Comparison of wheat simulation models for impacts of extreme temperature stress on grain quality

Abstract Shifting temperature patterns on global and regional scales accredited to climate change will bring more low-temperature stress (LTS) and high-temperature stress (HTS) events to further deteriorate wheat yield and quality. Crop models can serve as a beneficial platform for quantifying the impact of both high and low-temperature events on grain yield (GY) and grain quality. Wheat grain protein concentration (GPC) and grain protein yield (GPY), as two important measurements of wheat quality for nutrition value, is often ignored in crop modeling efforts to improve grain yield under climate change. This study was undertaken for comprehensive comparison of four broadly used wheat simulation models (DSSAT-CERES-Wheat, DSSAT-Nwheat, WheatGrow, and APSIM-Wheat) in quantifying and simulating the responses of wheat grain quality (GPC and GPY) under LTS and HTS at critical growth stages, and to identify gaps in simulating wheat grain protein concentration and protein yield for crop model improvement. Four-year environment-controlled phytotron experiments were conducted with two wheat varieties under LTS (at joining and booting stages) and HTS (at anthesis, grain filling, and combined stress at anthesis and grain filling stages). For per unit increase in cold degree days (CDD, degree days below 2 °C) at jointing and booting stages and heat degree days (HDD, degree days over 30 °C) at anthesis, grain filling and combined stress at anthesis and grain filling stages, GPC was increased by 0.2% to 0.4% and 1.1% to 1.6%, while GPY was decreased by 2.1% to 4.5% and 0.3% to 1.7%, respectively. Most of the crop models tended to reproduce some HTS impacts better during grain filling than at anthesis, but all the tested models call for improvements in simulating LTS at different stages, especially for GPY. Our results indicated the need of incorporating response functions of extreme temperature stresses into grain quality models to adapt to future climate scenarios.