INTELLIGENT SUPPORT SYSTEM FOR DECISION-MAKING IN PREDICTING THE NITROGEN STATUS OF WHEAT BASED ON SATELLITE, METEOROLOGICAL, AND SOIL DATA

Abstract

Efficient nitrogen management is a key challenge of modern wheat production, especially under conditions of spatial heterogeneity of soils and climatic variability. This study presents the development and testing of an intelligent decision support system for forecasting the nitrogen status of wheat based on the integration of remote sensing data, meteorological information, and soil characteristics. Vegetation indices derived from satellite imagery, together with aggregated weather parameters and soil properties, were used to form an input feature vector for each field. The nitrogen status indicator was calculated, normalized, and interpreted using a threshold-based approach to generate management recommendations. Experimental calculations for fields in the Kostanay region demonstrated the sensitivity of the proposed system to temporal and spatial changes in crop conditions. The results confirm the practical applicability of the developed approach for supporting nitrogen management decisions in precision agriculture.