Texture changes during thermal processing of food: experiments and modelling

TL;DR

This study develops and experimentally validates a model to predict how moisture content influences the Young's modulus and texture of hygroscopic foods during thermal processing, highlighting the importance of test standards.

Contribution

The paper introduces a physics-based model for predicting local and effective Young's moduli during thermal food processing, validated with experiments on potato samples.

Findings

Young's modulus varies up to 54% with strain rate.

Model accurately predicts drying behavior but deviates during frying.

Sensitivity of texture parameters emphasizes need for standardized testing.

Abstract

Texture is an important attribute in the quality assessment of processed food products. Youngs modulus is an indirect measure of texture. During thermal treatment of hygroscopic foods, parameters such as moisture content significantly affect Youngs modulus. However, the sensitivity to these parameters has not yet been quantified in terms of the stress strain behaviour. We have built an experimentally validated model to address this gap. This paper presents the stress strain behaviour and its sensitivity towards various parameters. Experiments are conducted with potato samples for stress strain behaviour, parametric sensitivity analysis, estimation of initial and critical values of moisture content and Youngs modulus. We found that the Youngs modulus and the ultimate strength vary by as much as 54 percent and 29 percent depending on the rate of applied strain, indicating the need for test standards. Further, we propose a model to predict the local Youngs moduli as a function of moisture content, and a relationship between these and the effective Youngs modulus. While model results agree well for drying, they deviate by as much as 16 percent from experiments for frying, indicating the necessity of incorporating additional physics. We expect this work to serve as a crucial step towards the physics based prediction modelling of local and effective Youngs moduli during thermal processing of food products.