In zones of deficiency of natural moisture (Krasnodar, Stavropol territories, Saratov, Volgograd, Astrakhan regions) high yields of potatoes and vegetables can be obtained only on irrigated lands. In zones of unstable natural moisture (Central Black Earth region, Central region, Altai territory) irrigation reclamation ensures stable and high yields of these crops. From 2005 to 2020, the area of irrigated lands in Russia increased from 4.55 to 4.63 million ha. Irrigated areas were mainly increased due to vegetable fields. Remote sensing technologies for agricultural land are beginning to be used on irrigated lands. The signals of the frequency channels are used to determine the normalized difference vegetation index NDVI, the moisture index of the Earth's surface LSWI. The known technologies do not allow remotely setting the timing of watering vegetables and potatoes. The proposed technology includes the creation of marker plots, the establishment of the timing of irrigation of the irrigation array according to the NDVI indices of plant sounding of the marker plot. Place at least one marker plot per 100 hectares. The area of the marker plot is not less than 200 m2. The rate of application of nitrogen fertilizers on the marker plot is 50–70% higher than the rate of application of fertilizers on the rest of the irrigation area. In the marker plot, there is an intense wilting of plant leaves with an NDVI less than 0.4. At this moment, watering of the entire irrigation array is scheduled. The features of the technology are shown on the results of mathematical modeling of the dynamics of NDVI, soil moisture on the marker plot and the irrigation array in the Saratov region. Crop – potatoes, fertilization rates on the irrigated array – N40P30K35, on the marker plot – N65P30K35, yield – 39 t/ha, chestnut soils, medium loamy, climatic indicators are average long-term. Determination of the NDVI index based on sounding signals, setting the timing of irrigation is performed using data from a gradient soil moisture meter and artificial intelligence training technology for an irrigation control system. A software and instrumental complex including a marker section, a gradient moisture meter and an artificial intelligence of the irrigation control system will ensure environmental safety and high efficiency in the production of potatoes and vegetables.
Key words: potatoes, vegetables, irrigation, remote sensing, marker plot, gradient moisture meter, artificial intelligence, irrigation control
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