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Lim, Jong Guk,Kim, Gi Young,Mo, Chang Yeun,Oh, Kyoung Min,Kim, Geon Seob,Yoo, Hyeon Chae,Ham, Hyeon Heui,Kim, Young Tae,Kim, Seong Min,Kim, Moon S. Korean Society for Agricultural Machinery 2017 바이오시스템공학 Vol.42 No.4
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.
( Jong Guk Lim ),( Gi Young Kim ),( Chang Yeun Mo ),( Kyoung Min Oh ),( Geon Seob Kim ),( Hyeon Chae Yoo ),( Hyeon Heui Ham ),( Young Tae Kim ),( Seong Min Kim ),( Moon S. Kim ) 한국농업기계학회 2017 바이오시스템공학 Vol.42 No.4
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.