Agriculture is the main resource component of food processing enterprises. It is necessary to find lines of contact between industry and agriculture. Such a connection can be seen in the development of cross-cutting scientific and technological areas, which include diverse modeling, the use of advanced planning methods, artificial intelligence (AI) systems and everything that is understood as digital technologies. Small and large businesses are making an active transition to digital technology. Industrial companies are rapidly advancing in the field of AI, investing in research and development in the field of industrial Internet. In this regard, smart agriculture is also coming to the fore. The docking of food processing industry, agriculture and business is the introduction of information technology in the agro-industrial complex (AIC). The comprehensive digitalization of agricultural production, from cultivation, harvesting and storage of crops to its delivery to a processing plant with subsequent processing, is a modern view of doing business. The article discusses the parametric optimization of a two-product workshop for the production of sugar. A mathematical model of the optimization process is proposed, and its numerical solution. The task of parametric optimization is to choose from a set of possible control actions a certain set of alternative options with a constant structure of the technological process. To solve the optimization problem, we used the method of extrapolation of expert estimates with non-transitive preferences.

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This paper suggests the method of utility estimation for certain alternatives based on their pairwise comparison. The pairwise comparison matrix being formed is interpreted as the result of a measurement with random errors. Finally, a numerical example is provided to illustrate operation of the method.

The article is devoted to the study of the problems of reducing the quality of root crops during post-harvest storage in heaps under the influence of harmful microflora. An increase in the productivity of processing enterprises is achieved in two ways: by regulating the microclimate in the formed dumps at the enterprises for processing raw materials; by regulating the delivery of raw materials from the fields for the formation of piles to the territory of enterprises. The subject of research is the process of storing sugar beets at processing plants. The reasons for the loss of beet mass are analyzed. The article describes the use of typical information technologies for solving applied problems of the food industry. As an example of the use of specialized tools and standard means of computer mathematics, the problem of approximating the dependence of temperature in a clump on the growth of colonies of pathogens of clump rot of sugar beet is considered. The initial data was taken from open sources. An example of constructing a mathematical model of the development of pathogens depending on temperature is given. A generalized algorithm for using the nonlinear regression method is presented. To check the quality of the regression model, we used the approximation accuracy coefficient. Various degrees of polynomial approximation are considered. The described technology can be used as a basis for approximating the dependence of the reproduction of pathogens and climatic parameters inside the clamps. This method can be generalized to calculate the intensity of development of other strains of microorganisms.