Acta Scientiarum Polonorum Technologia Alimentaria

Background. Artificial neural networks (ANN) are a common mathematical tool widely used in many research fields. Since they are applicable to non-linear relationships and do not require preliminary assumptions, they are a particularly promising tool in relation to meat processing. Thermal denaturation contains    a lot of information concerning the quality of meats. The aim was to create a methodology of kinetic analysis to obtain a quick and accurate tool for meat protein denaturation in non-isothermal conditions based on   The Coats-Redfern equation with the use of ANN.

Materials and methods. The analyses were carried out on samples of minced samples of Longissimus dorsi (pork). Thermal properties were determined using the differential scanning calorimetry (DSC) method with a Q100 TA Instruments apparatus. The data obtained was processed using the artificial neural network module in Statistica 13.0 software.

Results. The following models fit well with experimental data: F1 and F2 (r = 0.99, F Snedecor’s F statistics 836943.20 and 971947.41 respectively). Deviations from experimental conversion degrees were higher for model F2, while for F1, good conformity was obtained across the whole range of α(T).

Conclusions. This preliminary study confirmed that methods of traditional kinetics of processes in non-isothermal conditions based on the Coats-Redfern equation can be successfully applied to meat protein denaturation. The method of kinetic analysis allows a high level of accuracy to be achieved and meets the requirements of an efficient engineering tool.