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Screening of cannabinoids in industrial‐grade hemp using two‐dimensional liquid chromatography coupled with acidic potassium permanganate chemiluminescence detection

Overview of attention for article published in Journal of Separation Science (JSS) (formerly Journal of High Resolution Chromatography), May 2015
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

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Citations

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33 Dimensions

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72 Mendeley
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Title
Screening of cannabinoids in industrial‐grade hemp using two‐dimensional liquid chromatography coupled with acidic potassium permanganate chemiluminescence detection
Published in
Journal of Separation Science (JSS) (formerly Journal of High Resolution Chromatography), May 2015
DOI 10.1002/jssc.201500088
Pubmed ID
Authors

Jessica Pandohee, Brendan J Holland, Bingshan Li, Takuya Tsuzuki, Paul G Stevenson, Neil W Barnett, James R Pearson, Oliver A H Jones, Xavier A Conlan

Abstract

Widely known for its recreational use, the cannabis plant also has the potential to act as an antibacterial agent in the medicinal field. The analysis of cannabis plants/products in both pharmacological and forensic studies often requires the separation of compounds of interest and/or accurate identification of the whole cannabinoid profile. In order to provide a complete separation and detection of cannabinoids, a new two-dimensional liquid chromatography method has been developed using acidic potassium permanganate chemiluminescence detection, which has been shown to be selective for cannabinoids. This was carried out using a Luna 100 Å CN column and a Poroshell 120 EC-C18 column in the first and second dimension respectively. The method has utilised a large amount of the available separation space with a spreading angle of 48.4° and a correlation of 0.66 allowing the determination of more than 120 constituents and mass spectral identification of ten cannabinoids in a single analytical run. The method has potential to improve research involved in the characterisation of sensitive, complex matrices. This article is protected by copyright. All rights reserved.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 71 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 22%
Student > Bachelor 12 17%
Researcher 12 17%
Student > Master 6 8%
Professor > Associate Professor 3 4%
Other 4 6%
Unknown 19 26%
Readers by discipline Count As %
Chemistry 14 19%
Agricultural and Biological Sciences 7 10%
Pharmacology, Toxicology and Pharmaceutical Science 5 7%
Chemical Engineering 4 6%
Engineering 4 6%
Other 10 14%
Unknown 28 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 05 March 2019.
All research outputs
#7,301,044
of 25,368,786 outputs
Outputs from Journal of Separation Science (JSS) (formerly Journal of High Resolution Chromatography)
#402
of 3,583 outputs
Outputs of similar age
#81,371
of 279,161 outputs
Outputs of similar age from Journal of Separation Science (JSS) (formerly Journal of High Resolution Chromatography)
#12
of 39 outputs
Altmetric has tracked 25,368,786 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 3,583 research outputs from this source. They receive a mean Attention Score of 2.4. This one has done well, scoring higher than 88% of its peers.
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 279,161 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 39 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 69% of its contemporaries.