Field-based high-throughput phenotyping enhances phenomic and genomic predictions for grain yield and plant height across years in maize
Alper Adak,
Aaron J DeSalvio,
Mustafa A Arik
et al.
Abstract:Field-based phenomic prediction employs novel features, like vegetation indices (VIs) from drone images, to predict key agronomic traits in maize, despite challenges in matching biomarker measurement time points across years or environments. This study utilized functional principal component analysis (FPCA) to summarize the variation of temporal VIs, uniquely allowing the integration of this data into phenomic prediction models tested across multiple years (2018–2021) and environments. The models, which includ… Show more
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