CERES-Maize (DSSAT) Model Applications for Maize Nutrient Management Across Agroecological Zones: A Systematic Review

Abstract

Effective nutrient management is essential for boosting maize yield and quality and tackling factors that limit or reduce productivity. The Crop Environment Resource Synthesis (CERES)-Maize model embedded in the Decision Support Systems for Agrotechnology Transfer (DSSAT) cropping system model (CSM), known for its accurate predictions, serves as a valuable tool for guiding agricultural decisions, particularly in nutrient management, offering an efficient alternative to traditional long term field trials. This systematic review consolidates the current knowledge on nutrient management practices for maize using the CERES-Maize (DSSAT) model, providing insights that benefit researchers, agronomists, policymakers, and farmers. By leveraging crop system, soil carbon and nitrogen, and daily water balance models with crop/land management options, the model accurately predicts the effect of agricultural practices on crop growth, yield, and environmental impacts. This enables the evaluation of diverse management strategies to improve productivity and sustainability.

Keywords: CERES-maize; DSSAT; Zea mays L.; agroecology; nutrient management.

Figure 1

PRISMA flow diagram depicting the study selection process. This diagram illustrates the identification, screening, eligibility assessment, and inclusion of studies for the systematic review. It includes records identified from databases, registers, websites, and citation searches, as well as the reasons for exclusion at each stage.