Title: Kinetic models for apple quality indicators throughout a sustainable postharvest chain
Other Titles: Kinetiekmodellen voor indicatoren van appelkwaliteit doorheen een duurzame naoogstketen
Authors: Gwanpua, Sunny George
Issue Date: 19-Nov-2014
Abstract: Once harvested, apples, like every other fresh fruit and vegetable, undergo continuous changes in quality as part of the normal ripening and senescence. Ripening may be desirable in that it makes the fruit palatable, but it limits the storage life of the fruit. To ensure year-round supply of apples, considerable effort is made to slow down ripening. The most common practice is to store apples at low temperatures, under an atmosphere with reduced oxygen levels and elevated carbon dioxide level - often referred to as controlled atmosphere (CA) storage. CA storage prevents quality losses by inhibiting respiration and ethylene production, two vital reactions involved in quality degradation during ripening. Different apple cultivars have different optimal CA conditions, depending on their sensitivity to chilling, low oxygen, and high carbon dioxide injury. Although CA storage is extensively used commercially to prolong the storage life of many apple cultivars, its effect on quality deterioration, from a quantitative point of view, is poorly understood. Mathematical models offer an important tool that can assist in optimizing CA storage. Moreover, mathematical models may help to improve our understanding of the underlying mechanisms of an observed phenomenon.The first objective of this dissertation was to develop kinetic models describing the postharvest evolution of two important apple quality indicators, namely flesh firmness and skin green background colour. A mathematical model for firmness loss was developed by assuming that ethylene production, the synthesis of pectin degrading enzymes, and pectin degradation are the main reactions involved in softening. Appropriate kinetic equations for these reactions were proposed. To estimate the parameters of the model, firmness and ethylene emission data were collected from Jonagold, Braeburn, and Kanzi apples harvested at three different stages of maturity and stored at different temperatures and CA conditions, followed by exposure to ambient shelf life conditions. Moreover, stochastic model parameters were identified, and by treating these as fruit-specific model parameters, the Monte Carlo method was used to model the fruit-to-fruit biological variability in flesh firmness within a batch of apple. This modelling concept was extended to model the fruit-to-fruit variability in skin background colour of Jonagold apples. Colour loss was assumed to be due to chlorophyll breakdown, the rate of which was dependent on the endogenous ethylene concentration. Stochastic model parameters were identified, and by treating the stochastic model parameters as random factors, the Monte Carlo method was again used to model and describe the propagation of the fruit-to-fruit variability of the background colour within a population of fruit. Practical storage management applications of these models were discussed. Software code for predicting apple quality evolution, based on the quality models, was developed, and integrated in a newly developed software tool, the FRISBEE tool, for cold chain optimisation. This software tool was developed within the framework of the European Union FP7 project, FRISBEE (Food Refrigeration Innovations for Safety, consumersÂ’ Benefit, Environmental impact and Energy optimisation along the cold chain in Europe). Quality models for other food products (pork neck cutlet, ready-to-eat pork meal, salmon, spinach and ice cream) were also integrated in the FRISBEE tool. The objective of developing the FRISBEE tool was to provide a software tool for evaluating cold chains with respect to three important sustainability indicators: product quality, energy use and global warming impact.To get an in depth understanding on the mechanism of apple softening, pectin modifications and the evolution of pectin-modifying enzymes during postharvest storage and ripening were investigated. Jonagold apples were harvested at commercial maturity and stored at different temperatures and CA conditions for six months, followed by exposure to ambient shelf life conditions (18 – 20°C under air) for 2 weeks. The composition of the pectic material was analysed. Furthermore, firmness and ethylene production of the apples were assessed. Generally, the main changes in pectin composition associated with the loss of firmness during ripening in Jonagold apples were a loss of side chain neutral sugars, increased water solubility and decreased molar mass. Also, the activities of four important enzymes possibly involved in apple softening, namely beta-galactosidase (BG), alpha-arabinofuranosidase (AF), polygalacturonase (PG) and pectin methylesterase (PME), were measured. Pectin-related enzyme activities were highly correlated with ethylene production, but not always with pectin modifications. BG was found to be the cell wall enzyme most related to apple softening, as its activity was more correlated to softening. In addition, loss of side chain neutral sugars (particularly galactose, arabinose and xylose) was strongly correlated to loss in flesh firmness. PG activity was poorly correlated to softening, and no significant pectin depolymerisation was observed, except for apples that had undergone extensive softening. AF activity showed poor correlation to softening, although loss of arabinose was correlated to softening. PME activity was high, but the degree of methoxylation of the pectin polysaccharide remained unchanged during ripening. In addition, the expression profiles of the genes encoding these four cell wall enzymes were investigated by qRT-PCR. MdPG4, MdBG1 and MdBG6 genes were identified as key ripening-related, and could serve as molecular markers for apple softening. Further studies on genetic regulation of apple fruit softening should focus on these cell wall-related genes. A conceptual model for pectin disassembly during softening in postharvest ripening of apple was proposed.
Table of Contents: Acknowledgements i
Abstract v
Samenvatting ix
Abbreviations and Symbols xiii
Contents xvii
General Introduction 1
1.1. Apple cold chain and sustainability 1
1.2. Quality evolution and fruit ripening along a postharvest chain 3
1.2.1. Fruit quality factors 3
1.2.2. Quality changes during fruit ripening 4
1.2.3. The role of oxygen and carbon dioxide in fruit ripening 4
1.2.4. Ripening and the plant hormone ethylene 6
1.3. Softening and the cell wall 8
1.3.1. Plant cell walls 8
1.3.2. Cell wall modifications during fruit ripening 10
1.3.3. Cell wall enzymes and their role in ripening 12
1.4. Managing quality loss in postharvest chain 14
1.4.1. Postharvest handling techniques 14
1.4.2. Postharvest storage techniques 15
1.4.3. Quality modelling in postharvest biology 17
1.5. Main aim of thesis 20
1.6. Thesis objectives and outline 21
Kinetic modelling of firmness breakdown in apples along the postharvest chain 23
2.1. Introduction 24
2.2. Model Development 25
2.2.1. Kinetic basis of model 25
2.2.2. Model equations 27
2.2.3. Output relations 29
2.3. Materials and methods 30
2.3.1. Fruit 30
2.3.2. Storage experiments 30
2.3.3. Firmness measurements 30
2.3.4. Ethylene emission measurements 31
2.3.5. Initial values 31
2.3.6. Parameter estimation 32
2.4. Results and discussion 34
2.4.1. Model predictions 34
2.4.2. Sensitivity analysis 37
2.5. Conclusions 40
Stochastic modelling of postharvest biological variability in flesh firmness of apple 41
3.1. Introduction 42
3.2. Materials and methods 43
3.2.1. Fruit 43
3.3. Storage experiments 43
3.3.1. Measurements 44
3.4. Model development 45
3.4.1. Mathematical modelling of firmness breakdown 45
3.4.2. Introducing biological variations 46
3.4.3. Model calibration 47
3.5. Results and discussion 49
3.5.1. Average batch behaviour of firmness 49
3.5.2. Biological variation in firmness 53
3.5.3. Model validation 57
3.5.4. Practical applications 59
3.6. Conclusions 61
Managing postharvest biological variability in skin background colour 63
4.1. Introduction 64
4.2. Materials and methods 65
4.2.1. Fruit 65
4.2.2. Storage experiments 65
4.2.3. Measurements 66
4.3. Model development 66
4.3.1. Kinetic basis for postharvest loss in skin green background colour 66
4.3.2. Model equations 67
4.3.3. Model outputs 69
4.3.4. Model calibration 70
4.3.5. Identification of random model parameters 72
4.3.6. Monte Carlo simulations 73
4.4. Results and discussion 74
4.4.1. Relationship between chlorophyll content and colour measurements 74
4.4.2. General product behaviour 74
4.4.3. Model calibration 76
4.4.4. Random model parameters 76
4.4.5. Propagation of biological variation 77
4.4.6. Practical applications 83
4.5. Conclusions 86
The FRISBEE tool, a software for optimising the trade-off between food quality, energy use, and global warming impact of cold chains 87
5.1. Introduction 88
5.2. Development of the FRISBEE tool 89
5.2.1. Definition of reference cold chains 89
5.2.2. Kinetic models for food quality evolution 91
5.2.3. Energy use calculations 92
5.2.4. Global warming impact assessment 93
5.2.5. Software development process of the FRISBEE tool 93
5.3. Using the FRISBEE tool for Cold chain simulations 96
5.3.1. Examples of the FRISBEE tool simulations 98
5.4. Conclusions 103
Molecular basis of apple softening: pectin modifications and the role of pectin-modifying enzymes 105
6.1. Introduction 106
6.2. Materials and methods 107
6.2.1. Fruits 107
6.2.2. Storage experiments 107
6.2.3. Measurement of firmness 108
6.2.4. Measurement of ethylene production 108
6.2.5. Pectin characterization 108
6.2.6. Analysis of cell wall enzyme activity 110
6.2.7. Statistical analysis 113
6.3. Results and discussion 113
6.3.1. Effect of storage temperature and controlled atmosphere on the evolution of firmness and ethylene production 113
6.3.2. Changes in pectic polymers during softening of Jonagold apples stored under different conditions 115
6.4. Conclusions 123
Genetic regulation of pectin-modifying proteins during apple fruit softening 125
7.1. Introduction 126
7.2 Materials and methods 127
7.2.1 Plant material and storage experiments 127
7.2.2. Real-time quantitative PCR (qRT-PCR) 128
7.2.3. Evaluation of firmness and ethylene production measurements 129
7.2.4. Cell wall pectin characterization 129
7.2.5. Data analysis 129
7.3. Results 131
7.2.2. Detection of softening-related candidate genes in the apple genome 131
7.2.3. Expression analysis of softening-related candidate genes during storage under different conditions 131
7.2.4. Correlation analysis between cell wall gene expression, cell wall hydrolases, and flesh softening 134
7.2.5. 1-MCP treatment validates MdPG1, MdPG4, MdBG1 and MdBG6 as cell wall genes associated with ripening 136
7.4. Discussion 140
7.4.1. MdPG4 is the main ripening-related gene within the POLYGALACTURONASE gene family 140
7.4.2. PME is unlikely to play an important role in apple softening during ripening 141
7.4.3. Beta-galactosidase genes are the main cell wall genes regulating apple fruit softening 141
7.4.4. AF activities may be mediated by different cell wall genes 142
7.4.5. A conceptual model for cell wall disassembly during apple softening 143
7.4.6. Cell wall pectin degradation is important, but not sufficient, for apple fruit softening 145
7.5. Conclusion 146
7.6. Supporting Information 147
General conclusions and perspectives 151
8.1. General conclusions 151
8.2. Future perspectives 154
References 157
List of publications 173
Publication status: published
KU Leuven publication type: TH
Appears in Collections:Division of Mechatronics, Biostatistics and Sensors (MeBioS)
Bio- & Chemical Systems Technology, Reactor Engineering and Safety Section

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