Avalo is a fairly new startup that is deploying interpretable artificial intelligence to develop climate-resilient crops and accelerated crop breeding. Brendan Collins, co-founder and CEO of Avalo, was recently quoted in an article for USA Today (read more here) saying, “A traditionally bred crop takes 12 years to get to market… Our process, from discovery to market, is three years.” Colling also commented, “There is no single gene that makes your corn big or your strawberries red and juicy. It’s a process of thousands of genes interacting in really complex ways with each other and with a really dynamic, complicated environment. Using AI, we can understand the genetic basis for the traits we care about and cross-plant parents in the right ways to get the outcomes we want.”
Avalo’s core technology—Gene Discovery by Informationless Perturbation (GDIP)—draws upon Professor Cynthia Rudin’s work in interpretable artificial intelligence to more rapidly identify the genes responsible for specific traits in crops. Collins says, “I think the larger blow up of AI has really muddied the waters. But one thing I really want to emphasize is that the math we are using is brand new. It was basically invented in 2018, whereas the math that goes into large language models was basically invented in the 1940s; we just didn’t have the computing power to pull it off until more recently. But what we are doing is bleeding edge on machine learning theory, AI, and interpretability.”
Dr. Mariano Alvarez is the other co-founder, who says, “At the core of Avalo’s GDIP tech is “a way to identify important genetic information in a big sea of biological noise. This has two key applications, the first is identifying the genes that are responsible for a trait, and that could be disease resistance, heat resistance, or value-added traits for the downstream supply chain. The second is that it allows us to create models that are much more predictive of plant performance than we would have been able to create otherwise, using much less information. It quickly became apparent that using that predictive component would allow us to run a breeding program, a genomic selection program, at much lower cost with much higher efficiency.
The company is currently working on a new sugarcane model for Coc Cola, by developing a low-nitrogen, low-water variety of sugarcane to help the company reduce its scope three emissions. They are also working on a different variety of cotton. They say the industry has been breeding varieties that perform well in high-irrigation and high-nitrogen environments, but what more producers need is a variety that does well in a low-nitrogen and limited rainfall environment, but still has the premium fiber characteristics. Other projects include fast-growing broccoli, enabling farmers to get six, rather than four harvests a year from an indoor facility. Aside from the obvious economic benefits of more harvests per year, growers can also stop using pesticides as the crop grows too rapidly for pests to gain traction, said Collins. “There’s no pest life cycle that is shorter than 45 days. We were able to get a crop that was harvestable in 37 days.” You can learn more at the Avalo website HERE (Source: AgFunderNews; Avalo)
