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DEVELOPMENT OF OPTIMAL CROP PRODUCTION MODEL CONSIDERING EXISTING NATURAL-CLIMATIC RISKS INCREASING CROP YIELDS

Aigul ShaimerdenovaKazakh National Agrarian Research University, Republic of KazakhstanLG AGAPITOVADepartment of Economics, Organization and Management of Agro-industrial Complex, Northern Trans-Ural State Agricultural University, Russian FederationА. В. БоброваSouth Ural State University (National Research University), Russian FederationYergali S. AkhmetovDepartment of Land Management and Cadastre, M.H. Dulati Taraz Regional University, Republic of KazakhstanVA SINYUKOVFaculty of Management and Technology, Khabarovsk State University of Economics and Law (KSUEL), Russian FederationPN SHARONINThe Russian Presidential Academy of National Economy and Public Administration, Russian FederationAG DOBROVOLSKYDepartment of Economic Cybernetics, Kuban State Agrarian University named after I.T. Trubilin, Russian FederationD.I. RyakhovskyFinancial University under the Government of the Russian Federation, Russian FederationEE KRASNOVSKIYBauman Moscow State Technical University, Russian FederationAD TENFederal Research Center of Agrarian Economy and Social Development of Rural Areas -All-Russian Research Institute of Agricultural Economics, Russian Federation
2023en
ABI

Аннотация

Contemporary agriculture is a fertile ground for the effective use of economic and mathematical models, which can be evaluated to unwind several problems with characteristic optimization features: multiple solution opportunities and freedom of choice, limited production resources, and efficiency valuation. The presented study aims to develop a model of optimal crop production structure under the existing weather risks in the agricultural management system. The article reviews the basic theoretical concepts in optimizing the production structure of agricultural enterprises, examines the specific features of crop production, proves the influence of weather and climate conditions on forming the production structure, demonstrates the use of correlation and regression analysis for trend modeling and forecasting of crop yields, and offers suggestions for determining the optimal production structure. The study concludes that multivariate forecasting helps optimize management in economic organizations and ensure their development under the variability of natural conditions. Natural and climatic conditions significantly impact the development of production structures in agricultural enterprises, along with nature acting as an innate participant in the game.

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