ASPECTS OF OPTIMIZATION OF FACTORS AFFECTING RICE PRODUCTIVITY IN THE KRASNODAR TERRITORY

The standard technology of irrigation of rice paddies by flooding is the most water-intensive. The economic efficiency of land reclamation projects can be calculated only on the basis of a multifactorial analysis of the impact of irrigation and economic factors in rice cultivation on its productivity. The object of research was a section of the Petrovsko-Anastasievskaya irrigation system in the Krasnodar Territory. The rice variety, the method of sowing, the depth of seed embedding, and the irrigation regime were selected as the variables. Crop rotation, fertilization, the role of irrigation regime in different phases of rice plant development, and a number of other factors were not considered at this stage of the research. The purpose of the research was to develop a methodology for calculating the optimal irrigation rate, which ensures the greatest economic effect from rice cultivation, considering the rice paddy fields flooding regime, varietal characteristics of the crop and the method of sowing in the Krasnodar Territory. To solve this problem, an Excel version of the software module was developed, which allows determining the irrigation rate and a set of the above-mentioned factors leading to the most cost-effective solution and appropriate design recommendations. The Pearson curve of type I with parameters selected based on field and laboratory research materials was adopted as the basic dependence of yield on irrigation rate. In the simulation mode, three operating factors are considered: the irrigation regime; the method of sowing rice, and the rice variety. The minimum set of scenarios left for modeling the situation was 18 variants, which led in the considered example to an irrigation rate of about 20 thousand m3/ha under conditions of combined irrigation of medium-ripened rice varieties. The direction of further research is related to the substantiation of basic dependence of yield on irrigation rate, the expansion of the number of influencing factors and the refinement of single cost indicators.