Numerical studies on thermal processing of solid, liquid, and solid–liquid food products: A comprehensive analysis

Abstract This article uses the computational fluid dynamics approach to analyze the thermal processing of solid, liquid, and solid–liquid food products. To understand the underlying transport phenomena, microbial deactivation, and nutrient degradation, three food products, viz. lamb (solid), grapefruit juice (liquid), and paneer cubes in a brine solution (solid–liquid), are studied. The food products are processed under constant retort temperature for fixed durations of heating and cooling. The numerical models are solved to obtain the velocity and temperature distribution inside the food products. The solid food exhibits a low heating rate at the slowest heating zone due to the absence of convection. The solid–liquid food shows uniform microbial destruction with a standard deviation of 2.27 min in the lethality distribution. The maximum possible average retention of nutrients is 90.36% (at 80°C and 59.81 min) and 60.64% (at 125°C and 21.30 min) for liquid and solid–liquid foods, respectively. However, the average thiamine retention in solid food monotonically decreases in the temperature range of 120–140°C. Practical Applications The computational fluid dynamics approach offers practical applications in optimizing food processing parameters, improving thermal processing equipment, and preserving nutrient quality in diverse food products. The analysis of the velocity and temperature distribution enables the design of more efficient heating and cooling methods, assisting food processors in determining the ideal duration and temperature to achieve microbial destruction while minimizing nutrient degradation. Furthermore, this approach facilitates the evaluation and enhancement of thermal processing equipment by identifying areas of slow heating or inadequate heat transfer, ultimately leading to improved design and more uniform processing. Understanding nutrient retention during thermal processing is vital for maintaining nutritional quality. The findings of this work could be applied to develop guidelines for preserving nutrients in specific food products. In summary, the computational fluid dynamics approach enhances food safety by optimizing processing parameters, improving equipment design, and preserving nutrients in solid, liquid, and solid–liquid food products.