ArticleAnalytical science advances2020
Quantification of whisky congeners by
Article in Analytical science advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Food for Thought: Optical Sensor Arrays and Machine Learning for the Food and Beverage Industry.ACS sensors · 2024Review
- Growth of Plasmonic Nanoparticles for Aging Cask-Matured Whisky.ACS applied nano materials · 2022Article
- Quantification of whisky congeners byAnalytical science advances · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Whisky is a complex mixture made up of thousands of compounds originating in different stages of its production. Analysis of whisky congeners is critical to our understanding of the manufacturing process, quality control, and the detection of counterfeit products. The current chromatographic methods have a long analysis time, can require milliliters of sample and may not detect all required compounds in a single analysis. We have demonstrated that the majority of the whisky congeners of interest can be analyzed using
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.