MATHEMATICAL MODELING OF REGIONAL CROP YIELD UNDER CLIMATE CHANGE (BASED ON DATA FROM THE KIROV REGION)

Abstract
Due to climate change, crop production in the regions is facing gradual changes in the growing
conditions of previously zoned varieties and crops, as well as the increasing impact of extreme
weather events. Under these conditions, modeling and forecasting of crop productivity in response to
natural and climatic factors has become the urgent research field. This paper presents methodological
aspects of constructing a regression model for crop yields based on these factors, using the data of
Kirov Region. Using Statistica10.0 software, mathematical models have been developed for regional
yields of spring and winter wheat, oats, winter rye, and spring barley. The method used to select model factors is characterized by visual assessment of the specific impact of each factor on yield, and
it is applicable to solving problems of analysis and forecasting using historical regional data series.

Keywords: time series, trend, correlation and regression analysis, Kirov region, spring and
winter wheat, oats, winter rye, spring barley