Addressing yield stability drivers of canola in a changing climate using high throughput phenotyping
Term: 2 years, ending July 2024
Status: Complete
Researcher(s): Sally Vail, Isobel Parkin, Steve Robinson, Raju Soolanayakanahally, AAFC; Andrew Sharpe, GIFS; Bobbi Helgason, U of S
SaskCanola Investment: $116,667
Total Project Cost: $350,200
Funding Partners: MCGA, WGRF
Grower Benefits
The tools developed and verified through this project will enable efficient development of resilient varieties. The results support potential of canola digital phenotypes to field-scale agronomic applications. The expansive data sets and samples generated through this project are and will be used in various research projects, extending the utility of grower-invested research dollars.
Project Summary
The future of breeding canola for climate-resilient varieties could incorporate both drones and microbiomes. This project contributed toward futuristic objectives through conducting field trials studying a diverse germplasm resource, which possesses hidden genes for yield stability under variable environmental conditions. Unmanned Aerial Vehicle (UAV) or drone-based measurements for canola plant growth and staging were tested in these trials. We also took the temperature of plants to see if cooler plants have the potential to consistently yield more seed.
Tolerance to environmental stress underlies the ability of a variety to consistently yield under increasingly variable seasonal conditions. There is great potential to improve the efficiency and precision of identifying yield stable breeding lines using Digital Phenotyping, or the use of sensors and cameras to capture and process data and images collected remotely over the lifecycle of the crop. The Plant Phenotyping and Imaging Research Centre (P2IRC) at the University of Saskatchewan established a first-rate crop phenotyping research capacity in Canada. This project funded AAFC field trials of the spring Brassica napus Nested Association Mapping (NAM) population, which was developed specifically to study complex traits like yield stability and environmental stress tolerance. A sizable sufficient dataset to test and apply emerging phenotyping and selection techniques to improve canola yield stability for Canadian producers was attained.
Large nurseries of small nursery-style plots were grown for this project, which are similar to nursery trials conducted by industrial canola breeding companies (Figure 1). Dryland and irrigated sites were used for trials, simulating the range of environmental conditions faced by Prairie canola growers. Imaging platforms and sensors are comparable to systems used by canola growers and agronomists, thus results and datasets may be transferrable or useful in designing and optimizing models and tools for precision agriculture applications.
Digital canola phenotypes for flowering and maturity that were developed in larger plots on a training population of lines were tested and verified on smaller nursery-plots within large nurseries grown in contrasting environments. From these large trials, a dataset comprised of manual plant measurements (e.g. plant architecture and biomass, seed yield and quality) and digital phenotypes is being used in several subsequent projects leveraging the spring B. napus NAM population. On the NAM parental panel, a comprehensive set of thermal images from several environments were curated and annotated for organ-specific temperatures over time. These results will form protocols for application of thermal measurements to select for more resilient varieties. Advances made through this project will contribute towards the most comprehensive characterization of rhizosphere microbiome in B. napus, connecting microbial communities to digital phenotypes. This project also contributed to the several digital phenotyping tools including PlotVision for drone-image processing and a high-throughput ground-based imaging system (the ProTractor).
The greatest outputs from this project were the acquisition and cataloging of digital phenotyping datasets from UAV and ground-based imaging platforms on the B. napus NAM population, proof of concept of prototype canola digital phenotypes developed by P2IRC and contribution to digital phenotyping acquisition and processing tools for canola.
Figure 1. Stitched orthomosaic of drone-collected images from across the 2023 growing season of a trial at the AAFC Saskatoon Research and Development Centre Llewellyn Road Farm where approximately 200 NAM lines with 3 replicates were grown in single nursery-row plots.