doi: 10.15389/agrobiology.2020.3.451eng

UDC: 631.5:519.3

Supported financially from the federal budget under the Agreement on subsidies of December 10, 2019 No. 05.607.21.0302, the project unique identifier RFMEFI60719X0302



V.P. Yakushev, V.V. Yakushev, V.L. Badenko, D.A. Matveenko,
Yu.V. Chesnokov

Agrophysical Research Institute, 14, Grazhdanskii prosp., St. Petersburg, 195220 Russia, e-mail,,,, (✉ corresponding author)

Yakushev V.P.
Matveenko D.A.
Yakushev V.V.
Chesnokov Yu.V.
Badenko V.L.

Received December 16, 2019


In the context of changing socio-economic, natural and climatic conditions, there is a need for effective management tools to adapt agricultural activities. Such tools are farming systems, which are a set of interconnected agrotechnical, reclamation and organizational measures aimed at the efficient use of agrolandscapes, preservation and improvement of soil fertility, and obtaining high crop yields. The efficiency of agricultural production can be improved by using various forecasting methods based on the use of mathematical models. In crop production, statistical and dynamic simulation forecast models have been developed. The latter are more accurate and adaptive and allow you to get an answer to the question about the development of argoecosystems in the conditions of changing climatic conditions and the application of various agricultural measures. The paper provides an overview of methodological approaches for predicting crop productivity based on mass calculations of a simulation model of an agroecosystem in a geoinformation environment that can be used to justify farming systems. The analysis of the state of the problem is carried out, which presents the main current trends in the use of simulation models of agroecosystems in decision support systems for management in agriculture in general and in the support of farming systems in particular. Existing approaches and methods are classified based on spatial coverage into macro-scale, meso-scale, and micro-scale modeling methods. In the general case, these different methods require different methodological approaches are presented in the paper. The relevant basic methods and approaches for creating a universal environment for mass calculations of dynamic models of agroecosystems for different levels of spatial coverage are also presented. The analysis of the very important issue of choosing a set of control (base) points is presented where model calculations will be performed that should belong to real agricultural fields and sufficiently reflect the diversity of soil and climatic conditions of the region under consideration. Also presented are the requirements for a universal modeling environment for carrying out calculations on different models from various suppliers.

Keywords: agroecosystems, simulation modeling, mass calculations, forecasting, geographic information systems, farming systems.



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