Modulation of the phenolic composition and colour of red wines subjected to accelerated ageing by controlling process variables.

The aim of the present work was to evaluate the effect of the main factors conditioning accelerated ageing processes (oxygen dose, chip dose, wood origin, toasting degree and maceration time) on the phenolic and chromatic profiles of red wines by using a multivariate strategy based on experimental design methodology. The results obtained revealed that the concentrations of monomeric anthocyanins and flavan-3-ols could be modified through the application of particular experimental conditions. This fact was particularly remarkable since changes in phenolic profile were closely linked to changes observed in chromatic parameters. The main strength of this study lies in the possibility of using its conclusions as a basis to make wines with specific colour properties based on quality criteria. To our knowledge, the influence of such a large number of alternative ageing parameters on wine phenolic composition and chromatic attributes has not been studied previously using a comprehensive experimental design methodology.

Experimental design approach to evaluate the impact of oak chips and micro-oxygenation on the volatile profile of red wines.

A chemometric strategy based on combining an experimental design approach and response surface methodology was applied to gain further knowledge on the influence of chip maceration and micro-oxygenation related factors (oxygen doses, chip doses, wood origin, toasting degree and maceration time) on the volatile profile of red wines during the accelerated ageing process. The results obtained indicated that the volatile profile of wines could be modulated by applying different combinations of factor conditions. Thus, these results would be used to obtain wines with specific volatile profiles that would lead to particular olfactory attributes according to consumers' preferences. Moreover, it was shown that combining wood from different origins helped enhance the quality of the elaborated wines. To the best of our knowledge, this is the first time that an experimental design methodology has been applied to simultaneously evaluate the influence of five different ageing parameters on the volatile profile of red wines.

Classification of Spanish extra virgin olive oils by data fusion of visible spectroscopic fingerprints and chemical descriptors.

The potential of visible fingerprints and physical-chemical parameters in combination with multivariate data analysis was examined to classify extra virgin olive oils (EVOOs) from different Spanish regions according to their geographical origin. Firstly, spectral and quality parameters matrices were processed separately and subsequently were joined to evaluate the effect of synergy on the information obtained from the different methodologies. Linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA) were performed as classification methods. The results revealed a perfect discrimination between the defined categories after performing PLS-DA on the Fused matrix, reaching 100% of correct classifications and showed a clear improvement in the overall prediction rates (92.5%), so that the effect of synergy was confirmed. These accurate results emphasise the feasibility of the proposed strategy and encourage the development of similar approaches based on visible spectroscopy in olive oil quality and traceability determination.

Recognition of volatile compounds as markers in geographical discrimination of Spanish extra virgin olive oils by chemometric analysis of non-specific chromatography volatile profiles.

Chromatographic profiles obtained by headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography (GC) were processed as continuous and non-specific signals through multivariate analysis techniques in order to select and identify the most discriminate volatile marker compounds related to the geographical origin of extra virgin olive oils. The blind analysis of the chromatographic profiles was carried out on several steps including preliminary mathematical treatments, explorative analysis, feature selection and classification. The results obtained through the application of stepwise linear discriminant analysis (SLDA) method revealed a perfect discrimination between the different Spanish geographical regions considered (La Rioja, Andalusia and Catalonia). The assignment success rate was 100% in both classification and prediction by using cross validation procedure. In addition, it must be noted that the proposed strategy was able to verify the geographical origin of the samples involving only a reduced number of discriminate retention times selected by the stepwise procedure. This fact emphasizes the quality of the accurate results obtained and encourages the feasibility of similar procedures in olive oil quality and traceability studies. Finally, volatile compounds corresponding to the predictors retained were identified by gas chromatography-mass spectrometry (GC-MS) for a chemical interpretation of their importance in quality virgin olive oils.

Classification of archaeological sherds across the southeast United States based on variable selection from compositional fingerprints.

The transfer of advances in chemometrics into archaeometric research opens a wide range of new application possibilities in this rapidly developing field. The present research represents a feasibility study aimed at showing how the huge potential that multivariate analysis and feature selection techniques have demonstrated for classification purposes can be extrapolated to archaeological provenance studies, thus pursuing an enhancement of the resulting classification performance. The classification problem studied here was related to the discrimination of pottery sherds from different sources across the southeast of the United States from their compositional fingerprints. The sample elemental concentrations were analyzed using the stepwise linear discriminant analysis (SLDA) method, thus simultaneously performing feature selection and classification. Several approaches, more or less restrictive according to the geographical scope and the number of considered classes, were explored, following a hierarchical classification approach. In contrast to previous studies on the same data set, the reliable and unequivocal classification strategy presented here did not merely focus on developing a large-scale classification into broad geographical areas, but finer classifications were also successively obtained until samples were assigned into individual regions. The great discrimination ability and effectiveness of the classification methodology proposed are promising and encourage its application to new samples of unknown provenance and the feasibility of using similar approaches in other archaeological studies. The high quality results obtained were even more remarkable considering the relatively small number of discriminant variables selected in each case by the stepwise procedure.