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STATISTICAL EVALUATION OF ARRHENIUS MODEL AND ITS APPLICABILITY IN PREDICTION OF FOOD QUALITY LOSSES
Author(s) -
COHEN ELI,
SAGUY ISRAEL
Publication year - 1985
Publication title -
journal of food processing and preservation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.511
H-Index - 48
eISSN - 1745-4549
pISSN - 0145-8892
DOI - 10.1111/j.1745-4549.1985.tb00726.x
Subject(s) - arrhenius equation , statistics , non linear least squares , least squares function approximation , nonlinear system , mathematics , constant (computer programming) , exponential function , confidence interval , econometrics , quality (philosophy) , biological system , explained sum of squares , computer science , chemistry , activation energy , mathematical analysis , physics , quantum mechanics , biology , philosophy , organic chemistry , epistemology , estimator , programming language
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