Barley Grain Proteome Assessment Using Multi-Environment Trial Data and Machine Learning

Proteomics can be used to assess individual protein abundances, which could reflect genotypic and environmental effects and potentially predict grain/malt quality. In this study, 79 barley grain samples (genotype-location-year combinations) from Californian multi-environment trials (2017-2022) were assessed using liquid chromatography-mass spectrometry. In total, 3104 proteins were identified across all of the samples. Location, genotype, and year explained 26.7, 17.1, and 14.3% of the variance in the relative abundance of individual proteins, respectively. Sixteen proteins with storage, DNA/RNA binding, or enzymatic functions were significantly higher/lower in abundance (compared to the overall mean) in the Yolo 3 and Imperial Valley locations, Butta 12 and LCS Odyssey genotypes, and the 2017-18 and 2021-22 years. Individual protein abundances were reasonably predictive (RMSE