Click on “Download PDF” for the PDF version or on the title for the HTML version. If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options. Determining Wheat Vitreousness Using Image Processing and a Neural NetworkPublished by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org Citation: Paper number 026089, 2002 ASAE Annual Meeting . (doi: 10.13031/2013.10559) @2002Authors: Ning Wang, Floyd Dowell, Naiqian Zhang Keywords: Grading, Inspection, Automation, Machine Vision, Color The GrainCheck 310 is a real-time, image-based wheat quality inspection machine that can replace tedious visual inspections for purity, color, and size characteristics of grains. It also has the potential for measuring the vitreousness of durum wheat. Different neural network calibration models were developed to classify vitreous and nonvitreous kernels and evaluated using samples from GIPSA and from fields in North Dakota. Model transferability between different inspection machines was also tested. (Download PDF) (Export to EndNotes)
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