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27 April 2020 In-field high-throughput phenotyping approach using a multi-view and multi-sensor ground-based vehicle (Conference Presentation)
Vivian Vuong, David C. Slaughter, Clarice Roo, Dina St. Clair, Bryce Kubond, Paul Bosland
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Proceedings Volume 11414, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V; 114140H (2020) https://doi.org/10.1117/12.2560531
Event: SPIE Defense + Commercial Sensing, 2020, Online Only
Abstract
By the year 2050 the world population will increase to 9.7 billion people. Food production must increase by at least 70% in order to feed this population. One way to increase food production is to create crop cultivars that can produce high quality and high yielding crops without needing to increase the amount of resources required. Plant breeders are able to create new crop cultivars using high-throughput genotyping techniques, however the current bottleneck in plant breeding is in-field phenotyping. This study focuses on designing a high-throughput in-field proximal phenotyping system capable of collecting non-contact, high-resolution, multi-sensor, multi-view, phenomic data of vegetable plants.
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Vivian Vuong, David C. Slaughter, Clarice Roo, Dina St. Clair, Bryce Kubond, and Paul Bosland "In-field high-throughput phenotyping approach using a multi-view and multi-sensor ground-based vehicle (Conference Presentation)", Proc. SPIE 11414, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V, 114140H (27 April 2020); https://doi.org/10.1117/12.2560531
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KEYWORDS
Cameras
Imaging systems
Sensors
Infrared cameras
Infrared sensors
Infrared radiation
RGB color model
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