Document Type

Theses, Ph.D


This item is available under a Creative Commons License for non-commercial use only


4.4 AGRICULTURAL BIOTECHNOLOGY, Agricultural biotechnology and food biotechnology

Publication Details

Successfully submitted for the award of PhD.


Post-harvest life of fresh produce is limited due to high metabolic activity and microbial spoilage. Modified atmosphere packaging (MAP) has proven to be one of the most effective techniques to extend the shelf life of fresh produce commercially. Obtaining of an optimum concentration of oxygen and carbon dioxide inside the package depends upon the product properties, the environmental conditions of the cold chain, the permeable film, some of which are subjected to natural variability during the food distribution chain. This variability may generate produce that is out of specification that will lead to food waste. Uncertainty analysis of this problem may lead to relevant interventions to prevent these losses. The hypothesis of this work was to create a mathematical model that predicts key quality factors for MAP packaged fresh products in the supply chain distribution, which will help to assess the food losses in relation to quality thresholds. The model developed simulated the respiration rate as function of O2 and CO2 concentration and produce temperature using Michaelis-Menten equations. The exchange of gases (O2, CO2) and water vapour between the fruit surface, package atmosphere and external atmosphere was modelled taking into account the process of transpiration and condensation. In the transpiration model, the fresh produce surface was assumed to be perfectly saturated and the energy of respiration was used to evaporate surface water. Temperature changes in the headspace due to metabolic heat, convective heat transfer and heat exchange by gas transmission through the package were accounted for. The quality attributes of fresh produce included weight loss and colour change (L, a, and b values) for mushroom, from Botrytis and its fermentative activity for strawberry and weight loss and spoilage for tomato. ii These conditions were simulated for real and variable i) export cold chain and ii) retail display storage to evaluate the effect of cold chain variability (temperature and relative humidity) on the quality of fresh produce and associated waste generation. The prediction of propagation of biological variance on the quality of fresh produce during storage was obtained using a mathematical model. Sensitivity analysis of the stochastic MAP model pointed out the influence of input parameters on the quality of fresh produce. The conclusions of the study showed that the toolbox developed is able to interpret cold chain data: 1) mathematical prediction of quality; 2) simulation of cold chain conditions allowing for different variability components; 3) estimation of waste generation kinetics based in all quality criteria and thresholds; 4) sensitivity analysis to identify the most sensitive technological parameters; and 5) identification of interventions that affect the benchmarked technological parameters.