40 / SEEDWORLD.COM OCTOBER 2026 smaller crops. The organizations with the most data may be positioned to benefit first, while advances that allow models to work with smaller datasets could deter mine how broadly AI spreads through the breeding community. Zamft says public research infrastruc ture remains essential to agricultural innovation. Seed companies have built substantial research capabilities, but academic and public-sector research still feeds discoveries into commercial breed ing programs. As AI increases the value of large datasets, he expects pressure to grow for new approaches to sharing data. Why AI May Push Breeders to Share More Data For Zamft, collecting data at scale is a prerequisite for the kind of modeling AI enables. “Heritable Agriculture has developed our model through using public data, running our own trials and working with partners,” he says, “But I've long been an advocate of rip-the-bandage-off all-out data collection efforts, which would prob ably best come in the form of a public- private partnership.” Heritable Agriculture is currently engaged in such a partnership with fund ing from The Gates Foundation. Its sci entists are collaborating with researchers around the world to generate multi-omic datasets from drought and well-watered field trials of tropical maize at sites in Sub- Saharan Africa. Heritable Agriculture then uses its AI to mine the dataset for genes associated with drought resistance. The company also feeds those results into its models to create digital twins of crops and run digital trials. At the same time, the raw data and selected genes will be globally accessible to breeders. The effort illustrates a larger tension surrounding AI in crop breeding. Better models can expand what breeders are able to predict, select and test, but the technology still depends on the informa tion available to it. As AI moves further into breeding programs, the ability to col lect, organize and share useful data may become as important as the algorithms themselves. SW It’s reasonable to anticipate that the greatest gains in breeding will continue to be through small improvements that together add up to significant impacts. — Jacob Washburn Mariano Alvarez examines a crop in the field, where real-world observations and breeding data help inform the models behind Avalo’s AI platform. PHOTO: AVALO
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