Predictive Association between Trait Data and Ecogeographic Data for Nordic Barley Landraces

Abstract

Focused Identification of Germplasm (FIGS) is a new method to select plant genetic resources for the improvement of food crops. Traditional cultivars (landraces) and crop wild relatives (CWR) provide a valuable source for novel alleles in crop improvement programs, but conserved landraces and CWR often lack important documentation. Genebank collections worldwide provide ready access to plant genetic resources including online documentation. However, incomplete documentation, and in particular the lack of relevant characterization and evaluation data (traits), often limit the efficient use of plant genetic resources. This current study demonstrates how trait mining with the new FIGS method can be used to predict missing trait information for landraces. Ecogeographic data from the location of origin for 14 Nordic landraces of barley (Hordeum vulgare L.) was successfully correlated to morphological traits using a modern multilinear data modeling method (multilinear partial least squares [N‐PLS]). This result suggests that trait mining can efficiently be used as a targeted germplasm selection method and complement or replace the current core selection method in situations when the requirements for the trait mining method are fulfilled.