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The objective of this work is to report the improvement obtained in the discrimination of complex aroma and taste with subtle differences in odor and flavor, by the use of fast suitable procedures for the cases of measurements in the field demanding decision-making in real time. The proposed electronic sensing systems, formed by an E-nose and VE-tongue, were used to discriminate cumin cultivars from different geographical origins, as well as to quantify the cumin adulteration percentages by using unsupervised and supervised chemometric tools. Thus, the results obtained are sufficiently encouraging as a starting point for the development of new electronic sensing systems with more improvement such the reliability of the sensors’ performance as well as the chemometric tools in order to deal with a complex dataset.
An experimental investigation has been carried out to characterize and discriminate seven saffron samples and to verify their declared geographical origin using a voltammetric electronic tongue (VE-tongue). The ability of multivariable analysis methods such as Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) to classify the saffron samples according to their geographical origin have been investigated. A good discrimination has reached using PCA and HCA in the VE-tongue characterization case. Furthermore, cross validation and Partial Least Square (PLS) techniques were applied in order to build suitable management and prediction models for the determination of safranal concentration in saffron samples based on SPME-GC-MS and UV-Vis Spectrophotometry. The obtained results reveals that some relationships were established between the VE-tongue signal, SPMEGC-MS and UV-Vis spectrophotometry methods to predict safranal concentration levels in saffron samples by using the PLS model. In the light of these results, we can say that the proposed electronic system offer a fast, simple and efficient tool to recognize the declared geographical origin of the saffron samples.
Different electronic sensor systems coupled with multivariate data analysis were applied to characterize and classify seven saffron samples and to verify their declared geographical origin. The proposed electronic sensing consists of a low-cost electronic nose (E-nose) based on metal oxide semiconductor sensors and a voltammetric electronic tongue (VE-tongue) based on voltammetric sensors. The ability of multivariable analysis methods such as Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Support Vector Machines (SVMs) to classify the saffron samples according to their geographical origin have been investigated. Both PCA and HCA have shown an overlapping of E-nose responses. Moreover, the SVM analysis of the E-nose database reached a 66.07% success rate in the recognition of the saffron sample odour. On the other hand, good discrimination has been reached using PCA and HCA in the VE-tongue characterization case, besides a 100% accuracy in the saffron flavour recognition was attained. To validate the proposed electronic sensing systems, analytical chemical methods such as SPME-GC-MS and UV-Vis spectrophotometry were used. These analytical methods could be helpful tools to identify the composition of volatile compounds of the analysed saffron samples. Moreover, UV-Vis spectrophotometry was also used to determine the non-volatile profile of the samples from different geographic origins. It is demonstrated that the electronic sensing systems' findings are in a satisfactory correlation with the analytical methods. In the light of these results, we might say that the electronic systems offer a fast, simple and efficient tool to recognize the declared geographical origin of the saffron samples.
During their growth on wood many fungi produce characteristic volatile organic compounds as secondary metabolites. These microbial volatile organic compounds (MVOCs) can be used as indicators of fungal growth even when such growth is concealed. In order to investigate the formation of these volatile metabolites on building materials, specimens of pine sapwood on agar media colonized by the dry-rot fungus Serpula lacrymans and a mixture of six moulds were examined. MVOCs from this fungal growth were studied over a period of up to half a year by ion mobility spectrometry (IMS) headspace analysis using a sensitive, portable IMS mini-device. The IMS headspace spectra from the growing fungal specimens obtained during this time span are differed from non-incubated wood specimens and indicate the presence of a mixture of MVOCs. The composition and amount of volatile metabolites of the fungi changed during cultivation. This was confirmed by a principal component analysis (PCA). Identification of different MVOCs in the headspace according to drift time and the mobility of ionized gaseous species in reference to GC-MS investigations were proposed. It was concluded that IMS can be used as a rapid and sensitive on-site method to indicate actively growing fungi concealed within wood.
A portable device for calibration of trace humidity sensors and an adopted calibration procedure have been developed. The calibration device is based on humidity generation by permeating water through polymeric membrane tubes. Water vapour transmission rates for various polymers were experimentally determined in order to select the most suitable polymeric material. The developed trace humidity generator consists of a gas-flow polymeric hose immersed in a water reservoir thermostated by a sensorcontrolled heater. Mole fractions of water vapour between 1 µmol/ molˉ¹ and 350 µmol/molˉ¹ (equivalent to frost-point temperatures from -76 °C to -31 °C) were generated by varying either the operating temperature or gas flow. The operating temperature can be varied from 20 °C to 60 °C and kept stable within 0.1 K. Uncertainty analysis indicated that the trace humidity generator produces gas flows of constant humidity amounts with a relative expanded uncertainty less than 3.4% (k = 2) of the generated value.
The chapter describes the application of electronic noses (multigas sensors) for the quality control of spices and spice mixtures. Electronic noses were successfully applied for headspace analysis of spices. It was demonstrated in many investigations that electronic noses can contribute to the characterization of spices and spice mixtures in order to distinguish spices and spice mixtures, differentiate by origin, growth seasons,and processing,indicate adulteration from original, detect mold infestation. Electronic noses can be used as a fast screening method to provide information about the product quality. However, it needs samples and methods for reference, careful training, and complex calibration to consider influencing and disturbing effects as well as the possible limitations of the instrumentation. The correlation to classical chemical analysis methods is always advisable. Machined olfaction methods are capable to support the sensory analysis; however, they cannot yet substitute them.
The efficiency of gas sensor application for facilitating the safe use of hydrogen depends considerably on the sensor response to a change in hydrogen concentration. Therefore, the response time has been measured for five different-type commercially available hydrogen sensors. Experiments showed that all these sensors surpass the ISO 26142 standard; for the response times t90 values of 2 s to 16 s were estimated. Results can be fitted with an exponential or sigmoidal function. It can be demonstrated that the results on transient behaviour depend on both the operating parameters of sensors and Investigation methods, as well as on the experimental conditions: gas change rate and concentration jump.
Planar coulometric sensors were tested in humidified synthetic air at various gas temperatures. Generated frost point temperature in the gas ranged from -30 °C to -60 °C and were measured by coulometric sensors and in addition by a calibrated dew point hygrometer. The gas temperatures, which were measured by a calibrated Pt100 sensor, were set to -20 °C, 0 °C, 23 °C, 40 °C, 50 °C, and 60 °C during the experiments. Empiric nonlinear functions were calculated between the generated humidity and the sensor signals. In comparison to the measured signals at 23 °C, the sensor signals were lower at the other gas temperatures. The measurements at 60 °C showed indistinct results due to a great signal noise. The response behavior of the sensors was similar at 23 °C, 40 °C and 50 °C. In contrast to that, the sensors reacted slowly at a gas temperature of -20 °C and 0 °C. In summary, with coulometric sensors it was possible to measure continuously trace humidity with an expanded uncertainty below 2 K.
Trace humidity was measured by using miniaturized planar coulometric sensors in technical gases such as hydrogen, nitrogen, helium, nitrous oxide, and synthetic air. Frost point temperatures tf in the gases ranged from −60 °C to −30 °C, which is equivalent to a vapour mole fraction xv from 10 μmol mol−1 to 376 μmol mol−1. In addition, the generated humidity was determined by using a precision dew point hygrometer as reference. Nonlinear calibration functions were calculated that correlated electric current (sensor signal) and reference humidity. Parameters of functions were tested with one-way analysis of variances (ANOVA) to prove if all used sensors had a similar behavior in the same gas during experiments. Results of ANOVA confirmed that averaged functions can be applied for trace humidity measurement in nitrogen, helium, nitrous oxide, and synthetic air. The calculated functions were negligibly different for nitrogen, helium, and synthetic air. In humidified nitrous oxide, a minor change of parameters was observed due to lower electrical currents. In total contrast to that, the measured sensor signals were significantly higher in humidified hydrogen and each sensor required its own calibration function. The reason was a recombination effect that favoured multiple measurements of water molecules. Nevertheless, it was possible to measure continuously trace humidity in all tested gases by using coulometric sensors with an expanded uncertainty below 2 K (k = 2).