José Luis Aleixandre

Robust Ultraviolet–Visible (UV–Vis) Partial Least-Squares (PLS) Models for Tannin Quantification in Red Wine

The validation of ultraviolet-visible (UV-vis) spectroscopy combined with partial least-squares (PLS) regression to quantify red wine tannins is reported. The methylcellulose precipitable (MCP) tannin assay and the bovine serum albumin (BSA) tannin assay were used as reference methods. To take the high variability of wine tannins into account when the calibration models were built, a diverse data set was collected from samples of South African red wines that consisted of 18 different cultivars, from regions spanning the wine grape-growing areas of South Africa with their various sites, climates, and soils, ranging in vintage from 2000 to 2012. A total of 240 wine samples were analyzed, and these were divided into a calibration set (n = 120) and a validation set (n = 120) to evaluate the predictive ability of the models. To test the robustness of the PLS calibration models, the predictive ability of the classifying variables cultivar, vintage year, and experimental versus commercial wines was also tested. In general, the statistics obtained when BSA was used as a reference method were slightly better than those obtained with MCP. Despite this, the MCP tannin assay should also be considered as a valid reference method for developing PLS calibrations. The best calibration statistics for the prediction of new samples were coefficient of correlation (R2val) = 0.89, root mean standard error of prediction (RMSEP) = 0.16, and residual predictive deviation (RPD) = 3.49 for MCP and R2val = 0.93, RMSEP = 0.08, and RPD = 4.07 for BSA, when only the UV region (260-310 nm) was selected, which also led to a faster analysis time. In addition, a difference in the results obtained when the predictive ability of the classifying variables vintage, cultivar, or commercial versus experimental wines was studied suggests that tannin composition is highly affected by many factors. This study also discusses the correlations in tannin values between the methylcellulose and protein precipitation methods.

Mapping the scientific research in organic farming: a bibliometric review

The main aim of this study was to analyze the scientific productivity, collaboration and impact of research on organic agriculture through bibliometric analyses of articles included in the Science Citation Index Expanded database for the period 1954–2013. A number of 1009 research articles were published in 359 journals belonging to several subject areas, being Agriculture Multidisciplinary, Agronomy and Environmental Sciences the most productive. A social network analysis of collaboration between small countries and co-words was performed in order to analyze the most powerful scientific cooperation. The results highlight the important of the collaboration between small countries from north and eastern of Europe, as well as four non-European countries along with the US: Canada, Australia, Brazil and China, which is consistent with the importance that the consumption of products derived from organic farming has in these countries.

Spectrophotometric Analysis of Phenolic Compounds in Grapes and Wines

Phenolic compounds are of crucial importance for red wine color and mouthfeel attributes. A large number of enzymatic and chemical reactions involving phenolic compounds take place during winemaking and aging. Despite the large number of published analytical methods for phenolic analyses, the values obtained may vary considerably. In addition, the existing scientific knowledge needs to be updated, but also critically evaluated and simplified for newcomers and wine industry partners. The most used and widely cited spectrophotometric methods for grape and wine phenolic analysis were identified through a bibliometric search using the Science Citation Index-Expanded (SCIE) database accessed through the Web of Science (WOS) platform from Thompson Reuters. The selection of spectrophotometry was based on its ease of use as a routine analytical technique. On the basis of the number of citations, as well as the advantages and disadvantages reported, the modified Somers assay appears as a multistep, simple, and robust procedure that provides a good estimation of the state of the anthocyanins equilibria. Precipitation methods for total tannin levels have also been identified as preferred protocols for these types of compounds. Good reported correlations between methods (methylcellulose precipitable vs bovine serum albumin) and between these and perceived red wine astringency, in combination with the adaptation to high-throughput format, make them suitable for routine analysis. The bovine serum albumin tannin assay also allows for the estimation of the anthocyanins content with the measurement of small and large polymeric pigments. Finally, the measurement of wine color using the CIELab space approach is also suggested as the protocol of choice as it provides good insight into the wines color properties.

Application of Multivariate Regression Methods to Predict Sensory Quality of Red Wines

Several multivariate methods including partial least squares (PLS) regression, principal component regression (PCR) or multiple linear regression (MLR) have been applied to predict wine quality, based on the definition of chemical and phenolic parameters of grapes and wines harvested at different ripening levels. Three different models including grape phenolic maturity parameters (grape), wine phenolic parameters (wine) and a combination of grape and wine phenolic parameters (grape + wine) were analysed for each of the wine sensory attributes. The grape parameter model has been presented as the best test to predict wine quality based on sensory scores. On the other hand, wine models showed lower accuracy. The combination of grape and wine parameters presented intermediate results showing sometimes good predictability. Moreover, PLS and PCR appeared as more accurate multivariate methods compared to MLR. Although MLR showed higher correlation coefficients, lower RPD values were observed, displaying thus its lower prediction accuracy. Multivariate calibration statistics appeared as a promising tool to predict wine sensory quality in an easy and inexpensive way.

Nota. Diferenciación de vinos tintos varietales de la Comunidad Valenciana a partir del contenido de alcoholes y polioles / Note. Differentiation of varietal red wines from Communidad Valenciana (Spain) based on their composition in terms of alcohols and polyols:

The composition in terms of alcohols and polyols of 44 and 49 red wines (harvested in 1994 and 1995, respectively) produced in Comunidad Valenciana (Spain) from the grape varieties Cabernet Sauvignon, Tempranillo, Monastrell and Bobal was,analyzed. Discriminant analysis revealed differences among wines, and a clear separation of the samples (90 and 98%) was obtained. The most important compo nents in the differentation of the varieties studied were isoamyl alcohol for Cabernet Sauvignon, cis- 3-hexenol and isobutyl alcohol for Tempranillo, methanol and cis-3-hexenol for Monastrell, and 2,3- butanediol for Bobal. The classification obtained by elimination of the five less significant variables was similar to the one obtained using statistical treatment of all variables (with 84% and 90% in their respective harvests).

Chemometric compositional analysis of phenolic compounds in fermenting samples and wines using different infrared spectroscopy techniques

The wine industry requires reliable methods for the quantification of phenolic compounds during the winemaking process. Infrared spectroscopy appears as a suitable technique for process control and monitoring. The ability of Fourier transform near infrared (FT-NIR), attenuated total reflectance mid infrared (ATR-MIR) and Fourier transform infrared (FT-IR) spectroscopies to predict compositional phenolic levels during red wine fermentation and aging was investigated. Prediction models containing a large number of samples collected over two vintages from several industrial fermenting tanks as well as wine samples covering a varying number of vintages were validated. FT-NIR appeared as the most accurate technique to predict the phenolic content. Although slightly less accurate models were observed, ATR-MIR and FT-IR can also be used for the prediction of the majority of phenolic measurements. Additionally, the slope and intercept test indicated a systematic error for the three spectroscopies which seems to be slightly more pronounced for HPLC generated phenolics data than for the spectrophotometric parameters. However, the results also showed that the predictions made with the three instruments are statistically comparable. The robustness of the prediction models was also investigated and discussed.

Chemical and Sensory Characteristics of the Sparkling andNatural Ciders Stored in Different Types of Containers

The cider industry is becoming more prolific in many parts of the world, and with the growing demand for cider comes a growing demand for high-quality ciders from traditional cider-growing regions. The main goal of the project was to study the chemical and sensory characteristics of the sparkling and natural ciders stored in different types of containers after three month of preservation at 230C in the temperature controlled storage room. Sparkling is a sweet, carbonated cider formulated for the export market, while the natural is a traditional dry and acidic cider, but appealing to cider enthusiasts. Both ciders wereput into different containers, including plastic kegs, beer bottles, and plastic bottles systems. Over the course of three months, samples were taken from the ciders and subject to chemical and sensory analyses for quality control, with kegs and glass bottles retaining cider quality well. Theresults show that plastic and metal kegs seem to have preserved Natural cider better than the control standard bottles, while plastic bottles system did a worse job preserving the cider. Beer bottles did a good job in preserving the cider, as well.