MODELING OF GRAIN YIELD UNDER HARD-TO-PREDICT CLIMATE

Abstract

The features of the formation of grain yields in field crop production are presented, climatic indicators are highlighted as the main factors of instability of agricultural production. On the materials of agricultural organizations of the Glazov region and long-term observations of the Glazov meteorological station Udmurtia shows the dependence of crop productivity not only on the purposeful work of a person, but also, to a large extent, on climate conditions during the period of active growth of cultivated crops. Particular attention is paid to the temperature regime and the regime of moisture supply of plants during the growing season from May to August. It has been established that due to the application of mineral fertilizers, grain yields can be increased by an average of 66 kg per kilogram of fertilizers applied.Various regression models are proposed for predictive calculations of future grain harvests, which can also be used for planning when making management decisions. Conclusions were obtained that the ratio of precipitation to average temperatures in the month of June is the most significant of the climatic indicators affecting grain yields. Slightly weaker and with the opposite sign, the influence of the same ratio of climate indicators in May is confirmed. An example of the use of models for agricultural production in the study area is shown. Variants of possible models for a rough assessment of the climatic conditions of future harvests based on the use of neural networks are presented separately, which will justify the plan of agrotechnical measures for the cultivation of grain crops.