STATISTICAL EVALUATION OF ARRHENIUS MODEL AND ITS APPLICABILITY IN PREDICTION OF FOOD QUALITY LOSSES

To minimize quality losses occurring during processing and storage and to predict shelf-life, quantitative kinetic models, expressing the functional relationship between composition and environmental factors on food quality, are required. The applicability of these models is based on the accuracy of the model and its parameters. In this paper, the calculation of the Arrhenius parameters and the accuracy of the derived model were compared, using three statistical methods, namely: linear least squares, nonlinear least squares and weighted nonlinear least squares. Results indicated that the traditional two-step linear method, was the least accurate and the derived energy of activation and the pre-exponential factor had the largest confidence interval. The latter was shown to have a profound effect on the precision of the calculated rate constant and the predicted shelf life. Based on previous reports that indexes of deterioration