Mathematical models of agricultural production management in high risk environments

Abstract

The paper presents an algorithm for modeling the production of agricultural products in the formation of agrometeorological events. Stochastic models of variability of downpours, early snow-fall and crop yields are constructed to assess the likelihood of extreme events. Based on a probabilistic assessment of crop bio-productivity by a normative method, economic losses from agrometeorological events are determined. A model for optimizing crop production taking into account natural risks was built and implemented for an agricultural organization. The results were obtained according to data of the Irkutsk district.

Simulation-Based Modeling of Soil Dynamics for Understanding Crop Responses.

“…Shifting the focus in farming awareness impacts, Basir et al ( 2019) use the mathematical model to portray the potential brought about by the awareness programs on crop pests towards reduced losses in crops and improved food security through the decreased uses of pesticides. Ivanyo et al (2020) contributed by introducing a mathematical algorithm to optimize agricultural production in high-risk environments. At the backdrop where extreme agro-meteorological events are threatening and causing huge losses in the economy, the validated algorithm showcases the potentiality to make reductions in economic loss in using optimized crop production.…”