The Transferability of Spectral Grain Yield Prediction in Wheat Breeding across Years and Trial Locations.

ABSTRACT: Grain yield (GY) prediction based on non-destructive UAV-based spectral sensing could make screening of large field trials more efficient and objective. However, the transfer of models remains challenging, and is affected by location, year-dependent weather conditions and measurement dates. Therefore, this study evaluates GY modelling across years and locations, considering the effect of measurement dates within years. Based on a previous study, we used a normalized difference red edge (NDRE1) index with PLS (partial least squares) regression, trained and tested with the data of individual dates and date combinations, respectively. While strong differences in model performance were observed between test datasets, i.e., different trials, as well as between measurement dates, the effe

SUBMITTER: Prey L 

PROVIDER: S-EPMC10145428 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature