The patterns of parameter Г— environment Г— management interactions were investigated for the most influential parameters, considering a potential genetic range of +/- 20% compared to a reference cultivar. The Morris sensitivity analysis method was used to sample the parameter space and reduce computational requirements, while maintaining a realistic representation of the targeted trait Г— environment Г— management landscape (в€ј 82 million individual simulations in total). A large set of traits (90) was evaluated in a wide target population of environments (4 sites Г— 125 years), management practices (3 sowing dates Г— 3 nitrogen fertilization levels) and CO 2 (2 levels). The study focused on wheat in Australia, with an emphasis on adaptation to low rainfall conditions. A sensitivity analysis was used to assess the simulated impact on yield of a suite of traits involved in major processes of crop growth and development, and to evaluate how the simulated value of such traits varies across environments and in relation to other traits (which can be interpreted as a virtual change in genetic background). Application of numerical methods for model exploration assist in evaluating the major most influential inputs, providing the simulation model is a credible description of the biological system. yield) that are affected by inputs of genetic, physiology, pedo-climatic and management information.

The observed significant genetic variability in the response of wheat to heat stress needs to be considered through cultivar parameters in future simulation studies.ДЄnthesis crop models grain filling heat stress model evaluation winter wheat.A crop can be viewed as a complex system with outputs (e.g. Some of the tested models require improvements in the response to heat stress during grain filling, but all models need improvements in simulating heat stress effects on grain set during anthesis. Most of the crop models tended to reproduce heat stress impacts better during grain filling than at anthesis. The tested crop simulation models could reproduce some of the observed reductions in grain filling duration, final total aboveground biomass, and grain yield, as well as the observed increase in GPC due to heat stress.

For every unit increase of heat degree days (HDD, degree days over 30 вЊ), grain filling duration was reduced by 0.30-0.60%, total aboveground biomass was reduced by 0.37-0.43%, and grain yield was reduced by 1.0-1.6%, but GPC was increased by 0.50% for cv Yangmai16 and 0.80% for cv Xumai30. The observed impact of heat stress on grain filling duration, total aboveground biomass, grain yield, and grain protein concentration (GPC) varied depending on cultivar and accumulated heat stress. Heat stress at anthesis reduced observed grain numbers per unit area and individual grain size, while heat stress during grain filling mainly decreased the size of the individual grains. Four wheat models (DSSAT-CERES-Wheat, DSSAT-Nwheat, APSIM-Wheat, and WheatGrow) were evaluated with 4 years of environment-controlled phytotron experimental datasets with two wheat cultivars under heat stress at anthesis and grain filling stages. Crop models have been widely used to simulate future crop productivity but are rarely tested with observed heat stress experimental datasets. Higher temperatures caused by future climate change will bring more frequent heat stress events and pose an increasing risk to global wheat production.

Apsim wheat model