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The goal of this article is to guide the reader through the critical points to be faced when monitoring a fermentation following a Process Analytical Technology (PAT) approach. To achieve this purpose Attenuated Total Reflectance – Mid-Infrared (ATR-MIR) spectroscopy coupled to chemometric techniques are proposed. Each of the crucial steps (set up of microvinifications, sampling, spectroscopic analysis and chemometric data treatment) is deeply investigated, revealing how the sampling is decisive for the subsequent modeling phase, suggesting how to set parameters to obtain good quality signals, and explaining how to prepare the data for the chemometric modeling and to perform the calculations. The modeling strategies here presented, based mainly on basic chemometric tools such as principal component analysis and partial least square regression, proved to be effective to the purposes and affordable even for non-expert chemometric users. The article shows, using real examples, how to obtain or predict several parameters from a fermentation data set – control of the fermentation evolution, prediction of oenological parameters during the alcoholic fermentation and detection of deviations from the normal operation condition.

Wine production processes still rely on post-production evaluation and off-site laboratory analyses to ensure the quality of the final product. Here we propose an at-line methodology that combines a portable ATR-MIR spectrometer and multivariate analysis to control the alcoholic fermentation process and to detect wine fermentation problems. In total, 36 microvinifications were conducted, 14 in normal fermentation conditions (NFC) and 22 intentionally contaminated fermentations (ICF) with different lactic acid bacteria (LAB) concentrations. ATR-MIR measurements were collected during alcoholic and malolactic fermentations and relative density, pH, and l -malic acid were analyzed by traditional methods. Partial Least Squares Regression could suitably predict density and pH in fermenting samples (root mean squared errors of prediction of 0.0014 g mL−1 and 0.06 respectively). With regard to ICF, LAB contamination was detected by multivariate discriminant analysis when the difference in l -malic acid concentration between NFC and ICF was in the order of 0.7–0.8 g L−1, before the end of malolactic fermentation. This methodology shows great potential as a fast and simple at-line analysis tool for detecting fermentation problems at an early stage.

Despite the winemaker’s efforts, deviations such as bacterial spoilage can occur during wine alcoholic fermentation resulting in economic losses and low quality wines. When a deviation is suspected, samples are usually sent to an oenological laboratory for the off-line analysis of specific quality control parameters. The use of ATR-MIR as a fast analytical tool to monitor the fermentation process could be very useful, as getting real-time information of the process allows making readjustments before the process ends. In this study, we aimed at detecting white wine spoilage during alcoholic fermentation due to the action of lactic bacteria using a portable ATR-MIR instrument and MSPC charts. A total of 33 small-scale alcoholic fermentations were conducted (25 in normal operation conditions (NOC) and 8 simulating a bacterial spoilage with the addition of lactic bacteria (MLF)) to evaluate the capability of the MSPC charts to detect deviations from NOC. MSPC control charts were developed based on Q residuals and Hotelling’s T2 statistics. Time-wise unfolding was applied to the original three-way data to build different PCA models, obtaining very satisfactory results: MLF samples were detected before the end of alcoholic fermentation in the Q residuals charts after 80 hours and Hotelling T2 chart could also differentiate the samples after 100 hours.

We have investigated the effect of thermal treatment on the discrimination of pure extra virgin olive oil (EVOO) samples from EVOO samples adulterated with sunflower oil. Two groups of samples were used. One group was analyzed at room temperature (25°C) and the other group was thermally treated in a thermostatic water bath at 75°C for 8h, in contact with air and with light exposure, to favor oxidation. All samples were then measured with synchronous fluorescence spectroscopy. Fluorescence spectra were acquired by varying the excitation wavelength in the region from 250 to 720nm. In order to optimize the differences between excitation and emission wavelengths, four constant differential wavelengths, i.e., 20nm, 40nm, 60nm and 80nm, were tried. Partial least-squares discriminant analysis (PLS-DA) was used to discriminate between pure and adulterated oils. It was found that the 20nm difference was the optimal, at which the discrimination models showed the best results. The best PLS-DA models were those built with the difference spectra (75-25°C), which were able to discriminate pure from adulterated oils at a 2% level of adulteration. Furthermore, PLS regression models were built to quantify the level of adulteration. Again, the best model was the one built with the difference spectra, with a prediction error of 1.75% of adulteration.

DOI: 10.1016/j.saa.2016.10.042 URL: http://www.sciencedirect.com/science/article/pii/S1386142516306370 Filiació URV: SI Inclòs a la memòria: SI Headspace mass-spectrometry (HS-MS), mid infrared (MIR) and UV¿vis spectroscopy were used to authenticate whisky samples from different origins and ways of production ((Irish, Spanish, Bourbon, Tennessee Whisky and Scotch). The collected spectra were processed with partial least-squares discriminant analysis (PLS-DA) to build the classification models. In all cases the five groups of whiskies were distinguished, but the best results were obtained by HS-MS, which indicates that the biggest differences between different types of whisky are due to their aroma. Differences were also found inside groups, showing that not only raw material is important to discriminate samples but also the way of their production. The methodology is quick, easy and does not require sample preparation.

Three instrumental techniques, headspace-mass spectrometry (HS-MS), mid-infrared spectroscopy (MIR) and UV–visible spectrophotometry (UV–vis), have been combined to classify virgin olive oil samples based on the presence or absence of sensory defects. The reference sensory values were provided by an official taste panel. Different data fusion strategies were studied to improve the discrimination capability compared to using each instrumental technique individually. A general model was applied to discriminate high-quality non-defective olive oils (extra-virgin) and the lowest-quality olive oils considered non-edible (lampante). A specific identification of key off-flavours, such as musty, winey, fusty and rancid, was also studied. The data fusion of the three techniques improved the classification results in most of the cases. Low-level data fusion was the best strategy to discriminate musty, winey and fusty defects, using HS-MS, MIR and UV–vis, and the rancid defect using only HS-MS and MIR. The mid-level data fusion approach using partial least squares-discriminant analysis (PLS-DA) scores was found to be the best strategy for defective vs non-defective and edible vs non-edible oil discrimination. However, the data fusion did not sufficiently improve the results obtained by a single technique (HS-MS) to classify non-defective classes. These results indicate that instrumental data fusion can be useful for the identification of sensory defects in virgin olive oils.

DOI: 10.1016/j.talanta.2016.04.040 URL: http://www.sciencedirect.com/science/article/pii/S0039914016302818 Filiació URV: SI Headspace-Mass Spectrometry (HS-MS), Fourier Trans form Mid-Infrared spectroscopy (FT-MIR) and UV-Visible spectrophotometry (UV–vis) instrumental responses have been combined to predict virgin olive oil sensory descriptors. 343 olive oil samples analyzed during four consecutive harvests (2010–2014) were used to build multivariate calibration models using partial least squares (PLS) regression. There reference values of the sensory attributes were provided by expert assessors from an official taste panel. The instrumental data were modeled individually and also using data fusion approaches. The use of fused data with both low- and mid-level of abstraction improved PLS predictions for all the olive oil descriptors. The best PLS models were obtained for two positive attributes (fruity and bitter) and two defective descriptors (fusty and musty), all of them using data fusion of MS and MIR spectral fingerprints. Although good predictions were not obtained for some sensory descriptors, the results are encouraging, specially considering that the legal categorization of virgin olive oils only requires the determination of fruity and defective descriptors.

DOI: 10.1016/j.talanta.2016.04.040 URL: http://www.sciencedirect.com/science/article/pii/S0039914016302818 Filiació URV: SI Headspace-Mass Spectrometry (HS-MS), Fourier Trans form Mid-Infrared spectroscopy (FT-MIR) and UV-Visible spectrophotometry (UV–vis) instrumental responses have been combined to predict virgin olive oil sensory descriptors. 343 olive oil samples analyzed during four consecutive harvests (2010–2014) were used to build multivariate calibration models using partial least squares (PLS) regression. There reference values of the sensory attributes were provided by expert assessors from an official taste panel. The instrumental data were modeled individually and also using data fusion approaches. The use of fused data with both low- and mid-level of abstraction improved PLS predictions for all the olive oil descriptors. The best PLS models were obtained for two positive attributes (fruity and bitter) and two defective descriptors (fusty and musty), all of them using data fusion of MS and MIR spectral fingerprints. Although good predictions were not obtained for some sensory descriptors, the results are encouraging, specially considering that the legal categorization of virgin olive oils only requires the determination of fruity and defective descriptors.

We present a rapid method to quantify phenolic compounds all during the red winemaking process using Fourier transform mid-infrared (FT-MIR) spectroscopy and chemometrics. To get the reference values, we used the usual UV–vis spectroscopy methods, and the compounds studied were evaluated as total phenolic compounds (TPC), total anthocyanins (TA), and condensed tannins (CT). Sampling from five different grape varieties (Merlot, Tempranillo, Syrah, Carinena, and Cabernet sauvignon), harvested at different ripening states, and monitored over 10 days of vinification produced a total of 600 spectra. These were used to build and validate four different predictive models by partial least-squares (PLS) regression. The spectral regions selected for each model were between 979 and 2989 cm(–1), and when selecting the most suitable one in each case, good values of performance parameters were obtained (R2(val) > 0.95 and RPD > 4.0 for TPC; R2(val) > 0.90 and RPD > 3.0 for TA; R2(val) < 0.8 and RPD < 3.0 for CT). Furthermore, also more specific PLS regression models for each phenolic parameter and each grape variety were developed using different regions with results similar to those obtained when dealing with all of the grape varieties. It is concluded that FT-MIR spectroscopy together with multivariate calibration could be a rapid and valuable tool for wineries to carry out the monitoring of phenolic compound extraction during winemaking.

The sensorial representativeness of the headspace solid-phase microextraction (HS-SPME) aroma extract from commercial Sherry vinegars has been determined by direct gas chromatography-olfactometry (D-GCO). Extracts obtained under optimal conditions were used to characterize the aroma of these vinegars by means of GCO and aroma extract dilution analysis (AEDA). Among the 37 different odorants determined, 13 of them were identified for the first time in Sherry vinegars: 2 pyrazines (3-isopropyl-2-methoxypyrazine, 3-isobutyl-2-methoxypyrazine), 2 sulfur compounds (methanethiol, dimethyl trisulfide), 1 unsaturated ketone (1-octen-3-one), 1 norisoprenoid (β-damascenone), 1 ester (ethyl trans-cinnamate) and 6 aldehydes (2- and 3-methylbutanal, octanal, nonanal, (E)-2-nonenal and (E,E)-2,4-decadienal). The determination of the odor thresholds in a hydroacetic solution together with the quantitative analysis-which was also performed using the simple and fast SPME technique-allowed obtaining the odor activity values (OAV) of the aromatic compounds found. Thus, a first pattern of their sensory importance on commercial Sherry vinegar aroma was provided.

Because there is not a single method for carrying out phenolic ripening analysis, it is very difficult to compare the results obtained by different researchers. In this study, the three most widely used extraction methods of polyphenols (Glories, AWRI, and ITV) have been analytically compared by evaluating two of the most important parameters for the wine industry: total polyphenols and total anthocyanins. Samples from different grape varieties (Tempranillo, Garnacha, Carinena, Syrah, Merlot, and Cabernet Sauvignon), from three different vintages (2006, 2007, and 2008), and at different ripening states (from the beginning of ripeness until harvest) were analyzed to obtain a wide range of representative phenolic contents. To avoid external interferences on the comparisons, the same grape puree was used to make the maceration assays using the different solvents according to each extraction method. Although every extraction method exhibits a different extraction efficiency, the correlation between the results obtained with each one was very good both for total anthocyanins and for total polyphenols. Thus, after having determined a parameter value of the phenolic ripeness using a specific method, the relationship found can be used to predict the parameter value of the phenolic ripeness provided by the other two methods.

In this study the effect of thermal treatment on the enhancement of synchronous fluorescence spectroscopic method for discrimination and quantification of pure extra virgin olive oil (EVOO) samples from EVOO samples adulterated with refined oil was investigated. Two groups of samples were used. One group was analyzed at room temperature (25 °C) and the other group was thermally treated in a thermostatic water bath at 75 °C for 8h, in contact with air and with light exposure, to favor oxidation. All the samples were then measured with synchronous fluorescence spectroscopy. Synchronous fluorescence spectra were acquired by varying the wavelength in the region from 250 to 720 nm at 20 nm wavelength differential interval of excitation and emission. Pure and adulterated olive oils were discriminated by using partial least-squares discriminant analysis (PLS-DA). It was found that the best PLS-DA models were those built with the difference spectra (75 °C-25 °C), which were able to discriminate pure from adulterated oils at a 2% level of adulteration of refined olive oils. Furthermore, PLS regression models were also built to quantify the level of adulteration. Again, the best model was the one built with the difference spectra, with a prediction error of 3.18% of adulteration.

The ever increasing interest of consumers for safety, authenticity and quality of food commodities has driven the attention towards the analytical techniques used for analyzing these commodities. In recent years, rapid and reliable sensor, spectroscopic and chromatographic techniques have emerged that, together with multivariate and multiway chemometrics, have improved the whole control process by reducing the time of analysis and providing more informative results. In this progression of more and better information, the combination (fusion) of outputs of different instrumental techniques has emerged as a means for increasing the reliability of classification or prediction of foodstuff specifications as compared to using a single analytical technique. Although promising results have been obtained in food and beverage authentication and quality assessment, the combination of data from several techniques is not straightforward and represents an important challenge for chemometricians. This review provides a general overview of data fusion strategies that have been used in the field of food and beverage authentication and quality assessment.

Mid-infrared (MIR) spectra (4000–600 cm −1 ) of olive oils were analyzed using chemometric methods to identify the four main sensorial defects, musty, winey, fusty and rancid, previously evaluated by an expert sensory panel. Classification models were developed using partial least squares discriminant analysis (PLS-DA) to distinguish between extra-virgin olive oils (defect absent) and lower quality olive oils (defect present). The most important spectral ranges responsible for the discrimination were identified. PLS-DA models were able to discriminate between defective and high quality oils with predictive abilities around 87% for the musty defect and around 77% for winey, fusty and rancid defects. This methodology advances instrumental determination of results previously only achievable with a human test panel.

This paper deals with the application of a new headspace solid-phase microextraction (HS-SPME) method developed in order to analyse the total amount of chloroanisoles in different kinds of cork stoppers (natural, agglomerated and sparkling wine stoppers). This parameter must be determined because these compounds can migrate from cork to wine giving it unpleasant musty taint and, therefore, undermine its organoleptic quality. Unlike the releasable amount of chloroanisoles, the total amount of chloroanisoles has no dependence of the method used for its determination so it can be used as a quality control parameter. The application of this method allowed the simultaneous determination of 2,4-dichloroanisole, 2,6-dichloroanisole, 2,4,6-trichloroanisole, 2,3,4,6-tetrachloroanisole and 2,3,4,5,6-pentachloroanisole.

In the last 20 years, there has always been research into electronic noses with the main aim of achieving an instrument that can differentiate samples according to their complete volatile composition, quickly and objectively, so that quality in industry can be ensured and controlled. The electronic noses developed so far can be classified into two groups on the basis of their detection systems: classical instruments, which are based on solid state gas sensors, and new instruments, which are based on mass spectrometry (MS). In general, MS-based instruments have the advantage over the classical instruments (e.g., in stability, sensitivity and versatility). Furthermore, in the analysis of alcoholic beverages, the advantages of MS-based instruments are even more evident because the high ethanol content of the samples interferes with solid-state gas sensors. This article presents an overview of electronic nose applications in the field of alcoholic beverages. We describe the electronic noses that have been developed and discuss their advantages and disadvantages.

The influence of irrigation and plantation density on the methoxypyrazine content in musts and wines has been studied. Samples were monitored throughout grape ripening and wine-making. 3-Isobutyl-2-methoxypyrazine, 3-sec-butyl-2-methoxypyrazine and 3-isopropyl-2-methoxypyrazine were identified and quantified. Samples from irrigated vines had significantly higher average contents of 3-isobutyl-2-methoxypyrazine than samples from non-irrigated plants. Average levels of this compound were also higher in samples from vines with the higher plantation density. Copyright © 2005 Society of Chemical Industry

The relationship between the composition and the aroma of the wine can be established by using gas chromatography with olfactometric detection (sniffing or GCO), which combines the chromatographic response with the human nose response. To evaluate the contribution of the odor compounds in wine aroma, we designed a new approach of the aroma extract dilution analysis (AEDA) that lies in the GCO analysis of serially diluted wine samples using headspace solid-phase microextraction (HS-SPME) as the extraction technique. The fiber coating used was Flex divinyl-carboxen-polydimethylsiloxane. The method developed was applied to determine the aromatic composition of a red Grenache wine from Priorat (Spain). The method allows 38 important odorants to be determined in the AEDA study, 30 of them precisely identified. These results are similar to those reported by other studies related to this variety of wine. HS-SPME is a suitable technique to obtain representative extracts of wine aroma with several advantages such as simplicity, speediness, and little sample manipulation.

10.1016/j.foodchem.2013.12.032 In this study, near-infrared spectroscopy (NIR) coupled to chemometrics is used to develop a fast, simple, non-destructive and robust method for discriminating sweet and bitter almonds (Prunus amygdalus) by the in situ measurement of the kernel surface without any sample pre-treatment. Principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) models were built to discriminate both types of almonds, obtaining high levels of sensitivity and specificity for both classes, with more than 95% of the samples correctly classified and discriminated. Moreover, the almonds were also analysed by Raman spectroscopy, the reference technique for this type of analysis, to validate and confirm the results obtained by NIR.

This paper reports a new approach for validating bias in analytical methods that provide simultaneous results on multiple analytes. The validation process is based on a linear regression technique taking into account errors in both axes. The validation approach is used to individually compare two different chromatographic methods with a reference one. Each of the two methods to be tested is applied on a different set of data composed of two real data sets each. In addition, three different kinds of simulated data sets were used. All three methods are based on RP-high-performance liquid chromatography (HPLC) and are used to quantify eight biogenic amines in wine. The two methods to be tested use different derivatizing procedures: precolumn 6-aminoquinolyl-n-hydroxysuccinimidyl carbamate (AQC) and oncolumn o-phtalaldehyde (OPA), respectively. On the other hand, the reference method uses derivatization with OPA precolumn. Various analytes are determined in a set of samples using each of the methods to be tested and their results are regressed independently against the results of the reference method. Bias is detected in the methods to be tested by applying the joint confidence interval test to the slope and the intercept of the regression line which takes into account uncertainties in the two methods being compared. The conclusions about the trueness of the two methods being tested varied according to whether the joint confidence interval test was applied to data obtained from various biogenic amines considered simultaneously or individually.

This study describes the development of a method for determining eleven sulphur compounds in wine, which takes into account that thiols are easily oxidizable. The equilibria of the analytes between air and aqueous ethanol were studied and optimised using static headspace gas chromatography in order to obtain the best sensitivities. The influences of parameters such as temperature, time, ionic strength, headspace volume and the volume of headspace injected were determined. A cryogenic trap was used to concentrate the headspace analytes and they were chromatographically analysed using GC temperature programming on a poly(ethylene glycol) capillary column with FPD detection at 394 nm. The power relationship was observed between the chromatography response and a concentration of sulphur compounds in the range 2-150 micrograms l(-1) in the sample. Recoveries were determined by the standard addition technique and were higher than 90% for sulphides and disulphides and close to 80% for thiols. The overall method was successfully used to determine the sulphur compounds in white and red wines.

This paper describes a method for determining the most important biogenic amines in wines. It uses reversed phase high performance liquid chromatography (RP-HPLC) with gradient elution and fiuorimetric detection, performed on the amines after automatic precolumn derivatization with 6-aminoquinolyl-n-hydroxysuccinimidyl carbamate (AQC). Solid phase extraction (SPE) with strong cation exchanger (SCX) cartridges was used prior to derivatization to improve the selectivity and to reduce the detection limits (LOD) of the method. The overall method was used to determine the aforementioned amines in red wines from the Tarragona region.

A rapid method based on gas chromatography which determines parathion-methyl, fenitrothion, chlorpyrifos, dichlofluanid, vinclozolin, chlozolinate, procymidone and iprodione is described. It involves quantitative extraction with n-hexane and determination by capillary gas chromatography using an electron capture detector. Pesticides were satisfactorily separated in 15 min with a phenylmethylsilicone fused-silica capillary column under isothermal conditions. Quantitation was carried out using dieldrin as internal standard. The method seems appropriate for oenological laboratory work because of its simplicity and rapidity. It was successfully used to identify and quantify pesticides studied in musts and wines.

An on-column fluorometric derivatization method was developed for determining eight biogenic amines by HPLC and fluorometric detection. The derivatization was carried out by pumping the o-phthalaldehyde reagent through the column together with other solvents used as mobile phases. The on-column reaction conditions (pH, borate and o-phthalaldehyde concentrations) were optimized. The matrix effect, the thiol used in the derivative reagent and the effect of the temperature on the separation process were also studied. Solid-phase extraction was applied prior to the derivatization procedure as a clean-up of wines by using 2 different commercially available SAX and C18 cartridges to improve the accuracy and the precision of the method. The linearity range (0.5–15 mg 1−1) and detection limits (between 100 and 300 μg l−1) of this method were similar to the standard pre-column automated o-phthalaldehyde derivatization method. The method was checked with several red wines from Tarragona by comparing the results with the standard pre-column method.

AQC (6-aminoquinolyl-N-hydroxysuccinimidyl carbamate) was used as an alternative to the most common derivatization reagent, OPA (o-phthaldialdehyde), to determine sixteen biogenic amines in wines. OPA and AQC were compared in terms of the range of linearity, the limit of detection and the sensitivity (calibration line slopes) resulting from the application of each of the derivatization reagents. Sample handling is minimal because derivatization is fully automated by means of an injection programme. After derivatization, the derivatives were analysed by reversed-phase liquid chromatography with gradient elution and fluorimetric detection. All the amines studied eluted in less than 25 min under the optimum conditions established. Different variables that effect derivatization and separation were optimized. Good linearity of the responses was obtained between 0.05 and 10.00 mg l−1 depending on the amine derivative. The detection limits ranged between 5 and 50 μg l−1 for standard solutions and between 100 and 500 μg l−1 for wines. The method was successfully applied to the determination of the above amines in several types of wines from the Tarragona region.

Solid-phase extraction (SPE) was used simultaneously to clean up and concentrate samples prior to automatic derivatization to determine fifteen biogenic amines in wine. In the first step, SPE was used to remove polyphenolic compounds which interfere with further extraction and chromatographic analysis; in this study, treatments with polyvinylpyrrolidone, SAX and C18 cartridges were tested and compared. In the second step, C18 cartridges were used to concentrate the analytes after adding sodium octanesulfonate, sodium decanesulfonate and sodium dodecanesulfonate as ion-pair reagents. Reversed-phase chromatography with fluorimetric detection was performed on the extracted amines after automatic precolumn derivatization by treatment with o-phthalaldehyde. Biogenic amines can be separated and detected after the solid-phase extraction with an average sensitivity of the order of 20–90 μg l−1. Recoveries were determined by the standard addition technique and the overall method was successfully applied to the determination of the above-mentioned amines in red wines from the Tarragona region.

A suitable method for the determination of 16 biogenic amines in wine has been developed. The method involves clean-up of wine samples using ion-exchange cartridges and a preconcentration step, under controlled vacuum, before derivatization of the amines by treatment with phthalaldehyde (PA) and reversedphase HPLC with gradient elution and fluorimetric detection. Linearity of response was obtained for all the biogenic amines from 100 μg L−1 to mg L−1. Limits of detection for the amines were similar for all PA-derivatives (25–50 μg L−1) and the quantitation limits were about 0.1 mg L−1. After clean-up and preconcentration, the concentration levels increased 10-fold for all amines except putrescine and cadaverine, which gave poor recovery by this method unlike the rest which gave recoveries of almost 90%. The overall process was successfully applied to identify and quantify biogenic amines in several red wines from the Tarragona region.

A method suitable for the determination of 19 biogenic amines in wine has been developed. The method involves derivatization of amines by treatment with dansyl chloride and solid-phase extraction of the derivatives. Prior to the derivatization procedure, clean-up of the wine sample with polyvinylpyrrolidone is carried out. Reversed-phase gradient elution HPLC with UV detection at 250 nm was used to determine these compounds. Some consideration was given to the effect of temperature on the separation process. Linearity of derivatization was obtained for amounts of all the biogenic amines ranging from 500 μg·L−1 to 20 mg·L−1. Limits of detection (signal-to-noise ratio=3) of the amines were similar for all the dansylderivatives (between 50 and 150 μg·L−1). Addition of standard amines was used for the determination of amine recoveries. These were better than 85% for ethanolamine, tryptamine, phenetylamine, putrescine, cadaverine and histamine. The overall process was succesfully applied to identify and quantify biogenic amines in white and red wines.

Beer samples of the same brand and commercialized as a same product, but brewed in four different factories were analyzed with three techniques, an MS e-nose, a mid-IR optical-tongue and a UV-visible, to see if the factories show differences and to find out if the differences found could be attributed to different sensory properties. The data from the three instruments were fused to improve the ability of classification with respect to the individual use of the techniques. Two levels of data fusion were studied: low and mid level fusion, and the classification was performed by linear discriminant analysis (LDA). Mid-level fusion provided better classification results (above 95% correct classification) than those of low-level fusion and also than those obtained when using the individual techniques. Moreover, by means of the score and loading plots obtained by Fisher-LDA, it was possible to interpret the chemical information provided by the three techniques, and we were able to relate the variables associated to each sensor to the main compounds responsible of the sensory perception.

The system based on coupling a headspace sampler to a mass spectrometer (HS-MS), considered a kind of electronic nose (e-nose), is an emerging technique in the field of food aroma analysis. The global mass spectrum this system provides is a fingerprint of each sample analysed that contains the information related to volatile composition of the sample. The use of chemometric techniques allows to compare the spectra of the samples and then, to classify them according to different properties. In this paper, we present the development of a method for wine analysis using a HS-MS system and multivariate analysis techniques. The method was successfully applied to differentiate and classify wines according to its origin, variety and ageing. The main advantages of the proposed methodology are the minimum sample preparation required and the speed of analysis (10 min/sample).

The influence of vine training and sunlight exposure on the 3-alkyl-2-methoxypyrazines contents in musts and wines was studied by means of two previously reported methods based on headspace solid-phase micro-extraction. Experimental samples were monitored throughout grape ripening and wine making. 3-Isobutyl-2-methoxypyrazine, 3-sec-butyl-2-methoxypyrazine and 3-isopropyl-2-methoxypyrazine were identified. The 3-isobutyl-2-methoxypyrazine content decreased throughout grape ripening in all of the sample types studied. After 1 day of maceration with the skins, there was an increase, but after racking, no further increase was observed. No significant differences between samples were found during grape ripening. Wines from goblet-trained vines, however, contained significantly less 3-isobutyl-2-methoxypyrazine. Clusters protected from sunlight since the beginning of the veraison resulted in wines with a significantly lower content of this compound than the control samples. Keywords: 3-Alkyl-2-methoxypyrazines...

This paper discusses the fate of the concentration of some of the most widely used pesticides (parathion-methyl, fenitrothion, dichlofluanid, chlorpyrifos, vinclozolin, chlozolinate, procymidone, iprodione, copper oxychloride) during the vinification process. The vines were treated 2 days before harvest to find the maximum levels of these pesticides possible and to make it easier to study the influence of the different enological operations on their dissipation. All organic pesticides showed a continuous decrease throughout the wine making process. Dichlofluanid, chlorpyrifos, chlozolinate, parathion-methyl, fenitrothion were nearly undetectable at the end of the vinification. Procymidone, vinclozolin, and iprodione were the most persistent pesticides. The fate of copper and of other metabolically related metals (iron, zinc, manganese) was also studied. In the treated must, the initially high levels of copper decrease drastically during the alcoholic fermentation, reaching levels similar to the controls. ...