URBANA, IL (Chambana Today) – Researchers at the U of I, led by Juan David Arbelaez-Velez, have developed a new, more efficient method to improve rice quality by using marker-assisted multi-trait genomic selection (MT-GS).

The approach helps plant breeders predict multiple quality traits, such as cooking time, texture, and appearance. The prediction can happen earlier in the process, saving time and money while increasing breeding accuracy. The method builds on previous work done for oats, and shows promise for other small grains and crops worldwide.

While traditional breeding is slow and expensive, MT-GS uses whole-genome data to predict several traits. When combined with marker-assisted selection, which focuses on known genes linked to important traits, this method helps improve prediction accuracy by 2-10 times, depending on the trait.

A rising global population with growing economic power means demand for high-quality grain will continue to increase, making efficient and cost-effective breeding programs essential.

“If you think globally, there are a lot of different market types,” Arbelaez said. “For instance, countries like Peru and Chile tend to like rice that’s slightly stickier than in the rest of the South American countries. So by understanding the alleles that code for texture, we can identify lines of interest for various markets.” 

Arbelaez also stressed the importance of international collaboration and sustained research funding. He implemented the method at the International Rice Research Institute in the Philippines, and used samples from the Latin American Fund for Irrigated Rice.

“All agricultural research has been impacted by funding cuts,” he said. “There are revisions happening to a lot of programs that support the work we do.” 

To read more about Arbelaez’s research, read the full press release at the College of ACES’ website.