Predicting longitudinal traits derived from high-throughput phenomics in contrasting environments using genomic Legendre polynomials and B-splines

Published in bioRxiv, 2019

Recommended citation: Momen M., Campbell T.M., Walia H., Morota G. (2019) Predicting longitudinal traits derived from high-throughput phenomics in contrasting environments using genomic Legendre polynomials and B-splines https://www.biorxiv.org/content/10.1101/632117v1

Full text is here: **Abstract** Here we present our results from the performance of RRM applied to HTP temporal shoot biomass data in response to control and water-limited conditions using Legendre polynomials and spline functions. We selected drought stress because water limitation significantly impacts shoot growth (PSA) and is the major limitation for agricultural productivity and global food security.