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Discrimination model for cultivation origin of paper mulberry bast fiber and Hanji based on NIR and MIR spectral data combined with PLS-DA

Vol.32 No.1, 2019.2, 7-16 (10 pages)
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Abstract
The objective of this study was the development of a discrimination model for the cultivational origin of paper mulberry bast fiber and Hanji using near infrared (NIR) and mid infrared (MIR) spectroscopy combined with partial least squares discriminant analysis (PLS-DA). Paper mulberry bast fiber was purchased in 10 different regions of Korea, and used to make Hanji. PLS-DA was performed using pre-treated FT-NIR and FT-MIR spectral data for paper mulberry bast fiber and Hanji. PLS-DA of paper mulberry bast fiber and Hanji samples, using FT-NIR spectral data, showed 100% performance in cross validation and the confusion matrix (accuracy, sensitivity, and specificity). The discrimination models showed four regional groups which demonstrated clearer separation and much superior score plots in the NIR spectral data-based model than in the MIR spectral data-based model. Furthermore, the discrimination model based on the NIR spectral data of paper mulberry bast fiber had highly similar score morphology to that of the discrimination model based on the NIR spectral data of Hanji.

본 연구에서는 닥나무 인피섬유와 이를 이용하여 제조한 한지의 FT-NIR및 FT-MIR 스펙트럼 데이터를 각각PLS-DA에 적용하여 닥나무 인피섬유 및 한지의 원산지 판별 모델을 개발하고자 하였다. 본 연구를 위하여 서로 다른 원산지의 국내산 닥나무 인피섬유 10점을 채취하여 한지로 제조하였다. 상기시료의 FT-NIR 및 FT-IR 스펙트럼 데이터는 데이터 전처리 과정을 거쳐 PLS-DA를 수행하였다. 모델링 결과, 닥나무 인피섬유와 한지의 NIR 스펙트럼 데이터가 판별모델의 교차 검증결과 및 성능평가(정확도, 민감도, 특이도)에서 모두 100%로 MIR 스펙트럼 데이터보다 우수한 판별 성능을 나타냈다. 또한 지역별로 4개의 그룹을 형성하는 것을 확인 할 수 있었으며, 닥나무 인피섬유와 한지의 원산지 판별 모델간 score 형태가 유사하게 나타내는 것을 확인하였다.

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1. 서론
2. 재료 및 방법
3. 결과 및 고찰
4. 결론
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