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A comparison of semi-quantitative methods suitable for establishing volatile profiles

Overview of attention for article published in Plant Methods, August 2018
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Title
A comparison of semi-quantitative methods suitable for establishing volatile profiles
Published in
Plant Methods, August 2018
DOI 10.1186/s13007-018-0335-2
Pubmed ID
Authors

Victoria Ruiz-Hernández, María José Roca, Marcos Egea-Cortines, Julia Weiss

Abstract

Full scent profiles emitted by living tissues can be screened by using total ion chromatograms generated in full scan mode and gas chromatography-mass spectrometry technique using Headspace Sorptive Extraction. This allows the identification of specific compounds and their absolute quantification or relative abundance. Quantifications ideally should be based on calibration curves using standards for each compound. However, the unpredictable composition of Volatile Organic Compounds (VOCs) and lack of standards make this approach difficult. Researchers studying scent profiles therefore concentrate on identifying specific scent footprints i.e. relative abundance rather than absolute quantities. We compared several semi-quantitative methods: external calibration curves generated in the sampling system and by liquid addition of standards to stir bars, total integrated peak area per fresh weight (FW), normalized peak area per FW, semi-quantification based on internal standard abundance, semi-quantification based on the nearest n-alkane and percentage of emission. Furthermore, we explored the usage of nearest components and single calibrators for semi-quantifications. Any of the semi-quantification methods based on a standard produced similar or even identical results compared to quantification by a true-standard for a compound, except for the method based on standard addition. Each method beholds advantages and disadvantages regarding level of accuracy, experimental variability, acceptance and retrieved quantities. Our data shows that, except for the method of standard addition to the biological sample, the rest of the semi-quantification methods studied give highly similar statistical results. Any of the methodologies presented here can therefore be considered as valid for scent profiling. Regarding relative proportions of VOCs, the generation of calibration curves for each compound analysed is not necessary.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 105 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 17%
Researcher 15 14%
Student > Master 15 14%
Student > Doctoral Student 8 8%
Student > Bachelor 8 8%
Other 16 15%
Unknown 25 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 25%
Environmental Science 12 11%
Chemistry 9 9%
Biochemistry, Genetics and Molecular Biology 8 8%
Engineering 6 6%
Other 14 13%
Unknown 30 29%
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 21 August 2018.
All research outputs
#13,624,398
of 23,099,576 outputs
Outputs from Plant Methods
#639
of 1,094 outputs
Outputs of similar age
#169,774
of 331,387 outputs
Outputs of similar age from Plant Methods
#16
of 31 outputs
Altmetric has tracked 23,099,576 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,094 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 38th percentile – i.e., 38% 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 331,387 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.