Charlie Brummer

Biofortification tackles global micronutrient deficiencies through crop improvement without added inputs. To optimize breeding programs, an AI toolkit is being developed to predict and evaluate nutritional quality using machine learning. Open-source resources will benefit broader initiatives, and a hackathon will engage UC Davis students in advancing agricultural innovation.

Biofortification tackles global micronutrient deficiencies through crop improvement without added inputs. To optimize breeding programs, an AI toolkit is being developed to predict and evaluate nutritional quality using machine learning. Open-source resources will benefit broader initiatives, and a hackathon will engage UC Davis students in advancing agricultural innovation.

This two-part project aims to develop predictors for nutritional quality and aroma by leveraging genetic and phenotypic features, employing machine learning to assess the overall value of new varieties based on their molecular compositions for flavor and health effects, specifically focusing on three major compound classes: phenols, terpenes, and peptides.