Validation of UAV-based alfalfa biomass predictability using photogrammetry with fully automatic plot segmentation.

ABSTRACT: Alfalfa is the most widely cultivated forage legume, with approximately 30 million hectares planted worldwide. Genetic improvements in alfalfa have been highly successful in developing cultivars with exceptional winter hardiness and disease resistance traits. However, genetic improvements have been limited for complex economically important traits such as biomass. One of the major bottlenecks is the labor-intensive phenotyping burden for biomass selection. In this study, we employed two alfalfa fields to pave a path to overcome the challenge by using UAV images with fully automatic field plot segmentation for high-throughput phenotyping. The first field was used to develop the prediction model and the second field to validate the predictions. The first and second fields had 808 and 1025 pl

SUBMITTER: Tang Z 

PROVIDER: S-EPMC7870825 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature