Mid-Career Industry Fellowships - Grant ID: IM230100042
Funder
Australian Research Council
Funding Amount
$980,358.00
Summary
Unlocking the full reproductive potential for hybrid wheat breeding. Globally, wheat is cultivated as an inbred self-fertile crop with yield gains stagnating over the last decades. This contrasts with unabated yield gains and yield stability achieved for rice and corn through hybrid breeding and cross-pollination. Wheat hybrids hold potential for a 10-22% yield boost, but commercial deployment is restricted due to high seed production costs, a result of wheat’s floral architecture and poor outcr ....Unlocking the full reproductive potential for hybrid wheat breeding. Globally, wheat is cultivated as an inbred self-fertile crop with yield gains stagnating over the last decades. This contrasts with unabated yield gains and yield stability achieved for rice and corn through hybrid breeding and cross-pollination. Wheat hybrids hold potential for a 10-22% yield boost, but commercial deployment is restricted due to high seed production costs, a result of wheat’s floral architecture and poor outcrossing characteristics. This project aims to reduce costs by improving wheat’s female receptivity to airborne pollen, a major bottleneck to commercial realization of hybrids globally. Higher and more stable yields from wheat hybrids will ensure food security in the face of climate uncertainty and growing population.Read moreRead less
Co-variant analysis and statistical modelling for improved crop yield. This project plans to develop mathematical tools that will help to identify cereal plant varieties with the highest yield. This is a critical responsibility of plant breeders and many Australian breeders acquire and store important information related to the issue. However, there are as yet no mathematical tools that are able to co-analyse the heterogeneous and high-dimensional data in order to understand how external and int ....Co-variant analysis and statistical modelling for improved crop yield. This project plans to develop mathematical tools that will help to identify cereal plant varieties with the highest yield. This is a critical responsibility of plant breeders and many Australian breeders acquire and store important information related to the issue. However, there are as yet no mathematical tools that are able to co-analyse the heterogeneous and high-dimensional data in order to understand how external and internal factors correlate with the major growth and development stages at the crop level. This project seeks to develop and implement mathematical and statistical tools to analyse genetic, agronomic and phenomic factors that affect plant performance, to deliver advanced yield prediction.Read moreRead less