Drones for Breeding Better White Spruce

The field of tree genomics has seen unprecedented advances over the past decade. A suite of next generation genomic resources for improved tree breeding and selection will soon become available to breeders and forest managers, thanks to a project led by Drs. Ingo Ensminger (University of Toronto) and Nathalie Isabel (Forest and Environmental Genomics at Natural Resources Canada, Canadian Forest Service (CFS) – Quebec region) in partnership with PrecisionHawk.

An investment by Ontario Genomics through its Pre-Commercialization Business Development Fund (PBDF) will support rapid deployment of a software application to market. The software will allow users to determine the performance of individual trees and forest stands and to assess their phenology and water deficit at various time points in the season.

A team of scientists will use already established white spruce progeny trials in Quebec and Ontario and survey entire populations using a drone carrying optical sensors for leaf spectral measurements. Aerial sampling will be paralleled by leaf level sampling on subsets of seedlings on the ground (30-40 genotypes multiple times per site and year) looking at phenology, hydration level and spectral properties. The team will then develop algorithms for correlating plant phenology, leaf responses to hydration level and genotype information with drone-collected leaf spectral properties.

This survey data will be available to our partner company, PrecisionHawk, to create a software application that will be available to end users via the Algorithm Marketplace― the proprietary “app store” for drone data analysis.

These tools are expected to accelerate breeding cycles, through an innovative approach for large-scale phenotyping of tree responses to drought, monitor phenology, and assess differences between genotypes in large-scale field experiments.

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