Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200457034 ISBN 13: 9786200457035
Librería: Books Puddle, New York, NY, Estados Unidos de America
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Okt 2019, 2019
ISBN 10: 6200457034 ISBN 13: 9786200457035
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 39,90
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Mahonia bealei (Fort.) Carr. (M. bealei) plays an important role in the treatment of many diseases. In the present study, a comprehensive method combining supercritical fluid chromatography (SFC) fingerprints and chemical pattern recognition (CPR) for quality evaluation of M. bealei was developed. Similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA) were applied to classify and evaluate the samples of wild M. bealei, cultivated M. bealei and its substitutes according to the peak area of 11 components but an accurate classification could not be achieved. PLS-DA was then adopted to select the characteristic variables based on variable importance in projection (VIP) values that responsible for accurate classification. Six characteristics peaks with higher VIP values (¿1) were selected for building the CPR model. Based on the six variables, three types of samples were accurately classified into three related clusters. The model was further validated by a testing set samples and predication set samples. The results indicated the model was successfully established and predictive ability was also verified satisfactory. 68 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200457034 ISBN 13: 9786200457035
Librería: Majestic Books, Hounslow, Reino Unido
EUR 66,88
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200457034 ISBN 13: 9786200457035
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 66,78
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200457034 ISBN 13: 9786200457035
Librería: moluna, Greven, Alemania
EUR 34,25
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: HUANG YangIn December 2017, Dr. Yang HUANG obtained a double Ph.D degree from Jinan University (Guangzhou, China) and Univeristy of Liege (Liege, Belgium). At present, his research topics are mainly focused on quality evaluation and .
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Okt 2019, 2019
ISBN 10: 6200457034 ISBN 13: 9786200457035
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 39,90
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Mahonia bealei (Fort.) Carr. (M. bealei) plays an important role in the treatment of many diseases. In the present study, a comprehensive method combining supercritical fluid chromatography (SFC) fingerprints and chemical pattern recognition (CPR) for quality evaluation of M. bealei was developed. Similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA) were applied to classify and evaluate the samples of wild M. bealei, cultivated M. bealei and its substitutes according to the peak area of 11 components but an accurate classification could not be achieved. PLS-DA was then adopted to select the characteristic variables based on variable importance in projection (VIP) values that responsible for accurate classification. Six characteristics peaks with higher VIP values (¿1) were selected for building the CPR model. Based on the six variables, three types of samples were accurately classified into three related clusters. The model was further validated by a testing set samples and predication set samples. The results indicated the model was successfully established and predictive ability was also verified satisfactory.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200457034 ISBN 13: 9786200457035
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 40,89
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Mahonia bealei (Fort.) Carr. (M. bealei) plays an important role in the treatment of many diseases. In the present study, a comprehensive method combining supercritical fluid chromatography (SFC) fingerprints and chemical pattern recognition (CPR) for quality evaluation of M. bealei was developed. Similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA) were applied to classify and evaluate the samples of wild M. bealei, cultivated M. bealei and its substitutes according to the peak area of 11 components but an accurate classification could not be achieved. PLS-DA was then adopted to select the characteristic variables based on variable importance in projection (VIP) values that responsible for accurate classification. Six characteristics peaks with higher VIP values (¿1) were selected for building the CPR model. Based on the six variables, three types of samples were accurately classified into three related clusters. The model was further validated by a testing set samples and predication set samples. The results indicated the model was successfully established and predictive ability was also verified satisfactory.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200457034 ISBN 13: 9786200457035
Librería: preigu, Osnabrück, Alemania
EUR 35,60
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Supercritical Fluid Chromatography with Chemical Pattern Recognition | Quality Evaluation using SFC and CPR | Yang Huang (u. a.) | Taschenbuch | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200457035 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.