Coupling gas chromatography and electronic nose for dehydration and de-alcoholization of alcoholised beverages. Application to off-flavour detection in wine

International audienceAroma characterization of alcoholic beverages with sensor array electronic noses is a difficult challenge due to the masking effect of ethanol. Back-flush gas chromatography is proposed as a novel tool for the pretreatment of vapour samples before analysis in the electronic nose. The dehydration and desalcoholization step can be conducted in parallel with electronic nose detection, reducing significantly the analysis overall duration. As demonstration application, five molecules responsible for off-flavours in wines have been detected with a FOX 4000 system, after total dehydration and desalcoholization. Principal component analysis showed that discrimination between the control wine and off-flavour doped-wines became easy, even at concentrations corresponding to the human expert perception threshold. Back-flush gas chromatography is proposed as a novel tool for the pretreatment of vapour samples before analysis in the electronic nose. The dehydration and desalcoholization step can be conducted in parallel with electronic nose detection, reducing significantly the analysis overall duration. As demonstration application, five molecules responsible for off-flavours in wines have been detected with a FOX 4000 system, after total dehydration and desalcoholization. Principal component analysis showed that discrimination between the control wine and off-flavour doped-wines became easy, even at concentrations corresponding to the human expert perception threshold

Qualitative Analysis of Age and Brand of Unblended Brandy by Electronic Nose

Part 1: GIS, GPS, RS and Precision FarmingInternational audienceThis paper reports the capability of electronic nose based on gas chromatograph (GC-Flash) in age identification and brand classification of brandy. Three different kinds of brandies by the static headspace sampling for the injection of the volatile compounds were analyzed. The data were disposed by multivariate data processing based on principal component analysis (PCA) and cluster analysis (CA). The results show that PCA could identify the age as PC1 represented the raw information of age well; PCA on small difference ages of the samples could classify the brands of the samples. The CA would cluster samples by age through its analysis on the three different kinds of brandies respectively; The CA on all samples indicated that significant differences existed among different brands with age under 20 years and clustering process performed firstly in each group by age information and then clustering progressively by age among all groups. GC-Flash electronic nose can be applied to identify the brand and age of different brandies