M. Aleixandre

Identification of typical wine aromas by means of an electronic nose

In the field of electronic noses (e-noses), it is not very usual to find many applications to wine detection. Most of them are related to the discrimination of wines in order to prevent their illegal adulteration and detection of off-odors, but their objective is not the identification of wine aromas. In this paper, an application of an e-nose for the identification of typical aromatic compounds present in white and red wines is shown. The descriptors of these compounds are fruity, floral, herbaceous, vegetative, spicy, smoky, and microbiological, and they are responsible for the usual aromas in wines; concentrations differ from 2-8/spl times/ the threshold concentration humans can smell. Some of the measured aromas are pear, apple, peach, coconut, rose, geranium, cut green grass, mint, vanilla, clove, almond, toast, wood, and butter. Principal component analysis and linear discriminant analysis show that datasets of these groups of compounds are clearly separated, and a comparison among several types of artificial neural networks has been also performed. The results confirm that the system has good performance in the classification of typical red and white wine aromas.

Threshold detection of aromatic compounds in wine with an electronic nose and a human sensory panel.

An electronic nose (e-nose) based on thin film semiconductor sensors has been developed in order to compare the performance in threshold detection and concentration quantification with a trained human sensory panel in order to demonstrate the use of an e-nose to assess the enologists in an early detection of some chemical compounds in order to prevent wine defects. The panel had 25 members and was trained to detect concentration thresholds of some compounds of interest present in wine. Typical red wine compounds such as whiskeylactone and white wine compounds such as 3-methyl butanol were measured at different concentrations starting from the detection threshold found in literature (in the nanograms to milligrams per liter range). Pattern recognition methods (principal component analysis (PCA) and neural networks) were used to process the data. The results showed that the performance of the e-nose for threshold detection was much better than the human panel. The compounds were detected by the e-nose at concentrations up to 10 times lower than the panel. Moreover the e-nose was able to identify correctly each concentration level therefore quantitative applications are devised for this system.

Differentiation of red wines using an electronic nose based on surface acoustic wave devices

An electronic nose, utilizing the principle of surface acoustic waves (SAW), was used to differentiate among different wines of the same variety of grapes which come from the same cellar. The electronic nose is based on eight surface acoustic wave sensors, one is a reference sensor and the others are coated by different polymers by spray coating technique. Data analysis was performed by two pattern recognition methods; principal component analysis (PCA) and probabilistic neuronal network (PNN). The results showed that electronic nose was able to identify the tested wines.

Detection of toxic gases by a tin oxide multisensor

A tin oxide multisensor with eight sensor elements has been utilized to detect different gases that are emitted from the chemical industry. The different sensors have been prepared using the RF reactive sputtering technique. Some components of this multisensor were doped with Pt and Cr by sputtering. Each sensor has been characterized by electrical measurements for detection of atmospheric pollution (nitrogen dioxide, carbon monoxide, toluene, and propanal). The detected gases are toxic and their extreme concentrations recommended in air oscillate from 1 ppm to hundreds of ppm. Detections were carried out with a single gas or a gas mixture (two gases) in dry air at 250/spl deg/C. The sensitivity and selectivity to these gases were studied. Backpropagation neural networks and their classification results were discussed.

Tibialis Anterior muscle coherence during controlled voluntary activation in patients with spinal cord injury: diagnostic potential for muscle strength, gait and spasticity

BackgroundCoherence estimation has been used as an indirect measure of voluntary neurocontrol of residual motor activity following spinal cord injury (SCI). Here intramuscular Tibialis Anterior (TA) coherence estimation was performed within specific frequency bands for the 10-60 Hz bandwidth during controlled ankle dorsiflexion in subjects with incomplete SCI with and without spasticity.MethodsIn the first cohort study 15 non-injured and 14 motor incomplete SCI subjects were recruited to evaluate TA coherence during controlled movement. Specifically 15-30 Hz EMG was recorded during dorsiflexion with: i) isometric activation at 50, 75 and 100% of maximal voluntary torque (MVT), ii) isokinetic activation at 60 and 120°/s and iii) isotonic dorsiflexion at 50% MVT. Following identification of the motor tasks necessary for measurement of optimal TA coherence a second cohort was analyzed within the 10-16 Hz, 15-30 Hz, 24-40 Hz and 40-60 Hz bandwidths from 22 incomplete SCI subjects, with and without spasticity.ResultsIntramuscular 40-60 Hz, but not 15-30 Hz TA, coherence calculated in SCI subjects during isometric activation at 100% of MVT was lower than the control group. In contrast only isometric activation at 100% of MVT 15-30 Hz TA coherence was higher in subjects with less severe SCI (AIS D vs. AIS C), and correlated functionally with dorsiflexion MVT. Higher TA coherence was observed for the SCI group during 120°/s isokinetic movement. In addition 15-30 Hz TA coherence calculated during isometric activation at 100% MVT or 120°/s isokinetic movement correlated moderately with walking function and time from SCI, respectively. Spasticity symptoms correlated negatively with coherence during isometric activation at 100% of MVT in all tested frequency bands, except for 15-30 Hz. Specifically, 10-16 Hz coherence correlated inversely with passive resistive torque to ankle dorsiflexion, while clinical measures of muscle hypertonia and spasm severity correlated inversely with 40-60 Hz.ConclusionAnalysis of intramuscular 15-30 Hz TA coherence during isometric activation at 100% of MVT is related to muscle strength and gait function following incomplete SCI. In contrast several spasticity symptoms correlated negatively with 10-16 Hz and 40-60 Hz TA coherence during isometric activation at 100% MVT. Validation of the diagnostic potential of TA coherence estimation as a reliable and comprehensive measure of muscle strength, gait and spasticity should facilitate SCI neurorehabilation.

Electronic nose for the identification of spoiled Iberian hams

This paper reports the use of an electronic nose for the identification of spoiled hams during the curing process. The sensors involved are tin oxide semiconductor thin films. They were prepared by RF sputtering. Some of the sensors were doped with metal catalysts as Cr and In. A good discrimination of two types of Iberian hams (spoiled and unspoilt) has been obtained through the statistical methods of principal component analysis (PCA) and probabilistic neural network (PNN).

Detection of Iberian ham aroma by a semiconductor multisensorial system.

A semiconductor multisensorial system, based on tin oxide, to control the quality of dry-cured Iberian hams is described. Two types of ham (submitted to different drying temperatures) were selected. Good responses were obtained from the 12 elements forming the multisensor for different operating temperatures. Discrimination between the two types of ham was successfully realised through principal component analysis (PCA).

A Wireless and Portable Electronic Nose to Differentiate Musts of Different Ripeness Degree and Grape Varieties

Two novel applications using a portable and wireless sensor system (e-nose) for the wine producing industry—The recognition and classification of musts coming from different grape ripening times and from different grape varieties—Are reported in this paper. These applications are very interesting because a lot of varieties of grapes produce musts with low and similar aromatic intensities so they are very difficult to distinguish using a sensory panel. Therefore the system could be used to monitor the ripening evolution of the different types of grapes and to assess some useful characteristics, such as the identification of the grape variety origin and to prediction of the wine quality. Ripening grade of collected samples have been also evaluated by classical analytical techniques, measuring physicochemical parameters, such as, pH, Brix, Total Acidity (TA) and Probable Grade Alcoholic (PGA). The measurements were carried out for two different harvests, using different red (Barbera, Petit Verdot, Tempranillo, and Touriga) and white (Malvar, Malvasía, Chenin Blanc, and Sauvignon Blanc) grape musts coming from the experimental cellar of the IMIDRA at Madrid. Principal Component Analysis (PCA) and Probabilistic Neural Networks (PNN) have been used to analyse the obtained data by e-nose. In addition, and the Canonical Correlation Analysis (CCA) method has been carried out to correlate the results obtained by both technologies.

Calibration of a cluster of low-cost sensors for the measurement of air pollution in ambient air

Using a clustered system of sensors able to measure O3, NO/NO2, CO and CO2, we want to compare the performance of several calibration methods. Based on the outcome of the single sensors evaluation, the suitability of this cluster is investigated using deterministic or statistical methods such as multivariate regression and neural networks. The objective of the study is to assess if the measurement uncertainty of sensors can reach the Data Quality Objective of the European Air Quality Directive for indicative methods.

Study of a palladium coated Bragg grating sensor to detect and measure low hydrogen concentrations

In this work we present a sensor based in a Bragg grating coated by a small amount of palladium. We explain the process of fabrication in detail, from the etching of the fiber to the deposition of the palladium. In this sensor the amount of hydrogen absorbed by the Pd is hydrogen concentration dependant and causes a stress that alters the transmission or reflection spectra of the FBG.