Genomic strategies for reducing losses during processing and improving the nutritional value of wheat in human diets. Wheat breeding requires efficient tools to allow selection of varieties with both high grain yield and good functional and nutritional value. Whole genome analysis will be used to develop screening methods to deliver wheat varieties with novel processing and nutritional properties for human diets contributing to global food and nutritional security.
Discovery Early Career Researcher Award - Grant ID: DE170101296
Funder
Australian Research Council
Funding Amount
$372,000.00
Summary
Accelerated genomic selection to speed up genetic gain in wheat. This project aims to design drought-resistant crops. Since the Green Revolution, rates of genetic gain for wheat yield have begun to plateau, while climate change threatens productivity and global food security. Numerous breeding technologies have emerged, including genomic selection, speed breeding, high-throughput phenotyping and crop modelling. This project will develop and validate crop improvement protocols by fusing these fou ....Accelerated genomic selection to speed up genetic gain in wheat. This project aims to design drought-resistant crops. Since the Green Revolution, rates of genetic gain for wheat yield have begun to plateau, while climate change threatens productivity and global food security. Numerous breeding technologies have emerged, including genomic selection, speed breeding, high-throughput phenotyping and crop modelling. This project will develop and validate crop improvement protocols by fusing these four technologies. More efficient breeding techniques could accelerate genetic gain in wheat beyond what is expected in ongoing breeding programs, and enable breeders to develop robust cereal varieties in the face of climate change.Read moreRead less
Breaking the nexus: more biomass in cereal grain. Grain yield is controlled by complex, regulated genetic networks or quantitative trait loci (QTLs) derived from natural variations in many crop plants. Yield is a product of the three major parameters: panicle number, grain number and grain size, trade-offs are commonly observed between grain number and size. There is evidence to suggest it is possible to improve grain size without altering overall biomass. With the genomic and genetic resource t ....Breaking the nexus: more biomass in cereal grain. Grain yield is controlled by complex, regulated genetic networks or quantitative trait loci (QTLs) derived from natural variations in many crop plants. Yield is a product of the three major parameters: panicle number, grain number and grain size, trade-offs are commonly observed between grain number and size. There is evidence to suggest it is possible to improve grain size without altering overall biomass. With the genomic and genetic resource tools at hand. This project will elucidate the genetic architecture of grain size, and manipulate the key loci to generate more biomass in the grain, minimising or eliminating the adverse impact on seed number. This will maximise harvestable yield without imposing increased demand for water and nutrients.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101407
Funder
Australian Research Council
Funding Amount
$447,524.00
Summary
Revealing and navigating a path to climate-ready crops. This project aims to investigate how well multi-dimensional biological and environmental data can be integrated to improve the prediction of plant performance under climatic fluctuations. This project expects to generate new knowledge in the area of quantitative genetics using an approach that combines trans-disciplinary research fields. Expected outcomes of this project include an example for how to advance conventional prediction methods ....Revealing and navigating a path to climate-ready crops. This project aims to investigate how well multi-dimensional biological and environmental data can be integrated to improve the prediction of plant performance under climatic fluctuations. This project expects to generate new knowledge in the area of quantitative genetics using an approach that combines trans-disciplinary research fields. Expected outcomes of this project include an example for how to advance conventional prediction methods using fundamental biological models that underlie plant growth. This will provide significant benefits, such as an enhancement of collaborative research across areas with the potential to significantly advance the general understanding of how plants interact with the environment.Read moreRead less