Retention of quality attributes during drying of fruit and vegetables is a prime concern since the product’s acceptability depends on the overall quality; particularly on the nutritional, color, and physical attributes. However, these quality parameters deteriorate during drying. Food quality changes are strongly related to the drying conditions and researchers have attempted to develop mathematical models to understand these relationships. A better insight toward the degradation of quality attributes is crucial for making real predictions and minimizing the quality deterioration. The previous empirical quality models employed kinetic modeling approaches to describe the quality changes and therefore, lack the realistic understanding of fundamental transport mechanisms. In order to develop a physics based mathematical model for the prediction of quality changes during drying, an in-depth understanding of research progress made toward this direction is indispensable. Therefore, the main goal of this paper is to present a critical review of the mathematical models developed and applied to describe the degradation kinetics of nutritional, color, and texture attributes during drying of fruit and vegetables and microbial growth model during storage. This review also presents the advantages and drawbacks of the existing models along with their industrial relevance. Finally, future research propositions toward developing physics-based mathematical model are presented.

Shrinkage is an obvious phenomenon that occurs when drying plant-based food materials, and it has a crucial influence on heat–mass transfer mechanisms, energy consumption in drying, and dried product quality. The present study aims to develop a theoretical shrinkage model considering the drying kinetics and shrinkage velocity approach during the convective drying of jackfruit. Since there is no theoretical model in the literature that considers the transfer process along with shrinkage phenomena for jackfruit drying, this work focuses on presenting the drying and shrinkage kinetics behaviour through the development of a mathematical model. Two distinct models were developed, each considering the presence or absence of shrinkage phenomena. Model validation was carried out by comparing the predicted results with experimental data from drying tests conducted at 60 °C, and model accuracy was evaluated through statistical error analysis. In the shrinkage-induced model, the shrinkage exhibited a linear relationship with drying time, as the moisture content decreased from 5.25 to 0.47 kg/kg on a dry basis when the temperature increased to 54 °C. Notably, the shrinkage-induced model demonstrated superior performance, displaying low mean absolute error (MAE) values—0.27 kg/kg on a dry basis for moisture content, 2.07 °C for temperature variation, and 0.04 for shrinkage, when compared to the model without shrinkage. Furthermore, the mean relative error (MRE) values for the shrinkage-induced model were 45.71% and 33.33% lower than those of the model without shrinkage for average moisture content and temperature, respectively. The findings of this study provide valuable insights for the food drying industry, offering new knowledge about drying kinetics and shrinkage characteristics that can contribute to the development of energy-efficient drying systems.