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Olive oil authenticity studies by target and nontarget LC–QTOF-MS combined with advanced chemometric techniques

Overview of attention for article published in Analytical & Bioanalytical Chemistry, September 2016
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3 X users

Citations

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58 Dimensions

Readers on

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97 Mendeley
Title
Olive oil authenticity studies by target and nontarget LC–QTOF-MS combined with advanced chemometric techniques
Published in
Analytical & Bioanalytical Chemistry, September 2016
DOI 10.1007/s00216-016-9891-3
Pubmed ID
Authors

Natasa P. Kalogiouri, Nikiforos A. Alygizakis, Reza Aalizadeh, Nikolaos S. Thomaidis

Abstract

Food analysis is continuously requiring the development of more robust, efficient, and cost-effective food authentication analytical methods to guarantee the safety, quality, and traceability of food commodities with respect to legislation and consumer demands. Hence, a novel reversed-phase ultra high performance liquid chromatography-electrospray ionization quadrupole time of flight tandem mass spectrometry analytical method was developed that uses target, suspect, and nontarget screening strategies coupled with advanced chemometric tools for the investigation of the authenticity of extra virgin olive oil. The proposed method was successfully applied in real olive oil samples for the identification of markers responsible for the sensory profile. The proposed target analytical method includes the determination of 14 phenolic compounds and demonstrated low limits of detection ranging from 0.015 μg mL(-1) (apigenin) to 0.039 μg mL(-1) (vanillin) and adequate recoveries (96-107 %). A suspect list of 60 relevant compounds was compiled, and suspect screening was then applied to all the samples. Semiquantitation of the suspect compounds was performed with the calibration curves of target compounds having similar structures. Then, a nontarget screening workflow was applied with the aim to identify additional compounds so as to differentiate extra virgin olive oils from defective olive oils. Robust classification-based models were built with the use of supervised discrimination techniques, partial least squares-discriminant analysis and counterpropagation artificial neural networks, for the classification of olive oils into extra virgin olive oils or defective olive oils. Variable importance in projection scores were calculated to select the most significant features that affect the discrimination. Overall, 51 compounds were identified and suggested as markers, among which 14, 26, and 11 compounds were identified by target, suspect, and nontarget screening respectively. Retrospective analysis was also performed and identified 19 free fatty acids. Graphical Abstract Development of a novel RP-LC-ESI-QTOFMS analytical method employing target, suspect and non-target screening strategies coupled to advanced chemometric tools for the investigation of markers responsible for the sensory profile of extra virgin olive oil and guarantee authenticity.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 97 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 20%
Student > Ph. D. Student 17 18%
Researcher 12 12%
Student > Doctoral Student 8 8%
Student > Bachelor 5 5%
Other 11 11%
Unknown 25 26%
Readers by discipline Count As %
Chemistry 36 37%
Agricultural and Biological Sciences 8 8%
Engineering 5 5%
Biochemistry, Genetics and Molecular Biology 4 4%
Environmental Science 3 3%
Other 10 10%
Unknown 31 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 November 2016.
All research outputs
#15,740,207
of 25,374,917 outputs
Outputs from Analytical & Bioanalytical Chemistry
#4,753
of 9,619 outputs
Outputs of similar age
#202,041
of 348,371 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#45
of 190 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,619 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 348,371 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 190 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.