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 use of portable micro-spectrometers such as a micro near infrared region (microNIR) spectrometer is a promising technique for solving analytical problems in several areas of science. This work evaluated the potential of microNIR in quality control of Arabica coffee. Arabica coffee has a high commercial value product, motivating the development of analytical methods with high sensitivity and accuracy for detection of its adulteration. Herein, microNIR was successfully used to determine the quality of Arabica coffee by identification and quantification of adulterations such as Robusta coffee (in different roasting levels), as well as corn, peels, and sticks. MicroNIR was combined with multivariate calibration by partial least squares (PLS) and principal component analysis (PCA). A total of 125 blends were produced, containing thirteen different concentrations of the adulterants (corn and peels/sticks, and the Robusta coffee) ranging from 1 to 100wt%. Developed PCA and PLS models were also applied to monitor the quality of sixteen commercial coffee samples. The results obtained using microNIR proved the ability of the method to be efficient and capable in the prediction of adulterations with minimum quantification levels (LOQs of 5-8wt%), being able to be applied to quality control of commercial coffee samples. Therefore, microNIR can reduce and simplify the time of analysis and sample preparation step, as well as to guarantee the efficiency of real-time data acquisition owing to its portability.
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Source |
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http://dx.doi.org/10.1016/j.talanta.2017.08.009 | DOI Listing |
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