Multi temporal multispectral UAV remote sensing allows for yield assessment across European wheat varieties already before flowering.

ABSTRACT: High throughput field phenotyping techniques employing multispectral cameras allow extracting a variety of variables and features to predict yield and yield related traits, but little is known about which types of multispectral features are optimal to forecast yield potential in the early growth phase. In this study, we aim to identify multispectral features that are able to accurately predict yield and aid in variety classification at different growth stages throughout the season. Furthermore, we hypothesize that texture features (TFs) are more suitable for variety classification than for yield prediction. Throughout 2021 and 2022, a trial involving 19 and 18 European wheat varieties, respectively, was conducted. Multispectral images, encompassing visible, Red-edge, and near-infrared (NIR

SUBMITTER: Camenzind MP 

PROVIDER: S-EPMC10791776 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature