Exploiting High-Throughput Indoor Phenotyping to Characterize the Founders of a Structured Breeding Population.

Phenotyping is considered a significant bottleneck impeding fast and efficient crop improvement. Similar to many crops, , an internationally important oilseed crop, suffers from low genetic diversity, and will require exploitation of diverse genetic resources to develop locally adapted, high yielding and stress resistant cultivars. A pilot study was completed to assess the feasibility of using indoor high-throughput phenotyping (HTP), semi-automated image processing, and machine learning to capture the phenotypic diversity of agronomically important traits in a diverse breeding population, SKBnNAM, introduced here for the first time.