Scientists have developed a new method to estimate the crop biomass of wheat in all growth stages, which can compare hundreds of different genotypes to select the best candidates for breeding.
Crop biomass is a go-to trait commonly used by breeders and growers to evaluate the yield of a crop, and it is typically measured by weighing the plant material produced.
Agriculture Victoria Research Scientist Dr Bikram Banerjee said he was excited to have found an alternative to traditional methods.
"Harvesting, drying, and weighing plants can be very time consuming.
"We can now reliably estimate the dry biomass of wheat by flying a drone over a paddock to collect aerial images which provides us with the data we need."
Dr Banerjee said traditional methods to measure the dry biomass and fresh biomass of a crop becomes problematic when breeders want to compare hundreds of genotypes, with different growth behaviour.
"In this research, we wanted to test the ability of high-throughput technologies to reliably measure biomass for a large number of wheat genotypes in a non-invasive way over a large area."
"Our mathematical analysis showed a correlation of 96 per cent accuracy in layman's terms for dry biomass across all growth stages, it is unusual to get a correlation this high," Dr Banerjee said.
The new approach also outperformed all other widely used traditional methods commonly used to estimate the dry and fresh biomass of wheat.
"We wanted a system where we could screen thousands of genotypes across the life cycle of wheat without compromising accuracy, and these results showed our approach was robust for different growth stages.
"This tool has the potential to become the go-to technique for screening varieties for traits such as salinity, heat or frost tolerance, disease resistance, nutrient use efficiency and drought tolerance," Dr Banerjee said.
This innovative approach is already being incorporated into genetic improvement research conducted by Agriculture Victoria for screening genotypes for a range of grain crops, allowing farmers and breeders to not only predict their future productivity but also compare it with previous years.
Read Dr Bikram's research paper published in Remote Sensing.
