D. Sarti

This paper uses Bayesian causal forests to estimate the causal effect of nitrogen levels on maize traits, finding that environmental factors largely drive trait variation while genomic background influences baseline levels.

The paper introduces AMBARTI, a Bayesian additive regression tree model for genotype by environment interactions in plant genetics, showing it is competitive or superior to existing methods.