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Metrics (View:76)- Identification of Foreign Objects in Soybeans Using Near-infrared Spectroscopy
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근적외선 분광법을 이용한 콩과 이물질의 판별
Received: Oct 18, 2010; Revised: Feb 28, 2011; Accepted: Apr 18, 2011
Published Online: May 31, 2011
Abatract
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.