Overview of modelling approaches
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Wheat adaptation to climate change

Models fill in the data gaps to identify genotypes to maximize yield across the NE Australian wheat-belt under climate change.

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Crop failures and yield reduction due to heat and drought stresses are predicted to increase due to increasingly variable climate and a rise in the frequency of severe weather events.

Across Australia, temperature has increased by more than 1.4°C since 1910 and continued warming with more extremely hot days and fewer extremely cool days are expected. Much of Australia is experiencing historical droughts with a decrease in rainfall during the growing season projected in the future (CSIRO).

Australia is a significant contributor in the world food market. It is the 12th largest producer and the 7th largest exporter of wheat (FAO). Recent wheat yield losses due to heat and drought stress in Australia have been estimated to be as high as 27% and production is projected to continue to decline in the future with impacts on global wheat supply and food security.

It is therefore important to develop adaptation strategies to mitigate climate change impacts on global wheat production.

Genotypes vary in their sensitivity to the environmental conditions. However, it is not possible to grow all varieties in all environments and regions to guide adaptation to drought and heat stress.

A new study led by Dr. Daniela Bustos-Korts, researcher at Wageningen University & Research, uses models to fill in the data gaps to better predict response of genotypes to current and future environments.

Yield is more sensitive to stress during certain phases of development. Therefore, genotype choice could be used to minimize the impact of climate change. The study considered 156 hypothetical genotypes unique for their phenology.

The researchers characterized the genotype by environment interaction for grain yield over across 39 years of historical weather records using the Agricultural Production Systems sIMulator (APSIM) Wheat model.

Overview of modelling approaches
General overview of the modelling approaches used to generate the APSIM yield data, fitting of P-splines and generating predictions along the whole latitude-longitude surface, and use of P-spline predictions to classify locations.

The study confirmed that climate change is negatively affecting yield as hot and dry years are becoming more frequent. Mild years had an average yield that was 2.13 times larger than that of ‘hot and dry’ years.

By simulating the yield for each genotype over 39 years across the NE wheatbelt, the researchers were able to identify the highest-yielding genotype for each region under drought and heat stress. Studies like this contribute to global food security by enhancing adoption of adaptation and mitigation strategies against climate change. Bustos-Korts explains “future varieties will need to cope with more stressful conditions than in the past, making it important to select for flowering habits that contribute to temperature and water stress adaptation. This study provides useful information to select for varieties that are well-adapted to future growing conditions.”


This article is part of a special issue on linking crop/plant models and genetics. Read the other open access articles in the special issue here: https://academic.oup.com/insilicoplants/pages/linking-crop-plant-models-and-genetics

The APSIM Wheat model is open access and freely available at: https://www.apsim.info/ 

Rachel Shekar

Rachel (she/her) is a Founding and Managing Editor of in silico Plants. She has a Master’s Degree in Plant Biology from the University of Illinois. She has over 15 years of academic journal editorial experience, including the founding of GCB Bioenergy and the management of Global Change Biology. Rachel has overseen the social media development that has been a major part of promotion of both journals.

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