High-Throughput Yield Prediction of Diallele Crossed Sugar Beet in a Breeding Field Using UAV-Derived Growth Dynamics.

ABSTRACT: Data-driven techniques could be used to enhance decision-making capacity of breeders and farmers. We used an RGB camera on an unmanned aerial vehicle (UAV) to collect time series data on sugar beet canopy coverage (CC) and canopy height (CH) from small-plot breeding fields including 20 genotypes per season over 3 seasons. Digital orthomosaic and digital surface models were created from each flight and were converted to individual plot-level data. Plot-level data including CC and CH were calculated on a per-plot basis. A multiple regression model was fitted, which predicts root weight (RW) (r = 0.89, 0.89, and 0.92 in the 3 seasons, respectively) and sugar content (SC) (r = 0.79, 0.83, and 0.77 in the 3 seasons, respectively) using individual time point CC and CH data. Individ

SUBMITTER: Taguchi K 

PROVIDER: S-EPMC11283879 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature