IFDC Modelling and Mapping Information System
The publication discusses the importance of spatial analyses in determining the appropriate use and amount of fertilizers for different soil types, crops, weather conditions, and socio-economic factors. The research aims to optimize nutrient use efficiency, logistics, fertilizer value chain, and marketing strategies while assessing regional and national production volumes. The study utilizes legacy and new data, crop-soil modelling, advanced statistics, and machine learning to provide location and crop-specific fertilizer recommendations, yield predictions, and production volumes. Spatial mapping using machine learning and geostatistical methodologies is utilized to make baseline maps and adjust them with increasing data points. Soil chemical and physical properties, weather conditions, and fertilizer yield responses are analyzed to determine the appropriate fertilizer recommendation rates. The analysis provides insights into the optimal NPK composition and application rates for different soil types and crops and helps to identify the drivers for variability in crop yields.
Weather condition, Soil mapping, Agriculture, Soil properties