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Bizhen Hu, Mark A. Bennett, and Matthew D. Kleinhenz

. Seedling growth is tracked with destructive measures, machine vision systems ( Conrad, 2004 ; Giacomelli et al., 1996 ), and plant image analysis ( Bumgarner et al., 2012 ). Image analysis may complement or reduce the need for destructive sampling if data

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Sai Xu, Huazhong Lu, and Xiuxiu Sun

requirements of the progressing litchi industry. Even though machine vision ( Xiong et al., 2011 ) and spectrum technologies ( Xiong et al., 2018 ) have allowed intelligent and fast detection of many agricultural products, they are unsuitable for stored litchi

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Audrey Darrigues, Jack Hall, Esther van der Knaap, David M. Francis, Nancy Dujmovic, and Simon Gray

shoulder disorder in a uniform ripening tomato genotype HortScience 35 1114 1117 Granitto, P.M. Navone, H.D. Verdes, P.F. Ceccatto, H.A. 2002 Weed seeds identification by machine vision Computers

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Arnold W. Schumann

-based applicator of foliar sprays to rows of small plants and validated it on tomato and lettuce ( Lactuca sativa ). They developed a machine vision guided spray boom system with servo control for nozzle angle and spray pattern width to spray pesticide and found

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Rie Sadohara, James D. Kelly, and Karen A. Cichy

et al., 2008 ; Shinada et al., 1994 ), but no study has examined machine vision and image analysis technology for this purpose. Computer vision is widely used for evaluating the color of food products at a high resolution ( Wu and Sun, 2013 ). This

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Natalie R. Bumgarner, Whitney S. Miller, and Matthew D. Kleinhenz

and producers. Remote sensing includes photography, machine vision, thermal imaging, laser scanning, and multispectral imaging. Regardless of form, the use of remote sensing for nondestructive assessment of plants and canopies is increasingly common in

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Manjul Dutt and Robert Geneve

) and machine vision using a charged coupled device (CCD) camera integrated with a personal computer ( Dell'Aquila et al., 2000 ). Using sequential images to study imbibition in cabbage ( Brassica oleracea L. var. capitata L.) seeds, the variation

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David Obenland, Dennis Margosan, Sue Collin, James Sievert, Kent Fjeld, Mary Lu Arpaia, James Thompson, and David Slaughter

Longboat Key, FL Slaughter, D.C. Obenland, D.M. Thompson, J.F. Arpaia, M.L. Margosan, D.A. 2008 Non-destructive freeze damage detection in oranges using machine vision and ultraviolet fluorescence Postharvest Biol. Technol. 48 341 346 State of California

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Timothy M. Spann and Michelle D. Danyluk

. Ehsani, R. 2009 Detection and elimination of trash using machine vision and extended de-stemmer for a citrus canopy shaker and catch harvester. Paper No. FL09-129 Florida Section 2009 ASABE Annual Conference Meeting ASABE St. Joseph, MI

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Zhenhua Li, Yiling Liu, and RenXiang Liu

.F. 2005 The Ohio state university seed vigour imaging system (SVIS) for soybean and corn seedlings J. Seed Technol. 27 7 24 Howarth, M.S. Stanwood, P.C. 1993 Measurement of seedling growth rate by machine vision Trans. ASAE 36 959 963 Jalink, H. van der