If left unchecked, the disease can wipe out up to 70 percent of rice production. Pesticides have proven ineffective to stop it; thus, the only effective way to control the disease is to plant an RHBV-resistant variety.
Currently, there’s only one variety that is highly resistant to the virus and that is available in the market — Fedearroz 2000. The Latin American Fund for Irrigated Rice (FLAR) has been working to breed more RHBV-resistant rice, in collaboration with the CIAT Rice Program.
The process entails screening breeding lines to discard which ones are susceptible to the virus. FLAR organizes screenings twice a year, in April and in October, with each involving an average of 10,000 to 12,000 breeding lines.
Previously, FLAR would need to deploy two people to score the rice breeding lines in the field. The assessment would take place each morning over 10 days.
Such a method, FLAR Plant Breeder Maribel Cruz acknowledged, was highly subjective as it relied on what the field evaluators would see. The condition of their eyesight and the intensity of sunlight could affect their vision and therefore their scoring, she conceded.
For the next screening period, FLAR will begin using analysis of images from drones operated by the CIAT Phenomics Platform, led by Dr. Michael Gomez Selvaraj, to evaluate the breeding lines.
Using drones can standardize screening of rice breeding lines. Images taken by drones can indicate which lines would have symptoms of the virus: They are lighter in color, nearly white. RHBV-resistant breeding lines, meanwhile, would be vivid green.
“This is a breakthrough for rice breeding here in Latin America,” said Cruz. “Using drones will ensure objectivity in our screening.”
The drone operated by the CIAT Phenomics Platform can take an image of 10,000 breeding lines within minutes. Analyzing such image to identify plots with RHBV-susceptible crops is also quick, usually within a day.
“Our system can help save a lot of time in screening resistant breeding lines,” said Christian Delgado, a visiting researcher involved in the project.
Plans to enhance high-throughput image analysis to screen rice breeding lines is now underway.
According to Selvaraj, his team is now working on multispectral image assessment. This involves using drones and software that will assign a spectrum for RHBV susceptibility, another for nitrogen deficiency, and another for water stress, among other traits.
“We’re doing this to facilitate rice breeding,” Selvaraj said. “And I’m pleased that the tools we’ve developed and are developing can help our partners in their work.”