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Quality-by-Design: Multivariate Model for Multicomponent Quantification in Refining Process of Honey
OBJECTIVE: A method for rapid analysis of the refining process of honey was developed based on near-infrared (NIR) spectroscopy. METHODS: Partial least square calibration models were built for the four components after the selection of the optimal spectral pretreatment method and latent factors. RES...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5307907/ https://www.ncbi.nlm.nih.gov/pubmed/28216906 http://dx.doi.org/10.4103/0973-1296.196310 |
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author | Li, Xiaoying Wu, Zhisheng Feng, Xin Liu, Shanshan Yu, Xiaojie Ma, Qun Qiao, Yanjiang |
author_facet | Li, Xiaoying Wu, Zhisheng Feng, Xin Liu, Shanshan Yu, Xiaojie Ma, Qun Qiao, Yanjiang |
author_sort | Li, Xiaoying |
collection | PubMed |
description | OBJECTIVE: A method for rapid analysis of the refining process of honey was developed based on near-infrared (NIR) spectroscopy. METHODS: Partial least square calibration models were built for the four components after the selection of the optimal spectral pretreatment method and latent factors. RESULTS: The models covered the samples of different temperatures and time points, therefore the models were robust and universal. CONCLUSIONS: These results highlighted that the NIR technology could extract the information of critical process and provide essential process knowledge of the honey refining process. SUMMARY: A method for rapid analysis of the refining process of honey was developed based on near-infrared (NIR) spectroscopy. Abbreviation used: NIR: Near-infrared; 5-HMF: 5-hydroxymethylfurfural; RMSEP: Root mean square error of prediction; R: correlation coefficients; PRESS: prediction residual error-sum squares; TCM: Traditional Chinese medicine; HPLC: High-performance liquid chromatography; HPLC-DAD: HPLC-diode array detector; PLS: Partial least square; MSC: multiplicative scatter correction; RMSECV: Root mean square error of cross validation; RPD: Residual predictive deviation; 1D: 1(st) order derivative; SG: Savitzky-Golay smooth; 2D: 2(nd) order derivative. |
format | Online Article Text |
id | pubmed-5307907 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-53079072017-02-17 Quality-by-Design: Multivariate Model for Multicomponent Quantification in Refining Process of Honey Li, Xiaoying Wu, Zhisheng Feng, Xin Liu, Shanshan Yu, Xiaojie Ma, Qun Qiao, Yanjiang Pharmacogn Mag Brief Communication OBJECTIVE: A method for rapid analysis of the refining process of honey was developed based on near-infrared (NIR) spectroscopy. METHODS: Partial least square calibration models were built for the four components after the selection of the optimal spectral pretreatment method and latent factors. RESULTS: The models covered the samples of different temperatures and time points, therefore the models were robust and universal. CONCLUSIONS: These results highlighted that the NIR technology could extract the information of critical process and provide essential process knowledge of the honey refining process. SUMMARY: A method for rapid analysis of the refining process of honey was developed based on near-infrared (NIR) spectroscopy. Abbreviation used: NIR: Near-infrared; 5-HMF: 5-hydroxymethylfurfural; RMSEP: Root mean square error of prediction; R: correlation coefficients; PRESS: prediction residual error-sum squares; TCM: Traditional Chinese medicine; HPLC: High-performance liquid chromatography; HPLC-DAD: HPLC-diode array detector; PLS: Partial least square; MSC: multiplicative scatter correction; RMSECV: Root mean square error of cross validation; RPD: Residual predictive deviation; 1D: 1(st) order derivative; SG: Savitzky-Golay smooth; 2D: 2(nd) order derivative. Medknow Publications & Media Pvt Ltd 2017 /pmc/articles/PMC5307907/ /pubmed/28216906 http://dx.doi.org/10.4103/0973-1296.196310 Text en Copyright: © 2017 Pharmacognosy Magazine http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms. |
spellingShingle | Brief Communication Li, Xiaoying Wu, Zhisheng Feng, Xin Liu, Shanshan Yu, Xiaojie Ma, Qun Qiao, Yanjiang Quality-by-Design: Multivariate Model for Multicomponent Quantification in Refining Process of Honey |
title | Quality-by-Design: Multivariate Model for Multicomponent Quantification in Refining Process of Honey |
title_full | Quality-by-Design: Multivariate Model for Multicomponent Quantification in Refining Process of Honey |
title_fullStr | Quality-by-Design: Multivariate Model for Multicomponent Quantification in Refining Process of Honey |
title_full_unstemmed | Quality-by-Design: Multivariate Model for Multicomponent Quantification in Refining Process of Honey |
title_short | Quality-by-Design: Multivariate Model for Multicomponent Quantification in Refining Process of Honey |
title_sort | quality-by-design: multivariate model for multicomponent quantification in refining process of honey |
topic | Brief Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5307907/ https://www.ncbi.nlm.nih.gov/pubmed/28216906 http://dx.doi.org/10.4103/0973-1296.196310 |
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