Sergio Castro-Pacheco

This paper proposes using singular value decomposition in near infrared spectroscopy pre-processing for phenomic prediction, showing it performs as well as classical chemometrics methods with less parameter optimization.

This paper evaluates phenomic prediction (PP) accuracy in rice breeding, finding that multi-environment data improve PP performance, making it comparable to genomic prediction (GP) when all genotypes have NIRS measurements.