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논문 기본 정보

자료유형
학술저널
저자정보
Seo, Young-Wook (Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University) Ahn, Chi Kook (Foundation of Agri. Tech. Commercialization & Transfer) Lee, Hoonsoo (Environmental Microbiology and Food Safety Laboratory, Agricultural Research Service, US Department of Agriculture) Park, Eunsoo (Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University) Mo, Changyeun (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)
저널정보
한국농업기계학회 바이오시스템공학(구 한국농업기계학회지) 바이오시스템공학 제41권 제1호
발행연도
2016.1
수록면
51 - 59 (9page)

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Purpose: This study examined the performance of two spectroscopy methods and multivariate classification methods to discriminate viable pepper seeds from their non-viable counterparts. Methods: A classification model for viable seeds was developed using partial least square discrimination analysis (PLS-DA) with Fourier transform near-infrared (FT-NIR) and Raman spectroscopic data in the range of $9080-4150cm^{-1}$ (1400-2400 nm) and $1800-970cm^{-1}$, respectively. The datasets were divided into 70% to calibration and 30% to validation. To reduce noise from the spectra and compare the classification results, preprocessing methods, such as mean, maximum, and range normalization, multivariate scattering correction, standard normal variate, and $1^{st}$ and $2^{nd}$ derivatives with the Savitzky-Golay algorithm were used. Results: The classification accuracies for calibration using FT-NIR and Raman spectroscopy were both 99% with first derivative, whereas the validation accuracies were 90.5% with both multivariate scattering correction and standard normal variate, and 96.4% with the raw data (non-preprocessed data). Conclusions: These results indicate that FT-NIR and Raman spectroscopy are valuable tools for a feasible classification and evaluation of viable pepper seeds by providing useful information based on PLS-DA and the threshold value.

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