Online Event
September 01-03, 2022 | Online Event
GPMB 2022

Grain yield forecasting based on vegetative index data

Sergei Rodimtsev, Speaker at Plant Science Conferences 2022
Orel State University named after IS Turgenev, Russian Federation
Title : Grain yield forecasting based on vegetative index data


To predict the yield, some current indicators of the vegetation process are used, which are associated with the productivity of the crop. The results of the methodology for predicting grain yields based on the maximum value of the NDVI index, when the heading phase has begun, are proposed. The seasonal dynamics of NDVI in the phases of crop development was studied, peaks of NDVI values were noted in the heading phase of crops. Prognostic models of crop yields based on polynomial functions have been obtained.

Audience Take Away Notes: 

1. An analysis was made of the dynamics of changes in the vegetation index NDVI, according to long-term studies, for winter wheat and spring barley at the production sites of the Research and Production Center "Integration" of the Oryol State Agrarian University.

2. By studying the seasonal dynamics of the NDVI vegetation index by phases of crop development, peaks of NDVI values ??were noted in the heading phase of crops.

3. Correlation coefficients between the maximum seasonal values ??of NDVI indices and productivity were 0.79 and 0.75 for winter wheat and spring barley, respectively.

4. Received predictive models of crop yields based on polynomial (second degree) functions.

  • The results of the study give an idea of the dependence of yield properties on the values of the vegetative index in a particular phase of plant development. This was obtained for winter wheat and spring barley, in the conditions of central Russia.
  • This may be of interest for a comparative assessment of prognostic indicators of crop yields in specific soil-climatic zones.
  • These results can be used in the preparation of agricultural students. As an example of the implementation of one of the methods for predicting crop yields.
  • Specific prognostic mathematical models are given. They can be used for crop planning on farms.
  • Such forecasts are very relevant in unfavorable years, when a significant crop shortfall is expected. Usage
  • forecasts allows you to organize preventive measures to
  • damage minimization. In favorable years, to determine the possible volumes
  • grain exports and markets. They are an important link in
  • management decision support system in the agrarian
  • sector.
  • Statistical data of long-term estimates of the dependence of yield on the vegetative index may be useful. In addition, illustrative material can be used in presentations for student learning purposes.


Doctor Rodimtsev studied engineering at the Highway Institute of the city of Tashkent, Uzbekistan. He graduated from graduate school at the Oryol Agrarian University in 2001. In the same year he defended his Ph.D. thesis at the Russian Agrarian University. In 2008, in the same place, he defended his doctorate in agricultural mechanization. He worked at the Oryol Agrarian University as a teacher, head of the department, director of the institute, vice-rector for scientific work. He currently works at the Department of Machine Service and Repair of Oryol State University. More than 180 scientific papers have been published.