L.Gabrielli Favretto

Stereospecific analysis of the triacylglycerol fraction and linear discriminant analysis in a climatic differentiation of umbrian extra-virgin olive oils

Abstract Stereospecific analysis of the triacylglycerol fraction is an important tool for the characterisation of extra-virgin olive oils. The composition in the sn-1, sn-2 and sn-3 positions of triacylglycerols of extra-virgin olive oils produced in years 1992–1994 in areas characterised by increasing environmental severity (groups 1 and 2, respectively) is considered. This analytical method is based on chromatographic techniques, coupled with enzymatic ones. Linear discriminant analysis (LDA) has been applied successively for the differentiation and classification of the two groups for each year according to the positional distribution of fatty acids (palmitic, palmitoleic, stearic, oleic and linoleic acids) in the glycerol backbone. Even though the data were not very numerous, LDA has allowed a partial or total separation of scores along the discriminant eigenvector according to the climatic groups.

Gas chromatographic separation and chemometric analysis of mandarin essential oils

Abstract Capillary gas chromatography with flame ionization detection was applied to the separation of components of mandarin essential oils. Fifty-nine genuine samples were considered over the period October 1982–January 1983. Essential oils were obtained from unripened green fruits and ripened red fruits, as well as from fruits at intermediate ripening. Thirty-four pure components were systematically identified, but only 13 were used as variables for the further characterization by a chemometric procedure. Principal component analysis was applied to the differentiation of samples with different maturation and obtained with different technologies.

Principal components analysis for the estimation of interdependences among trace metals in cow milk

Seven trate metals (Cr, Mn, Fe, Ni, Cu, Cd, Pb) were determined in the dissolved ash of pasteurized milk by electrothermal atomic absorption spectrometry. The distribution of the concentration (c) of the metals in milk of χ = log10c for eaeh metal was investigated by means of the Lin-Mudholkar test for normality. Logarithmically transformed variables were first considered for further processing, as their distribution passed the normality test at a 0.05 significance level for a sample size of 48. The correlation matrix around the mean was used as a starting matrix for principal components analysis; the principal components were obtained from the FACTOR program of the SPSS package. Dimensions were reduced to four principal components, accounting for 78% of the total variance. Various orthogonal rotations indicated associations with Cd- Pb, Cr- Ni, and Mn- Cu. The correlation matrix was also estimated from the c matrix after row- normalization for each sample. The first eigenvalue estimated from this matrix accounted for 50% of the total variance, bur three eigenvalues were needed to reach 80% of explained variance. Cadmium and lead formed a cluster of variables, indicating a common origin. Features concerned with natural metal contents and contamination during transport and processing are diseussed.

Study on volatile components in salami by reverse carrier gas headspace gas chromatography-mass spectrometry.

Salami are a typical seasoned sausage of Italy; a number of types are produced, according to local traditional recipes. As industrial production has taken place, a number of problems rise in obtaining products similar to the traditional ones. The use of selected microbial starters is permitted by Italian law for some years and at present, microbiological research is engaged in selecting starters similar to the ones isolated from traditional products, with the aim of obtaining organoleptic characteristics close to the ones of traditional recipes. A study was carried out concerning the characterisation of volatile components of salami by headspace capillary gas chromatography-mass spectrometry. As during the sampling step, analytes could reach the analytical column, the carrier gas rate was back flushed in the latter, while a pre column was used as cold trap. Then GC-MS analysis follows. By these techniques, we were able to highlight typical profiles of different salami, as well as monitoring the ripening of a traditional and a starter added salami. Main peaks are of fermentative origin, while also peaks from spices were detected. Ethyl propionate was used as internal standard to be able to normalise the peaks amounts.

Differentiation of wild oysters from three sites by chemometric procedures

Abstract The total contents of twelve trace elements (Al, Cr, Mn, Fe, Co, Ni, Cu, Zn, Mo, Cd, Hg and Pb) in the whole soft part of oysters (Ostrea edulis L.) sampled at two sites of the gulf of Trieste and at one site of the Grado Lagoon (Northern Adriatic Sea) were considered. The trace elements were determined in the dissolved ash obtained from 21 samples, by eletrothermal atomic absorption spectrometry; mercury was determined by cold-vapour atomic absorption spectrometry after acid digestion. Oysters from the three sites were first differentiated by using discriminant analysis. The correlation matrix around the mean was used as the starting matrix for principal component analysis; dimensions were reduced to five principal components accounting for 84% of the total variance. A two-dimensional plot of the principal component scores was only partly successful in separating the oysters from the three different sites; a three-dimensional representation was satisfactory.

Principal component analysis: a chemometric aid for classification of polluted and unpolluted mussels

Abstract Ten trace elements (Al, Cr, Mn, Fe, Co, Ni, Cu, Zn, Cd and Pb) were determined in the dissolved ash of the edible part of wild mussels (28 samples) from a polluted site by electrothermal atomic absorption spectrometry. The distribution of the concentration of each element in the mussels was first investigated by means of a test of normality. The correlation matrix around the mean was used as a starting matrix for principal component analysis (PCA). Ten variables were reduced to two principal components, accounting for 77% of the total variance; Al, Cr, Mn, Fe, Zn, Cd and Pb are all positively associated with the first principal component and form a cluster of variables, indicating a common terrigenous origin. Comparison with 43 samples of unpolluted mussels from a nearby hatchery, on the basis of eight common variables (concentration of Mn, Fe, Co, Ni, Cu, Zn, Cd and Pb; 71 samples) by using a two-dimensional plot of PC scores, allows the mussels from the two sites to be differentiated.

Chemometric differentiation of raw and commercial milk by trace elements using principal component analysis

Nine trace elements (Cr, Mn, Fe, Ni, Cu, Zn, Mo, Cd, and Pb) were determined in the dissolved ash of 36 samples of raw milk. The distribution of the concentration of each element was first investigated by means of a test of normality. The matrix of the correlation between the concentrations of the elements was then used as a starting matrix for principal component analysis. Nine variables were reduced to four principal components, accounting for 75% of the total variance. The biophilic elements Mn-Fe and Cu-Mo were positively associated with the first two principal components, while Cr was correlated to the third and Ni and Cd with the fourth principal component. Pb and Zn are both negatively correlated to the first principal component. Comparison with 42 samples of a commercial milk, by using a two-dimensional plot of the principal component scores, rendered possible the differentiation between raw and commercial milk.

Chromium and nickel in roadside grapes.

Chromium and nickel concentration in roadside unwashed wine grapes and leaves is considered as a function of the distance from the suspected source, an isolated straight road. The analyses were performed with electrothermal atomization in a graphite furnace. The decrease in the concentration of the element can be described by means of a three-parameter exponential function c = A + (B - A)exp(-Cd), which allows the determination of the asymptotic level far from the emitting source (C infinity) and the pollution level (C0) at the edge of the road (d = 0). Least-squares nonlinear regression gives the estimation of the parameters A, B, and C. The results indicate that an effect is detectable up to a distance of about 50 m.