Abstract
To improve the sustainability of grain production at the regional level, reliable and operational methods for monitoring the state of crops during the entire growing season, as well as methods for early prediction of not only yield, but also the quality of winter wheat grain are needed. For this, satellite data of the seasonal dynamics of the vegetation index NDVI are used, which allows one to evaluate the physiological state of crops and the size of the future crop. The purpose of research is to identify the relationship between the data of remote sensing of the Earth and winter wheat quality indicators for the conditions of the Stavropol Territory. This work was carried out in the Department of Plant Physiology of the North-Caucasian Federal Scientific and Agricultural Agrarian Federal State Budgetary Scientific Institution together with the Space Research Institute of the Russian Academy of Sciences. Data on grain quality in the Stavropol Territory for the period from 2003 to 2018 were provided by the Stavropol branch of the Federal Center for the Safety and Quality Assessment of Grain and its Processing Products. Vegetation indices NDVI obtained using the VEGA service IKI RAS. An analysis of the data showed that the maximum correlation coefficient of NDVI with the amount of grains of the 2nd and 3rd classes was 0.83 with a minus sign in the phase of formation of the grain. With the amount of food grain, the maximum feedback is observed in the phase of the resumption of spring vegetation (correlation coefficients -0.62). The dynamics of the forecast of winter wheat grain quality in the Stavropol Territory in 2018 has a fairly wide range of changes, which is associated with the conditions of plant growth and development. For the conditions of the Stavropol Territory, the closest correlation between the vegetative index NDVI of winter wheat crops and quality indicators is observed from 10 to 22 calendar weeks. When analyzing the relationship of quality indicators with average NDVI values in different months of the growing season, close feedback was revealed for April, May, June, and also for the period April-May.
Highlights
To improve the sustainability of grain production at the regional level, reliable and operational methods for monitoring the state of crops during the entire growing season, as well as methods for early prediction of yield, and the quality of winter wheat grain are needed
The purpose of research is to identify the relationship between the data of remote sensing
An analysis of the data showed that the maximum correlation coefficient of NDVI
Summary
USE OF REMOTE SENSING EARTH DATA FOR REGIONAL ASSESSMENT OF WINTER WHEAT GRAIN QUALITY
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