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논문 기본 정보

자료유형
학술저널
저자정보
Lim, Jong Guk (Department of Agricultural Engineering, National Academy of Agricultural Sciences, Rural Development Administration) Kim, Gi Young (Department of Agricultural Engineering, National Academy of Agricultural Sciences, Rural Development Administration) Mo, Chang Yeun (Department of Agricultural Engineering, National Academy of Agricultural Sciences, Rural Development Administration) Oh, Kyoung Min (Department of Agricultural Engineering, National Academy of Agricultural Sciences, Rural Development Administration) Kim, Geon Seob (Department of Agricultural Engineering, National Academy of Agricultural Sciences, Rural Development Administration) Yoo, Hyeon Chae (Department of Agricultural Engineering, National Academy of Agricultural Sciences, Rural Development Administration) Ham, Hyeon Heui (Microbial Safety Team, National Institute of Agricultural Sciences, Rural Development Administration) Kim, Young Tae (Agricultural Machinery Certification Team, Department of Analysis and Citification, Foundation of Agriculture and Technology Commercialization and Transfer) Kim, Seong Min (Department of Bioindustrial Mac) Kim, Moon S.
저널정보
한국농업기계학회 바이오시스템공학(구 한국농업기계학회지) 바이오시스템공학 제42권 제4호
발행연도
2017.1
수록면
301 - 313 (13page)

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Purpose: This study was conducted to discriminate between normal hulled barley and Fusarium (Fusarium asiaticum and Fusarium graminearum) infected hulled barley by using the near-infrared spectroscopy (NIRS) technique. Methods: Fusarium asiaticum and Fusarium graminearum were artificially inoculated in hulled barley and the reflectance spectrum of the barley spike was obtained by using a near-infrared spectral sensor with wavelength band in the range 1,175-2,170 nm. After obtaining the spectrum of the specimen, the hulled barley was cultivated in a greenhouse and visually inspected for infections. Results: From a partial least squares discriminant analysis (PLS-DA) prediction model developed from the raw spectrum data of the hulled barley, the discrimination accuracy for the normal and infected hulled barley was 99.82% (563/564) and 100% (672/672), respectively. Conclusions: NIRS is effective as a quick and nondestructive method to detect whether hulled barley has been infected with Fusarium. Further, it expected that NIRS will be able to detect Fusarium infections in other grains as well.

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