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High-Throughput Phenotyping Methods for Green Fruit
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.orgCitation: 2018 ASABE Annual International Meeting 1800940.(doi:10.13031/aim.201800940)
Authors: Vivian L Vuong, David C Slaughter, Dina St. Clair, Paul Bosland, Bryce Kubond, Amanjot Kaur
Keywords: Phenotyping, sensor, tomato
Our engineering group at UC Davis has developed a new technique to distinguishing green tomato fruit from tomato leaves for high-throughput in-field phenotyping applications. This technique uses visible and near infrared reflectance techniques to create a high-contrast pseudo color representation of the outdoor scene. A digital single-lens reflex camera was modified to sense near-infrared light in addition to visible light for this application. Using this method, a machine vision index was created that amplifies the visual differences between green fruit and green leaves without compromising the ability to use shape recognition or other visual features of the scene besides color. This paper reports on the development and performance of this novel high-throughput phenotyping method for characterizing green fruits in vegetable crops.(Download PDF) (Export to EndNotes)