Comparison of different permanent chemical modifiers for lead determination in Orujo spirits by electrothermal atomic absorption spectrometry.

Different analytical methods for the determination of lead in Orujo spirits by electrothermal atomic absorption spectrometry (ETAAS) were developed using permanent modifiers (W, Ir, Ru, W-Ir and W-Ru) thermally deposited on platforms inserted in pyrolitic graphite tubes and Pd-Mg(NO(3))(2) conventional modifier mixture. In all cases, the Pb determination was performed without any sample pretreatment or preconcentration steps. The comparison between the chemical modifiers employed has been made in terms of pyrolysis and atomization temperatures, characteristic masses, detection limits, and atomization and background signal shapes. The limits of detection obtained were 0.375, 0.387, 0.109, 0.251 and 0.267ngmL(-1) for W, Ir, Ru, W-Ir and W-Ru, respectively and 0.710ngmL(-1) for Pd-Mg(NO(3))(2). The characteristic masses were 14.1, 11.2, 5.6, 8.3 and 9.3pg for W, Ir, Ru, W-Ir and W-Ru, respectively and 22.2pg for Pd-Mg(NO(3))(2). For all the developed procedures using the different modification systems, the relative standard deviations (<10%) and the analytical recoveries (95-103%) were acceptable. The more suitable methods for Pb determination in distillate spirits were those using permanent modifiers in contrast with classical Pd-Mg(NO(3))(2). The best analytical performance was achieved for W, Ir and W-Ir methods, which were applied to lead determination in Orujo spirit samples from Galicia (NW Spain). The Pb concentrations found in the analyzed samples were comprised in the range (

Characterization of Galician (N.W. Spain) quality brand potatoes: a comparison study of several pattern recognition techniques.

Authenticity is an important food quality criterion and rapid methods to guarantee it are widely demanded by food producers, processors, consumers and regulatory bodies. The objective of this work was to develop a classification system in order to confirm the authenticity of Galician potatoes with a Certified Brand of Origin and Quality (CBOQ) 'Denominación Específica: Patata de Galicia' and to differentiate them from other potatoes that did not have this CBOQ. Ten selected metals were determined by atomic spectroscopy in 102 potato samples which were divided into two categories: CBOQ and non-CBOQ potatoes. Multivariate chemometric techniques, such as cluster analysis and principal component analysis, were applied to perform a preliminary study of the data structure. Four supervised pattern recognition procedures [including linear discriminant analysis (LDA), K-nearest neighbours (KNN), soft independent modelling of class analogy (SIMCA) and multilayer feed-forward neural networks (MLF-ANN)] were used to classify samples into the two categories considered on the basis of the chemical data. Results for LDA, KNN and MLF-ANN are acceptable for the non-CBOQ class, whereas SIMCA showed better recognition and prediction abilities for the CBOQ class. A more sophisticated neural network approach performed by the combination of the self-organizing with adaptive neighbourhood network (SOAN) and MLF network was employed to optimize the classification. Using this combined method, excellent performance in terms of classification and prediction abilities was obtained for the two categories with a success rate ranging from 98 to 100%. The metal profiles provided sufficient information to enable classification rules to be developed for identifying potatoes according to their origin brand based on SOAN-MLF neural networks.

Authentication of Galician (N.W. Spain) quality brand potatoes using metal analysis. Classical pattern recognition techniques versus a new vector quantization-based classification procedure.

The objective of this work was to develop a classification system in order to confirm the authenticity of Galician potatoes with a Certified Brand of Origin and Quality (CBOQ) and to differentiate them from other potatoes that did not have this quality brand. Elemental analysis (K, Na, Rb, Li, Zn, Fe, Mn, Cu, Mg and Ca) of potatoes was performed by atomic spectroscopy in 307 samples belonging to two categories, CBOQ and Non-CBOQ potatoes. The 307 x 10 data set was evaluated employing multivariate chemometric techniques, such as cluster analysis and principal component analysis in order to perform a preliminary study of the data structure. Different classification systems for the two categories on the basis of the chemical data were obtained applying several commonly supervised pattern recognition procedures [such as linear discriminant analysis, K-nearest neighbours (KNN), soft independent modelling of class analogy and multilayer feed-forward neural networks]. In spite of the fact that some of these classification methods produced satisfactory results, the particular data distribution in the 10-dimensional space led to the proposal of a new vector quantization-based classification procedure (VQBCP). The results achieved with this new approach (percentages of recognition and prediction abilities > 97%) were better than those attained by KNN and can be compared advantageously with those provided by LDA (linear discriminant analysis), SIMCA (soft independent modelling of class analogy) and MLF-ANN (multilayer feed-forward neural networks). The new VQBCP demonstrated good performance by carrying out adequate classifications in a data set in which the classes are subgrouped. The metal profiles of potatoes provided sufficient information to enable classification criteria to be developed for classifying samples on the basis of their origin and brand.

Determination of six metals in galician red wines (in northwestern Spain) by capillary electrophoresis.

A simple technique is described for the routine simultaneous capillary electrophoretic determination of 6 cations in wine. Separation was achieved on a fused silica capillary column with a UV-Cat-1, alpha-hydroxysobutyric acid and 18-crown-6-ether buffer at pH 4.5 and indirect UV detection at 214 nm. The content of magnesium, sodium, potassium, calcium, manganese, and lithium was determined. The method is quantitative, with recoveries in the 92-102% range, and linear over more than one order of magnitude. The precision is better than 2.5-3.4%. The method is sensible, with detection limits between 0.01 and 0.06 mg/L. Twenty-five red wines with a Certified Brand of Origin from Galicia (north-western Spain) were analyzed by the proposed method. Various wines showed very similar electrophoretic profiles, but significant quantitative differences were observed.