About Flagship 1

Plant breeders work to improve the characteristics of plants, especially those related to productivity. The most important productivity traits are yield (the quantity of a given useful product, such as grain) and yield stability (the ability of plants to maintain high yields under stressful conditions).

Most crops are exposed to stresses such as drought or high temperatures, often combinations of several types of stress at the same time. Indeed, this is one of the main challenges associated with climate change. It is relatively simple to select plants for high yield, but much more difficult to select for yield stability because genetic progress is masked by the effect of environmental conditions on the phenotype, a phenomenon known as the genotype x environment (GxE) interaction. The more genetic information we have, the easier it becomes to understand GxE interactions and how to select for yield stability.

Flagship Project 1 is developing genomic and digital solutions to probe the genetic basis of physiological factors affecting yield and yield stability, as well as quality traits (such as seed protein and oil). We have generated specialized structured populations of wheat, canola and lentil that we can test under controlled environments and in the field, and by combining these assets with genotyping datasets, digital phenotyping and data modelling from field environments, we can finally dissect the genetic factors responsible for yield stability under stress. The project will deliver richly-annotated phenotype datasets (phenomics) to support genetic dissection and breeding (genomics), allowing the association of genotypes with phenotypes, ultimately delivering novel genomic and digital phenotyping tools to breeders to support the prediction of crop performance under stress.

Practical Applications

  • Incoming

The following projects are currently underway within Flagship 1:

Activity 1.1

Characterization of novel genomic variation in NAM populations

Cataloguing the genomic features of specialized crop populations and developing tools for their visualization.

  • Producing structured populations of wheat, canola and lentil based on a technique known as nested association mapping (NAM);
  • Generate a catalogue of genomic information from 2500 recombinant inbred lines in each population as a resource for genotype-phenotype association and the development of selectable markers for trait improvement;
  • Developing tools that allow researchers to quickly evaluate and compare the structure of plant genomes, including the positions of genes, sequence variations, and areas of synteny containing similar groups of genes in different crops.


Activity 1.2

Using the Digital Phenotype to Augment Genomic Selection

Collecting multi-environment digital phenotyping data for large structured populations of canola, wheat and lentil for sophisticated genomics and phenomics analysis.

  • Using aerial digital phenotyping (the collection of time-series image data from plants using remote sensors) in canola, wheat and lentil NAM populations to find digital image signatures as proxies for yield, yield stability and quality traits;
  • Integrating high-throughput phenotyping data to improves the performance of genomic selection for moderately to highly heritable traits by allowing the precise quantification of phenotypic variation, thus facilitating genetic gain by increasing selection intensity during the early stages of breeding.


Activity 1.3

Targeted phenotyping for traits impacting yield stability and seed quality

Using novel controlled-environment phenotyping platforms that capture whole-plant physiology, root development and the transport of stress-associated molecules to study the response to water deficit and the impact on yield and seed quality.