Rosa M. Peña

Chemometric classification of honeys according to their type. II. Metal content data

Abstract The objective of this work was to develop a method to confirm the geographical authenticity of Galician-labelled honeys as Galician-produced honeys. Eleven metals were determined in 42 honey samples divided into two categories: natural Galician honeys and processed non-Galician honeys. Multivariate chemometric techniques such as principal component analysis, linear discriminant analysis, KNN and SIMCA are used to classify honeys according to their type and origin on the basis of the chemical data. Using only three features, Cu, Mn and Li, an almost correct classification was achieved. ©

Characterisation of Galician (NW Spain) Ribeira Sacra wines using pattern recognition analysis

The objective of this work was to develop a classification system that would confirm the authenticity of Galician certified brand of origin (CBO) wines from the Ribeira Sacra area. Thirty-four chemical variables involving metals, volatile and phenolic compounds were determined in 39 red wines from Galicia divided into two categories: Ribeira Sacra CBO and non-Ribeira Sacra CBO. Feature selection techniques were employed to choose a set of optimally discriminating variables. Multivariate chemometric classification procedures were applied to modelling classes on the basis of the selected chemical data. The obtained results indicated good performance in terms of classification and prediction for CBO Ribeira Sacra wines in order to differentiate them from other similar wines produced in nearby geographical areas. Five key features (Fe, Li, Rb, delphinidin and epicatechin) provided sufficient information to enable classification rules to be developed for identifying wines according to their origin.

A rainwater quality monitoring network: a preliminary study of the composition of rainwater in Galicia (NW Spain).

A network consisting of 17 sampling stations strategically distributed in the geographical area of Galicia (NW Spain) was set up in January 1999 in order to monitorice the ionic rainwater quality in this Spanish region which has an area approximately 29.575 km(2) and a population of 2.8 million. This paper presents the preliminary results of the exploratory study on the ionic rainfall composition in this area during the first year. In each rainwater sample collected chloride, sulphate, nitrite, nitrate, phosphate, sodium, potassium, magnesium, calcium and ammonium were measured, as were pH, conductivity and precipitation-volume. An univariate study according to the location of each sampling site was performed. Multivariate chemometric techniques, such as principal component analysis and cluster analysis, were applied to the complete data set (consisting of 630 observations) in order to elucidate the factors affecting the ionic composition of rainwater.

Measurements and analysis of hydrogen peroxide rainwater levels in a Northwest region of Spain

Abstract The importance of atmospheric hydrogen peroxide (H2O2) in the oxidation of SO2 and other compounds, as well as its possible harmful affects on vegetation, has been well established. In this work, two FIA methods for determining H2O2 were compared, and a non-enzymatic method was adapted to analyze the rainwater samples. Measurements of hydrogen peroxide in rain samples were carried out at two different sites during 1993–1995, in the area surrounding a thermal power plant located in the Northwest of Spain. The concentration of H2O2 varied from values lower than the detection limit (0.002 μM ) to 2.706 μM . The effects of the rainwater components and the meteorological factors in temporal, seasonal and spatial H2O2 pattern concentrations were studied.

Simultaneous Determination of Organic Acids in Wine Samples by Capillary Electrophoresis and UV Detection: Optimization with Five Different Background Electrolytes

A simple technique is described for the routine capillary electrophoretic determination of organic acids in wine samples. Several aromatic and non-aromatic compounds, including phthalic acid, benzoic acid, sorbic acid, boric acid, and phosphate, were evaluated as background electrolytes in order to obtain the highest resolution and detection sensivity. Factors that affect capillary electrophoretic separation such as the concentration and pH of the background electrolyte (BGE), the concentration of the electroosmotic flow modifier (EOF), and methanol addition to the electrolyte were investigated systematically. Tartaric, malic, succinic, acetic, and lactic acids were determined simultaneously in approximately six minutes using an electrolyte containing 3 mM phosphate and 0.5 mM myristyltrimethylammonium bromide (MTAB) as electroosmotic flow modifier at pH 6.5. This method is quantitative, with recoveries in the 90-102% range and linear up to 50 mg L -1 . The precision is better than 1% and the procedure shows the appropriate sensibility, with detection limits between 0.015 and 0.054 mg L -1 . The proposed method was successfully employed for the determination of organic acids in wine samples by direct sample injection after appropriate dilution and filtration.

Comparison of ultrasound-assisted extraction and direct immersion solid-phase microextraction methods for the analysis of monoterpenoids in wine.

Ultrasound-assisted extraction (UAE) and direct immersion solid-phase microextraction (DI-SPME) were evaluated for the monoterpenic compounds determination in wine samples. The wine extracts obtained were analyzed by gas chromatography-mass spectrometry (GC-MS). The optimization of the variables affecting UAE and SPME methods was carried out in order to achieve the best extraction efficiency. Both UAE and SPME are quantitative (recoveries in the range 93-97% and 71.8-90.9%, respectively), precise (coefficients of variation below 5.5%), sensitive (limits of detection between 30-39mugL(-1) and 11-25mugL(-1), respectively) and linear over one order of magnitude. The application of both methods to red wine samples showed that UAE provided higher extraction of monoterpenic compounds than SPME. Although SPME remains an attractive alternative technique due to its speed, low sample volume requirements and solvent free character.

Pattern recognition analysis applied to classification of Galician (NW Spain) wines with Certified Brand of Origin Ribeira Sacra

In 39 red wines from Galicia (NW Spain), some trace elements were determined by atomic spectroscopy. Data were processed using multivariate chemometric techniques involving principal component analysis, discriminant analysis and K nearest neighbours to develop a typification for wine samples of Ribeira Sacra origin. The wines with Certified Brand of Origin (CBO) Ribeira Sacra can be differentiated from the wines of two other CBOs from Galicia: Ribeiro and Valdeorras. The latter CBOs make wines with the same grape variety; hence they are possible substitutes for falsification of Ribeira Sacra wines owing to their similar organoleptic properties. By means of multivariate techniques of data exploration, two main groups of samples (Ribeira Sacra and non-Ribeira Sacra wines) were observed. Exploratory analysis results were confirmed using supervised procedures of data classification. Using lithium and iron content as key features, a satisfactory classification was achieved.

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.

Spatial and Temporal Ozone Pattern Concentrations in a NW Region of Spain

Measurements of ozone were carried out at two different sites in the area surrounding a thermal power plant located in the Northwest of Spain during 1993–1995. The concentration of O3 in the ambient air varied from 6 to 257 μg m-3 exhibiting a wide temporal, seasonal and spatial variation. On a few occasions 1-hr ozone concentration was more than 180 μg m-3, which represents the maximum 1-hr limit of ozone in ambient air as prescribed by the European Commission.

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 (