Identification of environment types and adaptation zones with self-organizing maps; applications to sunflower multi-environment data in Europe.

ABSTRACT:

Key message

We evaluate self-organizing maps (SOM) to identify adaptation zones and visualize multi-environment genotypic responses. We apply SOM to multiple traits and crop growth model output of large-scale European sunflower data. Genotype-by-environment interactions (G × E) complicate the selection of well-adapted varieties. A possible solution is to group trial locations into adaptation zones with G × E occurring mainly between zones. By selecting for good performance inside those zones, response to selection is increased. In this paper, we present a two-step procedure to identify adaptation zones that starts from a self-organizing map (SOM). In the SOM, trials across locations and years are assigned to groups, called units, that are organized on a two-dimensional grid. Units

SUBMITTER: Bustos-Korts D 

PROVIDER: S-EPMC9205840 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature