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Juan Cacho

Publications and source records attributed to Juan Cacho.

24 records · Page 2Linked to original sources
PubMed2003

Quantitative gas chromatography-olfactometry. Analytical characteristics of a panel of judges using a simple quantitative scale as gas chromatography detector.

Some questions related to the ability of gas chromatography-olfactometry (GC-O) to provide quantitative measurements of the concentration of a given odorant in an extract are explored and discussed. A panel of eight individuals has been used to evaluate the intensity of 15 odorants present at different concentrations. The use of very simple scales, such as a 0-3 scale, makes it possible to build calibration graphs based on the different stimulus-response models (Fechner, Stevens, Hill) and, with a proper calibration, up to nine different concentration levels can be discriminated by an eight-judge panel. The signal shows a good long-term stability, and its precision varies between 3.7 and 8% of the whole scale, with 5.7% as average. Sensitivity is extremely dependent on the compound: in the best case a concentration change of 20% can be detected, while in the worst, concentrations must differ more than one order of magnitude. In average, concentrations must differ between 2 and 4.7 times (including calibration error) or between 1.2 and 2.3 (excluding calibration error). The performance of the different judges, the effect of the close elution of two odors and the benefits derived from the use of more complex scales (7-points) are briefly discussed from the perspective of the analytical performance of GC-O methods.

Calibration↗
PubMed2003

Impact odorants of different young white wines from the Canary Islands.

Five young monovarietal white wines from the Canary Islands made from Gual, Verdello, Marmajuelo, white Listán, and Malvasia grape cultivars were studied to determine the characteristics of their most important aromas and the differences among them. The study was carried out using gas chromatography-olfactometry (GC-O) to detect the potentially most important aroma compounds, which were then analyzed quantitatively by gas chromatography-flame ionization detection and gas chromatography-mass spectrometry. The strongest odorants in the GC-O experiments were similar in all cases, although significant differences in intensity between samples were noted. Calculation of the odor activity values (OAVs) showed that 3-mercaptohexyl acetate was the most active odorant in the Marmajuelo and Verdello wines, as were 3-methylbutyl acetate in the Gual wine, beta-damascenone in the Malvasia wine, and ethyl octanoate in the white Listán wine. However, the most important differences between varieties were caused by the three mercaptans (3-mercaptohexyl acetate, 3-mercaptohexanol, and 4-methyl-4-mercapto-2-pentanone) and the vinylphenols (4-vinylphenol and 2-methoxy-4-vinylphenol). The correlation between the olfactometric values and the OAVs was satisfactory in the cases when the compound eluted in the GC-O system was well isolated from other odorants and had aromatic importance and the OAVs for the different wines were sufficiently different.

Atlantic Islands↗
PubMed2003

Prediction of aged red wine aroma properties from aroma chemical composition. Partial least squares regression models.

Partial least squares regression (PLSR) models able to predict some of the wine aroma nuances from its chemical composition have been developed. The aromatic sensory characteristics of 57 Spanish aged red wines were determined by 51 experts from the wine industry. The individual descriptions given by the experts were recorded, and the frequency with which a sensory term was used to define a given wine was taken as a measurement of its intensity. The aromatic chemical composition of the wines was determined by already published gas chromatography (GC)-flame ionization detector and GC-mass spectrometry methods. In the whole, 69 odorants were analyzed. Both matrixes, the sensory and chemical data, were simplified by grouping and rearranging correlated sensory terms or chemical compounds and by the exclusion of secondary aroma terms or of weak aroma chemicals. Finally, models were developed for 18 sensory terms and 27 chemicals or groups of chemicals. Satisfactory models, explaining more than 45% of the original variance, could be found for nine of the most important sensory terms (wood-vanillin-cinnamon, animal-leather-phenolic, toasted-coffee, old wood-reduction, vegetal-pepper, raisin-flowery, sweet-candy-cacao, fruity, and berry fruit). For this set of terms, the correlation coefficients between the measured and predicted Y (determined by cross-validation) ranged from 0.62 to 0.81. Models confirmed the existence of complex multivariate relationships between chemicals and odors. In general, pleasant descriptors were positively correlated to chemicals with pleasant aroma, such as vanillin, beta damascenone, or (E)-beta-methyl-gamma-octalactone, and negatively correlated to compounds showing less favorable odor properties, such as 4-ethyl and vinyl phenols, 3-(methylthio)-1-propanol, or phenylacetaldehyde.

Chromatography, Gas↗
PubMed2002

Determination of minor and trace volatile compounds in wine by solid-phase extraction and gas chromatography with mass spectrometric detection.

A new method for the quantitative determination of important wine odorants has been developed. The wine (50 ml) is extracted in a 200 mg solid-phase extraction (SPE) cartridge filled with Lichrolut-EN resins from Merck. The elution is carried out with 1.3 ml of dichloromethane. These extracts are directly analyzed by GC-Ion Trap-MS without further concentration. Twenty-seven important wine odorants, such as volatile phenols, vanillin derivatives, aliphatic lactones, nor-isoprenoids, minor esters and terpenols, can be quantitatively determined in a single gas chromatography-mass spectrometry (GC-MS) run. The recoveries in the SPE isolation are in good agreement with those expected from the calculation of breakthrough volumes from solid-liquid distribution coefficients and are higher than 90%, except for guaiacol, vanillin, 2,6-dimethoxyphenol and 4-vinylphenol. In most cases, precision is below 10%. Method linearity is satisfactory, with r2 higher than 0.99 in all cases. The analysis of spiked samples has shown that there is good agreement between the real mass of compound added to the wine and that determined by analysis. In all cases detection limits are below the odor detection threshold of the compounds, and the calibrated interval covers the natural range of occurrence of the compounds in wine.

Gas Chromatography-Mass Spectrometry↗
PubMed2002

Chemical characterization of the aroma of Grenache rosé wines: aroma extract dilution analysis, quantitative determination, and sensory reconstitution studies.

The aroma of a Grenache rosé wine from Calatayud (Zaragoza, Spain) has been elucidated following a strategy consisting of an aroma extract dilution analysis (AEDA), followed by the quantitative analysis of the main odorants and the determination of odor activities values (OAVs) and, finally, by a series of reconstitution and omission tests with synthetic aroma models. Thirty-eight aroma compounds were found in the AEDA study, 35 of which were identified. Twenty-one compounds were at concentrations higher than their corresponding odor thresholds. An aroma model prepared by mixing the 24 compounds with OAV > 0.5 in a synthetic wine showed a high qualitative similarity with the aroma of the rosé wine. The addition of compounds with OAV < 0.5 did not improve the model, whereas the aroma of a model containing only odorants with OAV > 10 was very different from that of the wine. Omission tests revealed that the most important odorant of this Grenache rosé wine was 3-mercapto-1-hexanol, with a deep impact on the wine fruity and citric notes. The synergic action of Furaneol and homofuraneol also had an important impact on wine aroma, particularly in its fruity and caramel notes. The omission of beta-damascenone, which had the second highest OAV, caused only a slight decrease on the intensity of the aroma model. Still weaker was the sensory effect caused by the omission of 10 other compounds, such as fatty acids and their ethyl esters, isoamyl acetate, and higher alcohols.

Chromatography, Gas↗