%0 Journal Article
%T A New Mathematical Model for Food Thermal Process Prediction
%A Dario Friso
%J Modelling and Simulation in Engineering
%D 2013
%I Hindawi Publishing Corporation
%R 10.1155/2013/569473
%X A mathematical model was developed to correlate the four heat penetration parameters of 57 Stumbo¡¯s tables (18,513 datasets) in canned food: (the difference between the retort and the coldest point temperatures in the canned food at the end of the heating process), (the ratio of the heating rate index to the sterilizing value), (the temperature change required for the thermal destruction curve to traverse one log cycle), and , (the cooling lag factor). The quantities , , and , are input variables for predicting , while , and are input variables for predicting the value of , which is necessary to calculate the heating process time , at constant retort temperature, using Ball¡¯s formula. The process time calculated using the value obtained from the mathematical model closely followed the time calculated from the tabulated values (root mean square of absolute errors RMS = 0.567£¿min, average absolute error = 0.421£¿min with a standard deviation SD = 0.380£¿min). Because the mathematical model can be used to predict the intermediate values of any combination of inputs, avoiding the storage requirements and the interpolation of 57 Stumbo¡¯s tables, it allows a quick and easy automation of thermal process calculations and to perform these calculations using a spreadsheet. 1. Introduction Featherstone [1] indicated that the nutritional value of properly processed canned food is as good as that of fresh or frozen food. To assure a safe canned product with minimal damage to organoleptic quality and nutritional value, it needs to optimize the thermal processing of the product through rigorous calculations [2]. The general method was the first method developed for thermal process calculations [3]. The fundamental concepts on which it was based served as foundation for the development of the more sophisticated procedures [4]. Because the general method lacks the predictive power needed for design purpose, the difficulties associated with this procedure inspired interest in the formula method first proposed by Ball [5]. Over the years, Ball¡¯s formula method passed through rigorous evaluations, simplifications, and improvements [6, 7]. Additional formula methods were later developed by Hayakawa [8] and Steele and Board [9], but Smith and Tung [10], in a study on accuracy assessments of the methods, reported that Stumbo¡¯s tables [7] gave the best estimations of process lethality under various conditions. Although accurate, Stumbo¡¯s method is difficult to computerize because it involves 57 tables, as compared to Ball¡¯s method, where only one table is used. In fact, in
%U http://www.hindawi.com/journals/mse/2013/569473/