In this work we characterised Negroamaro red wines, made by an autochthonous cultivar of Southern Italy, by linking volatile composition to aroma properties. This linking was carried out by picturing "Aroma Wheels", built by Odour Activity Values (OAVs) of all the identified volatile compounds grouped in "aromatic series" belonging to 13 classes of sensory descriptors. The 18 most active odorants with OAV>1 were mainly alcohols, fatty acids and their ethyl esters. The "OAVs' Aroma Wheels" showed that the classes of sensory descriptors are first fruity and floral, next fatty and pungent and minor nutty and caramelised notes. Principal Component Analysis displayed correlations between sensory descriptors and wine samples; the main 7-fruity and 5-floral sensory features of Negroamaro wines have negative values of PC1 and they are negatively correlated with the second main sensory feature, i.e. 13-fatty, falling at positive value of PC1; this fit the aroma perception of this varietal.

Wine aroma volatiles of two different typical Apulian wines made by autochthonous grape varieties (i.e. Negroamaro and Primitivo) were extracted by solid phase extraction (SPE) and analyzed using gas chromatography-mass spectrometry (GC-MS) in conjugation with an electronic nose (E-nose). Eighteen compounds were found over their own odour threshold and they were taken into account for further data analysis. Sensor data were analyzed by principal component analysis (PCA) to investigate the discrimination capability of the sensor array. The concentrations of volatile chemical compounds in wines determined by GC-MS have been correlated with electronic nose (E-nose) responses using partial least squares (PLSs) and quadratic response surface regression (RSR) analysis. By means of these regression models, relationships between E-nose responses and wine aroma compounds were established. Quite all of the 18 wine odorant concentration were predicted at a satisfactory extent; RSR technique gave better prediction results compared to PLS. © 2012 Elsevier B.V. All rights reserved.

The present research was motivated by the growing interest of the scientific community towards the understanding of basic gas-surface interaction mechanisms in 1D nanostructured metal oxide semiconductors, whose significantly enhanced chemical detection sensitivity is known. In this work, impedance spectroscopy (IS) was used to evaluate how a top-down patterning of the sensitive layer can modulate the electrical properties of a gas sensor based on a fully integrated nanometric array of TiO2 polycrystalline strips. The aim of the study was supported by comparative experimental activity carried out on different thin film gas sensors based on identical TiO2 polycrystalline sensitive thin films. The impedance responses of the investigated devices under dry air (as the reference environment) and ethanol vapors (as the target gas) were fitted by a complex nonlinear least-squares method using LEVM software, in order to find an appropriate equivalent circuit describing the main conduction processes involved in the gas/semiconductor interactions. Two different equivalent circuit models were identified as completely representative of the TiO2 thin film and the TiO2 nanostructure-based gas sensors, respectively. All the circuit parameters were quantified and the related standard deviations were evaluated. The simulated results well approximated the experimental data as indicated by the small mean errors of the fits (in the range of 10(-4)) and the small standard deviations of the circuit parameters. In addition to the substrate capacitance, three different contributions to the overall conduction mechanism were identified for both equivalent circuits: bulk conductivity, intergrain contact and semiconductor-electrode contact, electrically represented by an ideal resistor R-g, a parallel RgbCgb block and a parallel R-c-CPEc combination, respectively. In terms of equivalent circuit modeling, the sensitive layer patterning introduced an additional parameter in parallel connection with the whole circuit block. Such a circuit element (an ideal inductor, L) has an average value of about 125 mu H and exhibits no direct dependence on the analyte gas concentration. Its presence could be due to complex mutual inductance effects occurring both between all the adjacent nanostrips (10 mu m spaced) and between the nanostrips and the n-type-doped silicon substrate underneath the thermal oxide (wire/plate effect), where a two order of magnitude higher magnetic permeability of silicon can give L values comparable with those estimated by the fitting procedure. Slightly modified experimental models confirmed that the theoretical background, regulating thin film devices based on metal oxide semiconductors, is also valid for nanopatterned devices.

IntroductionSemiconducting metal oxides belong to the frequently used materials in gas sensing both in environmental protection and in medicine [1]. Amongst the broad variety of well established oxides, like SnO2, TiO2, WO3, ZnO, iron oxide ?-Fe2O3 and cobalt - iron oxide CoFe2O4 attract now attention because of complex magnetic and electric properties and high chemical reactivity. Moreover, innovative sensors are built from nanoparticle (NP) arrays. In comparison with continuous films these devices with high surface/volume ratio are more sensitive [2]. Our sensors are appropriate for oxidizing NO2 gas. With ?-Fe2O3 the response R = Iair/Igas (the ratio of the device current in dry air vs. in air mixed with the analysed gas) is 38 at NO2 concentration Cg = 500 ppb and working temperature Tw = 350oC [3]. This result is comparable with the top published sensitivities, e.g. R = 8 at Cg = 500 ppb and Tw =250oC [4]. With CO and acetone (studied as a marker of diabetes in the patient's breath) the sensitivities are lower [2]. With CO R = 2.8 at Cg = 100 ppm and Tw = 350oC, with acetone R = 1.8 at Cg = 5 ppm at Tw = 500oC. (CO and acetone are reducing gases, hence here R = Igas/Iair). High sensitivity of NP sensors to oxidizing gases and lower sensitivity to reducing gases was explained by charge carrier self-exhaustion of NPs by surface traps [5]. For the further progress in the field the mechanism of conductivity of NP arrays is of considerable interest. In this paper we summarize the results obtained as a by product of ?-Fe2O3 and CoFe2O4 sensors testing.

Sn02 nanorods were successfully deposited on 3" Si/Si02 wafers by inductively coupled plasma-enhanced chemical vapor deposition (PECVD) and a wafer-level patterning of nanorods layer for miniaturized solid state gas sensor fabrication were performed. Uniform needle-shape Sn02 nanorods in situ grown were obtained under catalyst- and high temperature treatment-free growth condition. These nanorods have an average diameter between 5 and IS nm and a length of 160 to 300 nm. The Sn02-nanords based gas sensors were tested towards NH3 and CH30H and gas sensingtests show remarkable response, showing promising and repeatable results compared with the Sn02 thin films gas sensors.

SnO(2) nanorods were successfully deposited on 3" Si/SiO(2) wafers by inductively coupled plasma-enhanced chemical vapour deposition (PECVD) and a wafer-level patterning of nanorods layer for miniaturized solid state gas sensor fabrication were performed. Uniform needle-shaped SnO(2) nanorods in situ grown were obtained under catalyst- and high temperature treatment-free growth condition. These nanorods have an average diameter between 5 and 15 nm and a length of 160-300 nm. The SnO(2)-nanorods based gas sensors were tested towards NH(3) and CH(3)OH and gas sensing tests show remarkable response, showing promising and repeatable results compared with the SnO(2) thin films gas sensors.

Fe3O4/gamma-Fe2O3 nanoparticles (NPs) based thin films were used as active layers in solid state resistive chemical sensors. NPs were synthesized by high temperature solution phase reaction. Sensing NP monolayers (ML) were deposited by Langmuir-Blodgett (LB) techniques onto chemoresistive transduction platforms. The sensing ML were UV treated to remove NP insulating capping. Sensors surface was characterized by scanning electron microscopy (SEM). Systematic gas sensing tests in controlled atmosphere were carried out toward NO2, CO, and acetone at different concentrations and working temperatures of the sensing layers. The best sensing performance results were obtained for sensors with higher NPs coverage (10 ML), mainly for NO2 gas showing interesting selectivity toward nitrogen oxides. Electrical properties and conduction mechanisms are discussed.

Breathanalysishasapowerfulpotentialfordiseasediagnosticsandmetabolicstatusmonitoring.Asol-gelSnOz­basedmicromachinedsensorarraywasdevelopedandtestedforpotentialapplicationinbreathanalysis.Asuitablebreathsamplingsystemwasusedtosamplethealveolarairvolumefromtheairvolumeofoneexpiration.Breathtestsonalveolarairsampledbysomevolunteers,i.e.smokersandnonsmokersindividuals,werecarried out.PrincipalComponentAnalysisappliedtogassensorresponsesshowedgoodpropertiesofdiscriminationbetweensmokersandnonsmokersindividuals.

Saccharomyces cerevisiae is the yeast species predominating the alcoholic fermentation of grape must. The aim of this research was to evaluate the impact of indigenous S.cerevisiae strains biodiversity on the aroma of wines from Negroamaro grapes. Grapes collected in two different Negroamaro producing micro districts in Salento (Southern Italy), were subjected to natural fermentation and two indigenous S.cerevisiae populations were isolated. Fifteen strains for each of the two populations were selected and tested by micro fermentation assay in order to evaluate their specific contribute to the volatiles composition and sensory impact of the produced wines. The aromatic profile of wines obtained by each selected strain was characterized by different contents of acetates, ethyl esters of fatty acids, higher alcohols, thus showing to be related to the strains geographical origin. The sensorial analysis of wines produced by the six best performing strains confirmed that they are good candidates as industrial starter cultures, This study indicates that the use of a "microarea-specific" starter culture is a powerful tool to enhance the peculiarity of wines deriving from specific areas. © 2014 Elsevier Ltd.

The aim of this work is to study the influence of 30 different autochthonous Saccharomyces cerevisiae strains, isolated from Negroamaro grapes, sampled in the northern (NN strain) and in the southern (NS strain) of Salento (south Apulia, ITALY), on the volatile fraction of the corresponding Negroamaro wines made using the different isolated yeast strains by controlled microvinification processes. A further aim is to compare the volatile profiles of the as-obtained 30 different Negroamaro wines with the volatile profile of a Negroamaro wine produced by using a commercial yeast strain selected among the most employed by local producers. Modern wine makers prefer to employ commercial yeast strains due to their known specific yield and efficiency characteristics so as to ensure a reproducible product, reduce the risk of wine spoilage and allow a more predictable control of fermentation and quality. However, it's important to know the potential of using the autochthonous S. cerevisiae yeast strains with the best performance, in order to exploit them to improve wine quality and commercial standards. In the present work we have used two different analytical methods in order to analyze different compounds present in wine volatile fraction in a wide range of concentrations. Highly compounds concentrations (major volatiles) were directly determined on wine by GC-FID, whereas represented minor molecules were extracted by SPE method and then analysed by GC/MS. The complete volatile profile of all the wine samples was obtained together with a quantitative analysis by internal standardization method. Principal Component Analysis, applied to compound concentrations data showed that the wines, respectively produced with NN strains and strains NS, differentiated among them according to their aroma composition. The differences in the composition appear to be quantitative rather than qualitative. In fact, the formation of secondary products depends both on the yeast's enzymes and on the nitrogen nutrients and cofactors present in must so that the same yeast can produce different volatile patterns, depending on must composition.The obtained results suggest that the concentration of most of the volatile compounds was significantly influenced by the particular inoculated S. cerevisiae yeast strain. Autochthonous yeast strains have been shown to be able to produce wines with different volatile profiles. In particular most of NN strain have produced wines rich in alcohols and esters, most of NS strain have produced have produce wines rich in acids, esters and acetaldehyde.

The optimization of a sensor array for a concrete analytical task is usually concerned with choosing a set of sensors to provide the best classification. In this work, a method for the prediction of the quality of classification by evaluation of the uniqueness of the raw experimental data is proposed. The key feature of the method is the presentation of the response of array as a function of the responses of its sensors. The dispersion of those functions serves as quantitative measure of uniqueness of the experimental data for a given set of analytes.The efficiency of the approach has been successfully demonstrated using both simulated and experimental data obtained from the array of three mass-sensitive sensors. The best conformity of the classification efficiency in cluster analysis with results obtained in the framework of the proposed approach is observed in the case of Langmuir-type adsorption processes.

ZnO nanocrystals (2.5-4.5 nm) were prepared by a wet chemical method based on alkaline-activated hydrolysis and condensation of zinc acetate solutions. Dropcasting of the nanocrystals onto alumina substrates allowed the fabrication of gas sensing devices, that were tested towards NO2, acetone and methanol and showed promising results. At low working temperature, the ZnO quantum dots based sensors are selective to nitrogen oxide, in fact a good sensitivity is shown at 200 degrees C at low concentration (2 ppm), while at temperature above 350 degrees C, high responses are obtained for acetone and methanol. The results obtained are stimulating for further developing of nano-ZnO based sensor devices.

Volatile composition of monovarietal young red wines made from Negroamaro cultivar, an autochthonous grape variety of Vitis vinifera grown exclusively in Solento area (southeast of Italy in Apulia region), was investigated. Volatile compounds were extracted following a solid phase extraction (SPE) method, and then analysed by gas chromatography-mass spectrometry (GC/MS). Results showed a complex aroma profile rich in alcohols, esters and fatty acids, with a minor contribute from aldehydes, lactones, volatile phenols and sulphur compounds. For the first time, aromatic patterns that characterise wines produced from Negroamaro autochthonous grape variety were established, starting a fundamental register of typicity and geographical identity of Apulians wines. Statistical data analysis techniques (Principal component analysis (PCA) and ANOVA) showed the structure of the experimental data and the significant differences for each compound in the different wines. (C) 2011 Elsevier Ltd. All rights reserved.