Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: Dendrobium huoshanense (DHS) is a classic traditional Chinese medicine (TCM) with distinctive medicinal benefits and great economic worth; nevertheless, because of similar tastes and looks, it is simple to adulterate with less expensive substitutes (such as Dendrobium henanense [DHN]).
Objective: This work aimed to develop a reliable tool to detect and quantify the adulteration of DHS with DHN by using UV-Vis-shortwave near-infrared diffuse reflectance spectroscopy (UV-Vis-SWNIR DRS) combined with chemometrics.
Methods: Adulterated samples prepared in varying concentrations (0-100%, w/w) were analyzed with UV-Vis-SWNIR DRS methods. Partial least-square-discriminant analysis (PLS-DA) and partial least-squares (PLS) regression techniques were used for the differentiation of adulterated DHN from pure DHS and the prediction of adulteration levels.
Results: The PLS-DA classification models successfully differentiated adulterated and nonadulterated DHS with an over 100% correct classification rate. UV-Vis-SWNIR DRS data were also successfully used to predict adulteration levels with a high coefficient of determination for calibration (0.9924) and prediction (0.9906) models and low error values for calibration (3.863%) and prediction (5.067%).
Conclusion: UV-Vis-SWNIR DRS, as a fast and environmentally friendly tool, has great potential for both the identification and quantification of adulteration practices involving herbal medicines and foods.
Highlights: UV-Vis-SWNIR DRS combined with chemometrics can be applied to identify and quantify the adulteration of herbal medicines and foods.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1093/jaoacint/qsad090 | DOI Listing |
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