Characterization of Catalan red wines by pattern recognition methods

52 red wines produced in the Tarragona province (Catalonia, Spain), 1983 vintage, belonging to 4 different regions, namely Priorat, Terra Alta, Camp de Tarragona and Falset, have been characterized and differentiated according to their geographic origin on the basis of 17 parameters measured for each sample and 3 pattern recognition methods: Statistical Quadratic Discriminant Analysis, K-Nearest Neighbour and Linear Learning Machine. The meta! ions manganese, magnesium, iron and sodium, along with the enological parameters ethanol content, alkalinity of ashes and titratable acidity have been found as the most relevant ones in this study. The lack of varietal differences together with quite similar climatic and cultural conditions due to the geographic contiguity of the studied zones leads to a maximum prediction ability of 87 % with the Linear Learning Machine method

Near infrared spectroscopy and multivariate curve resolution-alternating least squares incorporating 13C-NMR information for monitoring epoxy resins reactions

This paper describes how data from two instrumental techniques - near infrared spectroscopy (NIR) and 13C nuclear magnetic resonance ( 13C-NMR) - are combined by means of multivariate curve resolution-alternating least squares (MCR-ALS) to obtain concentration and spectral profiles for the reaction between phenylglycidylether and aniline. The reaction, in stoichiometric proportions, was monitored by both spectroscopic techniques at 95°C. The concentration values obtained by 13C-NMR were used as an equality constraint during the multivariate curve resolution of the near infrared data. The results obtained were recovered without ambiguities: that is to say, there was a unique solution. The goodness of the results was tested by comparing the recovered concentration profiles with the values obtained by high performance liquid chromatography (HPLC) as a reference technique. The statistical tests showed that there were no significant differences between the results of both methods (α = 5%). Also, the recovered spectra were compared with the experimentally recorded spectra for the reagents (i.e. phenylglycidylether and aniline) and the final product and the correlation coefficients were, in all cases, higher than 0.998.Fil: Garrido, Mariano Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universitat Rovira I Virgili; EspañaFil: Larrechi, M. S.. Universitat Rovira I Virgili; EspañaFil: Rius, F. X.. Universitat Rovira I Virgili; Españ

Calculation of band boundaries of feasible solutions obtained by Multivariate Curve Resolution–Alternating Least Squares of multiple runs of a reaction monitored by NIR spectroscopy

10 pages, 7 figures, 1 table.-- Available online Nov 6, 2004.This study describes a method for calculating the band boundaries of feasible solutions for spectra and concentration profiles obtained by Multivariate Curve Resolution–Alternating Least Squares (MCR–ALS) analysis of a spectroscopic NIR data set. The data set is obtained by monitoring in situ the model reaction between phenyl glycidyl ether (PGE) and aniline. As this system happened to be rank-deficient, the resolution strategy used matrix augmentation. The calculation of band boundaries of feasible solutions is extended here to the simultaneous analysis of multiple data matrices. The boundaries were obtained by a non-linear constrained non-linear optimisation. The influence that the number and type of data matrices in the simultaneous analysis have on the amplitude of band boundaries is also discussed.The authors would like to acknowledge the economic support provided by the MCyT (project No. BQU 2003-01142).Peer reviewe

Application de l'analyse multidimensionnelle des données a la reconnaissance des vins rouges de la Rioja

L'application de l'analyse multidimensionnelle des données à la reconnaissance des vins de trois appellations de la Rioja, permet de choisir huit variables physico-chimiques, facilement accessibles, comme étant hautement significatives. En plus de ces paramètres analytiques, le cépage et les données climatiques ont un rôle important. Les meilleurs résultats sont obtenus au moyen de la méthode d'analyse discriminante linéaire des données avec laquelle le pourcentage d'attribution correcte des vins atteint 91,3 p. 100. +++ Application of multidimensional data analysis to the recognition of three Rioja appellation wines led to selecting 8 easly-obtained physicochemical variables as being highly significant. In addition to these analytical parameters, variety and climatic conditions play an important role. The best results were obtained using linear discriminant analysis of the data, which gave 91,3 p. 100 correct recognition of the wines