Digital Technology in Agriculture: An Approach to Modelling Crop Productivity on Trace Elements Contaminated Soil

Abstract

The article focuses on the use of climate data in modelling crop productivity and highlights the im-portance of continuous incoming meteorological infor-mation in predicting crop yields. The purpose of Article is to evaluate the challenges and potential of utilizing big data using climate data as an ex-ample for modelling crop productivity on contaminated sites with trace elements. The “MiscanCalc” and “Group Method of Data Han-dling” were developed to predict crop yields on soils con-taminated with toxic elements using meteorological data. These models evaluate the impact of climate data on bio-mass production, ripening and harvest periods, estimate future crop yields, and identify the predictors that have the greatest influence on these indicators.