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Identifying Distinctly Green and Heat Treated Seeds in Canola

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2010 Pittsburgh, Pennsylvania, June 20 - June 23, 2010  1009173.(doi:10.13031/2013.34183)
Authors:   Geetika Dilawari, Carol L Jones
Keywords:   Machine vision, canola, grading

According to USDA standard guidelines, US grade 1 canola should have not more than 3% of total damaged seeds (distinctly green seeds and heat treated seeds). Distinctly green seeds should not be more than 2% and heat treated seeds should not be more than 0.1% . Graders usually identify these seeds by crushing a sample of canola and inspecting the crushed seeds visually. But visual inspection can introduce human error. Therefore, there is a need to develop an automated system that can distinguish these seeds from the desired canola seeds. Machine vision can be a potential method to achieve this objective as similar technology has also been applied on wheat and soybean to classify damaged seeds.

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