A Compact and Low Cost Electronic Nose for Aroma Detection (original) (raw)

Identification of typical wine aromas by means of an electronic nose

IEEE Sensors Journal, 2006

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 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.

An Electronic Nose for Reliable Measurement and Correct Classification of Beverages

Sensors, 2011

This paper reports the design of an electronic nose (E-nose) prototype for reliable measurement and correct classification of beverages. The prototype was developed and fabricated in the laboratory using commercially available metal oxide gas sensors and a temperature sensor. The repeatability, reproducibility and discriminative ability of the developed E-nose prototype were tested on odors emanating from different beverages such as blackcurrant juice, mango juice and orange juice, respectively. Repeated measurements of three beverages showed very high correlation (r > 0.97) between the same beverages to verify the repeatability. The prototype also produced highly correlated patterns (r > 0.97) in the measurement of beverages using different sensor batches to verify its reproducibility. The E-nose prototype also possessed good discriminative ability whereby it was able to produce different patterns for different beverages, different milk heat treatments (ultra high temperature, pasteurization) and fresh and spoiled milks. The discriminative ability of the E-nose was evaluated using Principal Component Analysis and a Multi Layer Perception Neural Network, with both methods showing good classification results.

Classification of white wine aromas with an electronic nose

Talanta, 2005

This paper reports the use of a tin dioxide multisensor array based electronic nose for recognition of 29 typical aromas in white wine. Headspace technique has been used to extract aroma of the wine. Multivariate analysis, including principal component analysis (PCA) as well as probabilistic neural networks (PNNs), has been used to identify the main aroma added to the wine. The results showed that in spite of the strong influence of ethanol and other majority compounds of wine, the system could discriminate correctly the aromatic compounds added to the wine with a minimum accuracy of 97.2%.

Odour discrimination with an electronic nose

Sensors and Actuators B: Chemical, 1992

Smell is probably the least understood and exploited of the principal human senses, yet it is clearly important to both product and process control in many industries, such as foodstuffs, beverages, tobacco and perfumery. Advances in the field of integrated microelectronic devices have led to new instruments, robots, capable of vision and complex touch or taction, but not yet of smell. This paper reviews the research effort that has been carried out at Warwick University over recent years into the development of an electronic instrument that can mimic the human sense of smell. The approach that we have adopted is to construct a microprocessor-controlled system comprising an array of solid-state chemical gas sensors (with overlapping partial sensitivities to odorants) and associated signal processing and pattern recognition. This electronic system' is based upon our present knowledge of the biological system. Our earliest electronic nose consisted of an array of only three to twelve tin dioxide thick-film sensors, yet it can discriminate betwe_en alcohols, beverages, tobacco blends and coffees. Current efforts are reported towards the fabrication of an integrated microsensor metal oxide array, the development of other electronic devices using polymeric materials, and the implementation of various patternrecognition techniques, including correlation, principalcomponent analysis, cluster analysis and artificial neural networks. Finally, the application areas most likely to arouse widespread interest in the next decade are discussed.

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

Talanta, 2010

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.

Electronic nose for monitoring the flavour of beers

The Analyst, 1993

The flavour of a beer is determined mainly by its taste and smell, which is generated b y about 700 key volatile and non-volatile compounds. Beer flavour is traditionally measured through the use of a combination of conventional analytical tools (e.g., gas chromatography) and organoleptic profiling panels. These methods are not only expensive and time-consuming but also inexact due t o a lack of either sensitivity or quantitative information. In this paper an electronic instrument is described that has been designed to measure the odour of beers and supplement or even replace existing analytical methods. The instrument consists of an array of u p to 12 conducting polymers, each of which has an electrical resistance that has partial sensitivity to the headspace of beer. The signals f r o m the sensor array are then conditioned b y suitable interface circuitry and processed using a chemometric or neural classifier. The results of the application of multivariate statistical techniques are given. The instrument, or electronic nose, is capable of discriminating between various commercial beers and, more significantly, between standard and artificially-tainted beers. A n industrial version of this instrument is n o w undergoing trials in a brewery.

Acetic Acid Detection Threshold in Synthetic Wine Samples of a Portable Electronic Nose

Sensors, 2012

Wine quality is related to its intrinsic visual, taste, or aroma characteristics and is reflected in the price paid for that wine. One of the most important wine faults is the excessive concentration of acetic acid which can cause a wine to take on vinegar aromas and reduce its varietal character. Thereby it is very important for the wine industry to have methods, like electronic noses, for real-time monitoring the excessive concentration of acetic acid in wines. However, aroma characterization of alcoholic beverages with sensor array electronic noses is a difficult challenge due to the masking effect of ethanol. In this work, in order to detect the presence of acetic acid in synthetic wine samples (aqueous ethanol solution at 10% v/v) we use a detection unit which consists of a commercial electronic nose and a HSS32 auto sampler, in combination with a neural network classifier (MLP). To find the characteristic vector representative of the sample that we want to classify, first we select the sensors, and the section of the sensors response curves, where the probability of detecting the presence of acetic acid will be higher, and then we apply Principal Component Analysis (PCA) such that each sensor response curve is represented by the coefficients of its first principal components. Results show that the PEN3 electronic

The electronic NOSE and its application to the manufacture of food products

Journal of Automatic Chemistry, 1995

The Electronic NOSE described in this paper was not developed to replace the GC/MS or the sensory panel but to provide an instrumental measure of aroma quality which would be related to and complement the current methodology. The Electronic NOSE is a robust system which can detect complex vapours at levels similar to the human, which means typically in the parts per billion range. The system produces an output which can be easily related to sensory data and is easy to interpret by a non-skilled operator. No part of this system reacts with the sample under test.

Monitoring the aroma production during wine-must fermentation with an electronic nose

Biotechnology and Bioengineering, 2002

This work discusses the feasibility of using the electronic nose for the on-line and real-time monitoring of the production of a complex aroma profile during a bioconversion process. As a case study, the formation of the muscatel aroma during the wine–must fermentation was selected. During wine–must fermentation, aroma compounds responsible for the organoleptic character are produced in the ppm range, while simultaneously one of the main metabolic products, ethanol, is produced in much higher quantities (up to 10% wt). Because the sensors of the electronic nose array are cross-selective to different volatile compounds, it was investigated in detail how far the electronic nose was able to evaluate the aroma profile along the fermentation. This article discusses and evaluates subsequently the integration of a membrane separation process—organophilic pervaporation—for selectively enriching aroma compounds relative to ethanol, to improve sample discrimination. © 2002 John Wiley & Sons, Inc. Biotechnol Bioeng 77: 632–640, 2002; DOI 10.1002/bit.10141