Agro-meteorological Crop Yield Modeling: A Comprehensive Review

Abstract

Agro-meteorological crop yield modeling is essential for addressing climate variability, resource limitations, and food security challenges. This review explores the principles of crop modeling, focusing on core components, validation techniques, and operational tools. It examines key modeling approaches, including simulation and statistical methods, and their applications in precision agriculture, institutional planning, and policy development. Advanced techniques such as remote sensing and data assimilation are highlighted for their role in improving model accuracy and applicability. Given the significant influence of weather and climate on agriculture, predictive tools are crucial for ensuring sustainable crop production. Agro-meteorological models integrate weather data, crop physiology, and management practices to forecast yields and support informed decision-making. This review provides a comprehensive overview of fundamental concepts, model classifications, evaluation methods, and practical applications. It concludes by emphasizing the need for continued advancements and hands-on training to enhance model effectiveness and adoption across diverse agricultural systems.

Environ. Sci. & Natural Resources, 14(1&2): 55-64, 2025