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Leaner and greener analysis of cannabinoids

Overview of attention for article published in Analytical & Bioanalytical Chemistry, February 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

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1 news outlet
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12 X users
facebook
2 Facebook pages

Citations

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51 Dimensions

Readers on

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211 Mendeley
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Title
Leaner and greener analysis of cannabinoids
Published in
Analytical & Bioanalytical Chemistry, February 2017
DOI 10.1007/s00216-017-0256-3
Pubmed ID
Authors

Elizabeth M. Mudge, Susan J. Murch, Paula N. Brown

Abstract

There is an explosion in the number of labs analyzing cannabinoids in marijuana (Cannabis sativa L., Cannabaceae) but existing methods are inefficient, require expert analysts, and use large volumes of potentially environmentally damaging solvents. The objective of this work was to develop and validate an accurate method for analyzing cannabinoids in cannabis raw materials and finished products that is more efficient and uses fewer toxic solvents. An HPLC-DAD method was developed for eight cannabinoids in cannabis flowers and oils using a statistically guided optimization plan based on the principles of green chemistry. A single-laboratory validation determined the linearity, selectivity, accuracy, repeatability, intermediate precision, limit of detection, and limit of quantitation of the method. Amounts of individual cannabinoids above the limit of quantitation in the flowers ranged from 0.02 to 14.9% w/w, with repeatability ranging from 0.78 to 10.08% relative standard deviation. The intermediate precision determined using HorRat ratios ranged from 0.3 to 2.0. The LOQs for individual cannabinoids in flowers ranged from 0.02 to 0.17% w/w. This is a significant improvement over previous methods and is suitable for a wide range of applications including regulatory compliance, clinical studies, direct patient medical services, and commercial suppliers.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 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 211 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 211 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 41 19%
Student > Bachelor 31 15%
Student > Master 24 11%
Student > Ph. D. Student 22 10%
Student > Doctoral Student 8 4%
Other 21 10%
Unknown 64 30%
Readers by discipline Count As %
Chemistry 41 19%
Agricultural and Biological Sciences 27 13%
Biochemistry, Genetics and Molecular Biology 18 9%
Pharmacology, Toxicology and Pharmaceutical Science 14 7%
Engineering 6 3%
Other 33 16%
Unknown 72 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 30 November 2023.
All research outputs
#2,086,688
of 25,382,440 outputs
Outputs from Analytical & Bioanalytical Chemistry
#128
of 9,619 outputs
Outputs of similar age
#39,423
of 324,444 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#1
of 165 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,619 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done particularly well, scoring higher than 98% 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 324,444 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 165 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.