Use of experimental design to optimize the analysis of volatile compounds by dynamic headspace extraction followed by cold trapping and capillary GC

A central composite design has been used to improve the extraction performance of a dynamic headspace method; extraction yield was evaluated on a homogeneous sample of cheese powder. The volatile compounds were stripped from the sample with nitrogen and adsorbed on a Tenax trap, analysis being performed with a thermal cold trapping injector connected directly to a capillary GC. Three variables (sample temperature, extraction time, and nitrogen flow rate) were investigated, and a quadratic model with interactions was postulated. Twenty experiments was performed, each producing five responses. It was shown that the best conditions for the extraction procedure were those characterized by the highest values of the three variables investigated.     

Simultaneous kinetic-spectrophotometric determination of sulfide and sulfite and genetic algorithim variable selection using partial least squares calibration

Simultaneous multicomponent analysis is usually carried out using multivariate calibration models, such as the partial least squares (PLS) one, that utilize the full spectrum. It has been shown by both experimental and theoretical considerations that better results can by obtained by proper selection of the spectral range to be included in calculations. A genetic algorithm (GA) is one of the most popular methods for selecting variables for PLS calibration of mixtures with almost identical spectra without loss of predictive capability. In this work, a simple and precise method for rapid and accurate simultaneous determination of sulfide and sulfite ions based on the addition reaction of these ions with new fuchsin at pH 8 and 25°C using PLS regression and GA for variable selection is proposed. The concentrations of sulfide ions varied between 0.05–2.50 and 0.15–2.00 μg/mL, respectively. A series of model solutions containing different concentrations of sulfide and sulfite were used to check the predictive ability of GA-PLS models. The root mean square error of prediction with PLS on the whole data set was 0.19 μg/mL for sulfide and 0.09 μg/mL for sulfite. After the application of GA, these values reduced to 0.04 and 0.03 μg/mL, respectively. The text was submitted by the authors in English.     

Direct thermal extraction and gas chromatographic-mass spectrometric determination of volatile compounds of extra-virgin olive oils

The instrumental performances of a Thermo Desorption-Cooled Injection System coupled with a gas chromatography-mass spectrometer (GC-MS) were improved by a Plackett-Burman experimental design for the direct thermal extraction of volatile compounds from extra-virgin olive oils. The obtained experimental conditions were applied to the analysis of samples from West Liguria (cv. Taggiasca > or = 90%) and Spain (cv. Arbequina), which shared such similar sensorial features that Taste Panel did not distinguish them. Principal component analysis (PCA) was then applied to the experimental data. Three linear combinations of the amounts of the lipoxygenase oxidation products proved to be decisive and sufficient in the differentiation of the two groups of samples.     

Classification of GC‐MS measurements of wines by combining data dimension reduction and variable selection techniques

Different classification methods (Partial Least Squares Discriminant Analysis, Extended Canonical Variates Analysis and Linear Discriminant Analysis), in combination with variable selection approaches (Forward Selection and Genetic Algorithms), were compared, evaluating their capabilities in the geographical discrimination of wine samples. Sixty‐two samples were analysed by means of dynamic headspace gas chromatography mass spectrometry (HS‐GC‐MS) and the entire chromatographic profile was considered to build the dataset. Since variable selection techniques pose a risk of overfitting when a large number of variables is used, a method for coupling data dimension reduction and variable selection was proposed. This approach compresses windows of the original data by retaining only significant components of local Principal Component Analysis models. The subsequent variable selection is then performed on these locally derived score variables. The results confirmed that the classification models achieved on the reduced data were better than those obtained on the entire chromatographic profile, with the exception of Extended Canonical Variates Analysis, which gave acceptable models in both cases. Copyright © 2008 John Wiley & Sons, Ltd.     

Optimization of a glucose biosensor setup based on a Ni/Al HT matrix

An amperometric glucose biosensor was developed using an anionic clay matrix of hydrotalcitic nature (Ni/Al-NO₃ HT) as enzyme support, which was electrochemically synthesized at −0.90 V versus SCE, using a rotating disk Pt electrode to assure homogeneity of the electrodeposition suspension. The biorecognition element was glucose oxidase (GOx) immobilized on HT during the electrosynthesis, which was followed by cross-linking with glutaraldehyde vapours to avoid the enzyme release.The performances of the biosensor, in terms of sensitivity to glucose calculated from the slope of the calibration curve, are dependent on parameters related to the electrodeposition.An experimental design was applied to detect the optimal conditions of electrosynthesis in order to optimize the glucose biosensor performance. The factors taken into account were enzyme concentration and Ni/Al molar ratio. A full factorial design was performed to study linear interactions between factors and their quadratic effects and the optimal setup was evaluated by the isoresponse curves. The significant factors were enzyme concentration (linear and quadratic terms) and the interaction between enzyme concentration and Ni/Al molar ratio. Under the optimized electrodeposition conditions, the reproducibility of the biosensor fabrication was very good, being the RSD of the sensitivity about 5%.     

A Preliminary Color Study of Different Basil-Based Semi-Finished Products during Their Storage

Basil-based semi-finished products, which are mainly used as an intermediate to produce the typical pesto sauce, are prepared and exported all over the world. Color is a fundamental organoleptic requirement for the acceptability of these semi-finished products by the manufacturers of the pesto sauce. Some alternative formulations, which adjust the typical industrial recipe by both changing the preservative agent (ascorbic acid, citric acid, or a mixture of both) and introducing a preliminary thermic treatment (blast chilling), were evaluated. In this work, a fast and non-destructive spectrophotometric analysis, to monitor the color variations in these food products during their shelf-life, was proposed. The raw diffuse reflectance spectra (380–900 nm) obtained by a UV–visible spectrophotometer, endowed with an integrating sphere, together with the CIELab parameters (L*, a*, b*) automatically obtained from these, were considered, and elaborated using multivariate statistical analysis (principal component analysis). From this preliminary study, blast chilling, together with the use of ascorbic acid, proved to be the best solution to better preserve the color of these products during their shelf-life.     

Multi-Elemental Analysis as a Tool to Ascertain the Safety and the Origin of Beehive Products: Development,Validation, and Application of an ICP-MS Method on Four Unifloral Honeys Produced in Sardinia,Italy

Despite unifloral honeys from Sardinia, Italy, being appreciated worldwide for their peculiar organoleptic features, their elemental signature has only partly been investigated. Hence, the principal aim of this study was to measure the concentration of trace and toxic elements (i.e., Ag, As, Ba, Be, Bi, Cd, Co, Cr, Cu, Fe, Hg, Li, Mn, Mo, Ni, Pb, Sb, Sn, Sr, Te, Tl, V, and Zn) in four unifloral honeys produced in Sardinia. For this purpose, an original ICP-MS method was developed, fully validated, and applied on unifloral honeys from asphodel, eucalyptus, strawberry tree, and thistle. Particular attention was paid to the method’s development: factorial design was applied for the optimization of the acid microwave digestion, whereas the instrumental parameters were tuned to minimize the polyatomic interferences. Most of the analytes’ concentration ranged between the relevant LoDs and few mg kg⁻¹, while toxic elements were present in negligible amounts. The elemental signatures of asphodel and thistle honeys were measured for the first time, whereas those of eucalyptus and strawberry tree honeys suggested a geographical differentiation if compared with the literature. Chemometric analysis allowed for the botanical discrimination of honeys through their elemental signature, whereas linear discriminant analysis provided an accuracy level of 87.1%.     

Application of multi-way analysis to UV–visible spectroscopy,gas chromatography and electronic nose data for wine ageing evaluation

In this study, a multi-way method (Tucker3) was applied to evaluate the performance of an electronic nose for following the ageing of red wines. The odour evaluation carried out with the electronic nose was combined with the quantitative analysis of volatile composition performed by GC–MS, and colour characterisation by UV–visible spectroscopy. Thanks to Tucker3, it was possible to understand connections among data obtained from these three different systems and to estimate the effect of different sources of variability on wine evaluation. In particular, the application of Tucker3 supplied a global visualisation of data structure, which was very informative to understand relationships between sensors responses and chemical composition of wines. The results obtained indicate that the analytical methods employed are useful tools to follow the wine ageing process, to differentiate wine samples according to ageing type (either in barrel or in stainless steel tanks with the addition of small oak wood pieces) and to the origin (French or American) of the oak wood. Finally, it was possible to designate the volatile compounds which play a major role in such a characterisation.