrhenius principle by the equation, 
 Q10 = exp [10 Ea/(R T (T+10)]  
 where the Q10 depends on the Ea and the absolute temperature (Fu and Labuza, 1997). 
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 2.11.1.3 Application of the Arrhenius Theorem in Predicting Product Shelf Life 
The Arrhenius concept is used to model the temperature dependence of deterioration of zero 
order and first order reaction such as microbial activity, lipid oxidation, etc (Fu and Labuza, 
1997). The Arrhenius equation is given as: 
 
K = K0 e 
–Ea/RT    or 
ln (K) = -Ea/R・1/T + ln (Ea)  
Where: 
K: Rate of reaction constant 
K0: is the pre-exponential factor 
Ea: the activation energy in cal/mol 
R: the gas constant in cal/mol 
T: the temperature in oK  
A plot of shelf-life (lnK) against temperature (-Ea/R・1/T) gives a straight line; the slope 
indicating temperature sensitivity of the reactions involved. The steeper the slope the smaller the 
change in temperature needed to cause significant changes in deterioration (Fu and labuza, 
1997). Based on these the predictions shelf life of the product at different temperatures can be 
made (Petrou et al., 2002).  
 
2.12 Conclusion 
Malnutrition remains a problem in Africa including Ghana. Food supplementation has been 
identified as one of the effective ways of reducing malnutrition and can be a tool for improving 
food security especially for vulnerable groups. Food supplements such as ready to use 
supplementary foods (RUSF) provide (macro and micro-) nutrients calculated to meet minimum 
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requirements of the target group’s daily requirements. The formulation and processing of such 
products require an understanding of the functionality of the ingredients, their degradation 
kinetics during processing and storage, as well as the nutritional requirements of the target group 
for which the food is intended.  In the processing of such supplementary foods the calorie 
content, bioavailability and absorption rates of the nutrients are usually of great consideration. 
Consequently the application of enzymes such as amylases and proteases has been used to 
enhance the nutritional quality of various supplementary foods.  
The acceptability of supplementary foods by the target consumers is vital to the achievement of 
the purpose for which they are intended.  In fluid supplementary foods the flow properties as 
well as emulsion stability are also important quality criteria, and are modified by the application 
of appropriate stabilizers and emulsifiers. Apart from consumer acceptability of the food, the 
keeping quality of the food is equally important, especially for its application in wide variations 
of space and time. It is important therefore, to determine the period within which the food can 
retain its quality (shelf life) taking into consideration the factors that can contribute to the loss of 
quality.  
 
  
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CHAPTER THREE 
 
3.0  MATERIAL AND METHODS 
3.1 Raw Materials 
Groundnuts (Arachis hypogea) a cultivar locally known as Chinese, a locally available long grain 
rice (Uncle Sam) (Oryza sativa L.) and cowpeas (Vigna unguilata) were purchased from a local 
market (Madina market). Sugar used as sweetener was also purchased from a shop. Bromelain 
was obtained from herbal extract plus, (USA) and amylase was obtained from DSM (South 
Africa). 
 
3.2 Sample Preparation 
Groundnuts and cowpeas were well sorted to remove broken, pecks and discoloured grains, 
before passing through the various units of operations of the process.  
 
3.2.1 Roasting  
Peanuts were roasted at 150o C for 45minutes in an electric oven (to about L50 value in colour) 
to enhance flavour and to inactivate the enzymes. 
 
3.2.2 Soaking 
Cowpeas were decorticated using the method described by Sefa-Dedeh, (1978) and then soaked 
in 1% sodium bicarbonate (NaHCO3) for 16 hours. This was done in order to soften the 
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ingredients and also reduce the beany flavour and yet prevent putrefaction from occurring in the 
process.  
 
3.2.3 Cooking  
Cowpeas and rice where cooked by boiling. Rice was boiled for 30minutes while it took 
180minutes to boil decorticated cowpeas. 
 
3.2.4  Homogenisation  
The roasted peanuts, cooked cowpeas and rice were mixed in the ratio of 3:3:4 (on dry matter 
bases) and co-milled in a colloid mill (Machine No. 84492, Premier colloid mills limited, 
Walton-on Thame, Surrey, England) with sufficient added water to obtain a homogenized 
mixture containing 20% solids. The product was warmed to about 40°C and amylase enzyme 
added. The product was stood for about 1 hour at 40°C to allow time for the maximum 
hydrolysis of the starches by amylase enzymes. Afterwards bromelain enzymes (proteases) were 
also added to the product and left to stand for 3 hours to enable hydrolysis of the proteins in the 
product. 
 
3.2.5 Thermal Processing 
The product was heated in an open jacketed kettle and maintained at 95°C for 15 minutes to 
inactivate the enzymes. It was hot-filled into 330mL bottles, capped and pasteurized by 
immersing in boiling water for 10minute, 20minute or 30minute. Some of the bottled product 
was sterilized by retorting at 119oC for 10minutes, and then left to cool at room temperature.  
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3.3 Process Flow Chart for RUSF Production  
 
 
 
 
 
 
  
 
 
 
 
 
 
 
Figure 3.1: Process Flow Chart for RUSF Production 
Add Water 
 
Cooked Rice 
 
0.5% of Amylase 
 
Bicarbonate 
treated, 
decorticated, and 
cooked cowpeas 
Hydrolyse at 45oc for 60min 
0.5% of Bromelain 
 
Hydrolyse at 37oc for 60min 
Protein and starch hydrolysate 
Add emulsifier, 
stabilizers, sugar 
and vitamin-
mineral mixture 
 
Heat 100oc for 15min 
Drinkable 
RUSF 
Sterilize 
RUSF 
Fill and Seal 
Raw peanuts 
Roasting (150oC) for 45mins 
Dehulling 
Co-milling 
Co-milled peanuts and cowpeas 
 
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3.4 Chemical Determinations 
3.4.1 Proximate Analysis 
Total solids and Ash were analyzed on all the samples using AOAC methods 925.09 and 923.03 
respectively. Crude fibre was also determined using standard procedures method 962.09 (AOAC, 
1990). To determine the moisture content of the liquid sample, the samples were kept in the oven 
at a temperature of 50oC for about 10hours and then increased to 105oC for two hours according 
to method 925, AOAC (2005) with modifications. Carbohydrate was determined by difference. 
Protein was analysed using a conversion factor of 6.25 using kjeldahl method; 955.04, AOAC 
(2005). Fat was determined using the Werner-Schmid process in which the sample was heated 
with 6M HCL in a ratio 1:1 to dissolve the protein and the fat settled as a layer on the top of the 
acid. The fat was extracted by shaking the mixture with diethyl ether which was evaporated and 
the fat calculated as % fat based on the weight taken (about 5g in this work) (Pearson, 1976).  
 
3.4.2 Mineral Analysis 
3.4.2.1  Determination of Na and K 
Na and K were determined using Spectra AA 220FS flame photometer (Varian Co., Mulgrave, 
Australia) with an acetylene flame following the manufacturer’s procedure in the manual. Na and 
K standards were prepared from a stock standard of 1000µg/ml using deionised water which was 
also used as blank.  
 
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3.4.2.2   Determination of Phosphorus 
P was determined spectrophotometrically as stated by Bray and Kurtz (1945). One (1) ml of 
filtered sample was added to 30ml of deionised water. A drop of P-nitrophenol and Ammonium 
solution was added until solution turned light yellow. A blue colour was developed by adding 
8ml of L-ascorbic acid. The solution in the 50ml volumetric flask was made to the mark using 
deionised water and absorbance was read at 712nm on a Shimadzu UV-120-02 
spectrophotometer. Percentage Phosphorus is calculated as: 
% P = Spectrophotometer reading x vol. of extract x 100 
                                                              Aliquot           106 
 
3.4.2.3  Determination of Ca, Cr, Cu, Fe, Mg, Mn, Zn, Ni and Pb 
Atomic absorption spectroscopy (AAS) was used to determine the concentrations of Ca, Cr, Cu, 
Fe, Mg, Mn, Zn, Ni and Pb. The AAS (Model: PERKIN ELMER Analyst 400) was equipped 
with the winlab 32 software to select a wavelength, slit, current and the mineral of interest. The 
air-acetylene (10:2.5) flame at a temperature of about 23000C was used for igniting the aspirated 
sample standards were prepared from commercial stock standards of 1000µg/ml of each mineral 
using deionised water. The blank (deionised water) and standard solutions were aspirated by the 
machine to create a calibration curve. Concentration of the each mineral was given as ppm and 
converted to mg/100ml. 
 
 
 
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3.5 Determination of the Degree of Hydrolysis of the Macromolecule by Enzymes 
3.5.1 Starch 
The degree of starch hydrolysis was determined by monitoring reducing sugars levels. Luff 
schoorl method of determining reducing sugars (Egan et al. 1981). Twenty five (25) ml of 
copper reagent (Copper II pentahydrate, Citric acid and Sodium carbonate) was measured into 
25ml of the sample and refluxed for 10minutes. It was cooled and titrated with 0.1N Sodium 
thiosulphate after adding 3.0 g of potassium iodide and 20 ml of 6N HCL. 1.0 ml starch indicator 
was added, and titration continued until the blue colour changed to give a white precipitate of 
cuprous iodide. The reducing sugars were estimated by calculating from a standard based on the 
amount of thiosulphate used (titre value). 
 
3.5.2 Protein Hydrolysis by (Bromelain) Protease Enzymes 
3.5.2.1 Preparation of Samples 
Fifty (50) ml of the homogenized mixture of rice peanuts and cowpeas were taken and 0.5%, 1% 
and 1.5% commercial bromelain was added to them and then incubated for 1hr, 2hr and 3hrs 
each at 37oc, 40oc and 43oc. The samples were then evaluated for the degree of hydrolysis by 
monitoring the production of –NH2 using 2, 4, 6-trinitrobenzenesulphonic acid (TNBSA). The 
process was assessed qualitatively using sodium dodecyl sulphate-poly acrylamide gel 
electrophoresis (SDS-PAGE). 
 
 
 
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3.5.2.2  Trinitrobenzene Sulphonic Acid (TNBSA) Method 
 The samples were reacted with TNBSA to produce a chromogenic derivative that was measured 
quantitatively at 340nm. The standard curve was generated using L-leucine concentration 
between 0.5 and 1. 
 
 
Figure 3.2 Reaction of TNBSA with amino groups 
 
3.5.2.3 SDS-PAGE  
Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) was done according 
to the method described by Laemmli, (1970) on the bromelain hydrolyzed and non hydrolyzed 
products. Proteins were extracted from the sample using ammonium sulphate precipitation. In the 
process the samples were centrifuged at14500 rev/min and the filtrate that contains the proteins 
was collected to which ammonium sulphate was added to 40% saturation. The precipitated 
proteins were collected after centrifugation at 10000 rev/min. More ammonium sulphate was 
added to the supernatant to make 70% saturated to obtain more proteins. The proteins collected 
at both stages were pooled and dissolved together with a solution containing 50mM pyridine, 10 
mM thiourea, 1% SDS and  5mM phenylmethanesulphonylflouride. The protein solution was 
then diluted in a ratio 1:2 respectively with the sample buffer tris buffer (pH 6.8), 10% SDS, 
glycerol, dithiotrietol and bromophenol blue. 15µl of this mixture sample was loaded into the 
wells and 10µl of the molecular weight marker was also loaded as a standard (low molecular 
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weight standard). The samples were run with the Bio RadR mini protean II. The running or 
electrode buffer was diluted ten-fold and used to fill the space in between the plates in the tank 
and the samples were run at 200 volts until the blue marker dye reached the bottom of the gel.  
 
3.6 Effect of Particle Size Distribution on Product Separation. 
The mixture of roasted peanuts, cooked rice and cowpeas was passed through the colloid mill 
(Machine No. 84492, Premier colloid mills limited, Walton-on Thame, Surrey, England). The 
milled mixture had particle size range between 500µ-75µ.  Different particle size products were 
obtained by passing the mixture through the sieves (500µ, 300µ and 106µ) thus yielding 
products with particle sizes ≤ 500µ, 300µ and 106µ respectively. The filtrates were poured into a 
well graduated 100ml measuring cylinder and their sedimentation rates monitored at the intervals 
of 3, 6, 12, 24, 48, 72 and 96 hours each. The rate of sedimentation was estimated as the 
difference between the previous level of clear solution and the level at the time of inspection. 
 
3.7   Effects of Stabilizers on Physical Stability and Flow Behaviour of Product.  
Three commercially available gums: carboxymethylcellulose (CMC), Xanthan gum and 
carrageenan were each incorporated into the product and passed through the colloid mill. The 
flow behaviour (i.e. shear rate shear stress relationships) of the products were characterized at 
room temperature (25°C).  The rate of product separation was determined with time by 
monitoring the volume of the clear solution on top of the product. Three separate levels of each 
stabilizer (0.05%, 0.075% and 0.1%) were used. As was done for the particle size, the readings 
were taken at time intervals of 3, 6, 12, 24, 48, 72 and 96 hours each and again the rate of 
sedimentation was used as an indicator of the efficacy of the stabilizer for the product. 
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3.7.1 Apparent Viscosity  
Viscosity measurement of the different samples was done using a Brookfield digital viscometer 
(model DV-1; Brookfield engineering Labs Inc., Middleboro, U.S.A) with a LV spindle number 
2. The viscosity of all the samples with different stabilizers was taken at different spindle speeds. 
Viscosity readings for each sample were taken at six (6) different shear rates in (cp).  
 
3.8 Storage Stability and Shelf-life Studies 
Accelerated shelf-life studies were done on the product over a period of five weeks. The shelf 
life of the product was determined by applying the Arrhenius model which uses the effect of 
temperature on product deterioration with time. Microbial growth, hydrolytic rancidity and 
oxidative rancidity were used to assess the rate of deterioration of the product. However, only the 
data for hydrolytic rancidity was used for the estimation of product shelf life. 
 
3.8.1 Microbial Analysis  
Microbial examinations were done to detect the rate of growth of micro-organisms whose 
presence in food products at certain levels may be used to assess the quality and\or safety. 
Enumeration tests including total plate count, E. coli, yeast and moulds were done as indicators 
of the rate of the build-up of microbial load. The entire tests were done over a period of 5weeks 
at different temperatures (25°C, 35°C and 45°C). 
 
Plate count agar, Eosin methylene blue and potato dextrose agar were used to culture for total 
plate count, E. coli, yeast and moulds respectively. The media were prepared using methods 
specified on the labels and peptone water was used as the diluents in all analysis. Two dilutions 
were used and two replicates were done for each. The drop plate method as described by 
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Herigstad et al., (2001) with a few modifications was used for all the microbial analysis. Each 
plate was divided into four quadrants and 0.025ml of the sample was used to obtain about 4-6 
drops on each quadrant. The samples were incubated in ovens set to temperatures of 37oC, 
44.5oC, 25oC total plate count, E. coli, yeast and moulds respectively. Microbial colonies were 
counted with the aid of a colony counter and then multiplied by (4*10) to give the count per ml. 
 
3.8.2 pH and Titratable Acidity  
pH was determined according to the method described by AOAC (1990), method 981.12.  
Titratable acidity was determined according to the AOAC (2005) method 970.21 and expressed 
as the percentage of lactic acid by titrating samples with 0.1M NaOH and the values reported as 
moles of sodium hydroxide per 25ml of sample.  
 
3.8.3 Free fatty Acids and Peroxide Value Test 
Fat extractions were done using a solvent extraction method. About 200ml of 40-60°C petroleum 
ether was added to 50ml of RUSF samples and shaken for about 2hours to obtain the fats in the 
petroleum ether which was decanted and evaporated on a water bath to obtain the fat. 
  
 
For lipid stability, free fatty acids (FFA) content and peroxide value (PV) of the extracted oil 
were determined over the storage period of the product as an indicator of lipid hydrolysis and 
oxidation. The FFA content was determined according to the AOAC general method 965.33, 
whilst the PV was determined using AOAC general method 940.28.   
 
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47 
 
CHAPTER FOUR 
 
4.0  RESULTS AND DISCUSSIONS 
4.1 Nutrient Composition of Drinkable RUSF 
The drinkable RUSF was formulated as an intervention food. It was deliberately formulated 
to have high protein and energy content, using locally available raw materials that had high 
protein, high carbohydrate and fat. Table 4.1 shows that even though the product had a very 
high moisture content, and consequently fluid, it also had a very high energy content of 
564.52 ± 2.76 Kcal/100g. 
 
Being a supplementary food the nutrients available in the drinkable RUSF, should provide a 
percentage of the recommended daily allowances of nutrients for the target consumers 
which were women of reproductive age. Table 4.1 shows that a (330mL) bottle of RUSF 
contained 316.13 Kcal of energy, and could meet about 25% RDA of carbohydrate, and 43% 
of the fat requirement of adult women thus providing them with a lot of energy needed for 
their daily activity which will be supplemented by other foods they may eat. It also provided 
28% needed proteins.  The Table also shows that while a good fraction (at least 25%) of 
macromolecules were met by the formulation, the requirements for micronutrients were 
marginally met. 
 
 
 
 
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Table 4.1: Nutrient Composition of RUSF and the Percentage of RDAs of WRA to be Met 
Macronutrients  g/100g  g/bottle 
DMB 
RDA of WRA 
(g/d) 
% RDA met for 
WRA 
 
       Moisture 
content 
83.03 ± 0.02 - - - 
  Energy (Kcal) 564.52 ± 2.76   316.13 - - 
       Carbohydrate 
(DMB)  
59.15 ± 0.76 33.12 1301 25.48 
       Protein  22.93 ± 0.77 12.84 46
1 27.91 
       Fat  15.26 ± 0.04 8.55 20
2 42.75 
       Fibre  12.70 ± 0.50 7.11 - - 
Ash  2.66 ± 0.20 1.49 - - 
 
Micronutrients  mg/100g 
DMB 
mg/bottle 
DMB 
RDA of WRA 
(mg/d) 
% RDA met for 
WRA 
 
       Calcium  50.50 ± 2.61 28.28 1000
1 2.83 
       Iron  2.18 ± 0.01 0.37 18
1 2.06 
       Magnesium  6.84 ± 0.07 1.16 310
1 0.35 
       Manganese 0.88 ± 0.00 0.15 1.8
3 8.33 
       Zinc  1.47 ± 0.01 0.25 8
1 3.13 
       Phosphorus  58.75 ± 1.63 9.97 700
1 1.42 
      Potassium  489.69 ± 0.36 83.10 4700
3 1.77 
      Sodium  712.02 ± 0.65 120.83 1500
3 8.06 
DMB= Dry matter basis; WRA= Women of reproductive age; 1recommended dietary 
allowances (RDAs) [dietary reference intakes (DRI, 2002/2005)]. 
 
4.2  Degree of Hydrolysis of Macromolecules 
To enhance the digestibility of the product and increase the energy density, the mixture of 
rice cowpeas and peanuts was treated with starch digestive enzymes (amylases) and 
proteases (bromelain) to hydrolyse the starches and proteins. This was done at varying 
conditions to determine the optimum conditions of hydrolysis of the polymers by the 
enzymes in the substrate (RUSF). 
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4.2.1 Hydrolysis of Starches in the Product Formulation 
Reducing sugars analysis was done to determine the degree of hydrolysis of starches. The 
overall average amount of reducing sugars obtained from the samples was 31.24±1.34 
mg/ml. The concentration of amylase enzyme did not show any significant effect on the 
hydrolysis. Figure 4.1 shows that as the temperature of hydrolysis of starch by the amylase 
enzyme increased the reducing sugars content increased to a maximum at about 50°C and 
remained constant between 50° and 55°. This implies that optimum hydrolysis occurred at 
50°C. 
  
Figure 4.1: Effects of temperature on the degree of hydrolysis of starches of the drinkable 
RUSF 
This result agreed with the findings of other researches on the activity of amylases. The 
activity of alpha amylases has been shown to be between 40-75°C (Sodhi et al., 2005; Yook 
and Robyt 2002) and the optimum activity was obtained at 50°C (Yook and Robyt, 2002). 
28 
29 
30 
31 
32 
33 
34 
40 42 44 46 48 50 52 54 56 
R
e
d
u
ci
n
g 
Su
ga
rs
 m
g/
m
l 
Temperature  (◦c) 
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However Sodhi et al., (2005) had optimum amylase activity at higher temperature of 65°C 
as was also documented by Sim and Berry (1996). Concerning the time of hydrolysis, starch 
hydrolysis increased almost linearly with a higher rate as the time increased from 45 to 60 
minutes (Figure 4.2). The effect of hydrolysis time on reducing sugars content was 
significant at all incubation temperatures. Also at the same incubation time an increase in 
temperature led to a higher amount of reducing sugars (Figure 4.3). The highest degree of 
starch hydrolysis was obtained at the temperature range of 50-55°C and for the highest time 
of one hour.  
 
Figure 4.2: Effects of time on the degree of hydrolysis of the starches of the drinkable RUSF 
20 
22 
24 
26 
28 
30 
32 
34 
36 
38 
20 25 30 35 40 45 50 55 60 65 
R
e
d
u
ci
n
g 
Su
ga
rs
 (
m
g/
m
l)
 
Time (mins) 
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Figure 4.3: Combined effects of temperature and time on the degree of hydrolysis of the 
starches of the drinkable RUSF 
 
4.2.2 Trinitrobenzene Sulphonic Acid Determination of –NH2 groups (as a Measure 
of Protein Hydrolysis) 
There was a linear relationship between incubation temperature and protein hydrolysis. As 
incubation temperature increased for bromelain hydrolysis of the proteins, there was an 
increase in TNBSA bound -NH2 groups (Figure 4.4). This implies that the activity of the 
enzyme (commercial bromelain) was well within the incubation temperature range used (37-
43°C). Bromelain is a complex mix of natural enzymes that is known to work within a wide 
range of temperature depending on the substrate. Corzo et al., (2012), indicated 55°C, 59°C 
and 37°C as optimum temperature of activity on three different subtrates.  The linear 
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52 
 
relationship (Figure 4.4) indicates the probability of an increase in bromelain activity with 
further increases in temperature. The observation may be due to the fact that optimum 
temperature for bromelain activity may not have been met in this work contradicting the 
observation made by Jutamongkon and Charoenrein, (2010) on fruit bromelain that there 
was loss of activity at temperatures beyond 40°C. This however may be agreeing with the 
optimum range (50°C-60°C) obtained by Gautam et al., (2010) for their stem bromelain. 
 
 
Figure 4.4: Effects of temperature on the degree of hydrolysis of the RUSF proteins 
 
Similar to temperature, increasing the time of hydrolysis also increased the degree of 
hydrolysis however there was a peak after 120minutes beyond began to drop (figure 4.5).  
This implies that after 120 minutes free -NH2 groups were no longer available to react with 
TNBSA probably because they recombined after some time in plastein reactions.  Plastein 
5.6 
5.8 
6 
6.2 
6.4 
6.6 
6.8 
36 37 38 39 40 41 42 43 44 
N
H
2
 
Temperature (◦c) 
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reaction involves the enzymatic hydrolysis of proteins into small molecular polypeptides and 
the rearrangement of these peptides, into new protein-like substances. Electrophoresis 
analysis of plastein synthesised by papain showed the presence of one major band with 
molecular weight of 2.8 KDalton, while synthesis with bromelain showed the presence of 
two bands with a molecular weight of less than 6.5 KDalton and 3.5 KDalton (Madzlan et 
al, 2006). Beyond 2hours, there was an apparent reduction of hydrolysis probably because 
of condensation of free amino groups in the plastein reaction. 
 
 
Figure 4.5: Effects of time on the degree of hydrolysis of the drinkable RUSF proteins 
 
The combined effects of incubation temperature and time are shown in Figure 4.6. At lower 
temperatures (i.e. below 39°C), increasing hydrolysis time increased the degree of 
5.6 
5.8 
6 
6.2 
6.4 
6.6 
6.8 
7 
0 50 100 150 200 
N
H
2
 
Time (mins) 
University of Ghana          http://ugspace.ug.edu.gh
54 
 
hydrolysis. The maximum protein hydrolysis by bromelain was attained at 2 hours 
incubation above 42°C. Beyond 2 hours of incubation at low temperatures (i.e. below 39°C), 
there was no further change in hydrolysis. However at higher temperatures (i.e. 42°C), there 
was a decrease in amino groups after incubation for longer periods than 2 hours (Figure 4.6). 
Madzlan et al., (2006) reported the formation of plastein reaction products at 37°C after 9-
24 hours of incubation. 
 
Figure 4.6: Combined effects of temperature and incubation time on the degree of hydrolysis 
of the drinkable RUSF proteins. 
 
In this work the degree of hydrolysis as determined by -NH2 yield was optimum at the 
highest temperature (Figure 4.6) and though the decline in the amount of -NH2 occurred 
after 120 minutes of incubation, it is clear that within the time range used in this experiment, 
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55 
 
60minutes of incubation could also give the same effect at 42°C. Consequently, although 
time had a significant effect on the degree of hydrolysis, its effect was not as high as that of 
incubation temperature. The highest amount of –NH2 (7.2) obtained was due to the effect the 
highest temperature used (43°C). The amount of –NH2 obtained at the highest time 6.45 was 
much lower (figure 4.6). 
 
Figure 4.7: Combined effects of temperature and concentration of the enzyme on the degree 
of hydrolysis of the drinkable RUSF proteins 
 
Figure 4.7 shows that although the enzyme concentration had an effect on the bromelain 
hydrolysis, it was observed that its effect was more profound as the temperature increased. It 
was realised that the rate of increase was reducing with increased concentration, still 
confirming the higher effect of temperature on hydrolysis.  
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4.2.3 Sodium Dodecyl Sulphate Polyacrylamide Gel Electrophoresis (SDS-PAGE) of 
Protein Hydrolysates. 
The effectiveness of bromelain hydrolysis of the food proteins was monitored using sodium 
dodecyl sulphate polyacrylamide gel electrophoresis, and the gels are presented as plate 4.1. 
Molecular weight markers with bands ranging from 97.4Kda to 14.4Kda were used. The two 
zymograms in plate 1 represent (a) protein hydrolysates obtained after 1 hour incubation 
with bromelain and (b) protein hydrolysates after 3 hours incubation with bromelain. For the 
non hydrolyzed sample, there were clear protein bands with weights above 97.4 Kda. The 
absence of those bands in the bromelain treated samples (for both the 1 hour and 3 hour 
hydrolyzed samples) implies that those proteins were successfully hydrolysed by the 
protease (bromelain).   
 
However, in the samples that were hydrolysed for three hours (Plate 1) there appeared low 
molecular weight bands (below 21.5 and above 14.4Kda), that were neither present in the 
non hydrolyzed samples nor the 1 hour hydrolyzed samples. This is probably further proof 
of the possibility of recombination of amino groups to form new peptides in a plastein 
reaction.  The formation of two electrophoretic bands after bromelain induced plastein 
reaction has been reported (Madzlan et al., 2006). The authors noted that electrophoresis 
analysis of plastein synthesised by papain showed the presence of one major band with 
molecular weight of 2.8 KDalton while, synthesis with bromelain showed the presence of 
two bands with a molecular weight of less than 6.5 KDalton and 3.5 KDalton.  In the current 
work the electrophoretic analysis of the protein hydrolysates with bromelain showed the 
bands, which however were much bigger than those reported by Madzlan et al., (2006).  
 
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57 
 
97.4kda
66.2kda
45kda
21.5kda
14.4kda
Unhydrolysed
RUSF
Molecular Weight 
Marker
Hydrolysed RUSF Samples
Samples Hydrolysed for One (1) Hour Samples Hydrolysed for Three (3) Hours 
 
Plate 4.1: SDS PAGE zymogram showing the effect of bromelain hydrolysis on RUSF 
proteins 
 
4.3 Physical Stability of the Product (RUSF). 
The physical stability experiments were done to determine the most significant cause(s) of 
product separation and hence to ascertain the factors to be put in place to render the product 
physically stable. Different particle sized products were obtained by passing different 
batches of the colloid milled product mixture through ASTM sieve sizes 500µ, 300µ and 
106µ respectively. This yielded different RUSF products with particle size distribution 
ranges within ≤ 500µ, 300µ and 106µ respectively and these were used for the settling rate 
analysis. Additionally three stabilizers applied to the product to assess the effect of 
stabilizers on the product’s physical stability.  
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4.3.1 The Effect of Particle Size on the Rate of Separation 
 Figure 4.8 and Table 4.2 show that the samples with the finest particle sizes (≤ 106µ) gave 
the steepest slope (i.e. fastest settling rate) indicating the rate of decay was higher than that 
of the samples with larger sizes (≤ 500µ, and ≤ 300µ).  
 
 
Figure 4.8: Effects of product particle size on the settling rate of RUSF samples with 
different particle sizes. 
 
*Volume of solution refers to the volume of RUSF suspension without supernatant.  
 
 
 
 
 
 
82 
84 
86 
88 
90 
92 
94 
96 
98 
100 
0 20 40 60 80 100 
v
o
lu
m
e 
o
f 
S
o
lu
ti
o
n
 (
m
l)
 
Time (Hours) 
≤ 500µ 
≤ 300µ 
≤ 106µ 
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Table 4.2: Degradation Rate Values Showing the Rate of Sedimentation of RUSF Samples 
with Different Particle Sizes 
 
Product Particle Size  Rate  R2 
106  -0.09
a  0.8347  
300  -0.074
b  0.6635  
500  -0.068
c 0.6778 
 
Stoke’s law states that the settling or sedimentation velocity (Vm) of a moving particle in a 
medium is directly proportional to the square of its size (or diameter, D), the differential in 
the densities of the particle and medium) and inversely proportional to the viscosity of the 
fluid:  
Vm = D
2g ( p- f)/18µ.......................................................  Equation 4.1 
Where  
       Vm = terminal or settling velocity 
        D   = Diameter of particle (assuming it is a sphere) 
          p and  f = density of the particle and the fluid respectively 
        µ = viscosity of the fluid. 
Based on Stoke’s law the observations made in Figure 4.8 and Table 4.2, indicate that the 
particle sizes of the samples used did not influence settling rate significantly since the 
samples with the least sizes were settling faster.  The density differential between the 
particles and the fluid which also has a direct influence on the rate of sedimentation was an 
important factor in this experiment since during milling the lightest fractions such as the 
cellulose, and pectin that make up the fibre component of the food are the most resistant to 
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size reduction and generally remain as the larger particles. On the other hand, components 
such as starches and proteins with higher densities are far more friable and hence form the 
finer fractions of the milled product (Hemery et al., 2009; Glitsø, and Bach Knudsen, 1999). 
Consequently the smaller or finer particles obtained after milling, had high densities which 
outweighed the effect of the diameter of the particles thus causing a higher sedimentation 
rate in the finer than the coarser components.  However since the ≤ 500µ samples contained 
in addition to the coarse, the denser particles which were contained in the ≤ 106µ samples, 
the observation could not solely be due to the densities of the particles. This notwithstanding 
the terminal velocity of a moving particle is affected inversely by viscosity of the medium. 
Therefore since the samples used in this work were not significantly affected by particle 
size, the effect of density was similar for all samples and yet there was a very glaring 
difference between the fine samples and the others which was attributed to a high difference 
in viscosity of the fine samples than the others. A lower fluid viscosity of the finer samples 
which had less particles will markedly increase their velocity since there will be less 
resistance to movement. 
 
4.3.2 Effects of Stabilizers on the Flow Behaviour of the drinkable RUSF. 
 
From the Stokes Law (Equation 4.1) the viscosity of the fluid had a strong influence on the 
particle separation (or phase separation) of the product. The less viscous the fluid medium, 
the greater the sedimentation rate. Consequently the effects of hydrocolloids (as stabilizers 
and viscosity modifiers) on the flow behaviour of the product as well as particles 
sedimentation rates were examined.  Shear stress and shear strain data obtained from 
apparent viscosity determinations of the product (using the Haake rotational viscometer) 
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were fitted to the power law model (Steffe, 1996), from which the flow behaviour 
parameters were estimated. Table 4.3 gives the means of the consistency coefficients (k) and 
the flow behaviour indices (n) for the three stabilizers (carboxy methyl cellulose, 
carrageenan and xantham gum) used in the product to modify its flow behaviour. All the 
stabilizers increased the apparent viscosity of the fluid 441.457±4.234. The highest 
concentrations of all stabilizers gave products with the highest consistency (apparent 
viscosity) 
 
Table 4.3: Effects of Stabilizers on some Rheological Characteristics of the Drinkable RUSF 
Stabilizer Concentration 
(%) 
k n 
CMC 0.05 447.60±3.74c 0.30±0.01c 
CMC 0.075 853.46±45.98b 0.43±0.24b 
CMC 0.1 1013.43±61.36a 0.45±0.01a 
Carrageenan  0.05 700.27±24.39c 0.41±0.01c 
Carrageenan 0.075 1049.16±83.54b 0.51±0.01b 
Carrageenan 0.1 1090.56±54.49a 0.49±0.01a 
Xanthan Gum 0.05 802.39±13.25c 0.40±0.01a 
Xanthan Gum 0.075 894.13±10.40b 0.45±0.01b 
Xanthan Gum 0.1 1111.31±4.99a 0.50±0.00c 
* (Figures with the same superscript are not significantly different) 
The flow behaviour parameters k and n in Table 4.3 show that the stabilizers modified the 
viscosity of the products differently. For each stabilizer increasing levels of incorporation 
from 0.05% to 0.1% significantly (p≤ 0.05) increased the apparent viscosity, k.  Among the 
three stabilizers, xanthan gum Produced the most profound increase in the apparent viscosity 
of the product while carboxy methyl cellulose (CMC) had the least effect.  They have been 
found to increase the consistency of food products by acting as thickeners, the efficiency of 
that depending on the molar mass and hydrodynamic size of the polymer which is also 
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62 
 
affected by the molecular structure as well as the charge of the polymer (Philips and 
Williams, 2009). Though all three gums used here have similar structure xanthan gum is 
known to have a higher viscosity at low shear rate which is drastically reduced with increase 
in shear indicating high psuedoplasticity. This behaviour according to Philips and Williams 
(2009) results from the ability of the xanthan molecule to form intermolecular aggregates 
through hydrogen bonding and polymer entanglements in solution leading to a highly 
ordered network of entangled stiff molecules making it a preferred choice when stabilizing 
emulsions and suspensions and when good flow properties are required. This was also 
evident in this work since xanthan gum gave the lowest rate of separation (Table 4.4) as 
illustrated in Figure 4.9 using the highest concentrations of the gums where xanthan gum is 
showing a more gradual rate than carrageenan and CMC. 
 
In all cases however, the flow behaviour index (n) was less than unity (1) suggesting that no 
matter the stabilizer used the flow behaviour was always non-Newtonian, and psuedoplastic 
(or shear thinning).  It has been suggested that most cereal fluid products are shear thinning 
and can be described by the power law model. As an example, Wang et al. (1999) observed 
that the cooked slurries of rice were shear-thinning, with no obvious yield stress at 
experimental levels of concentration and temperature. The shear-thinning nature of the fluid 
implies that with a little force applied by shaking the product will readily flow which is a 
desirable flow property for the drinkable RUSF since it has to be readily available to the 
consumer. 
 
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4.3.2 Effects of Stabilizer on Sedimentation Rates of Particles in the drinkable RUSF 
Table 4.4 shows the sedimentation rates and the R-squared values of the fitted plots. As 
discussed in section 4.3.1 in particulate fluid foods particles tend to sediment upon standing 
of the product. The rate of sedimentation is influenced by the particle size, the differential 
densities between the particles and the fluid and inversely dependent on the viscosity of the 
fluid. The various types of hydrocolloids influence the viscosity of the fluid foods 
differently based on their hydrodynamic mass, volume and stokes radius. Figure 4.9 shows 
the influence of three stabilizers (CMC, Carageenan and xanthan gum) on the settling rate of 
the drinkable RUSF. The settling rates of the various are summarised in table 4.4. The 
influence of the hydrocolloids on the settling rates is reflected in the viscosities of the 
product when the products containing hydrocolloids (section 4.3.2). CMC having the lowest 
viscosity also had the fastest settling rate. Consequently in order to reduce to the settling rate 
of the product it may be desirable to use a hydrocolloid that will increase the viscosity as in 
the case of xanthan gum.  
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Figure 4.9: Effects of three different stabilizers on the sedimentation of RUSF 
 
 
 
 
 
 
 
 
91 
92 
93 
94 
95 
96 
97 
98 
99 
100 
101 
0 20 40 60 80 100 120 
V
o
lu
m
e 
o
f 
so
lu
ti
o
n
(m
l)
 
Time(Hours) 
CMC 
Carrageenan 
Xanthan Gum 
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Table 4.4: Degradation Rate Values Showing the Effects of Stabilizers on the Rate of 
Sedimentation of the drinkable RUSF 
 
Stabilizer Rate R
2
 
CMC   
0.05 -0.059
a
 0.7535 
0.075 -0.049
b
 0.7906 
0.1 -0.045
c
 0.7599 
Carrageenan   
0.05 -0.048
a
 0.6796 
0.075 -0.035
b
 0.6726 
0.1 -0.034c 0.7988 
Xanthan Gum   
0.05 -0.047
a
 0.6835 
0.075 -0.039
b
 0.7411 
0.1 -0.018
c
 0.6621 
 
 4.4 The Effect of Pasteurisation Time, Storage Temperature and Storage Time on 
Microbial Growth, and Physico-Chemical Properties of the RUSF  
Critical parameters evaluated for the microbial stability were the process severity 
(pasteurisation and sterilisation) using pasteurisation time, storage temperature and storage 
time. The pasteurisation schedule was such that it took about forty three (43) minutes to get 
the samples to the temperature of pasteurisation (95°c) (figure 4.10) where it stayed for 10, 
20, or 30 minutes. On the other hand for the retorted (sterilized) samples (figure 4.11) it took 
25 minutes for it to come up to 119°c where it was maintained for 10minutes.The 
importance of the rate of heat penetration is based on its lethal effect on the micro-organisms 
of and the quality deterioration of the food product.  
 
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Figure 4.10: Heat penetration curve of pasteurised RUSF samples (at 95°C for 10,20 
&30min) 
 
0 
20 
40 
60 
80 
100 
120 
0 20 40 60 80 100 
T
em
p
er
a
tu
re
 (
°C
) 
Time (min) 
Medium 
Sample 
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67 
 
 
Figure 4.11: Heat penetration curve of retorted RUSF samples (sterilised at 119°C for 
10min) 
 
The effects of these processing schedules on the microbial stability of the product under 
different conditions of storage (time and temperature) were monitored using microbial 
counts. This approach is supported by Awuah et al., Ramaswamy and Economides, (2007) 
who observed that in thermal processing the primary objective is to eliminate spoilage 
micro-organisms and pathogenic micro-organisms or reduce them to levels that will make 
the food product safe for consumption and this can be used as means of assessing the 
efficiency of a thermal process.  
 
0 
20 
40 
60 
80 
100 
120 
140 
0 5 10 15 20 25 30 35 40 45 
T
em
p
er
a
tu
re
 (
°C
) 
Time (min) 
Retort 
Sample 
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Table 4.5 shows the ANOVA summary table of the effects of processing and storage 
variables on microbial counts of the product. All the main effects had significant influence 
on microbial growth. There were also significant interactions between the variables such that 
the microbial counts due to storage temperature and storage time depended on the severity 
of the heat treatment regime. The effects of Storage time on microbial growth on the other 
hand also depended on the storage temperature. 
Similar observations were made for the effects of the pasteurisation time, storage 
temperature and storage time on the FFA and PV of the products (Table 4.6). The effects of 
storage time and temperature on FFA and PV depended on the pasteurisation regimes. 
Furthermore the effects of the storage time depended on the storage temperature. 
 
 
Table 4.5: Anova Summay (P-Values) Showing the Effects of Different Processing and 
Storage Variables on Microbial Parameters of RUSF Samples 
 
Variable 
 
P-value 
TVC E.coli Yeasts and Moulds 
Pasteurization Time (A) ˂.0001 0.0006 0.0013 
Storage Temperature (B) ˂.0001 ˂.0001 ˂.0001 
Storage Time (C) ˂.0001 ˂.0001 ˂.0001 
A*B ˂.0001 ˂.0001 0.0012 
A*C ˂.0001 ˂.0001 ˂.0001 
B*C ˂.0001 ˂.0001 ˂.0001 
A*B*C ˂.0001 ˂.0001 ˂.0001 
 
 
 
 
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Table 4.6: Anova Summay (P-Values) Showing the Effects of Different Processing and 
Storage Variables on Physico-Chemical Parameters of RUSF Samples 
 
Variable 
 
P-value 
Free Fatty 
Acids 
Peroxide 
Value 
pH Titratable 
Acidity  
Pasteurization Time (A) ˂.0001 ˂.0001 0.4722 ˂.0001 
Storage Temperature (B) ˂.0001 ˂.0001 ˂.0001 ˂.0001 
Storage Time (C) ˂.0001 ˂.0001 0.8656 ˂.0001 
A*B ˂.0001 ˂.0001 0.0468 ˂.0001 
A*C ˂.0001 ˂.0001 0.0233 ˂.0001 
B*C ˂.0001 ˂.0001 0.5397 ˂.0001 
A*B*C ˂.0001 ˂.0001 0.0949 ˂.0001 
 
4.4.1 Comparison between Retorted RUSF (119°C) and Pasteurised (95°C) RUSF 
Samples  
It was observed that the TVC for the retorted samples was significantly higher than that of 
the samples pasteurised for 20 and 30 minutes but was equivalent with 10minutes 
pasteurised samples. This suggests that pasteurising the samples at 95°C for 30minutes was 
far more efficient in reducing the microbial load than retorting for 10minites at 119C 
(Figure 4.12). The effects of retorting at 119°C for 10minutes and pasteurising at 95°C for 
10minutes on microbial loads were not significantly different (figure 4.12). Sterilising 
particulate fluids in a still retort may not be as efficient as using agitated retorts due to slow 
rate of heat transfer. Consequently 10 minutes of retort time was probably too short for 
adequate heat transfer to cause microbial destruction (Ansar Ali et al., 2006).  
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Figure 4.12: Effects of heat treatment on microbial loads (TVC) of RUSF samples  
The observations made in this experiment are confirmed by this principle as the time taken 
to destroy the same number of micro-organisms (D-value) is higher at lower temperature 
than at higher temperatures and explains why the microbial count reduces with an increase 
in time (from 10minutes to 30minutes) (Stoforos, 1995). 
 
The FFA and PV of the samples differed significantly with processing schedules (Figure 
4.13 and 4.14). Samples that were pasteurised for 10minutes showed relatively lower FFA 
and PV.  As the pasteurisation time increased to 30minutes, FFA and PV also increased, 
suggesting that increasing the severity of heat treatment increased the deterioration rate of 
0 
0.5 
1 
1.5 
2 
2.5 
10 20 30 RT(10) 
Lo
g 
TV
C
 (
cf
u
/m
l)
 
Heat Treament (mins) 
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the fats. The FFA and PV of the samples that were sterilised by retorting for 10minutes were 
not significantly different from 20minutes pasteurised samples.  This trend suggests that the 
severity of the heat treatment of the retorted samples was probably not different from the 
20minutes pasteurised samples confirming that still retorts are not efficient for sterilising 
particulate fluids.    
 
Figure 4.13: Effects of heat treatment on free fatty acids of RUSF samples 
 
1.36 
1.38 
1.4 
1.42 
1.44 
1.46 
1.48 
1.5 
10 20 30 RT(10) 
FF
A
 (
%
) 
Heat Treatment(mins) 
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Figure 4.14: Effects of heat treatment on peroxide value of RUSF Samples 
4.5 Product Stability and Shelf-life Estimation 
The stability of a product is a function of time during which it may deteriorate chemically or 
undergo microbial spoilage. The rate at which these occur influences the rate of spoilage and 
consequently how long it may store under given conditions before it becomes unacceptable 
for human consumption (i.e. shelf life). The samples obtained after pasteurisation were 
stored at three different temperatures (25, 35 and 45°C) for five weeks. Samples were 
obtained from each of the storage temperatures and the microbial load, FFA and PV 
monitored on weekly basis. Figure 4.15 shows the trends of microbial load (log cfu) with 
storage time at the three different storage temperatures. The rates of microbial growth were 
different for each of the storage temperatures. For each storage temperature there were 
0 
0.5 
1 
1.5 
2 
2.5 
3 
3.5 
4 
4.5 
10 20 30 RT (10min) 
P
V
(m
e
q
/k
g)
 
Heat Treatment (mins) 
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increases in load until week three. Sample stored at 45°C showed a faster growth whilst 
those stored at 35°C had slower rate of growth throughout the study. There was no obvious 
peak for the one stored at 35°C whilst the one stored 45༦C peaked between third and fourth 
week. On the other hand even though there was a rapid growth of micro-organism in sample 
stored at 25༦C it peaked between weeks two and three and then started to decline.  
 
 
Figure 4.15: Bacteria growth (TVC) in RUSF samples during 5 weeks of storage at 25°C, 
35°C and 45°C 
 
 
0 
1 
2 
3 
4 
5 
6 
7 
0 1 2 3 4 5 6 
L
o
g
 c
fu
/m
l 
Time(Weeks) 
45OC 
35OC 
25OC 
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4.5.1 Microbial Growth as Indices for Product Stability 
The growth of micro-organisms depends on a number of factors of which the medium and 
environmental factors such as temperature and pH are very vital.  In a given medium, 
different micro-organisms have different temperatures at which the rate of growth is 
maximum (Prescott et al., 2002). In this work the effect of temperature changes on the 
quality indicators of food (RUSF) were investigated (figure 4.15). Total plate count was 
high for all the storage temperatures. This was because the growth of most spoilage bacteria 
(mesophiles) has been found to be within the temperature range of 20°c to 45°c (Hogg, 
2005). It was also observed that, though the counts at 25°c were lower than 35°c right from 
week one (1), they were higher than 45°c for the first two (2) weeks after which the value 
for 45°c shot up beyond that of 35°c.  
 
In relation to time it was found that the growth of micro-organisms slowed down by the 
fourth (4th) week. A decline in the growth may be the result of a change in their 
environmental conditions that requires a re-organisation of their metabolic activities 
(Prescott et al., 2002). With time in a microbial population, the metabolic activities of 
rapidly growing micro-organisms result in the production of waste which may have toxic 
effect on the micro-organisms. In addition as micro-organisms continue to multiply and 
increase in number the competition for nutrients and oxygen increases. In this work the 
depletion of oxygen may have had the most remarkable effect on microbial growth since the 
product was bottled and there was a limited source of oxygen to the organisms.  
 
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4.5.2 pH and Titratable Acidity 
One way in which micro-organisms alter their environmental conditions is to change the pH 
by the production of organic acids as metabolic wastes. The production of acids was very 
typical of microbial growth in this work since the pH of the product dropped from 6.7±0.3 to 
4.27±0.22. The changes in pH seemed to correlate with the rate of microbial growth at the 
different storage temperatures.  The pH drop was higher for product stored at 35 and 45 
storage condition than at 25༦C (figure 4.16). 
  
The trends in pH and titratable acidity were probably influenced by the hydrolysis of the 
proteins. This is because the hydrolysis produced peptides, carboxylic and amino groups. On 
the other hand bacteria growth and fermentation of sugars in the product also produced 
organic acids.  The increasing amino groups tend to create a buffer system against changes 
in pH and consequently there seemed not to be a discerning trend in the pH and titratable 
acidity with storage time (Figures 4.16 and 4.17).  
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Figure 4.16: Changes in pH of RUSF samples during 5 weeks of storage at 25°C, 35°C and 
45°C 
 
3.9 
4 
4.1 
4.2 
4.3 
4.4 
4.5 
4.6 
0 1 2 3 4 5 6 
p
H
 
Storage Time (Weeks) 
45oc 
35oc 
25oc 
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Figure 4.17: Changes in titratable acidity of RUSF samples during 5 weeks of storage at 
25°C, 35°C and 45°C 
 
Figure 4.18 shows that there was a general increase in the growth of yeasts and moulds 
throughout the storage period. This was contrary to what was observed for the bacteria 
growth in figure 4.15. Yeasts and moulds are known to be more tolerant to acid environment 
because they are better able to make use of acids (Prescott et al., 2002).  
 
0 
0.5 
1 
1.5 
2 
2.5 
3 
0 1 2 3 4 5 6 
T
it
ra
ta
b
le
 A
ci
d
it
y
(%
) 
Storage Time(Weeks) 
45oc 
35oc 
25oc 
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Figure 4.18: Changes in the growth of Yeasts and Moulds Growth in RUSF samples during 
5 weeks of storage at 25°C, 35°C and 45°C. 
 
4.5.3 Free Fatty Acids and Peroxide Value as Indices of Product Stability 
FFA and PV are frequently monitored as indices of lipid degradation or otherwise. For an 
oily or fatty product, it is desirable that both indices should remain low to indicate product 
quality stability under the storage conditions. Figure 4.19 shows a gradual increase in FFA 
for the first three weeks and a rapid increase thereafter. Even though they followed the same 
trends, samples stored at 25༦C had lower FFA values whilst samples stored at 45°C generally 
had higher FFA values throughout the storage period. FFAs are a result of triacylglycerols 
(TAG) hydrolysis especially under aqueous conditions. TAG hydrolysis to FFA was 
0 
1 
2 
3 
4 
5 
6 
7 
0 1 2 3 4 5 6 
L
o
g
 c
fu
/m
l 
Storage Time (Weeks) 
45oc 
35oc 
25oc 
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enhanced by the increasing storage temperature and hence the higher values at 45༦C than at 
25°C. 
 
Figure 4.20 shows the trends in peroxide values of the products that were stored at different 
temperatures. At all three temperatures there was an induction period of three weeks during 
which there was a gradual increase of PV. The PV values of the samples stored at 45༦C were 
higher than those stored at 25༦C even during the induction period. Autoxidation of lipids 
proceed with heat it is therefore the reason why PV increased with increased storage 
temperature (from 25°C to 45°C). Many other researchers obtained similar results on the 
exposure fatty products to heat with time. Nieto et al., (2011) for instance observed an 
increase in oxidation product in their cooked lamb with the storage time and exposure to 
environmental temperatures.  Al-Ismail et al., (2007) also observed an increase in rancidity 
of milk product with storage time and air drying.  
 
For the products stored at 25°C there was increase in the PV up to week 4 after which it 
levelled off.  On the other hand, there were no obvious trends in PV for product stored at 
45°C after week three. Hydroperoxides formation in lipids are primary oxidation products 
that are known to be weak and transient and easily breakdown to secondary oxidation 
products that are more stable (Sewald and DeVries, 2012). Consequently a decrease in 
hydroperoxides does not necessarily means a discontinuation of oxidation but rather that the 
oxidation process is near completion.  
 
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Figure 4.19: Changes in free fatty acids values of RUSF samples during 5 weeks of storage 
at 25°C, 35°C and 45°C 
 
0 
0.5 
1 
1.5 
2 
2.5 
3 
3.5 
4 
4.5 
5 
0 1 2 3 4 5 6 
F
F
A
%
 
Storage Temperature (Weeks) 
25oc 
35oc 
45oc 
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Figure 4.20: Changes in peroxide values of RUSF samples during 5 weeks of storage at 
25°C, 35°C and 45°C 
 
4.6 Estimation of Product Shelf-life 
Processed foods being biological materials undergo biological and chemical deterioration 
upon storage. The rate of deterioration influences how long the product maintains its 
keeping quality under given holding conditions before it becomes unacceptable for human 
consumption (i.e. shelf life). In order to estimate the shelf life of a product critical quality 
parameters that indicate product acceptability are monitored under specified conditions. The 
0 
2 
4 
6 
8 
10 
12 
0 1 2 3 4 5 6 
P
V
(m
eq
/k
g
) 
Storage Time (Weeks) 
25oc 
35oc 
45oc 
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monitoring process could be direct or indirect. In the indirect method usually done using 
accelerated shelf life studies the product is held at elevated temperatures and the product 
quality parameters (microbial load and lipid oxidation indices, water activity, etc) are 
monitored over a reasonable period of time. The basis of this method is that product spoilage 
(whether chemical or biological) are based on three basic mechanisms (chemical reaction 
kinetics, Q10 factor and Arrhenius model) (Fu and Labuza, 1997). Furthermore to estimate 
the shelf life of a product the product must be well understood and the possible modes of 
deterioration well explored to establish the most suitable means of spoilage, and determine 
the mechanism (NZFSA, 2005). Table 4.7 shows the design of shelf life studies done in this 
work using the indirect method. 
 
Table 4.7 Experimental Design for Shelf Life Studies on the Drinkable RUSF 
Method  Indirect(Accelerated)  
Desired Shelf Life  6 months  
Actual Test Time  5 weeks  
Temperatures  25°C , 35°C, 45°C 
Microbial  Total Plate count, yeast and moulds, E. coli  
Chemical tests  FFA, PV  
 
The modes of deterioration of the products as established in section 4.5.0 were microbial 
degradation, lipid hydrolysis and oxidation. However as observed in section 4.4.1 the 
problem of microbial growth was more due to inadequate heat process schedule which could 
easily be solved by the use of better processing equipment. On the other hand product 
deterioration due to lipid hydrolysis and oxidation is a more intrinsic problem that is not 
easily solvable by mere change of equipment. Consequently the shelf life estimation was 
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done based on lipid hydrolysis (FFA) as a measure of chemical deterioration and the onset 
of rancidity. The FFA values were therefore used as the most suitable mode of quality 
deterioration for the estimation of the shelf life of the product. Based on the observation 
made in section 4.5.3 that high lipid degradation reactions occurred at elevated temperatures 
(35°C and 45°C), the effect of temperature on lipid hydrolysis  (FFA production) was used 
as the mechanism of deterioration.  The shelf life estimation of the product was therefore 
based on the time before the surge in FFA values. The Arrhenius theory was used in the 
predictive modelling of shelf life.   
The Arrhenius equation is given as follows 
K = K0 e 
–Ea/RT   where, 
K: Rate of reaction constant 
Ea: the activation energy in cal/mol 
R: the gas constant in cal/mol 
T: the temperature in °K (°C +273)   
The Arrhenius equation can be linearised into a log form as follows   
Ln(K) =ーEa/R・1/T + ln(Ea)   
The FFA data obtained from the samples stored at the three different temperatures were 
fitted into the linearised Arrhenius model as presented in figure 4.21. The slope of the curves 
in the figure shows that the degradation rate i.e. FFA hydrolysis was steeper in samples 
stored at 45°C and least for samples stored at 25°C. Based on figure 4.19 the FFA values 
rapidly increased after the third week. Consequently three weeks was used as the maximum 
acceptable storage period under accelerated storage conditions.  
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 Figure 4.21: Effect of storage time on the rate of deterioration of fat (log FFA).  
 
Table 4.8 Degradation Rate Models for RUSF at Different Storage Temperatures 
Storage 
Temperature(°C) 
Degradation Rate Equation R2 
25 Y= -0.0356x+0.6201 0.881 
35 Y=-0.023x+0.5195 0.8158 
45 Y=-0.0593x+0.5822 0.9932 
        Where Y is the log of FFA and X is time in weeks 
 
0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0 1 2 3 4 5 6 
L
o
g
 F
F
A
 
Time (Weeks) 
25°C 
35°C 
45°C 
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Figure 4.22: Predictive shelf life of RUSF as a function of storage temperature based on the 
Arrhenius model  
 
Table 4.9: Predicted Shelf Life of RUSF as a Function of Temperature 
Storage Temperature (°C) Shelf Life (days) 
25 22 
35 20 
45 18 
 
Based on the model derived from Figure 4.22 the shelf-life of the product can be estimated 
for each temperature as presented in Table 4.9. The product stored at lower temperature 
(25°C) had a higher shelf life (22days) while those stored at higher temperature had a lower 
y = -0.0362x + 4.1318 
R² = 0.975 
0 
0.5 
1 
1.5 
2 
2.5 
3 
3.5 
20 25 30 35 40 45 50 
S
h
el
f 
li
fe
 (
W
ee
k
s)
 
Temperature (°C) 
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shelf life (18 days). For the product to store longer than three weeks therefore refrigeration 
storage conditions need to be explored. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 CHAPTER FIVE 
 
5. 0 CONCLUSIONS AND RECOMMENDATIONS 
5.1 Conclusions 
The RUSF samples made up of small particle sizes (≤106µ) had faster settling rate as 
compared to larger particle sizes (≤ 300µ and ≤500µ) indicating that the effect of particle 
sizes on product separation was based on the density differential of the particles and the 
fluid.  
The viscosity of the fluid had a significant effect on product separation rate and the increase 
in the viscosity using different stabilizers reduced the settling rate of the drinkable RUSF. Of 
the three different stabilizers used, xanthan gum proved to be the best stabilizer and its 
application in the product greatly slowed down the separation rate and provided some 
measure of physical stability to the product. 
Enzyme hydrolysis of the macromolecules (starch and proteins) was extensive as monitored 
by the increased amounts of reducing sugars, and amino groups (reaction with TNBSA).  
Maximal hydrolysis of starches by alpha amylase occurred after 1 hour at 50°C while that of 
proteins by bromelain peaked after 2hours at 43°C.  Beyond 2 hours, plastein-like reactions 
occurred to reduce the concentration of free amino ends. Reformation of peptides as was 
observable on the SDS-PAGE zymogram of 3hours hydrolysates gave credence to the 
possibility of Plastein reactions under the incubation conditions. 
Stabilisation of the product by thermal processing using pasteurisation or sterilisation 
techniques proved inadequate as determined by microbial count (TVC). Pasteurisation at 
95°C for 30minutes or retorting at 119°C for 10minutes still showed microbial count. Heat 
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penetration data from both pasteurization and sterilization processes showed that thermal 
processing was inadequate to assure microbial stability of the product. 
Accelerated shelf life studies using lipid hydrolysis indicator of FFA showed the product to 
be stable at room temperature (25°C) for 22days. Practically however, the product shelf 
stability did not go beyond three days at ambient conditions due to microbial spoilage. Heat 
penetration data from both pasteurization and sterilization processes confirmed that thermal 
processing was inadequate to assure microbial stability of the product. 
 
5.2 Recommendations 
 Options, such as the use of chemical preservatives and other physical methods to 
improve the microbiological stability of the product need to be explored. 
 Alternative means of packaging may be considered if thermal processing of the 
product will be continued in order to explore more severe thermal process schedules. 
 Alternative means of processing e.g. UHT processing, extrusion into cakes or 
biscuits could be considered in order to change the state of the product thus 
eliminating the effects of water activity in enhancing microbial growth. 
 Higher temperatures for bromelain hydrolysis and longer times for amylase 
hydrolysis could be considered to maximize the activity of the enzymes in further 
research. 
 Further work on plastein reactions and the reformation of peptide bonds during 
incubation of protein hydrolyzates with bromelain need to be carried out to take 
advantage of this phenomenon to improve the functional and nutritional quality of 
high protein foods. 
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APPENDICES 
Appendix 1: Analysis of Variance (ANOVA) Table for Degree of Starch Hydrolysis 
Source DF       SS     Mean Square    F -Value    Pr > F 
Temp 2 181.9863111      90.9931556      50.33    <.0001 
Time 2 643.1525333     321.5762667     177.87    <.0001 
Concentration 2 7.3381333       3.6690667       2.03    0.1510 
Temp*Time 4 82.3246222      20.5811556      11.38    <.0001 
Temp*Concentration 4 90.8035556      22.7008889      12.56    <.0001 
Time*Concentration 4 2.7050667       0.6762667       0.37    0.8250 
Temp*Time*Concentration 8 89.2039111      11.1504889       6.17    0.0002 
 
Appendix 2: ANOVA Table for Degree of Protein Hydrolysis 
Source DF       SS     Mean Square    F Value    Pr > F 
Temp 2 8.35318412 4.17659206      30.95    <.0001 
Time 2 4.61869927 2.30934964      17.11    <.0001 
Conc 2 5.12500198      2.56250099      18.99    <.0001 
Temp*Time 4 17.46599747 4.36649937      32.36    <.0001 
Temp*Conc 4 21.66291865 5.41572966 40.13    <.0001 
Time*Conc 4 14.95476322 3.73869081 27.70    <.0001 
Temp*Time*Conc 8 13.90152361 1.73769045 12.88    <.0001      
 
Appendix 3: ANOVA Table for Particle size 
Source DF       SS     Mean Square    F Value    Pr > F 
Particle size  2 30.175658 15.087829     143.33    <.0001 
Holding Time  6 1044.322511 174.053752    1653.51    <.0001 
Particle size* 
Holding Time 
11 18.476190 1.679654      15.96    <.0001 
 
 
 
 
 
 
 
 
 
 
 
 
 
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Appendix 4: Viscosities of Samples Using Different Stabilizers  
Stabilizer RPM 
100 60 50 20 10 5 
No Stabilizer 97.1 104.4 114.1333 205.5 216.1 228.5667 
0.05%CMC 115.22 130.92 137.09 210.7 207.8 293.33 
0.075%CMC 131.37 155.56 163.92 256.86 363.72 489.58 
0.1%CMC 131.37 155.56 163.92 256.86 363.72 489.58 
0.05%Carrageenan 109.76 140.5 130.5 187.88 266.98 387.17 
0.075%Carrageenan 108.49 135.76 131.27 208.8 353.75 465.05 
0.1%Carrageenan 117.18 143.14 152.69 244 352.1 500.27 
0.05%Xanthan gum 122.33 141.16 144.69 227.62 330.13 438.45 
0.075%Xanthan gum 120.02 144.62 150.44 241.13 351.31 519.1 
0.1%Xanthan gum 141.45 148.41 154.78 240 313.15 440.42 
 
Appendix 5: ANOVA Table for Stabilizer Treated Samples 
Source DF       SS     Mean Square    F Value    Pr > F 
Stabilizer (A) 2 45.107143       22.553571 51.90    <.0001 
 
Concentration (B) 2 95.583333 47.791667 109.99    <.0001 
Holding Time (C) 6 1115.686508 185.947751 427.93 <.0001 
 
A*B 4 5.166667 1.291667 2.97 0.0259 
 
A*C 12 25.503968 2.125331 4.89    <.0001 
 
B*C 12 38.111111 3.175926 7.31 <.0001 
A*B*C 24 17.055556 0.710648 1.64    0.0618 
 
 
 
 
 
 
 
 
 
 
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Appendix 6: Values for Microbial Growth, pH and Titratable Acidity at Different Pasteurisation Time, 
Storage temperature and Storage Time. 
Pasteurisation Time 
(min) 
Storage Temperature 
(°C) 
Storage Time 
(weeks) 
Replicate pH Titratable Acidity TVC1 E. coli Yeast and 
Molds 
10 25 1 1 4.44 1.90609 100 0 0 
10 25 1 2 4.48 2.07544 100 0 0 
10 25 2 1 4.5 1.44128 340 0 0 
10 25 2 2 4.42 1.51424 240 0 0 
10 25 3 1 4.34 1.98987 160 0 16 
10 25 3 2 4.42 1.58901 164 0 36 
10 25 4 1 4.8 1.16744 84 0 20 
10 25 4 2 4.86 1.37012 108 0 4 
10 25 5 1 4.7 4.1653 0 0 92 
10 25 5 2 4.76 3.92388 0 0 140 
10 35 1 1 4.23 3.24288 416 0 12 
10 35 1 2 4.43 2.82491 360 0 0 
10 35 2 1 4.1 2.9267 20 4 0 
10 35 2 2 3.94 3.24288 16 0 0 
10 35 3 1 4.05 1.16744 92 0 16 
10 35 3 2 4.13 1.16744 96 0 8 
10 35 4 1 4.1 2.07544 100 12 0 
10 35 4 2 4.2 2.252 148 4 4 
10 35 5 1 4.14 2.53035 92 20 128 
10 35 5 2 4.22 2.43576 60 16 160 
10 45 1 1 4.2 1.44128 0 0 0 
10 45 1 2 4.02 1.74395 0 0 0 
10 45 2 1 4.05 1.90609 480 0 56 
10 45 2 2 4.13 1.82412 560 0 48 
10 45 3 1 4.03 1.98987 100 16 116 
10 45 3 2 4.03 1.90609 184 4 80 
10 45 4 1 4 1.58901 300 0 32 
10 45 4 2 4.1 1.82412 308 0 24 
10 45 5 1 4.3 1.44128 108 48 72 
10 45 5 2 4.32 1.51424 84 32 92 
20 25 1 1 4.3 1.10348 0 0 0 
20 25 1 2 4.5 0.98097 0 0 0 
                                                          
1 These are raw values. They are multiplied by 10 to arrive at the colony forming units of TVC, E. coli, yeast 
and mould per ml. 
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20 25 2 1 4.35 2.9267 28 0 0 
20 25 2 2 4.65 3.13568 32 0 0 
20 25 3 1 4.5 2.82491 8 0 4 
20 25 3 2 4.5 2.72492 48 0 0 
20 25 4 1 4.3 2.62673 16 0 0 
20 25 4 2 4.46 2.9267 12 0 0 
20 25 5 1 4.33 2.43576 0 0 0 
20 25 5 2 4.39 2.07544 0 0 4 
20 35 1 1 4.05 1.66558 292 0 0 
20 35 1 2 3.91 1.82412 336 0 0 
20 35 2 1 4.2 2.07544 8 12 0 
20 35 2 2 3.86 1.82412 0 4 0 
20 35 3 1 4.05 2.53035 92 0 12 
20 35 3 2 4.01 2.43576 140 0 36 
20 35 4 1 4.03 2.34298 56 0 4 
20 35 4 2 4.09 1.98987 120 0 0 
20 35 5 1 4 1.66558 12 0 72 
20 35 5 2 4.08 1.82412 8 0 68 
20 45 1 1 4.8 2.07544 0 0 0 
20 45 1 2 4.84 1.82412 0 0 0 
20 45 2 1 4.2 1.37012 200 0 28 
20 45 2 2 4.3 1.30076 208 0 52 
20 45 3 1 3.95 2.53035 156 4 172 
20 45 3 2 4.05 2.53035 188 0 152 
20 45 4 1 4.15 1.37012 172 0 20 
20 45 4 2 4.35 1.30076 164 0 12 
20 45 5 1 4.31 1.98987 36 0 92 
20 45 5 2 4.33 1.74395 8 0 52 
30 25 1 1 4.4 1.51424 172 0 0 
30 25 1 2 4.46 1.51424 128 0 0 
30 25 2 1 4.4 3.57528 32 0 0 
30 25 2 2 4.52 3.24288 48 0 0 
30 25 3 1 4.5 2.252 20 0 4 
30 25 3 2 4.56 2.53035 40 0 12 
30 25 4 1 4 1.58901 24 0 0 
30 25 4 2 3.88 1.66558 20 0 0 
30 25 5 1 4.4 2.07544 4 0 4 
30 25 5 2 4.6 1.98987 0 0 16 
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30 35 1 1 4 1.37012 8 0 0 
30 35 1 2 3.84 1.51424 8 0 0 
30 35 2 1 4.01 1.10348 12 8 0 
30 35 2 2 3.97 1.10348 8 12 0 
30 35 3 1 4.53 2.53035 112 8 4 
30 35 3 2 4.59 2.53035 24 0 0 
30 35 4 1 3.92 2.07544 124 0 0 
30 35 4 2 3.98 2.16282 100 0 0 
30 35 5 1 4.06 1.98987 20 20 116 
30 35 5 2 4.02 1.74395 12 40 128 
30 45 1 1 4 1.51424 0 0 0 
30 45 1 2 4.36 1.51424 4 0 0 
30 45 2 1 4.24 3.57528 160 0 40 
30 45 2 2 4.28 2.9267 220 0 20 
30 45 3 1 4.1 1.30076 192 0 28 
30 45 3 2 4.18 1.37012 200 0 36 
30 45 4 1 4.15 2.252 176 0 0 
30 45 4 2 4.05 2.53035 200 0 0 
30 45 5 1 4.03 1.66558 28 8 112 
30 45 5 2 4.13 1.58901 20 0 180 
40 25 1 1 4.56 2.62673 200 0 8 
40 25 1 2 4.5 2.62673 160 0 4 
40 25 2 1 4.52 1.82412 108 0 0 
40 25 2 2 4.64 2.16282 44 0 0 
40 25 3 1 5.52 2.34298 0 0 68 
40 25 3 2 3.6 2.43576 0 0 52 
40 25 4 1 4.41 2.43576 44 0 0 
40 25 4 2 4.43 2.62673 24 0 0 
40 25 5 1 4.2 2.62673 8 0 92 
40 25 5 2 4.6 2.34298 16 0 48 
40 35 1 1 4.02 1.82412 508 0 0 
40 35 1 2 4.1 1.98987 492 0 0 
40 35 2 1 4.03 2.62673 464 0 0 
40 35 2 2 4.11 2.82491 560 0 4 
40 35 3 1 4.06 3.13568 192 0 100 
40 35 3 2 4.12 3.24288 160 0 0 
40 35 4 1 4 3.80588 112 24 48 
40 35 4 2 3.9 3.68968 164 4 28 
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40 35 5 1 3.9 2.9267 100 40 60 
40 35 5 2 4 3.57528 64 76 60 
40 45 1 1 4.01 2.82491 12 0 0 
40 45 1 2 3.89 2.9267 0 0 0 
40 45 2 1 4.4 2.62673 224 0 0 
40 45 2 2 4.46 2.62673 240 0 0 
40 45 3 1 4.3 2.53035 48 12 28 
40 45 3 2 4.32 2.07544 12 4 52 
40 45 4 1 4.44 1.44128 112 0 24 
40 45 4 2 4.52 1.82412 120 0 32 
40 45 5 1 4.2 1.58901 36 4 128 
40 45 5 2 4.26 1.82412 28 12 152 
 
Appendix 7: ANOVA Table for pH 
Source DF       SS     Mean Square    F Value    Pr > F 
Pasteurisation 
Time (A)  
3 0.21121000 0.07040333 1.79 0.1586 
Storage 
Temperature (B) 
2 3.61410667 1.80705333 45.96    <.0001 
Storage Time (C) 4 0.06312000 0.01578000 0.40 0.8069 
A*B 6 0.45560000 0.07593333 1.93    0.0903 
A*C 12 0.76304000 0.06358667 1.62    0.1110 
B*C 8 0.12446000 0.01555750 0.40    0.9187 
A*B*C 24 1.32690000 0.05528750 1.41    0.1439 
 
Appendix 8: ANOVA Table for Titratable Acidity 
Source DF       SS     Mean Square    F Value    Pr > F 
Pasteurisation Time 
(A)  
3 5.32005308 1.77335103 62.33    <.0001 
Storage 
Temperature (B) 
2 3.09896179 1.54948090 54.46    <.0001 
Storage Time (C) 4 2.12654363 0.53163591 18.69 <.0001 
A*B 6 4.51656171 0.75276028 26.46    <.0001 
A*C 12 9.29712548 0.77476046 27.23    <.0001 
B*C 8 4.88889057 0.61111132 21.48    <.0001 
A*B*C 24 25.63676168 1.06819840 37.54    <.0001 
 
 
 
 
 
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Appendix 9: ANOVA Table for TVC 
Source DF       SS     Mean Square    F Value    Pr > F 
Pasteurisation 
Time (A)  
3 183775.4667 61258.4889 90.76    <.0001 
Storage 
Temperature 
(B) 
2 148824.2667 74412.1333 110.25 <.0001 
 
Storage Time 
(C) 
4 278139.4667 69534.8667 103.02    <.0001 
A*B 6 285690.9333 47615.1556 70.55    <.0001 
A*C 12 196127.2000 16343.9333 24.22    <.0001 
B*C 8 498995.7333 62374.4667 92.42 <.0001 
A*B*C 24 394254.4000      16427.2667      24.34    <.0001 
Appendix 10: ANOVA Table for E. Coli 
Source DF       SS     Mean Square    F Value    Pr > F 
Pasteurisation 
Time (A)  
3 491.733333 163.911111 6.68    0.0006 
Storage 
Temperature (B) 
2 1156.266667 578.133333 23.57    <.0001 
 
Storage Time (C) 4 2731.466667 682.866667 27.83    <.0001 
A*B 6 977.066667 162.844444 6.64    <.0001 
A*C 12 1429.600000 119.133333 4.86    <.0001 
B*C 8 2059.733333 257.466667 10.49    <.0001 
A*B*C 24 3241.600000      135.066667 5.51    <.0001 
 
Appendix 11: ANOVA Table for Yeast and Mould 
Source DF       SS     Mean Square    F Value    Pr > F 
Pasteurisation 
Time (A)  
3 4251.2000 1417.0667 5.94    0.0013 
Storage 
Temperature 
(B) 
2 22120.8000 11060.4000 46.39    <.0001 
Storage Time 
(C) 
4 118356.5333 29589.1333 124.12    <.0001 
A*B 6 6090.4000 1015.0667       4.26    0.0012 
A*C 12 19755.4667 1646.2889 6.91    <.0001 
B*C 8 19505.8667 2438.2333 10.23    <.0001 
A*B*C 24 40762.9333 1698.4556 7.12    <.0001 
 
 
 
 
 
 
 
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Appendix 12: Values of FFA PV at Different Pasteurisation Time, Storage temperature and Storage Time. 
Pasteurisation 
Temperature 
(°C) 
Storage 
Temperature (°C) 
Storage time 
(weeks) 
Replicate FFA PV 
10 25 1 1 1.4651 2.9567 
10 25 1 2 1.4588 2.9876 
10 25 2 1 1.7468 6.1889 
10 25 2 2 1.7484 6.1969 
10 25 3 1 2.6905 7.5901 
10 25 3 2 2.6891 7.5932 
10 25 4 1 3.3419 8.1252 
10 25 4 2 3.3833 8.1894 
10 25 5 1 2.4255 9.605 
10 25 5 2 2.4261 9.8456 
10 35 1 1 1.4575 5.3654 
10 35 1 2 1.4598 5.3391 
10 35 2 1 2.0268 5.653 
10 35 2 2 2.0249 5.5855 
10 35 3 1 2.7519 7.1552 
10 35 3 2 2.78043 7.1894 
10 35 4 1 3.4373 8.321 
10 35 4 2 3.4356 8.34 
10 35 5 1 2.4255 9.1245 
10 35 5 2 2.4261 9.2071 
10 45 1 1 1.7361 5.3654 
10 45 1 2 1.7484 5.3391 
10 45 2 1 2.143 7.2057 
10 45 2 2 2.1419 7.182 
10 45 3 1 2.1112 7.1562 
10 45 3 2 2.158 7.1479 
10 45 4 1 3.1392 6.9562 
10 45 4 2 3.1574 6.9479 
10 45 5 1 2.3986 10.4997 
10 45 5 2 2.4005 10.3855 
20 25 1 1 1.564 3.18 
20 25 1 2 1.5726 3.173 
20 25 2 1 1.7765 6.2875 
20 25 2 2 1.7632 6.2894 
20 25 3 1 2.7437 7.8511 
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20 25 3 2 2.7423 7.8266 
20 25 4 1 3.5274 8.7614 
20 25 4 2 3.5532 8.7423 
20 25 5 1 2.4663 9.454 
20 25 5 2 2.44789 9.3967 
20 35 1 1 1.7935 5.578 
20 35 1 2 1.6769 5.9878 
20 35 2 1 2.2182 6.1882 
20 35 2 2 2.2158 6.1845 
20 35 3 1 2.4856 7.4875 
20 35 3 2 2.4315 7.6755 
20 35 4 1 3.485 8.7475 
20 35 4 2 3.4825 8.7155 
20 35 5 1 2.3892 10.0123 
20 35 5 2 2.389 10.1987 
20 45 1 1 1.5058 6.9493 
20 45 1 2 1.5108 6.9721 
20 45 2 1 2.2268 7.1835 
20 45 2 2 2.233 7.1917 
20 45 3 1 2.2474 7.2235 
20 45 3 2 2.2445 7.3517 
20 45 4 1 3.1474 7.5255 
20 45 4 2 3.1405 7.5517 
20 45 5 1 2.5226 10.9671 
20 45 5 2 2.5161 10.9813 
30 25 1 1 1.5172 4.5954 
30 25 1 2 1.5163 4.59 
30 25 2 1 1.7956 6.4694 
30 25 2 2 1.7996 6.4514 
30 25 3 1 2.858 8.0767 
30 25 3 2 2.8532 7.9984 
30 25 4 1 3.6612 9.7406 
30 25 4 2 3.651 9.7619 
30 25 5 1 2.5823 9.5566 
30 25 5 2 2.5939 9.6666 
30 35 1 1 1.6769 5.9878 
30 35 1 2 1.6742 5.9075 
30 35 2 1 2.2922 6.6876 
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30 35 2 2 2.3213 6.6354 
30 35 3 1 2.5897 7.6936 
30 35 3 2 2.5888 7.7242 
30 35 4 1 3.4825 8.7155 
30 35 4 2 3.5397 9.1926 
30 35 5 1 2.399 10.5676 
30 35 5 2 2.3895 10.6889 
30 45 1 1 1.621 7.3493 
30 45 1 2 1.627 7.3602 
30 45 2 1 2.2922 6.6876 
30 45 2 2 2.3213 6.6354 
30 45 3 1 2.2444 7.7062 
30 45 3 2 2.2568 7.6962 
30 45 4 1 3.2334 8.7562 
30 45 4 2 3.2378 8.7562 
30 45 5 1 2.5926 11.7965 
30 45 5 2 2.5879 11.7929 
40 25 1 1 1.409 3.5978 
40 25 1 2 1.4332 3.596 
40 25 2 1 1.691 6.6275 
40 25 2 2 1.695 6.6421 
40 25 3 1 2.501 6.596 
40 25 3 2 2.494 6.5993 
40 25 4 1 3.2937 7.7899 
40 25 4 2 3.2992 7.7542 
40 25 5 1 2.3645 7.7001 
40 25 5 2 2.3624 7.5878 
40 35 1 1 1.6748 6.9492 
40 35 1 2 1.6861 6.9993 
40 35 2 1 2.0598 5.1772 
40 35 2 2 2.0671 5.186 
40 35 3 1 2.2515 7.4993 
40 35 3 2 2.2504 7.4842 
40 35 4 1 3.2465 7.3793 
40 35 4 2 3.2414 7.3742 
40 35 5 1 2.3201 8.9001 
40 35 5 2 2.294 8.8822 
40 45 1 1 1.6814 7.9302 
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40 45 1 2 1.6841 7.942 
40 45 2 1 1.9644 9.0785 
40 45 2 2 1.9671 9.0184 
40 45 3 1 2.0431 9.073 
40 45 3 2 2.0427 9.1855 
40 45 4 1 3.0175 9.573 
40 45 4 2 3.0341 9.5855 
40 45 5 1 2.2976 9.9404 
40 45 5 2 2.3089 9.9483 
 
 
Appendix 13: ANOVA Table for FFA 
Source DF       SS     Mean Square    F Value    Pr > F 
Pasteurisation Time (A)  3 0.96425795 0.32141932 652.47 <.0001 
Storage Temperature (B) 2 6.97562002 3.48781001 7080.10 <.0001 
Storage Time (C) 4 92.85365675 23.21341419 47122.2 <.0001 
A*B 6 0.05529211 0.00921535 18.71 <.0001 
A*C 12 0.27277348 0.02273112 46.14 <.0001 
B*C 8 2.92311819 0.36538977 741.73 <.0001 
A*B*C 24 0.44862985 0.01869291 37.95 <.0001 
 
 
Appendix 14: ANOVA Table for PV 
Source DF       SS     Mean Square    F Value    Pr > F 
Pasteurisation Time (A)  3 16.1171339 5.3723780 2823.01    <.0001 
Storage Temperature (B) 2 208.5032246 104.2516123 54780.9 <.0001 
Storage Time (C) 4 250.3641765 62.5910441 32889.6    <.0001 
A*B 6 3.1207495 0.5201249 273.31    <.0001 
A*C 12 11.5664477 0.9638706 506.48    <.0001 
B*C 8 69.6502363 8.7062795    4574.87    <.0001 
A*B*C 24 17.6058904 0.7335788 385.47    <.0001 
 
 
 
 
 
 
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Appendix 15: L-leucine Standards for TNBSA  
Concentration Absorbance  
0.25 0.84 
0.25 0.868 
0.5 1.314 
0.5 1.189 
0.75 1.454 
0.75 1.506 
1 1.485 
1 1.518 
 
 
 
 
 
 
 
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