Modeling of crop cultivation systems taking into account agroecological requirements

Abstract

The growing need for sustainable agricultural production in a context of climate variability and environmental degradation underscores the importance of integrating agroecological criteria into cropping systems modeling. Therefore, this study incorporates natural system indicators, such as heat input, moisture availability, and vegetation duration, into crop yield prediction. The primary objective is to develop a mathematical model that simulates the productivity of cereal, barley, and potato crops based on the climatic and technological characteristics of agricultural landscapes. The model calculates specific coefficients of temperature, moisture, and growing season to assess crop suitability and forecast yield potential. The model's ability to reflect ecological conditions with high sensitivity was found, enabling crop yield predictions in specific geographical areas. Furthermore, the use of graphical dependencies allows for a detailed understanding of how environmental factors interact with crop physiology. This knowledge is particularly relevant for the development of agroforestry ecosystems, which not only enhance biodiversity and ecological balance but also contribute to socioeconomic resilience in rural areas.