Mikhail Y. Puchkov1; Alexander V. Koshkarov2; Maksim A. Lysakov1; Konstantin V. Isaev3; Elena G. Loktionova4; Sergey D. Fomin5,6; Elena S. Vorontsova6,7 and Vasily M. Strukov1
1 Astrakhan State University, Educational and Experimental Farm, 414056 Astrakhan, Russian Federation
2 Astrakhan State University, Department of Information Technologies, 414056 Astrakhan, Russian Federation
2 Precaspian Agrarian Federal Scientific Center of the Russian Academy of Sciences, 416251 Astrakhan region, Russian Federation
4 Astrakhan State University, Department of Ecology, Environmental Management, Land Management and Life Safety, 414056 Astrakhan, Russian Federation
5 Volgograd State Agrarian University, 400002 Volgograd, Russian Federation
6 All-Russian Research Institute of Irrigated Agriculture, 400002 Volgograd, Russian Federation
7 Volga Region Research Institute of Manufacture and Processing of Meat-and-Milk Production, 400131 Volgograd, Russian Federation
Puchkov, M.Y., Koshkarov, A.V., Lysakov, M.A., Isaev, K.V., Loktionova, E.G., Fomin, S.D., Vorontsova, E.S. & Strukov, V.M. (2020). Regression model of the formation of pasture with programmable productivity of the arid lands of the South-East European of Russia. Bulg. J. Agric. Sci., 26 (5), 919–926
Recently, due to the changing climatic parameters such as the distribution of atmospheric precipitation and the annual cycle of temperature, there has been a change in the amount of formation of soil moisture reserves. Since the productivity of pasture ecosystems in arid territories is limited by the amount of soil moisture, the modeling of its formation has great practical significance in productivity forecasting. The objective of the study is to create a mathematical model for determining the timing of the formation of pasture agrophytocenoses with programmable productivity, depending on atmospheric processes (air temperature, depth of precipitation and relative air humidity). The main research method is the use of an empirical-statistical approach in modeling a complex atmosphere-plant-soil system. The research resulted in the obtention of regression models, that describe the state of soil moisture reserves and the productivity of pasture ecosystems: we obtained the regression equation for the formation of a soil moisture reserve (0–20 cm), depending on meteorological factors: moisture reserve = 37 – 0.426t, t – air temperature (°C); we obtained equations of formation of soil moisture reserves due to the relative air humidity and the amount of atmospheric precipitation: the moisture reserve = -75 + 1.369f + 0.287R, where f – relative air humidity (%), R – amount of precipitation (mm). It is clear that there is a direct correlation between the formation of soil moisture reserves with the relative air humidity and the amount of precipitation; in the regression equation of the following form we obtained the connection of pasture agrophytocenoses from the moisture reserve in the soil layer of 0–20 cm: the yield of dry matter (t/ha) = 1.9758 + 0.0049w – 0.0069R, where w – moisture reserve in the soil layer 0–20 cm (mm).