ArticleRSC advances2023
Development of an automated Raman system and use of principal component analysis to classify real and counterfeit liquors.
Article in RSC advances, 2023. 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
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Who cites it
3 citing papers in PubMed.
- Portable Spatially Offset Raman Spectroscopy for Rapid Detection of Methanol and Ethanol in Pisco Through Sealed Containers.Molecules (Basel, Switzerland) · 2026Article
- Recent Advances in Raman Spectral Classification with Machine Learning.Sensors (Basel, Switzerland) · 2026Review
- Raman analysis of lipids in cells: Current applications and future prospects.Journal of pharmaceutical analysis · 2025Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We developed an automated Raman measurement platform for the customized design of various solution containers. We used the software LabVIEW to integrate the entire automatic measurement process. By designing an intuitive human-machine interface, the user only needs to input a few setting parameters and can efficiently operate the machine in automation mode for an array of solutions containing real or counterfeit liquors such as kaoliang liquor, vodka, rum, gin, rice wine, ethanol, and methanol. In this study, data from various alcoholic beverage solutions were subjected to principal component analysis (PCA) to distinguish from the low-concentration counterfeit liquors (methanol <50 g L
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Registered trials
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