A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data.

ABSTRACT: High throughput phenotyping (HTP) platforms and devices are increasingly used for the characterization of growth and developmental processes for large sets of plant genotypes. Such HTP data require challenging statistical analyses in which longitudinal genetic signals need to be estimated against a background of spatio-temporal noise processes. We propose a two-stage approach for the analysis of such longitudinal HTP data. In a first stage, we correct for design features and spatial trends per time point. In a second stage, we focus on the longitudinal modelling of the spatially corrected data, thereby taking advantage of shared longitudinal features between genotypes and plants within genotypes. We propose a flexible hierarchical three-level P-spline growth curve model, with plants/plots

SUBMITTER: Perez-Valencia DM 

PROVIDER: S-EPMC8873425 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature