Identification of typical weather conditions in statistical observations to simulate production functions of winter wheat

The paper deals with the issue of building a regression model of winter wheat yield depending on heat and moisture supply. Such models are recommended to be built separately for each typical outcome of random weather conditions of the growing season. The authors propose an algorithm to identify typical weather outcomes over the years of observations, divide the statistical sample into groups and further evaluate the regressions. To identify outcomes, analysis was made of hydrothermal coefficient during the critical period ofplant development, as well as the deviations of average daily temperatures and the amount ofprecipitation over the months of the growing season. The authors developed an algorithm in processing statistics of experiments with winter wheat, which were performed at the Kaluga Research Institute of Agriculture from 1967 to 1999. They demonstarated production functions of winter wheat depending on the levels of nitrogen nutrition, calculated for weather conditions with insufficient, normal, and excessive moisture supply. The level of nitrogen nutrition is represented by an integrated indicator of the amount of nitrogen available to plants from all sources (soil, crop-root residues of the forecrop, organic and mineral fertilizers), taking into account utilization factors. Based on the analysis of production functions, it was shown that in the Kaluga region under conditions of normal moisture supply, the maximum yield of winter wheat of 4.75 t/ha is achieved at a nitrogen nutrition level of200 kg/ha; with low moisture provision, the maximum yield of 4.31 t/ha is achieved at a nitrogen supply level of195 kg/ha, and with excessive moisture supply, the maximum yield of 4.04 t/ha is achieved at a nitrogen supply level of 175 kg/ha.

продукционные функции озимой пшеницы, регрессионные модели урожайности, случайные факторы тепло- и влагообеспеченности, типовые исходы погодных условий, winter wheat production functions, crop yield regression models, random factors of heat and moisture availability, typical weather outcomes

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