Application of multivariate statistical methods to the differentiation of gin brands

Martín-Álvarez, Pedro J.; Herranz, Alberto Herranz

doi:10.1002/jsfa.2740570210

Cited by 12 publications

(3 citation statements)

References 15 publications

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“…Besides, considering that a majority of the compounds selected as descriptors for discrimination purposes are volatile in nature, the analytical technique more prone to volatile congener determination is gas chromatography (GC). Thus, GC has been suitably used for discrimination purposes of several kinds of spirits and liquors such as gins (2), brandies and cognacs (3,4), rums (5), tequilas (6), and whiskeys (7)(8)(9). Our research, now in progress, is focused on whiskey discrimination, especially to distinguish among single malt Scotch whiskey, bourbon whiskey, and Irish whiskey.…”

Section: Introductionmentioning

confidence: 99%

Supervised Pattern Recognition Procedures for Discrimination of Whiskeys from Gas Chromatography/Mass Spectrometry Congener Analysis

González-Arjona

López-Pérez

González-Gallero

et al. 2006

J. Agric. Food Chem.

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The volatile congener analysis of 52 commercialized whiskeys (24 samples of single malt Scotch whiskey, 18 samples of bourbon whiskey, and 10 samples of Irish whiskey) was carried out by gas chromatography/mass spectrometry after liquid-liquid extraction with dichloromethane. Pattern recognition procedures were applied for discrimination of different whiskey categories. Multivariate data analysis includes linear discriminant analysis (LDA), k nearest neighbors (KNN), soft independent modeling of class analogy (SIMCA), procrustes discriminant analysis (PDA), and artificial neural networks techniques involving multilayer perceptrons (MLP) and probabilistic neural networks (PNN). Classification rules were validated by considering the number of false positives (FPs) and false negatives (FNs) of each class associated to the prediction set. Artificial neural networks led to the best results because of their intrinsic nonlinear features. Both techniques, MLP and PNN, gave zero FPs and zero FNs for all of the categories. KNN is a nonparametric method that also provides zero FPs and FNs for every class but only when selecting K = 3 neighbors. PDA produced good results also (zero FPs and FNs always) but only by selecting nine principal components for class modeling. LDA shows a lesser classification performance, because of the building of linear frontiers between classes that does not apply in many real situations. LDA led to one FP for bourbons and one FN for scotches. The worse results were obtained with SIMCA, which gave a higher number of FPs (five for both scotches and bourbons) and FNs (six for scotchs and two for bourbons). The possible cause of these findings is the strong influence of class inhomogeneities on the SIMCA performance. It is remarkable that in any case, all of the methodologies lead to zero FPs and FNs for the Irish whiskeys.

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Section: Introductionmentioning

confidence: 99%

Supervised Pattern Recognition Procedures for Discrimination of Whiskeys from Gas Chromatography/Mass Spectrometry Congener Analysis

González-Arjona

López-Pérez

González-Gallero

et al. 2006

J. Agric. Food Chem.

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“…The analysis of methanol and fusel oils enables different varieties of whiskies to be distinguished (Wilson et 01., 1991) and the composition ofthe 402 FERMENTED BEVERAGE PRODUCTION terpenic fraction extracted from gins is a good criterion for the characterisation of gin brands (Martin-Alvarez and Herranz, 1991). It should also be mentioned that high resolution I3C-NMR, which combines structural and quantitative information, is very helpful for defining variety profiles (Rapp and Markowetz, 1989).…”

Section: Detection Of Variety Mislabelling (Wines and Spirits)mentioning

confidence: 98%

Fermented Beverage Production

1995

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“…Chemometric methods,10, 11 such as principal component analysis (PCA) and hierarchical cluster analysis (HCA), have been successfully applied to chemical composition information to perform exploratory analysis of beverage samples 12–16. For instance, Herranz and coworkers17–19 characterized samples of whisky, rum, and gin by using ethyl acetate or terpene contents as variables. Seeber and coworkers20 also used multivariate analysis to distinguish between different vintages of Chardonnay musts and wines using amino acids, volatile organic compounds, and metal contents as variables.…”

Section: Introductionmentioning

confidence: 99%

Differentiation of rum and Brazilian artisan cachaça via electrospray ionization mass spectrometry fingerprinting

et al. 2007

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Rum and cachaça are sugarcane distillates produced on large scales and of similar composition, and their differentiation is currently a subject of commercial dispute and a challenging analytical task. We have investigated the ability of direct-infusion electrospray ionization mass spectrometry in the negative ion mode, i.e. ESI(-)-MS, to distinguish between samples of these distillates. ESI(-)-MS fingerprints were collected for some samples of Brazilian artisan cachaça, aged in two types of wooden casks, i. e. amburana (Amburana cearensis) and jequitibá (Cariniana estrellensis), and of commercial rum. The mass spectra were found to be very distinctive, showing sets of diagnostic ions for each type of sample, i. e. (1) cachaça aged in amburana (m/z 271, 313, 377) and jequitibá (m/z 171, 255, 455) casks; and (2) commercial rum (m/z 89, 97, 179, 255, 283). When applied to the ESI(-)-MS data, principal component analysis and hierarchical cluster analysis split rum and cachaça samples into well-defined groups. Moreover, the two types of cachaça samples aged in wooden casks of amburana or jequitibá were also split into two distinct groups. Direct-infusion ESI(-)-MS can therefore be potentially applied to the rapid, simple, and accurate differentiation of these commercially important sugarcane distillates.

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Application of multivariate statistical methods to the differentiation of gin brands

Abstract: Several multivariate statistical methods (principal component, discriminant (linear, quadratic and nearest neighbour)

Cited by 12 publications

References 15 publications

Supervised Pattern Recognition Procedures for Discrimination of Whiskeys from Gas Chromatography/Mass Spectrometry Congener Analysis

Supervised Pattern Recognition Procedures for Discrimination of Whiskeys from Gas Chromatography/Mass Spectrometry Congener Analysis

Fermented Beverage Production

Differentiation of rum and Brazilian artisan cachaça via electrospray ionization mass spectrometry fingerprinting

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