Cherry refers to traditional fruit crops grown in Ukraine. Its value lies in its precocity, winter hardiness, stable yield, early fruits ripening and unpretentiousness to soil conditions. One of the main requirements for modern varieties of cherries is the high yield. A prerequisite for successful cultivation of cherries is to select varieties that meet local climate.
Therefore, determining the characteristics of cherry reactions to the current agro-climatic conditions of the Southern Steppe zone of Ukraine and identifying the main weather factors that affect the crop yield is an actual question.
The purpose of the research was to establish objective agro-climatic indicators that have an impact on cherry yield in the Southern Steppe zone of Ukraine and to create a mathematical model of crop yield based on the identified stress factors.
To achieve this goal, we performed correlation and regression analyzes: the strength of correlation relationships between agro-climatic indicators and crop yield was calculated; determined a set of weather factors that significantly affect cherry yield; the obtained equations for the dependence of the average yield of cherries on the stress factors that will help to predict the parameter under the action of objective environmental stress factors.
During the research 20 paired correlation dependencies were investigated in the stages: vegetation period, flowering, fruit ripening and harvesting. For ten weather factors their influence on the cherry yield indicators for the period 2007-2019 was determined. A strong correlation (r = 0.68… -0.86) with cherry yield is set for the following factors: the sum of active temperatures during the growing season (until the fruit ripening stage), average monthly rainfall for August, absolute minimum relative humidity in May; during flowering – the difference between the average maximum and minimum air temperatures, the sum of active temperatures, the sum of effective temperatures, the hydrothermal coefficient (HTC), the sum and the total number of days with precipitation.
When constructing a regression model of the dependence of the Y cherry yield on the factors of weather conditions (Xi, where i=1..10)a large number of factors were insignificant at the same time a large value of the coefficient of determination R2=0,99580.
The regression model of the dependence of the Y cherry yield on the factors of weather conditions looks like:
Unambiguously the best model by all criteria was not found. Therefore, it is decided to determine the most effective model based on practical feasibility. It was chosen the model with, firstly, the smallest value of insignificant factors and, secondly, the highest value of the indicator AIC.
This model is:
The generalized coefficient of determination is equal R2adjusted=0,996, which indicates a significant correlation of the selected factors with the indicator Y (cherry yield). The value of statistics when checking the adequacy of the model by Fisher’s criterion F=84,44 at a value p-value=6,898∙105, which indicates the adequacy of the model at the level of significance α=0,05.
The above equation is generally statistically significant. The described dependence of cherry yield on stressful weather factors may serve as a basis for some management decisions and the resulting regression equation can be used to build statistical forecasts.
Keywords: yield, cherry, weather factors, multifactorial model, temperature, precipitation, humidity.
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