A set of economic and mathematical models for assessment of agricultural crop cultivation technologies

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Abstract

Research objectives. The paper describes the process of development of a set of mathematical models for assessment of agricultural production technologies to be used as the basis of a software complex module for managing technological processes in crop farming. The reported study was funded by RFBR according to the research project № 18-37-00148. Methods. Given the specifics of management in agriculture, it is worth noting that the lack of objective information across the production cycle in crop farming and the subsequent misalignment with an optimum technology results in overshooting labour and material costs, lost profits for the enterprise or even losses. These issues have to be addressed through advanced studies of economic and mathematical models and methods for analysis and assessment of economic efficiency of agricultural crop cultivation technologies and the development of a comprehensive automated information support system for decision-making in crop farming management. Results. A methodology is proposed for selecting economically efficient technological processes in crop farming, involving the sequential application of results obtained through the analysis of technological process criteria by the methods of binary decision matrices, cobweb diagrams and the matrix assessment model, taking into account their orientation at the economic performance of crop farming. Practical significance and applicability of results. The authors developed a complex of software and information support and assessment of technological processes in crop farming, with experimental trials showing improved efficiency of crop farming production through the well-reasoned selection of agricultural crop cultivation technologies.

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Tkachenko, V. V., Lukyanenko, T. V., & Shadrina, Z. A. (2019). A set of economic and mathematical models for assessment of agricultural crop cultivation technologies. International Journal of Recent Technology and Engineering, 8(2), 3829–3833. https://doi.org/10.35940/ijrte.B2464.078219

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