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Paper spray mass spectrometry and PLS-DA improved by variable selection for the forensic discrimination of beers
- Source :
- Analytica Chimica Acta. 940:104-112
- Publication Year :
- 2016
- Publisher :
- Elsevier BV, 2016.
-
Abstract
- Paper spray mass spectrometry (PS-MS) combined with partial least squares discriminant analysis (PLS-DA) was applied for the first time in a forensic context to a fast and effective differentiation of beers. Eight different brands of American standard lager beers produced by four different breweries (141 samples from 55 batches) were studied with the aim at performing a differentiation according to their market prices. The three leader brands in the Brazilian beer market, which have been subject to fraud, were modeled as the higher-price class, while the five brands most used for counterfeiting were modeled as the lower-price class. Parameters affecting the paper spray ionization were examined and optimized. The best MS signal stability and intensity was obtained while using the positive ion mode, with PS(+) mass spectra characterized by intense pairs of signals corresponding to sodium and potassium adducts of malto-oligosaccharides. Discrimination was not apparent neither by using visual inspection nor principal component analysis (PCA). However, supervised classification models provided high rates of sensitivity and specificity. A PLS-DA model using full scan mass spectra were improved by variable selection with ordered predictors selection (OPS), providing 100% of reliability rate and reducing the number of variables from 1701 to 60. This model was interpreted by detecting fifteen variables as the most significant VIP (variable importance in projection) scores, which were therefore considered diagnostic ions for this type of beer counterfeit.
- Subjects :
- Paper
Chromatography
Chemistry
010401 analytical chemistry
Beer
Feature selection
Context (language use)
02 engineering and technology
021001 nanoscience & nanotechnology
Mass spectrometry
Linear discriminant analysis
01 natural sciences
Biochemistry
Stability (probability)
Mass Spectrometry
United States
0104 chemical sciences
Analytical Chemistry
Statistics
Principal component analysis
Partial least squares regression
Mass spectrum
Environmental Chemistry
0210 nano-technology
Spectroscopy
Subjects
Details
- ISSN :
- 00032670
- Volume :
- 940
- Database :
- OpenAIRE
- Journal :
- Analytica Chimica Acta
- Accession number :
- edsair.doi.dedup.....24bf9ebb2988d465be1c17d1e3e30ced