Applications and advances in electronic-nose technologies

Aheto J, Zhang D, Feng F. Detection of Beef Adulterated with Pork Using a Low-Cost Electronic Nose Based on Colorimetric Sensors

The present study was aimed at developing a low-cost but rapid technique for qualitative and quantitative detection of beef adulterated with pork. An electronic nose based on colorimetric sensors was proposed. The fresh beef rib steaks and streaky pork were purchased and used from the local agricultural market in Suzhou, China. The minced beef was mixed with pork ranging at levels from 0%~100% by weight at increments of 20%. Protein, fat, and ash content were measured for validation of the differences between the pure beef and pork used in basic chemical compositions. Fisher linear discriminant analysis (Fisher LDA) and extreme learning machine (ELM) were utilized comparatively for identification of the ground pure beef, beef–pork mixtures, and pure pork. Back propagation-artificial neural network (BP-ANN) models were built for prediction of the adulteration levels. Results revealed that the ELM model built was superior to the Fisher LDA model with higher identification rates of 91.27% and 87.5% in the training and prediction sets respectively. Regarding the adulteration level prediction, the correlation coefficient and the root mean square error were 0.85 and 0.147 respectively in the prediction set of the BP-ANN model built. This suggests, from all the results, that the low-cost electronic nose based on colorimetric sensors coupled with chemometrics has a great potential in rapid detection of beef adulterated with pork.

Assessment of the Portable C-320 Electronic Nose for Discrimination of Nine Insectivorous Bat Species: Implications for Monitoring White-Nose Syndrome

The development of new C-320 electronic-nose (e-nose) methods for pre-symptomatic detection of White-Nose Syndrome (WNS) in bats has required efficacy studies of instrument capabilities to discriminate between major sources of volatile organic compounds (VOCs) derived from clinical samples. In this phase-2 study, we further tested this e-nose for capabilities to distinguish between bat species based on differences in whole-body VOC emissions. Live healthy individuals of nine bat species were temporarily captured outside of caves in Arkansas and Louisiana. VOC emissions from bats were collected using newly developed portable air collection and sampling-chamber devices in tandem. Sensor-array output responses to bat VOC emissions were compared to those of 22 pure VOC analytical standards from five chemical classes. Distinct smellprint signatures were produced from e-nose analyses of VOC metabolites derived from individual bat species. Smellprint patterns were analyzed using 2-dimensional and 3-dimensional Principal Component Analysis (PCA) to produce aroma map plots showing effective discrimination between bat species with high statistical significance. These results demonstrate potential instrument efficacy for distinguishing between species-specific, bat-derived VOC metabolite emissions as major components of clinical samples collected from bats in caves for disease detection prior to symptom development. This study provided additional information required to fully test the efficacy of a portable e-nose instrument for diagnostic applications in subsequent phase-3 testing of noninvasive, early WNS disease detection in intra-cave hibernating bats.

Odorant-Based Detection and Discrimination of Two Economic Pests in Export Apples

Detection of pest infestations in fresh produce traded internationally could offer improved prospects for reducing the movement of unwanted pests. Because immature stages of some pests can be difficult to find visually, other cues such as herbivore-induced volatiles that can potentially be detected at the early stages of infestation are worth investigating. In this study, we artificially infested postharvested apples (Malus × domestica 'Royal Gala') with two economic apple pests, the specialist codling moth (CM, Cydia pomonella Linnaeus, Lepidoptera: Tortricidae) and the generalist Queensland fruit fly (QFF, Bactrocera tryoni, Froggatt, Diptera: Tephritidae) and collected volatile organic compounds (VOCs) over time (days 0, 6, and 14-15). In both infestation experiments, we found a strong and significant interaction between time and treatment. Apples infested with the QFF emitted lower total amounts of VOCs than uninfested apples, whereas apples infested with the CM released similar total amounts of VOCs. Apples infested with CM had increases in several hexyl and butyl esters, which were particularly noticeable after 15 d. In contrast, changes in ethyl esters were characteristics of QFF infestation and could be detected from day 6. Our multilevel and multivariate statistical analysis identified specific volatile biomarkers for each species at each sampling time that can be used to design a new tool for remote detection and surveillance of these invasive pests in harvested apples. Nevertheless, other information such as the cultivar as well as the storage condition needs to be taken into consideration to increase accuracy of future odorant-based sensors for pest identification.

Odour Emissions of Municipal Waste Biogas Plants—Impact of Technological Factors, Air Temperature and Humidity

Biogas plants processing municipal waste are an important part of a circular economy (energy generation from biogas and organic fertiliser production for the treatment of selectively collected biowaste). However, the technological processes taking place may be associated with odour nuisance. The paper presents the results of pilot research conducted at six municipal waste biogas plants in Poland. It shows the relations between odour intensity and concentration and the occurring meteorological and ambient conditions (air temperature and relative humidity) and technological factors at biogas plants processing municipal waste. The impact of meteorological and ambient conditions was identified by measuring air temperature and relative humidity and observing their changes. The impact of technological factors was identified by measuring odorant concentration (volatile organic compounds and ammonia) and observing their changes between individual measurement series. At most analysed biogas plants, the influence of technological factors on odour emissions took place and was clearly noted. The elements of biogas installations characterised by the highest concentration of these odorants were indicated. Special attention should be paid to the choice of technological solutions and technical and organisational measures to reduce the impact of unfavourable atmospheric conditions on odour emissions.

Design and development of instrumentation for the measurement of sensor array responses

Indigenous instrumentation has been designed and developed for the measurement of the concentration of analytes from eight conductometric metal oxide sensors. The hardware scheme of instrumentation is based on the astable multivibrator configuration. The hardware measures the resistance output from the sensors, conditions, processes, and displays the data on the liquid crystal display. An 8051 based processor averages the data, converts them into engineering units, and sends them to remote PC through ethernet communication for post-data analysis. A graphical user interface (GUI) is developed to acquire, monitor, and display the eight channels' sensor output. GUI plots the online data and offline data as a popup window. The hardware and software of the instrument were tested with standard resistors for calibration and found that in-house developed instrumentation is able to measure with an accuracy of ±0.5% with a resolution of 500 Ω. The instrument has been tested with a semiconductor metal oxide sensor, viz., chromium niobate (CrNbO₄).

Comparison of bayberry fermented wine aroma from different cultivars by GC-MS combined with electronic nose analysis

Four bayberry cultivars (Biqi, Dongkui, Wandao, and Dingao) in eastern China were selected to produce the fermented bayberry wine. The volatile flavor compounds in different bayberry wine were compared by gas chromatography-mass spectrometry (GC-MS) and electronic nose. The results showed that 46 volatile flavor compounds were found in bayberry wine, including 19 esters, 7 alcohols, 6 acids, 2 aldehydes, 2 ketones, 3 terpenes, and 7 others compounds. The most important contribution to the aroma of bayberry wine was esters and alcohols, respectively. Differentiation of four kinds of bayberry wine was conducted analysis by E-nose. Sensory evaluation showed that Biqi bayberry wine was highly evaluated for its highest score in color, floral aroma, overall acceptability, and fruity aroma. Our results suggest that there were differences in the flavor characteristics of bayberry wine brewed from different varieties of bayberry. The results of this study will provide valuable information for bayberry wine makers to select raw materials.

Improvement of sensitivity of surface plasmon resonance imaging for the gas-phase detection of volatile organic compounds

The analysis of volatile organic compounds (VOCs) is an important issue in various domains. For this, electronic noses (eN) are very promising as novel analytical tools that are portable, inexpensive, and efficient for reliable and rapid analyses. Recently, we have demonstrated that surface plasmon resonance imaging (SPRI) is especially interesting for the development of eNs dedicated for gas-phase analysis of VOCs. To further improve the performance of the eN based on SPRI, in this study, we investigated the influence of the LED wavelength on the sensitivity of the system. For this, a complete theoretical study together with a related experimental investigation for the validation were carried out. We have shown that the wavelength of the light source has an impact on the surface sensitivity of SPRI for the detection of VOCs. Indeed, in the studied wavelength range from 530 nm to 740 nm, both bulk sensitivity and surface sensitivity increase as the wavelength increases with good coherence between theoretical and experimental results. With the optimal LED wavelength, the detection limits of our eN reach low ppb range for VOC such as 1-butanol.

The odour assessment of thyme essential oils in electrospun fibre mat with a virtual sensor array data and its relation to antibacterial activity

Aims: The ability of a single-sensor gas diagnosis device (SSGDD) as a virtual sensor array data to appraise thyme essential oils (TEO) based on its quantitatively release rate from nanofibres was aimed.Methods: To form nylon 6 fragrant electrospun nanofibre, TEO was added as a natural antibacterial substance under homogeniser to make a stable emulsion.Results: The optimised nanofibre inactivated against Escherichia Coli and Staphylococcus Aureus bacteria up to >75% at once and to > 41.9% over 2-weeks period. Moreover, large differences in sensor responses to samples with experimental variables (percent TEO and storage time) and different odour intensity exist which correctly classified by discriminant function analysis.Conclusions: Odour intensity as an accessible incubator evinces the nanofibres efficiency which correlated to the antibacterial activity. With applying SSGDD technique as a quantified subjective solution, carefully odour assessment is possible and prepared mats could be demonstrated as a face-masks' promising candidate.

Portable Low-Cost Electronic Nose Based on Surface Acoustic Wave Sensors for the Detection of BTX Vapors in Air

A portable electronic nose based on surface acoustic wave (SAW) sensors is proposed in this work to detect toxic chemicals, which have a great potential to threaten the surrounding natural environment or adversely affect the health of people. We want to emphasize that ferrite nanoparticles, decorated (Au, Pt, Pd) and undecorated, have been used as sensitive coatings for the first time in these types of sensors. Furthermore, the proposed electronic nose incorporates signal conditioning and acquisition and transmission modules. The electronic nose was tested to low concentrations of benzene, toluene, and xylene, exhibiting excellent performance in terms of sensitivity, selectivity, and response time, indicating its potential as a monitoring system that can contribute to the detection of toxic compounds.

Beverage and Food Fragrance Biotechnology, Novel Applications, Sensory and Sensor Techniques: An Overview

Flavours and fragrances are especially important for the beverage and food industries. Biosynthesis or extraction are the two main ways to obtain these important compounds that have many different chemical structures. Consequently, the search for new compounds is challenging for academic and industrial investigation. This overview aims to present the current state of art of beverage fragrance biotechnology, including recent advances in sensory and sensor methodologies and statistical techniques for data analysis. An overview of all the recent findings in beverage and food fragrance biotechnology, including those obtained from natural sources by extraction processes (natural plants as an important source of flavours) or using enzymatic precursor (hydrolytic enzymes), and those obtained by de novo synthesis (microorganisms' respiration/fermentation of simple substrates such as glucose and sucrose), are reviewed. Recent advances have been made in what concerns "beverage fragrances construction" as also in their application products. Moreover, novel sensory and sensor methodologies, primarily used for fragrances quality evaluation, have been developed, as have statistical techniques for sensory and sensors data treatments, allowing a rapid and objective analysis.

Cuprous Oxide Based Chemiresistive Electronic Nose for Discrimination of Volatile Organic Compounds

This paper reports a facile functionalization method on a metal-oxide semiconductor and a cuprous oxide (Cu₂O) based chemiresistive electronic nose for the detection of volatile organic compounds (VOCs). A library of functionalized Cu₂O nanospheres was developed through silanization using chemically diverse organosilanes. An electronic nose was fabricated with unmodified Cu₂O nanospheres and five types of functionalized Cu₂O nanospheres as the sensing elements. The electronic nose showed stable and rapid resistance responses to 25-200 ppm model VOCs, with the operating temperature of 180 °C. Single VOCs and ternary VOC mixtures could be discriminated by the electronic nose, and six types of tea leaves were also proved to be distinguishable as an illustration of the application of the electronic nose. We expected that the silanization could provide a simple approach for material diversification and the electronic nose would have further application in identification and discrimination of complex gas samples.

A Hardware-Deployable Neuromorphic Solution for Encoding and Classification of Electronic Nose Data

In several application domains, electronic nose systems employing conventional data processing approaches incur substantial power and computational costs and limitations, such as significant latency and poor accuracy for classification. Recent developments in spike-based bio-inspired approaches have delivered solutions for the highly accurate classification of multivariate sensor data with minimized computational and power requirements. Although these methods have addressed issues related to efficient data processing and classification accuracy, other areas, such as reducing the processing latency to support real-time application and deploying spike-based solutions on supported hardware, have yet to be studied in detail. Through this investigation, we proposed a spiking neural network (SNN)-based classifier, implemented in a chip-emulation-based development environment, that can be seamlessly deployed on a neuromorphic system-on-a-chip (NSoC). Under three different scenarios of increasing complexity, the SNN was determined to be able to classify real-valued sensor data with greater than 90% accuracy and with a maximum latency of 3 s on the software-based platform. Highlights of this work included the design and implementation of a novel encoder for artificial olfactory systems, implementation of unsupervised spike-timing-dependent plasticity (STDP) for learning, and a foundational study on early classification capability using the SNN-based classifier.

Application of electronic nose as a non-invasive technique for odor fingerprinting and detection of bacterial foodborne pathogens: a review

Food safety issues across the global food supply chain have become paramount in promoting public health safety and commercial success of global food industries. As food regulations and consumer expectations continue to advance around the world, notwithstanding the latest technology, detection tools, regulations and consumer education on food safety and quality, there is still an upsurge of foodborne disease outbreaks across the globe. The development of the Electronic nose as a noninvasive technique suitable for detecting volatile compounds have been applied for food safety and quality analysis. Application of E-nose for pathogen detection has been successful and superior to conventional methods. E-nose offers a method that is noninvasive, fast and requires little or no sample preparation, thus making it ideal for use as an online monitoring tool. This manuscript presents an in-depth review of the application of electronic nose (E-nose) for food safety, with emphasis on classification and detection of foodborne pathogens. We summarise recent data and publications on foodborne pathogen detection (2006-2018) and by E-nose together with their methodologies and pattern recognition tools employed. E-nose instrumentation, sensing technologies and pattern recognition models are also summarised and future trends and challenges, as well as research perspectives, are discussed.

Discrimination of Red Wines with a Gas-Sensor Array Based on a Surface-Acoustic-Wave Technique

We applied a thermal-desorption gas-chromatograph mass-spectrometer (TD-GC–MS) system to identify the marker volatile organic compounds (VOCs) in the aroma of red wine. After obtaining the marker VOC, we utilized surface acoustic waves (SAWs) to develop a highly sensitive sensing system as ‘electronic nose’ to detect these marker VOC. The SAW chips were fabricated on a LiNbO₃ substrate with a lithographic process. We coated sensing polymers on the sensing area to adsorb the marker VOC in a sample gas. The adsorption of the marker VOC altered the velocity of the SAW according to a mass-loading effect, causing a frequency decrease. This experiment was conducted with wines of three grape varieties—cabernet sauvignon, merlot and black queen. According to the results of TD-GC–MS, the King brand of red wine is likely to have unique VOC, which are 2-pentanone, dimethyl disulfide, 2-methylpropyl acetate and 2-pentanol; Blue Nun-1 probably has a special VOC such as 2,3-butanedione. We hence used a SAW sensor array to detect the aroma of red wines and to distinguish their components by their frequency shift. The results show that the use of polyvinyl butyral (PVB) as a detecting material can distinguish Blue Nun-2 from the others and the use of polyvinyl alcohol (PVA) can distinguish King from the others. We conducted random tests to prove the accuracy and the reliability of our SAW sensors.

Detection of Emerald Ash Borer Infestations in Living Green Ash by Noninvasive Electronic-Nose Analysis of Wood Volatiles

The emerald ash borer (EAB) has been the most destructive and costly nonnative insect to threaten the health of ash (Fraxinus) species in North America for at least the past 25 years. The development of methods for detecting visually-hidden EAB galleries at early stages of infestation would provide a useful tool to more effectively facilitate the planning and implementation of targeted EAB pest-suppression and management activities. We tested the efficacy of using a dual-technology electronic-nose (e-nose)/gas chromatograph device as a means for detection of EAB infestations in green ash trees in different EAB-decline classes by analysis of VOC emissions in sapwood. We found significant differences in VOC profiles for trees from the four decline classes. The VOC composition, quantities, and types of volatile metabolites present in headspace volatiles varied considerably across sample types, and resulted in distinct e-nose smellprint patterns that were characteristic of each unique chemical composition. In addition, specific VOC metabolites were identified as potential healthy and EAB-infestation biomarkers, indicative of the health states of individual trees. Few significant differences in major bark phenolic compounds were found between ash decline classes using LC-MS. The e-nose was effective in discriminating between uninfested and EAB-infested trees based on sapwood VOC emissions.

Tracing food packaging contamination: an electronic nose applied to leftover food

The use of former food products (FFPs) as alternative feed ingredients in farm animal diets has several benefits. In fact, FFPs are a way of converting losses from the food industry into ingredients for the feed industry. FFPs are produced from packaged food and in general, they are recognised as safe. Packaging materials are not accepted as a feed ingredient according to Regulation (EC) No 767/2009, which imposes a rigorous evaluation of possible residues. A sensitive and objective detection method is therefore essential for an effective risk evaluation. Six FFP samples were subjected to electronic nose analysis. Each sample was assessed under three conditions: as-received, cleaned and experimentally-spiked. Packaging remnants were also quantified using a stereomicroscope. Data were analysed via principal component analysis using SPSS software. Although the stereomicroscopy analysis showed a low content of packaging remnants in as-received samples, the electronic nose was able to differentiate between cleaned, as-received and spiked samples. However, this method was not effective when different FFPs were analysed together. In the view of the limitations of this method, it can be concluded that the electronic nose can be considered an objective and sensitive method for the detection of packaging remnants in FFPs composed of the same matrix.

Determination of Odor Intensity of Binary Gas Mixtures Using Perceptual Models and an Electronic Nose Combined with Fuzzy Logic

Measurement and monitoring of air quality in terms of odor nuisance is an important problem. From a practical point of view, it would be most valuable to directly link the odor intensity with the results of analytical air monitoring. Such a solution is offered by electronic noses, which thanks to the possibility of holistic analysis of the gas sample, allow estimation of the odor intensity of the gas mixture. The biggest problem is the occurrence of odor interactions between the mixture components. For this reason, methods that can take into account the interaction between components of the mixture are used to analyze data from the e-nose. In the presented study, the fuzzy logic algorithm was proposed for determination of odor intensity of binary mixtures of eight odorants: n-Hexane, cyclohexane, toluene, o-xylene, trimethylamine, triethylamine, α-pinene, and β-pinene. The proposed algorithm was compared with four theoretical perceptual models: Euclidean additivity, vectorial additivity, U model, and UPL model.

New developments on ultrasound-assisted processing and flavor detection of spices: A review

Spices are widely used to add unique flavors to food; such uniqueness may, however, suffer significant loss during processing, which is in many cases needed to preserve or transform spices into food ingredients. Here, the effects of ultrasound-assisted drying, extraction and microencapsulation on flavor of spices along with selected progresses made on ultrasonic detection of the flavor are reviewed. Flavors of some spices, e.g., laurel, onion and peppermint, dried with the aid of ultrasound are noted to be better than those of shade-dried, infrared, microwave and hot-air dried products. Ultrasound-assisted extraction can be effectively used to extract essential oils or oleoresins from spices. Compared with selected extraction methods, the variety of flavor substances obtained via ultrasound-assisted extraction is richer and their concentrations are also higher, making the flavors of the extracts stronger. Ultrasound-assisted microencapsulation has noted to increase the compound embedding and loading ratios, resulting in better maintenance of flavor over a longer period of time. Ultrasound has finally proved to be an efficient, green, economical and sensitive flavor detection technology for spices.

Intelligent Selection of Metal-Organic Framework Arrays for Methane Sensing via Genetic Algorithms

Gas sensor arrays, also called electronic noses, use many chemically diverse materials to adsorb and subsequently identify gas species in complex mixture environments. Ideally these materials should have maximally complementary adsorption profiles to achieve the best sensing performance, but in practice they are selected by trial-and-error. Thus current electronic noses do not achieve optimal detection. In this work, we employ metal-organic frameworks (MOFs) as sensing materials and leverage a genetic algorithm to identify optimal combinations of them for detecting methane leaks in air. We build on our previously reported computational design methodology, which ranked MOF arrays by their Kullback-Liebler divergence (KLD) values for probabilistically describing the concentrations of each gas species in an unknown mixture. We ran the genetic algorithm to find optimal MOF arrays of various sizes when selecting from a library of 50 different MOF materials. The genetic algorithm was able to accurately predict the best arrays of any desired size when compared to brute-force screening. Thus, this search optimization can be integrated into the efficient design of MOF-based electronic noses.

Sensors for detecting pulmonary diseases from exhaled breath

This review presents and discusses a new frontier for fast, risk-free and potentially inexpensive diagnostics of respiratory diseases by detecting volatile organic compounds (VOCs) present in exhaled breath. One part of the review is a didactic presentation of the overlaying concept and the chemistry of exhaled breath. The other part discusses diverse sensors that have been developed and used for the detection of respiratory diseases (e.g. chronic obstructive pulmonary disease, asthma, lung cancer, pulmonary arterial hypertension, tuberculosis, cystic fibrosis, obstructive sleep apnoea syndrome and pneumoconiosis) by analysis of VOCs in exhaled breath. The strengths and pitfalls are discussed and criticised, particularly in the perspective in disseminating information regarding these advances. Ideas regarding the improvement of sensors, sensor arrays, sensing devices and the further planning of workflow are also discussed.

Detection of volatile organic compounds from exhaled breath by nanomaterial-based sensors is a new diagnostics frontier in the screening of pulmonary diseases.http://bit.ly/2JoBKXn

Evolution of Electronic Noses from Research Objects to Engineered Environmental Odour Monitoring Systems: A Review of Standardization Approaches

Since electronic noses are used more and more for air quality monitoring purposes, and in some countries are starting to have a legal value, there is a need for standardization and programs for the quality verification of instruments. Such quality programs have the aim to guarantee the main characteristics of the instrument for both the final user and local authorities, let the user establish a suitable maintenance procedure and give information on measurement uncertainty. One critical aspect when dealing with electronic noses for environmental odour monitoring is that environmental odours are complex mixtures that are not repeatable nor reproducible, giving that they are not suitable for quality verifications. This paper aims to review and discuss the different approaches that can be adopted in order to perform quality checks on electronic noses (e-noses) used for environmental odour monitoring, thereby referring to existing technical standards, such as the Dutch NTA 9055:2012, the new German VDI 3518-3:2018, and the Italian UNI 1605848 project, which directly refer to electronic noses. Moreover, also the European technical standards that are prescriptive for automatic measuring systems (AMSs) are taken into consideration (i.e., EN 14181:2014 and EN 15267:2009), and their possible applicability to electronic noses is investigated. Finally, the pros and cons of the different approaches are presented and discussed in the conclusions section.

A Wearable IoT Aldehyde Sensor for Pediatric Asthma Research and Management

A cloud-based wearable IoT aldehyde sensor system for asthma research and management.

Application of Electronic Nose for Evaluation of Wastewater Treatment Process Effects at Full-Scale WWTP

This paper presents the results of studies aiming at the assessment and classification of wastewater using an electronic nose. During the experiment, an attempt was made to classify the medium based on an analysis of signals from a gas sensor array, the intensity of which depended on the levels of volatile compounds in the headspace gas mixture above the wastewater table. The research involved samples collected from the mechanical and biological treatment devices of a full-scale wastewater treatment plant (WWTP), as well as wastewater analysis. The measurements were carried out with a metal-oxide-semiconductor (MOS) gas sensor array, when coupled with a computing unit (e.g., a computer with suitable software for the analysis of signals and their interpretation), it formed an e-nose—that is, an imitation of the mammalian olfactory sense. While conducting the research it was observed that the intensity of signals sent by sensors changed with drops in the level of wastewater pollution; thus, the samples could be classified in terms of their similarity and the analyzed gas-fingerprint could be related to the pollution level expressed by physical and biochemical indicators. Principal component analysis was employed for dimensionality reduction, and cluster analysis for grouping observation purposes. Supervised learning techniques confirmed that the obtained data were applicable for the classification of wastewater at different stages of the purification process.

Application of electronic nose for determination of Slovak cheese authentication based on aroma profile

Electronic nose with sensors is used in many industries and for various applications such as quality control, process monitoring, shelf life evaluation, origin or authenticity assessment. The aim of this work was to investigate the electronic nose with FID detectors applicability for characterization of steamed cheese and for the assessment of steamed cheese quality decay during storage. Samples of smoked and unsmoked steamed cheese varieties from 5 Slovak enterprises concerning different regions of Slovakia were analysed. Data from aroma profiles were processed by statistical technique PCA. Compounds like acetaldehyde, 1-propanal, propanoic acid, ethyl hexanoate, furfural, butan-2-one, isovaleric acid, 1-hexanol or α-pinene were determined as significant flavours in fresh steamed cheese samples. In the current study, no significant differences in aroma profiles between fresh and stored cheese samples were confirmed. Thus, differences in main odour substances composition of steamed cheese varieties, obtained from various producers in several geographic regions of Slovakia, were minor.

Breath Analysis Using eNose and Ion Mobility Technology to Diagnose Inflammatory Bowel Disease-A Pilot Study

Early diagnosis of inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), remains a clinical challenge with current tests being invasive and costly. The analysis of volatile organic compounds (VOCs) in exhaled breath and biomarkers in stool (faecal calprotectin (FCP)) show increasing potential as non-invasive diagnostic tools. The aim of this pilot study is to evaluate the efficacy of breath analysis and determine if FCP can be used as an additional non-invasive parameter to supplement breath results, for the diagnosis of IBD. Thirty-nine subjects were recruited (14 CD, 16 UC, 9 controls). Breath samples were analysed using an in-house built electronic nose (Wolf eNose) and commercial gas chromatograph-ion mobility spectrometer (G.A.S. BreathSpec GC-IMS). Both technologies could consistently separate IBD and controls [AUC ± 95%, sensitivity, specificity], eNose: [0.81, 0.67, 0.89]; GC-IMS: [0.93, 0.87, 0.89]. Furthermore, we could separate CD from UC, eNose: [0.88, 0.71, 0.88]; GC-IMS: [0.71, 0.86, 0.62]. Including FCP did not improve distinction between CD vs UC; eNose: [0.74, 1.00, 0.56], but rather, improved separation of CD vs controls and UC vs controls; eNose: [0.77, 0.55, 1.00] and [0.72, 0.89, 0.67] without FCP, [0.81, 0.73, 0.78] and [0.90, 1.00, 0.78] with FCP, respectively. These results confirm the utility of breath analysis to distinguish between IBD-related diagnostic groups. FCP does not add significant diagnostic value to breath analysis within this study.

Electronic Noses in Medical Diagnostics

BACKGROUND

Electronic nose technology is being developed in order to analyse complex mixtures of volatiles in a way parallel to biologic olfaction. When applied in the field of medicine, the use of such devices should enable the identification and discrimination between different diseases. In this review, a comprehensive summary of research in medical diagnostics using electronic noses is presented. A special attention has been paid to the application of these devices and sensor technologies, in response to current trends in medicine.

METHODS

Peer-reviewed research literature pertaining to the subject matter was identified based on a search of bibliographic databases. The quality and relevance of retrieved papers was assessed using standard tools. Their content was critically reviewed and certain information contained therein was compiled in tabularized form.

RESULTS

The majority of reviewed studies show promising results, often surpassing the accuracy and sensitivity of established diagnostic methods. However, only a relatively small number of devices have been field tested. The methods used for sample collection and data processing in various studies were listed in a table, together with electronic nose models used in these investigations.

CONCLUSION

Despite the fact that devices equipped with arrays of chemical sensors are not routinely used in everyday medical practice, their prospective use would solve some established issues in medical diagnostics, as well as lead to developments in prophylactics by facilitating a widespread use of non-invasive screening tests.

Rapid Evaluation Methods for Quality of Trout (Oncorhynchus mykiss) Fresh Fillet Preserved in an Active Edible Coating

In this study different methods were used to evaluate the effectiveness of a carrageenan coating and carrageenan coating incorporating lemon essential oil (ELO) in preserving the physicochemical and olfactory characteristics of trout fillets stored at 4 °C up to 12 days. The fillet morphological structure was analyzed by histological and immunological methods; lipid peroxidation was performed with the peroxide and thiobarbituric acid reactive substances (TBARS) tests. At the same time, two less time-consuming methods, such as Attenuated Total Reflectance-Fourier Transformed Infrared (ATR-FTIR) spectroscopy and the electronic nose, were used. Uncoated trout fillets (UTF) showed a less compact tissue structure than carrageenan-coated threads (CTF) and coated fillets of carrageenan (active) ELO (ACTF), probably due to the degradation of collagen, as indicated by optical microscopy and ATR-FTIR. UTF showed greater lipid oxidation compared to CTF and ACTF, as indicated by the peroxide and TBARS tests and ATR-FTIR spectroscopy. The carrageenan coating containing ELO preserved the olfactory characteristics of the trout fillets better than the carrageenan coating alone, as indicated by the electronic nose analysis. This study confirms that both carrageenan and ELO containing carrageenan coatings slow down the decay of the physicochemical and olfactory characteristics of fresh trout fillets stored at 4 °C, although the latter is more effective.

Nanostructured P3HT as a Promising SensingElement for Real-Time, Dynamic Detection ofGaseous Acetone

The dynamic response of gas sensors based on poly(3-hexylthiophene) (P3HT) nanofibers (NFs) to gaseous acetone was assessed using a setup based on flow-injection analysis, aimed at emulating actual breath exhalation. The setup was validated by using a commercially available sensor. The P3HT NFs sensors tested in dynamic flow conditions showed satisfactory reproducibility down to about 3.5 ppm acetone concentration, a linear response over a clinically relevant concentration range (3.5-35 ppm), excellent baseline recovery and reversibility upon repeated exposures to the analyte, short pulse rise and fall times (less than 1 s and about 2 s, respectively) and low power consumption (few nW), with no relevant response to water. Comparable responses’ decay times under either nitrogen or dry air suggest that the mechanisms at work is mainly attributable to specific analyte-semiconducting polymer interactions. These results open the way to the use of P3HT NFs-based sensing elements for the realization of portable, real-time electronic noses for on-the-fly exhaled breath analysis.

Discrimination of Different Species of Dendrobium with an Electronic Nose Using Aggregated Conformal Predictor

A method using electronic nose to discriminate 10 different species of dendrobium, which is a kind of precious herb with medicinal application, was developed with high efficiency and low cost. A framework named aggregated conformal prediction was applied to make predictions with accuracy and reliability for E-nose detection. This method achieved a classification accuracy close to 80% with an average improvement of 6.2% when compared with the results obtained by using traditional inductive conformal prediction. It also provided reliability assessment to show more comprehensive information for each prediction. Meanwhile, two main indicators of conformal predictor, validity and efficiency, were also compared and discussed in this work. The result shows that the approach integrating electronic nose with aggregated conformal prediction to classify the species of dendrobium with reliability and validity is promising.

[Medical diagnosis by breath analysis: odor sensors]

An odor sensor is a device for detecting target odors within a mixture, used in many fields including medical diagnosis. Electronic noses are networks of olfactory sensors, consisting of a surface whose properties are modified in the presence of odors, coupled with a measurement system. Their olfactory signature is analyzed in comparison with databases. Such portable devices can monitor body odors, e.g. in the breath, so as to reliably diagnose various pathologies at an early stage and non-invasively. It is tempting to use the naturally optimized molecular recognition of odorants and intrinsic sensitivity of the animal olfactory system to detect and discriminate minute amounts of odorants. New bioelectronic hybrid devices or "bioelectronic noses" can be designed by replacing the artificial sensory elements of e-noses by proteins naturally binding odorants, particularly olfactory receptors. As in the animal olfactory system, the detection and discrimination of odorants require a network of olfactory receptors. Prototypes of such miniaturized bioelectronic noses yield promising results.

Multi-layer graphene as a selective detector for future lung cancer biosensing platforms

Highly selective, fast detection of specific lung-cancer biomarkers (CMs) in exhaled human breath is vital to the development of enhanced sensing devices. Today, e-nose is a promising approach for the diagnosis of lung cancer. Nevertheless, considerable challenges to early-stage disease diagnostics still remain: e.g. decrease in sensor sensitivities in the presence of water vapor, sensor drift leading to the inability to calibrate exactly, relatively short sensor lifetimes, and difficulty discriminating between multiple diseases. However, there is a wide scope for breath diagnostics techniques, and all advanced electrodes applicable to e-nose devices will benefit them. Here, we present the promising sensing capabilities of bare multi-layer graphene (MLG) as a proof of concept for advanced e-nose devices and demonstrate its utility for biomolecule discrimination of the most common lung CMs (ethanol, isopropanol, and acetone). We report on a comparative study involving exposure of the three CM solutions on flat MLG (f-MLG) and patterned MLG (p-MLG) electrodes, where the electrical conductivity of p-MLG is significantly increased while applying acetone. Based on sensitivity tests, we demonstrate the ability to monitor the electrical response of graphene electrodes employing graphene of various wettabilities. Specifically, the f-MLG electrode displays almost 2 times higher sheet resistance (30 Ω sq-1) compared to the hydrophilic p-MLG (12 Ω sq-1). We show significant sensitivity to selected specific molecules of pristine f-MLG and p-MLG while applying CM solutions with a 1.4 × 105 ppm concentration. Finally, we show the selectivity of f-MLG and p-MLG-based sensors when exposed to 2.0 × 105 ppm solutions containing different CM combinations. Both sensors were selective in particular to acetone, since the presence of acetone leads to a sheet resistance increase. We demonstrate that an advanced e-nose approach integrated with MLG electrodes has significant potential as a design concept for utilization of molecular detection at variable concentrations such as in early-stage disease diagnosis. This early-stage approach will provide convenient and reusable complex monitoring of CMs compared to typical contact sensors which require target analysis and are limited by disposable measuring. Moreover, further integration of the Internet of Things will introduce advanced e-nose devices as a biotechnological innovation for disease resilience with the potential for commercialization.

Sick Building Syndrome and Other Building-Related Illnesses

Sick building syndrome (SBS) and building-related illnesses are omnipresent in modern high-rise buildings. The SBS is a complex spectrum of ill health symptoms, such as mucous membrane irritation, asthma, neurotoxic effects, gastrointestinal disturbance, skin dryness, sensitivity to odours that may appear among occupants in office and public buildings, schools and hospitals. Studies on large office buildings from USA, UK, Sweden, Finland, Japan, Germany, Canada, China, India, Netherlands, Malaysia, Taiwan, and Thailand, substantiate the occurrence of SBS phenomena. The accumulated effects of a multitude of factors, such as the indoor environmental quality, building characteristics, building dampness, and activities of occupants attribute to SBS. A building occupant manifests at least one symptom of SBS, the onset of two or more symptoms at least twice, and rapid resolution of symptoms following moving away from the workstation or building may be defined as having SBS. Based on the peer-reviewed documentation, this chapter elaborates the magnitude of building-related health consequences due to measurable environmental causations, and the size of the population affected. The mechanisms and causative factors of SBS and illnesses include, for example, the oxidative stress resulting from indoor pollutants, VOCs, office work-related stressors, humidification, odours associated with moisture and bioaerosol exposure. Related regulatory standards and strategies for management of SBS and other illnesses are elaborated.

Volatolomics: A broad area of experimentation

Chemical analysis (detection and monitoring) of compounds associated with the metabolic activities of an organism is at the cutting edge of science. Volatile metabolomics (volatolomics) are applied in a broad range of applications including: biomedical research (e.g. disease diagnostic tools, personalized healthcare and nutrition, etc.), toxicological analysis (e.g. exposure tool to environmental pollutants, toxic and hazardous chemical environments, industrial accidents, etc.), molecular communications, forensics, safety and security (e.g. search and rescue operations). In the present review paper, an overview of recent advances and applications of volatolomics will be given. The main focus will be on volatile organic compounds (VOCs) originating from biological secretions of various organisms (e.g. microorganisms, insects, plants, humans) and resulting fusion of chemical information. Bench-top and portable or field-deployable technologies-systems will also be presented and discussed.

Organizational and Technological Aspects of a Platform for Collective Food Awareness

Can Internet-of-food technologies foster collective food awareness within a food consumer community? The paper contributes to answer this question in a fourfold aspect. Firstly, we model a cooperative process for generating and sharing reliable food information that is derived from food instrumental measurements performed by consumers via smart food things. Secondly, we outline the functional architecture of a platform capable to support such a process and to let a consumer community share reliable food information. Thirdly, we identify main entities and their attributes necessary to model the contextualized interaction between a consumer and the platform. Lastly, we review articles reviewing technologies capable of acquiring and quantifying food characteristics for food performances assessment. The purpose is to give an insight into current research directions on technologies employable in a platform for collective food awareness.

Effect of the catalyst on the physical and aroma attributes of interesterified milk fat-vegetable oil blends

Abstract The present study aimed to verify the influence of the catalyst (sodium methoxide and the lipase from Rhizopus oryzae immobilized on a hybrid support - silica-polyvinyl alcohol) on the physical and aroma attributes of the products obtained from the interesterification of milk fat with vegetable oils (soybean and canola). The evaluation was carried out using an electronic nose (e-nose) and a texture analyzer. Interesterification reactions were carried out with binary blends (65% of milk fat and 35% of vegetable oil) using 0.75% sodium methoxide (60 °C for 60 min) and immobilized Rhizopus oryzae lipase at a fixed proportion of 500 units of activity per gram of blend (45 °C for 6 h). The results showed that the e-nose sensors discriminated satisfactorily the aromas of both raw materials and products and were able to distinguish them according to the catalyst used. In relation to the texture, both catalysts generated products with appropriate consistencies with satisfactory plasticity and spreadability at refrigerator temperatures.

Detection of lung cancer with electronic nose and logistic regression analysis

Lung cancer is a very common malignancy with a low five-year survival rate. Artificial olfactory sensor (electronic nose) is a tool that recently has been studied as a probable optimal screening tool for early detection of lung cancer, but still no statistical method has been put forward as the preferable one. The aim of the study was to explore the use of logistic regression analysis (LRA) to analyse patients' exhaled breath samples with electronic nose in order to differentiate lung cancer patients (regardless of the stage of the cancer) from patients with other lung diseases and healthy individuals. Patients with histologically or cytologically verified, untreated lung cancer, patients with other lung diseases such as benign lung tumors, chronic obstructive pulmonary disease, asthma, pneumonia, etc, and healthy volunteers were enrolled in the study, in total 252 cancer patients and 223 patients without cancer. Breath sample collection and analysis were performed with Cyranose 320 sensor device and data further analysed using LRA. The LRA correctly differentiated lung cancer patients from no-cancer patients. The overall sensitivity in detecting patients having cancer was 95.8% for smokers and 96.2% for non-smokers and the overall specificity was 90.6% for non-smokers and 92.3% for smokers. Exhaled breath analysis by electronic nose using LRA is able to discriminate lung cancer patients from patients with other lung diseases and from healthy individuals.

Mango Fruit Yield and Critical Quality Parameters Respond to Foliar and Soil Applications of Zinc and Boron

Mango (Mangifera indica L.), the sixth most important fruit crop worldwide, is likely at risk under a climate change scenario of accelerated soil organic matter mineralization and constrained plant nutrient supplies such as zinc (Zn) and boron (B). We identified the optimum nutrient formulation and application method to possibly rectify nutrient deficits in mango plants grown in one of the warmest and driest regions—Multan, Pakistan. We evaluated the yield and physiological (quality) responses of 20-year-old mango trees to seven treatments of foliar and soil applications of Zn and B. Combined soil application of B and Zn resulted in optimum increases in leaf mineral B and Zn and fruit-set, retention, yield, pulp recovery and total soluble solids at ripening (p = 0.021), while reducing titratable acidity and early fruit shedding (p = 0.034). Additionally, this treatment improved fruit quality (taste, flavour, texture, aroma, acceptability; p ≤ 0.05). Yield was found to be correlated with retention percentage (P ≤ 0.001; R² = 0.91), which was in turn related to fruit-set number panicle⁻¹ (P = 0.039; R² = 0.61). Therefore, we suggest that combined soil application of B and Zn mitigates leaf mineral deficiencies and improves the yield and quality of mango more efficiently than other individual or combined foliar or soil treatments used in this study.

Ultrasensitive, Low-Power Oxide Transistor-Based Mechanotransducer with Microstructured, Deformable Ionic Dielectrics

The development of a highly sensitive artificial mechanotransducer that mimics the tactile sensing features of human skin has been a big challenge in electronic skin research. Here, we demonstrate an ultrasensitive, low-power oxide transistor-based mechanotransducer modulated by microstructured, deformable ionic dielectrics, which is consistently sensitive to a wide range of pressures from 1 to 50 kPa. To this end, we designed a viscoporoelastic and ionic thermoplastic polyurethane (i-TPU) with micropyramidal feature as a pressure-sensitive gate dielectric for the indium-gallium-zinc-oxide (IGZO) transistor-based mechanotransducer, which leads to an unprecedented sensitivity of 43.6 kPa^-1, which is 23 times higher than that of a capacitive mechanotransducer. This is because the pressure-induced ion accumulation at the interface of the i-TPU dielectric and IGZO semiconductor effectively modulates the conducting channel, which contributed to the enhanced current level under pressure. We believe that the ionic transistor-type mechanotransducer suggested by us will be an effective way to perceive external tactile stimuli over a wide pressure range even under low power (<4 V), which might be one of the candidates to directly emulate the tactile sensing capability of human skin.

Evolution of clinical and environmental health applications of exhaled breath research: Review of methods and instrumentation for gas-phase, condensate, and aerosols

Human breath, along with urine and blood, has long been one of the three major biological media for assessing human health and environmental exposure. In fact, the detection of odor on human breath, as described by Hippocrates in 400 BC, is considered the first analytical health assessment tool. Although less common in comparison to contemporary bio-fluids analyses, breath has become an attractive diagnostic medium as sampling is non-invasive, unlimited in timing and volume, and does not require clinical personnel. Exhaled breath, exhaled breath condensate (EBC), and exhaled breath aerosol (EBA) are different types of breath matrices used to assess human health and disease state. Over the past 20 years, breath research has made many advances in assessing health state, overcoming many of its initial challenges related to sampling and analysis. The wide variety of sampling techniques and collection devices that have been developed for these media are discussed herein. The different types of sensors and mass spectrometry instruments currently available for breath analysis are evaluated as well as emerging breath research topics, such as cytokines, security and airport surveillance, cellular respiration, and canine olfaction.