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KMID : 1024420110150020136
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Food Engineering Progress
2011 Volume.15 No. 2 p.136 ~ p.142
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Identification of Foreign Objects in Soybeans Using Near-infrared Spectroscopy
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Lim Jong-Guk
Kang Suk-Won
Lee Kang-Jin
Mo Chang-Yeun
Son Jae-Yong
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Abstract
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The objective of this research was to classify intact soybeans and foreign objects using near-infrared (NIR) spectroscopy. Intact soybeans and foreign objects were scanned using a NIR spectrometer equipped with scanning monochromator. NIR spectra of intact soybeans and foreign objects in the wavelength range from 900 to 1800 nm were collected. The classification of intact soybeans and foreign objects were conducted by using partial least-square discriminant analysis (PLS-DA) and soft independent modelling of class analogy (SIMCA) multivariate methods. Various types of data pretreatments were tested to develop the classification models. Intact soybeans and foreign objects were successfully classified by the PLS-DA prediction model with mean normalization pretreatment. These results showed the potential of NIR spectroscopy combined with multivariate analysis as a method for classifying intact soybeans and foreign objects.
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KEYWORD
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NIR, Soybeans, Foreign objects, PLS-DA, SIMCA
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