Abstract
Today, the effective and sustainable operation of agricultural production requires the deployment of information systems using a set of digital technologies. Predictive analytics in these systems shall take the dominant position since it is difficult or almost impossible to make a correct decision on its management without forecasting the transformation of conditions, objects and processes occurring in agriculture. The paper deals with a decision support system for use by specialists in crop production. The guidelines of farm management on the basis of key nodes of production decision-making are highlighted over the entire period of agronomic work. The structure includes 12 key nodes, 28 models, 1 database and 415 agricultural indicators available to the user. The system issues a document with a recommendation to the producer for each node. On the basis of forecast models of agrometeorological resource and spring wheat yield, planned models are built. They allow calculating the time, analyzing the economic performance and interaction of machinery in various agro-mechanical activities throughout the agricultural season. Databases of crop varieties (hybrids), pesticides and fertilizers relevant to the territory of the Russian Federation have been developed. Models and methods were tested on one of experimental farms of Novosibirsk region.
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Riksen, V., Maksimovich, K., Kizimova, T., Galimov, R., Fedorov, D. (2023). Elements of the Decision Support System in the Agricultural Production Processes. In: Ronzhin, A., Kostyaev, A. (eds) Agriculture Digitalization and Organic Production . Smart Innovation, Systems and Technologies, vol 331. Springer, Singapore. https://doi.org/10.1007/978-981-19-7780-0_34
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DOI: https://doi.org/10.1007/978-981-19-7780-0_34
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