Temporal phenomic predictions from unoccupied aerial systems can outperform genomic predictions.

ABSTRACT: A major challenge of genetic improvement and selection is to accurately predict individuals with the highest fitness in a population without direct measurement. Over the last decade, genomic predictions (GP) based on genome-wide markers have become reliable and routine. Now phenotyping technologies, including unoccupied aerial systems (UAS also known as drones), can characterize individuals with a data depth comparable to genomics when used throughout growth. This study, for the first time, demonstrated that the prediction power of temporal UAS phenomic data can achieve or exceed that of genomic data. UAS data containing red-green-blue (RGB) bands over 15 growth time points and multispectral (RGB, red-edge and near infrared) bands over 12 time points were compared across 280 unique maize h

SUBMITTER: Adak A 

PROVIDER: S-EPMC9836347 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature