Designing high‐yielding wheat ideotypes for a changing climate

Abstract

Global warming is characterized by shifts in weather patterns and increases in climatic variability and extreme events. New wheat cultivars will be required for a rapidly changing environment, putting severe pressure on breeders who must select for climate conditions which can only be predicted with a great degree of uncertainty. To assist breeders to identify key wheat traits for improvements under climate change, wheat ideotypes can be designed and tested in silico using a wheat simulation model for a wide range of future climate scenarios predicted by global climate models. A wheat ideotype is represented by a set of cultivar parameters in a model, which could be optimized for best wheat performance under projected climate change. As an example, high-yielding wheat ideotypes were designed at two contrasting European sites for the 2050 (A1B) climate scenario. Simulations showed that wheat yield potential can be substantially increased for new ideotypes compared with current wheat varieties under climate change. The main factors contributing to yield increase were improvement in light conversion efficiency, extended duration of grain filling resulting in a higher harvest index, and optimal phenology.

Yield stability and lower susceptibility to abiotic stresses of improved open-pollinated and hybrid maize cultivars

“…As one example, by using a crop model, Hammer et al (2009) could provide evidence that one trait that had a positive effect on water capture and a direct effect on biomass accumulation was the increase in root density in maize. This corroborates the statement that a well-designed and calibrated model can provide important support for breeding programs (Semenov and Stratonovitch 2013).…”

Combined Effect of Drought Stress and Elevated Atmospheric CO2 Concentration on the Yield Parameters and Water Use Properties of Winter Wheat (Triticum aestivum L.) Genotypes

“…Wheat production will play an important role in the food supply of the future, but it is highly sensitive to climatic and environmental variations (Parry et al. , Semenov and Stratonovitch ). Water deficit is one of the main limiting factors for cereal production in many parts of the world, especially in arid and semi‐arid regions (Shahbaz et al.…”

Using numerical plant models and phenotypic correlation space to design achievable ideotypes

“…Phenotypes with the best performance can be identified by solving the following optimization problem (Semenov & Stratonovitch ; e.g. Martre et al ).…”