Giovanni Galli

This study uses hyperspectral and genomic data to classify plant growth-promoting bacteria inoculation status and predict growth traits in maize, finding that hyperspectral data better predict shoot dry mass and stalk diameter while genomic data better predict plant height.

This study develops a low-cost greenhouse-based high-throughput phenotyping platform to assess maize growth under plant growth-promoting bacteria inoculation, showing moderate to high genomic heritability and correlation with manual measurements.

The paper introduces CV-α, a validation method for genomic prediction that improves precision and enables statistical tests by reducing residual dependence compared to traditional methods.

EnvRtype provides a software toolkit for integrating enviromics data into quantitative genomics to improve whole-genome prediction accuracy across different environments.