Sorghum [Sorghum bicolor (L.) Moench] is the fifth most important grain crop globally. It stands out for its diversity of plant types, end-uses, and roles in cropping systems. This diversity presents opportunities but also complicates evaluation of production options, especially under climate uncertainty. Ecophysiological models can dissect interacting effects of plant genotypes, crop management, and environment. We describe the sorghum module of the Cropping System Model (CSM) as implemented in the Decision Support System for Agrotechnology Transfer (DSSAT) to illustrate potential applications and suggest areas for model improvement. Crop growth is simulated based on radiation use efficiency. Development responds to temperature and photoperiod. Partitioning rules vary with growth stages, respecting mass balance and maintaining functional equilibrium between roots and shoots. Routines for climate, soil, crop management, and model controls are shared with other crops in CSM. Modeled responses for eight real-world and hypothetical cases are presented. These include growth under well-managed conditions, responses to row-spacing, population, sowing date, irrigation, defoliation, and increased atmospheric carbon dioxide concentration ([CO2]), and a long-term sorghum and winter wheat (Triticum aestivum L.) rotation. Among traits and experiments considered, model accuracy was high for phenology (r2 = 0.96, P < 0.01 for anthesis and r2 = 0.91, P < 0.01 for maturity), moderate for grain yields (r2 values from 0.30 to 0.52, P < 0.01), depending on the simulated experiments, and low for unit grain weight (r2 = 0.02, not significant, NS) and leaf area index for forage sorghum (r2 = 0.18, NS).
ASJC Scopus subject areas
- Agronomy and Crop Science