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http://dx.doi.org/10.5307/JBE.2013.38.4.318

Determination of Germination Quality of Cucumber (Cucumis Sativus) Seed by LED-Induced Hyperspectral Reflectance Imaging  

Mo, Changyeun (National Academy of Agricultural Science, Rural Development Administration)
Lim, Jongguk (National Academy of Agricultural Science, Rural Development Administration)
Lee, Kangjin (National Academy of Agricultural Science, Rural Development Administration)
Kang, Sukwon (National Academy of Agricultural Science, Rural Development Administration)
Kim, Moon S. (Environmental Microbiology and Food Safety Laboratory, Agricultural Research Service, US Department of Agriculture)
Kim, Giyoung (National Academy of Agricultural Science, Rural Development Administration)
Cho, Byoung-Kwan (Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University)
Publication Information
Journal of Biosystems Engineering / v.38, no.4, 2013 , pp. 318-326 More about this Journal
Abstract
Purpose: We developed a viability evaluation method for cucumber (Cucumis sativus) seed using hyperspectral reflectance imaging. Methods: Reflectance spectra of cucumber seeds in the 400 to 1000 nm range were collected from hyperspectral reflectance images obtained using blue, green, and red LED illumination. A partial least squares-discriminant analysis (PLS-DA) was developed to predict viable and non-viable seeds. Various ranges of spectra induced by four types of LEDs (Blue, Green, Red, and RGB) were investigated to develop the classification models. Results: PLS-DA models for spectra in the 600 to 700 nm range showed 98.5% discrimination accuracy for both viable and non-viable seeds. Using images based on the PLS-DA model, the discrimination accuracy for viable and non-viable seeds was 100% and 99%, respectively Conclusions: Hyperspectral reflectance images made using LED light can be used to select high quality cucumber seeds.
Keywords
Cucumber seed; Germination prediction; Hyperspectral imaging; PLS-DA; LED;
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