In the conditions of the Southern Steppe zone of Ukraine, the receiving high yields of garden crops depends not only on the complex of agro-technical and management measures. Natural and climatic factors have a significant, and sometimes decisive, impact on productivity. Cherry culture is a business card of stone bones in the southern region of Ukraine. Given the above, the definition of the ecological suitability or discomfort of individual weather factors for cherry yields in the Southern Steppe zone of Ukraine remains an important issue for the research by scientists.
The purpose of the research was to substantiate the effect of meteorological factors on the cherry yield in the conditions of the Southern Steppe zone of Ukraine and to create a mathematical model of the crop yield based on the identified stress factors.
The article describes the priority meteorological factors for increasing the sweet cherry yield in the conditions of the Southern Steppe zone of Ukraine. Using the methods of mathematical statistics, an agricultural assessment of the effect of weather conditions on the cherry yield during the period 2008-2018 was obtained. During the correlation analysis it was found that the yield is affected by a complex of hydrothermal conditions (factors). The 202 factors were selected for the study, which may affect cherry yield changes. The average correlation relationships are set for 78 of 202 factors in the range of r – 0.33… 0.66.
The nine stress factors as components of a common set of weather conditions in the region, which affect the sweet cherry yield are revealed by the results of correlation analysis.
The results of the correlation analysis revealed nine stress factors as components of a holistic complex of weather conditions in the region that affect the sweet cherry yield. These include: the absolute minimum air temperature in April and May, the sum of active temperatures in the spring period, the total number of days with precipitation in December and during flowering; the sum of precipitation during flowering period, hydrothermal coefficientin flowering period, the average minimum temperature during flowering period, the average maximum temperature in March.
The methods of variation statistics were used in the study during the analysis and processing of experimental data, as well as in predicting the final conclusions. Using the linear dependence function: Y = a0 + a1X1 + a2X2 + … + AnXn allowed us to formulate a multifactor model:
The development of the latter one made it possible to predict the sweet cherry yield depending on the influence of environmental stressors.
Keywords: yield, sweet cherry, weather factors, multifactorial model, temperature, precipitation, humidity.