Dissecting Physiological and Agronomic Diversity in Safflower Populations Using Proximal Phenotyping

Safflower (Carthamus tinctorius L.) is a highly adaptable but underutilized oilseed crop capable of growing in marginal environments, with crucial agronomical, commercial, and industrial uses. Considerable research still needed to develop commercially relevant varieties, requiring effective, high-throughput digital phenotyping identify key selection traits. In this study, field trials comprising globally diverse collection 350 safflower genotypes were conducted during 2017–2019. Crop traits assessed included phenology, grain yield, oil quality, as well unmanned aerial vehicle (UAV) multispectral data for estimating vegetation indices. Phenotypic performance dependent on environmental conditions, especially rainfall. High-performing had intermediate growth spineless performing similarly spiked genotypes. Phenology parameters significantly correlated height, weak interaction yield The produced total content values ranging from 20.6–41.07%, oleic acid 7.57–74.5%, linoleic 17.0–83.1%. Multispectral used model NDVI EVI changes, yield. identified the start flowering dissected according class, pattern, estimation. Overall, UAV-multispectral derived are applicable agronomical large collections suitable breeding programs.