MODELING AND OPTIMIZATION OF CONSTANT RETORT TEMPERATURE (CRT) THERMAL PROCESSING USING COUPLED NEURAL NETWORKS AND GENETIC ALGORITHMS

Abstract

ABSTRACTCoupled artificial neural network (ANN) models and genetic algorithms (GA) were applied for developing prediction models and for optimization of constant temperature retort (CRT) thermal processing of conduction heating foods. ANN prediction models were developed for process time (Pt), average quality retention (Qv), surface cook value (Fs), equivalent energy consumption (En), final temperature difference (Tg) at can center, and lethality ratio (p, heating/total lethality). The processing conditions as inputs for ANN models were as follows: retort temperature (RT = 110–140C), thermal diffusivity (α= 1.1–2.14*10−7m2/s), volume of can (V = 1.64–6.55*10−4m3), ratio of height to diameter of can (Rdh= 0.2–1.8), total desired lethality value (F0= 5–10 min) at can center and quality kinetic destruction parameters: decimal destruction time (Dq– 150–300 min) and their temperature dependence (zq= 15–40C). The data for training and testing ANN models were obtained from a finite difference computer simulation program. A second order central composite design was used for constructing the experimental data for training ANN models, while an orthogonal experimental design with 6 factors and 3 levels was used for the generalization of trained ANN models. ANN model linked Genetic Algorithms (GA) were employed for searching for the optimal quality retention and corresponding retort temperature, and for investigating the effects of main processing factors. ANN‐based prediction models successfully described the various outputs of CRT thermal processing (correlation coefficients: R2 > 0.98; relative errors: Er ≤ 3%). The coupled ANN‐GA models, verified under several typical processing conditions, could be effectively used for optimization of CRT thermal processing. The main processing conditions and their interactions in the order of their importance with respect to the optimal quality retention and corresponding retort temperature were: V >zq >Rdh >; and zq >Fd > Rdh >V, respectively.