Turning up the heat on chickpea yield - a multi-omics prediction approach

Chickpea is one of Australia's most economically important pulse crops, however yield is variable across regions and seasons. High temperatures during reproduction can cause flower and pod abortion, reduced pollen viability, and impaired grain filling, leading to significant yield loss. This project aims to enhance breeding efficiency for high yielding chickpea cultivars under varying heat-stress conditions by developing new knowledge, innovative tools and methodologies through a novel multi-omics approach that integrates genomics, epigenomics, phenomics and enviromics.
Through multi-environment field trials that span heartland and expansion production regions, the project evaluates a diverse chickpea panel under optimal and delayed sowing times to investigate relationships among yield and phenology traits, and identify genomic regions and germplasm associated with superior yield and stability under high temperatures. UAV-derived multispectral imagery is used to predict agronomic traits associated with heat tolerance that are traditionally difficult to capture at large spatial and temporal scale, such as total aboveground biomass and crop growth rates. These layers of information will be integrated with epigenomic and enviromic data into a genotype-by-environment prediction framework to explore whether combining multiple layers of biological information provides greater predictive power, with the ultimate aim of accelerating the development of climate-resilient chickpea varieties for growers.