Determination of glucose in tea using Near inferred spectroscopy combined with chemometrics

カテゴリ: 研究会(論文単位)

論文No: DEI18023

グループ名: 【A】基礎・材料・共通部門 誘電・絶縁材料研究会

発行日: 2018/01/23

タイトル(英語): Determination of glucose in tea using Near inferred spectroscopy combined with chemometrics

著者名: Wongravee Kanet(Chulalongkorn University),Makmuang Sureerat(Chulalongkorn University),Pienpinijtham Prompong(Chulalongkorn University),Ekgasit Sanong(Chulalongkorn University)

著者名(英語): Kanet Wongravee(Chulalongkorn University),Sureerat Makmuang(Chulalongkorn University),Prompong Pienpinijtham(Chulalongkorn University),Sanong Ekgasit(Chulalongkorn University)

キーワード: Chemometrics|Near Infared Spectroscopy|glucose|non-alcoholic drink|PCA|PLSR|Chemometrics|Near Infared Spectroscopy|glucose|non-alcoholic drink|PCA|PLSR

要約(日本語): In many research uses, near infrared (NIR) spectroscopy combined with chemometrics has been employed to determine and quantify amount of glucose. By conventional way, a calibration curve is required to build a statistical model for quantitative analysis of a system. Several calibration curve might be required for several systems. To avoid these complicated set up, we propose a new alternative technique called “global model” for quantitative analysis of glucose in nonalcoholic drinks. To construct the global model, it involves the extraction and selection of significant components (water and glucose in the case) prior to build the calibration model. The global calibration model was used to predict concentrations of glucose in non-alcoholic drinks without any requirement for new set of calibration curve. Partial least-squares regression (PLSR) was used to construct calibration models to predict concentrations of glucose. The corresponding values for the root mean square error of calibration (RMSEC), cross validation (RMSECV) and prediction (RMSEP) of the global model to predict glucose contration in tea were found to be 0.04, 0.30 and 0.57, respectively.

要約(英語): In many research uses, near infrared (NIR) spectroscopy combined with chemometrics has been employed to determine and quantify amount of glucose. By conventional way, a calibration curve is required to build a statistical model for quantitative analysis of a system. Several calibration curve might be required for several systems. To avoid these complicated set up, we propose a new alternative technique called “global model” for quantitative analysis of glucose in nonalcoholic drinks. To construct the global model, it involves the extraction and selection of significant components (water and glucose in the case) prior to build the calibration model. The global calibration model was used to predict concentrations of glucose in non-alcoholic drinks without any requirement for new set of calibration curve. Partial least-squares regression (PLSR) was used to construct calibration models to predict concentrations of glucose. The corresponding values for the root mean square error of calibration (RMSEC), cross validation (RMSECV) and prediction (RMSEP) of the global model to predict glucose contration in tea were found to be 0.04, 0.30 and 0.57, respectively.

原稿種別: 英語

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