Prediction and discrimination of taxonomic relationship within Orostachys species using FT-IR spectroscopy combined by multivariate analysis = FT-IR 스펙트럼 데이터의 다변량 통계분석 기법을 이용한 바위솔속 식물의 분류학적 유연관계 예측 및 판별

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dc.contributor.authorY K Kwon-
dc.contributor.authorSuk Weon Kim-
dc.contributor.authorJ M Seo-
dc.contributor.authorT H Woo-
dc.contributor.authorJang Ryol Liu-
dc.date.accessioned2017-04-19T09:22:25Z-
dc.date.available2017-04-19T09:22:25Z-
dc.date.issued2011-
dc.identifier.issn1229-2818-
dc.identifier.uri10.5010/JPB.2011.38.1.009ko
dc.identifier.urihttps://oak.kribb.re.kr/handle/201005/10088-
dc.description.abstractTo determine whether pattern recognition based on metabolite fingerprinting for whole cell extracts can be used to discriminate cultivars metabolically, leaves of nine commercial Orostachys plants were subjected to Fourier transform infrared spectroscopy (FT-IR). FT-IR spectral data from leaves were analyzed by principal component analysis (PCA) and Partial least square discriminant analysis (PLS-DA). The dendrogram based on hierarchical clustering analysis of these PLS-DA data separated the nine Orostachys species into five major groups. The first group consisted of O. iwarenge ‘Yimge’, ‘Jeju’, ‘Jeongsun’ and O. margaritifolius ‘Jinju’ whereas in the second group, ‘Sacheon’ was clustered with ‘Busan,’ both of which belong to O. malacophylla species. However, ‘Samchuk’, belong to O. malacophylla was not clustered with the other O. malacophylla species. In addition, O. minuta and O. japonica were separated to the other Orostachys plants. Thus we suggested that the hierarchical dendrogram based on PLS-DA of FT-IR spectral data from leaves represented the most probable chemotaxonomical relationship between commercial Orostachys plants. Furthermore these metabolic discrimination systems could be applied for reestablishment of precise taxonomic classification of commercial Orostachys plants.-
dc.publisherKorea Soc-Assoc-Inst-
dc.titlePrediction and discrimination of taxonomic relationship within Orostachys species using FT-IR spectroscopy combined by multivariate analysis = FT-IR 스펙트럼 데이터의 다변량 통계분석 기법을 이용한 바위솔속 식물의 분류학적 유연관계 예측 및 판별-
dc.title.alternativePrediction and discrimination of taxonomic relationship within Orostachys species using FT-IR spectroscopy combined by multivariate analysis-
dc.typeArticle-
dc.citation.titleJournal of Plant Biotechnology-
dc.citation.number1-
dc.citation.endPage14-
dc.citation.startPage9-
dc.citation.volume38-
dc.contributor.affiliatedAuthorSuk Weon Kim-
dc.contributor.affiliatedAuthorJang Ryol Liu-
dc.contributor.alternativeName권용국-
dc.contributor.alternativeName김석원-
dc.contributor.alternativeName서정민-
dc.contributor.alternativeName우태하-
dc.contributor.alternativeName유장렬-
dc.identifier.bibliographicCitationJournal of Plant Biotechnology, vol. 38, no. 1, pp. 9-14-
dc.identifier.doi10.5010/JPB.2011.38.1.009-
dc.subject.keywordFourier transformation - infrared spectroscopy-
dc.subject.keywordOrostachys plants-
dc.subject.keywordPartial least square discriminant analysis (PLS-DA)-
dc.subject.keywordPrincipal component analysis-
dc.subject.localfourier transform infared spectroscopy-
dc.subject.localFourier transform-infrared spectroscopy-
dc.subject.localFourier transformation infrared (FT-IR) spectroscopy-
dc.subject.localFT-IR spectroscopy-
dc.subject.localFourier transform infrared spectroscopy (FT-IR)-
dc.subject.localFT-IR-
dc.subject.localFourier transformation - Infrared spectroscopy-
dc.subject.localFourier transformation - infrared spectroscopy-
dc.subject.localFTIR-
dc.subject.localfourier transformation infrared spectroscopy-
dc.subject.localFourier transform infrared spectroscopy-
dc.subject.localFourier transformation infrared spectroscopy (FT-IR)-
dc.subject.localFT-IR (Fourier transform infrared spectroscopy)-
dc.subject.localFourier transform IR-
dc.subject.localFourier transform-infrared spectroscopy (FT-IR)-
dc.subject.localOrostachys plants-
dc.subject.localPartial least squares discriminant analysis (PLS-DA)-
dc.subject.localPartial least squares-discriminant analysis (PLS-DA)-
dc.subject.localPartial least square discriminant analysis (PLS-DA)-
dc.subject.localprincipal component analysis (PCA)-
dc.subject.localPrincipal Component Analysis-
dc.subject.localPrincipal component analysis (PCA)-
dc.subject.localprincipal component analysis-
dc.subject.localprincipal components analysis-
dc.subject.localPrincipal component analysis-
dc.description.journalClassN-
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Jeonbuk Branch Institute > Biological Resource Center > 1. Journal Articles
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