Abstract
AbstractThe scientific areas of plant genomics and phenomics are capable of improving plant productivity, yet they are limited by the manual labor that is currently required to perform in‐field measurement, and a lack of technology for measuring the physical performance of crops growing in the field. A variety of sensor technology has the potential to efficiently measure plant characteristics that are related to production. Recent advances have also shown that autonomous airborne and manually driven ground‐based sensor platforms provide practical mechanisms for deploying the sensors in the field. This paper advances the state‐of‐the‐art by developing and rigorously testing an efficient system for high throughput in‐field agricultural row‐crop phenotyping. The system comprises an autonomous unmanned ground‐vehicle robot for data acquisition and an efficient data post‐processing framework to provide phenotype information over large‐scale real‐world plant‐science trials. Experiments were performed at three trial locations at two different times of year, resulting in a total traversal of 43.8 km to scan 7.24 hectares and 2423 plots (including repeated scans). The height and canopy closure data were found to be highly repeatable (r2 = 1.00 N = 280, r2 = 0.99 N = 280, respectively) and accurate with respect to manually gathered field data (r2 = 0.95 N = 470, r2 = 0.91 N = 361, respectively), yet more objective and less‐reliant on human skill and experience. The system was found to be a more labor‐efficient mechanism for gathering data, which compares favorably to current standard manual practices.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.