Improving prediction of temperature profiles of packaged food during retort processing

Abstract A one-dimensional (1D) apparent position (AP) numerical solution (APNS) method was previously proposed to predict the evolution of temperature at the slowest heating point (SHP) of canned food in any shaped container during retort processing. In this study, the APNS method was implemented in a two-dimensional (2D) computational domain in a conductive cylinder that provides a contour of AP for the SHP instead of a single AP in the existing 1D method, enabling the selection of the optimal AP that could substantially improve the prediction accuracy of the APNS method. The 2D method was implemented in a web-based software tool. This tool provided a perfect prediction of a simulated product temperature profile of a conductive canned food in a truncated cone-shaped container, and reasonably good predictions of experimentally measured product temperature profiles of canned food in different shaped containers subjected to natural convection or mixed convection/conduction at non-constant heating temperature.