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: 3122
Function: getPubMedXML
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
Nuclear Magnetic Resonance (NMR) spectroscopy is emerging as a powerful technique in olive oil fingerprinting, but its analytical robustness has to be proved. Here, we report a comparative study between two laboratories on olive oil (1)H NMR fingerprinting, aiming to demonstrate the robustness of NMR-based metabolomics in generating comparable data sets for cultivar classification. Sample preparation and data acquisition were performed independently in two laboratories, equipped with different resolution spectrometers (400 and 500 MHz), using two identical sets of mono-varietal olive oils. Partial Least Squares (PLS)-based techniques were applied to compare the data sets produced by the two laboratories. Despite differences in spectrum baseline, and in intensity and shape of peaks, the amount of shared information was significant (almost 70%) and related to cultivar (same metabolites discriminated between cultivars). In conclusion, regardless of the variability due to operator and machine, the data sets from the two participating units were comparable for the purpose of classification.
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Source |
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http://dx.doi.org/10.1016/j.foodchem.2015.12.064 | DOI Listing |
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