MODELING AS A METHOD FOR SCIENTIFIC COGNITION OF COMPLEX MEAT SYSTEMS

The paper examines the issues associated with the integration of knowledge in meat product technology + computers + mathematical methods. The possibilities to use a computer system and mathematical methods for an optimal solution to tasks in the field of food biotechnology and meat product technology are demonstrated. The applied software program SSS Bio realized in the computer system was developed and described. Using the one-way analysis of variance, which is one of the system modules, a comprehensive amount of statistical data for interpretation of the results was obtained. The program modules (correlation and regression analysis) allow establishing the model structure and parameters that link quantitative resulting and factorial variables, as well as assessing a degree of their correspondence with the experimental data. This kind of statistical analysis makes it possible to solve the main task of an experiment when the observed and resulting variables are quantitative. Based on the experimental data obtained with the use of the computer system SSS Bio, the mathematical models of moisture binding capacity (MBC), moisture holding capacity (MHC) and fat binding capacity (FBC) in sausage meat were calculated for sausages with isolated soya protein depending on the fat and protein content using the module of multiple regression of the computer system. The obtained stochastic dependence of changes in MBC (Y) on the total protein (X1) and fat (X2) content in sausage meat shows that at the constant level of fat, an increase in total protein favors a growth in MBC of sausage meat. However, a growth in MBC per unit of protein decreases with an increase in the fat amount.