근적외선 분광법을 이용한 콩과 이물질의 판별

임종국¹, 강석원¹^,^*, 이강진¹, 모창연¹, 손재용¹

Identification of Foreign Objects in Soybeans Using Near-infrared Spectroscopy

Jong-Guk Lim¹, Sukwon Kang¹^,^*, Kangjin Lee¹, Changyeon Mo¹, Jaeyong Son¹

¹농촌진흥청 국립농업과학원 농업공학부

¹National Academy of Agricultural Science, RDA

^*Corresponding author: Sukwon Kang, Researcher, National Academy of Agricultural Science, RDA, Suwon-city, Gyeonggi-do 441-100, Republic of Korea. Tel: +82-31-290-1903; Fax: +82-31-290-1900, E-mail : skang@korea.kr

ⓒ Copyright 2011 Korean Society for Food Engineering. This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.

Keywords: NIR; Soybeans; Foreign objects; PLS-DA; SIMCA