On some models of optimization of crop production under conditions of biological risks

Abstract

The aim of the work is to build and use problems of parametric and stochastic programming to solve problems of optimizing the production of agricultural products under conditions of biological risks. To achieve the goal, two tasks were solved: determining the patterns of variability of some series characterizing possible risks in crop production, and building mathematical models to optimize crop production, taking into account the damage caused by plant pests. The paper proposes models for optimizing the production of crop products under conditions of biological risks. Some indicators of such tasks are described using probabilistic estimates. To optimize the production of agricultural products under the influence of biological risks, mathematical models with probabilistic estimates, as well as a parametric programming model, were built. Examples of approbation of models in the planning of production of crop production are given. The work used materials on the number of rodents, invasions of locust pests for the long-term period 2009-2020. according to the Irkutsk region. In addition, information on the yield of agricultural crops in the municipalities of the southern territory of the region, as well as data on the activities of CJSC Irkutsk Semen, located in the Irkutsk region, are involved. To model series on the number of rodents, areas of distribution of acridoids and the number of their larvae per unit area, methods of probability theory and mathematical statistics were used (technologies for constructing probability distribution laws, regression analysis and assessment of the quality of models). The variability of agricultural crop yields was assessed using the methods of constructing trends and factor dependencies. When optimizing the production of crop products, methods for constructing and solving extreme problems were used. Models of parametric and stochastic programming are proposed. At the same time, the experience of developing applied models for optimizing the production of agricultural products with and without taking into account risks was applied.