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
The potential of Raman chemical imaging for simultaneously detecting multiple adulterants in milk powder was investigated. Potential chemical adulterants, including ammonium sulphate, dicyandiamide, melamine, and urea, were mixed together into skim dry milk in the concentration range of 0.1-5.0% for each adulterant. Using a 785-nm laser, a Raman imaging system acquired hyperspectral images in the wavenumber range of 102-2538 cm(-1) for a 25 × 25 mm(2) area of each mixture sample, with a spatial resolution of 0.25 mm. Self-modelling mixture analysis (SMA) was used to extract pure component spectra, by which the four types of the adulterants were identified at all concentration levels based on their spectral information divergence values to the reference spectra. Raman chemical images were created using the contribution images from SMA, and their use to effectively visualise identification and spatial distribution of the multiple adulterant particles in the dry milk was demonstrated.
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Source |
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http://dx.doi.org/10.1016/j.foodchem.2012.10.115 | DOI Listing |
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