Applications and Advances in Electronic-Nose Technologies

Electronic-nose devices have received considerable attention in the field of sensor technology during the past twenty years, largely due to the discovery of numerous applications derived from research in diverse fields of applied sciences. Recent applications of electronic nose technologies have come through advances in sensor design, material improvements, software innovations and progress in microcircuitry design and systems integration. The invention of many new e-nose sensor types and arrays, based on different detection principles and mechanisms, is closely correlated with the expansion of new applications. Electronic noses have provided a plethora of benefits to a variety of commercial industries, including the agricultural, biomedical, cosmetics, environmental, food, manufacturing, military, pharmaceutical, regulatory, and various scientific research fields. Advances have improved product attributes, uniformity, and consistency as a result of increases in quality control capabilities afforded by electronic-nose monitoring of all phases of industrial manufacturing processes. This paper is a review of the major electronic-nose technologies, developed since this specialized field was born and became prominent in the mid 1980s, and a summarization of some of the more important and useful applications that have been of greatest benefit to man

Odour Detection Methods: Olfactometry and Chemical Sensors

The complexity of the odours issue arises from the sensory nature of smell. From the evolutionary point of view olfaction is one of the oldest senses, allowing for seeking food, recognizing danger or communication: human olfaction is a protective sense as it allows the detection of potential illnesses or infections by taking into account the odour pleasantness/unpleasantness. Odours are mixtures of light and small molecules that, coming in contact with various human sensory systems, also at very low concentrations in the inhaled air, are able to stimulate an anatomical response: the experienced perception is the odour. Odour assessment is a key point in some industrial production processes (i.e., food, beverages, etc.) and it is acquiring steady importance in unusual technological fields (i.e., indoor air quality); this issue mainly concerns the environmental impact of various industrial activities (i.e., tanneries, refineries, slaughterhouses, distilleries, civil and industrial wastewater treatment plants, landfills and composting plants) as sources of olfactory nuisances, the top air pollution complaint. Although the human olfactory system is still regarded as the most important and effective “analytical instrument” for odour evaluation, the demand for more objective analytical methods, along with the discovery of materials with chemo-electronic properties, has boosted the development of sensor-based machine olfaction potentially imitating the biological system. This review examines the state of the art of both human and instrumental sensing currently used for the detection of odours. The olfactometric techniques employing a panel of trained experts are discussed and the strong and weak points of odour assessment through human detection are highlighted. The main features and the working principles of modern electronic noses (E-Noses) are then described, focusing on their better performances for environmental analysis. Odour emission monitoring carried out through both the techniques is finally reviewed in order to show the complementary responses of human and instrumental sensing

The teleost taar family of olfactory receptors: From rapidly evolving receptor genes to ligand-induced behavior

Trace amine-associated receptors (TAARs) have recently been shown to function as olfactory receptors in mammals. In this current study, the taar gene family has been delineated in jawless, cartilaginous, and bony fish (zero, 2, and >100 genes, respectively). I conclude that the taar genes are evolutionary much younger than the related OR and ORA/V1R olfactory receptor families, which are present already in lamprey, a jawless vertebrate. The 2 cartilaginous fish genes appear to be ancestral for 2 taar classes, each with mammalian and bony fish (teleost) representatives. Unexpectedly, a whole new clade, class III, of taar genes originated even later, within the teleost lineage. Taar genes from all 3 classes are expressed in subsets of zebrafish olfactory receptor neurons, supporting their function as olfactory receptors. The highly conserved TAAR1 (shark,mammalian, and teleost orthologs) is not expressed in the olfactory epithelium and may constitute the sole remnant of a primordial, non olfactory function of this family. Class III comprises three-fourths of all teleost taar genes and is characterized by the complete loss of the aminergic ligand-binding motif, stringently conserved in all 25 genes of the other 2 classes. Two independent intron gains in class III taar genes represent extraordinary evolutionary dynamics, considering the virtual absence of intron gains during vertebrate evolution. The dN/dS analysis suggests both minimal global negative selection and an unparalleled degree of local positive selection as another hallmark of class III genes. The accelerated evolution of class III teleost taar genes conceivably might mark the birth of another olfactory receptor gene family. Ligands have only been identified for a handful of olfactory receptors of mammals and insects, while only a single teleost olfactory receptor have been deorphanized, a member of the OlfC family, OlfCa. Zebrafish TAAR olfactory receptors of classI are good candidates for having amines as possible ligands, due to the presence of the aminergic ligand binding motifs. This study identifies diamines as specific ligands for a taar receptor, DrTAAR13c. These diamines activate a sparse subset of olfactory sensory neurons, as indicated by c-Fos expression in olfactory epithelium. Diamines, putrescine and cadaverine, are foul-smelling aliphatic polycations that occur naturally as a result of bacterial decarboxylation of amino acids lysine and arginine, respectively. The 15 concentration of diamines in their environment is correlated to the degree of putrefication. In the behavioral assay, zebrafish exposed to even low concentration of diamines show dramatic, quantifiable aversion, while it shows attraction towards food stimulus and no response for water. The ligand spectrum of TAAR13c closely parallels the behavioral effectiveness of these diamines. This data is consistent with the existence of a defined neuronal microcircuit that elicits a characteristic behavior upon activation of a single olfactory receptor, a novum in the vertebrate sense of smell

The electronic nose coupled with chemometric tools for discriminating the quality of black tea samples in situ

An electronic nose (E-nose), comprising eight metal oxide semiconductor (MOS) gas sensors, was used in situ for real-time classification of black tea according to its quality level. Principal component analysis (PCA) coupled with signal preprocessing techniques (i.e., time set value preprocessing, F1; area under curve preprocessing, F2; and maximum value preprocessing, F3), allowed grouping the samples from seven brands according to the quality level. The E-nose performance was further checked using multivariate supervised statistical methods, namely, the linear and quadratic discriminant analysis, support vector machine together with linear or radial kernels (SVM-linear and SVM-radial, respectively). For this purpose, the experimental dataset was split into two subsets, one used for model training and internal validation using a repeated K-fold cross-validation procedure (containing the samples collected during the first three days of tea production); and the other, for external validation purpose (i.e., test dataset, containing the samples collected during the 4th and 5th production days). The results pointed out that the E-nose-SVM-linear model together with the F3 signal preprocessing method was the most accurate, allowing 100% of correct predictive classifications (external-validation data subset) of the samples according to their quality levels. So, the E-nose-chemometric approach could be foreseen has a practical and feasible classification tool for assessing the black tea quality level, even when applied in-situ, at the harsh industrial environment, requiring a minimum and simple sample preparation. The proposed approach is a cost-effective and fast, green procedure that could be implemented in the near future by the tea industry.Ministry of Research, Technology and Higher Education of the Republic of Indonesia through a research scheme of PTUPT 2019 (Contract No. 2688/UN1.DITLIT/DIT-LIT/LT/2019). This work was also financially supported by strategic project UID/EQU/50020/2019—Associate Laboratory LSRE-LCM, strategic project PEst-OE/AGR/UI0690/2014–CIMO, strategic funding UID/BIO/04469/2019-CEB and BioTecNorte operation (NORTE-01-0145-FEDER-000004), all funded by European Regional Development Fund (ERDF) through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI)—and by national funds through FCT—Fundação para a Ciência e a Tecnologia I.P.info:eu-repo/semantics/publishedVersio

Mapping odorant sensitivities reveals a sparse but structured representation of olfactory chemical space by sensory input to the mouse olfactory bulb

© 2022, Burton et al. This article is distributed under the terms of the Creative Commons Attribution License. https://creativecommons.org/licenses/by/4.0/In olfactory systems, convergence of sensory neurons onto glomeruli generates a map of odorant receptor identity. How glomerular maps relate to sensory space remains unclear. We sought to better characterize this relationship in the mouse olfactory system by defining glomeruli in terms of the odorants to which they are most sensitive. Using high-throughput odorant delivery and ultrasensitive imaging of sensory inputs, we imaged responses to 185 odorants presented at concentrations determined to activate only one or a few glomeruli across the dorsal olfactory bulb. The resulting datasets defined the tuning properties of glomeruli - and, by inference, their cognate odorant receptors - in a low-concentration regime, and yielded consensus maps of glomerular sensitivity across a wide range of chemical space. Glomeruli were extremely narrowly tuned, with ~25% responding to only one odorant, and extremely sensitive, responding to their effective odorants at sub-picomolar to nanomolar concentrations. Such narrow tuning in this concentration regime allowed for reliable functional identification of many glomeruli based on a single diagnostic odorant. At the same time, the response spectra of glomeruli responding to multiple odorants was best predicted by straightforward odorant structural features, and glomeruli sensitive to distinct odorants with common structural features were spatially clustered. These results define an underlying structure to the primary representation of sensory space by the mouse olfactory system.Peer reviewe

Instrumental and chemometric methodologies to assess sensory quality of Mediterranean food

L'oli d'oliva, el vi o els fruits secs són productes típics de la regió Mediterrània que ofereixen un valor afegit gràcies als seus beneficis per a la salut i excel·lents característiques sensorials. Per aquest motiu és necessari un control de la qualitat i autenticitat d'aquests productes, que són altament susceptibles a fraus i adulteracions. Un aspecte important és l'avaluació de la qualitat sensorial, que descriu paràmetres percebuts pels sentits (gust, visió, olor i tacte) mitjançant panells validats i entrenats d'experts. Aquests panells tendeixen a ser subjectius i requereixen llargs temps d'anàlisi i alts costos. Com a conseqüència hi ha hagut un increment en el desenvolupament de tècniques d'anàlisi capaces de simular les respostes obtingudes amb el panell de tast humà. L'anomenat 'panell electrònic' ofereix respostes objectives mitjançant l'ús de tècniques multivariants que permeten establir correlacions entre els descriptors definits pels humans i els senyals obtingudes instrumentalment. Aquesta tesi pretén oferir tècniques instrumentals alternatives, ràpides i senzilles per determinar la qualitat sensorial d'aliments com l'oli d'oliva, el vi o les ametlles. Els estudis duts a terme inclouen el tractament de les respostes sensorials obtingudes mitjançant metodologies de referència (principalment panells de tast humans), l'optimització dels procediments analítics per treballar amb tècniques instrumentals i el desenvolupament d'eines quimiomètriques adequades per construir els models multivariants. També s'han desenvolupat estratègies de fusió de dades per combinar les diferents dades instrumentals que simulen els sentits humans (olor, gust i visió).El aceite de oliva, el vino o los frutos secos son productos típicos de la región Mediterránea que ofrecen un valor añadido gracias a sus beneficios para la salud y excelentes características sensoriales. Por este motivo es necesario un control de la calidad y autenticidad de estos productos, que son altamente susceptibles a fraudes y adulteraciones. Un aspecto importante es la evaluación de la calidad sensorial, que describe parámetros percibidos por los sentidos (gusto, visión, olor y tacto) mediante paneles validados y entrenados de expertos. Estos paneles tienden a ser subjetivos, requieren largos tiempos de análisis y altos costes. Como consecuencia ha habido un incremento en el desarrollo de técnicas de análisis capaces de simular las respuestas obtenidas con el panel de cata humano. El llamado 'panel electrónico' ofrece respuestas objetivas mediante el uso de técnicas multivariantes que permiten establecer correlaciones entre los descriptores definidos por los humanos y las señales obtenidas instrumentalmente. Esta tesis pretende ofrecer técnicas instrumentales alternativas, rápidas y sencillas para determinar la calidad sensorial de alimentos como el aceite de oliva, el vino o las almendras. Los estudios llevados a cabo incluyen el tratamiento de las respuestas sensoriales obtenidas mediante metodologías de referencia (principalmente paneles de cata humanos), la optimización de los procedimientos analíticos para trabajar con técnicas instrumentales y el desarrollo de herramientas quimiométricas adecuadas para construir los modelos multivariantes. También se han desarrollado estrategias de fusión de datos para combinar los diferentes datos instrumentales que simulan los sentidos humanos (olor, gusto y visión).Olive oil, wine or nuts are typical products of the Mediterranean region that offer added value thanks to its health benefits and excellent sensory characteristics. Therefore, the control the quality and authenticity of these products is necessary, mainly because they are highly susceptible to fraud and adulterations. An important aspect is the evaluation of sensory quality that describe parameters perceived by the senses (taste, sight, smell and touch) using validated and trained panels of experts. These panels tend to be subjective, requiring long-time analysis and high costs. As a result there has been an increase in the development of analytical techniques capable to simulate the responses obtained with the human taste panel. The so-called 'electronic panel' provides objective responses using multivariate techniques, which establish correlations between descriptors defined by humans and signals obtained instrumentally. This thesis aims to offer fast and simple alternative instrumental techniques to determine the sensory quality of foods such as olive oil, wine and almonds. Studies carried out include the treatment of sensory responses obtained by reference methodologies (mainly human taste panels), optimization of analytical procedures to work with instrumental techniques and the development of appropriate chemometric tools to build multivariate models. Data fusion strategies have also been studied by combining different instrumental data that simulate the human senses (smell, taste and sight)

Transferable Odor Differentiation Models for Infectious Disease Diagnostics

__Abstract__ In recent years the interest for the application of an electronic nose (eNose) in medical Diagnostics is increasing. There is a need for this since eNose Diagnostics is non-invasive, easy to run, fast and cheap. The eNoses, now on the market, however, turn out to be unsuitable for large-scale application. This is mainly due to insufficient reproducibility of measurement results. In this work an eNose is used which is cheap and suited for mass applications. The usage of advanced temperature control guarantees the reproducibility between eNoses. In practice, this means that a once developed analysis model for a specific disease easily can be transferred to any number of other eNoses. Application of mass-produced components keeps the cost low. In the research it is shown that temperature variation is the main cause of the significant differences in measurement characteristic between the metal oxide sensors on which the eNose is based. To illustrate the practical applicability pilot studies are described for sepsis (bacterial infection of the blood), tuberculosis (TB) and metritis (infection of the uterus in cows). In the sepsis and metritis studies the measurements were conducted in the headspace of the blood cultures and uterus mucus respectively. In the tuberculosis study the exhaled breath of patients analyzed. For the sepsis diagnostics 30 eNoses are used to identify 11 to identify clinical relevant pathogens in blood. The eNose can significantly speed up the diagnostic process: on average 78% of the pathogens were correctly identified within 6-8 hours after inoculation in contrast to the 24 hours typically needed with the current methods. The TB-study was conducted in Dhaka (Bangladesh) with 3 eNoses. It turned out to be possible to distinguish between healthy people and those with active TB infection [sensitivity 93.5%, specificity 85.3%] but also to identify an active TB infection in a group of TB suspects [sensitivity 76.5%, specificity 87.2%]. These results are significantly better than the much-used screening test based on microscopy. Currently there is no objective diagnosis for metritis. A vet performs the diagnosis based on a number of characteristics such as temperature and appearance of the sample. The eNose proved to be more reliable and objective than a control panel of veterinarians [sensitivity 100%, specificity 91.6%]

Sensores: De los biosensores a la nariz electrónica

The recent advances in sensor devices have allowed the developing of new applications in many technological fields. This review describes the current state-of-the-art of this sensor technology, placing special emphasis on the food applications. The design, technology and sensing mechanism of each type of sensor are analysed. A description of the main characteristics of the electronic nose and electronic tongue (taste sensors) is also given. Finally, the applications of some statistical procedures in sensor systems are described briefly.Los recientes avances en los sistemas de sensores han permitido el desarrollo de nuevas aplicaciones en muchos campos tecnológicos. Este artículo de revisión describe el estado actual de esta nueva tecnología, con especial énfasis en las aplicaciones alimentarias. El diseño, la tecnología y el mecanismo sensorial de cada tipo de sensor son analizados en el artículo. También se describen las principales características de la nariz y la lengua electrónica (sensores de sabor). Finalmente, se describe brevemente el uso de algunos procedimientos estadísticos en sistemas de sensores.Peer reviewe

Ability, repeatability, and reproducibility of rapid evaporative ionization mass spectrometry to predict beef quality attributes

Includes bibliographical references.2022 Fall.Tenderness, juiciness, and flavor are beef quality attributes that influence consumer satisfaction eating beef. Rapid evaporative ionization mass spectrometry (REIMS) is a novel technique that provides chemical information of biological tissues with the potential to predict beef quality attributes. Two studies were conducted to evaluate the ability of REIMS to predict quality attributes of beef (study I) and to evaluate the repeatability and reproducibility of REIMS in a beef matrix (study II). In study I, USDA Select or upper two-thirds Choice (n = 42, N=84) striploins and tenderloins were collected approximately 36h post-mortem from a commercial beef abattoir. Slivers of the longissimus dorsi muscle between the 12-13th rib were collected during grading (GR, 36h post-mortem) and analyzed using REIMS. Striploins (LM) and tenderloins (PM) were cut into portions and assigned to 6 aging periods (3, 14, 28, 42, 56, and 70 days). However, only samples aged 3, 14, and 28 days were used to represent industry practices in study I. After aging, portions were cut into 2.54-cm steaks to analyze juiciness, tenderness, and 10 flavor attributes with a trained sensory panel. In addition, tenderness measures were performed using slice shear force (SSF) and Warner-Bratzler shear force (WBF). Samples were categorized by SSF, WBF, and sensory panel tenderness (PT) into "tough" and "tender"; by juiciness into "dry" and "juicy"; and by flavor into "acceptable" and "unacceptable" classes using a composite score of all flavor descriptors. Combinations of three dimensionality reduction methods (principal component analysis [PCA], feature selection, [FS], and a combination of both [PCA-FS]) with 13 machine learning algorithms were used to create classification models based on REIMS data for tenderness, juiciness, and flavor classes at the three aging periods. The predictive ability of the models was assessed with the overall accuracy resulting from 10-fold cross-validation. Among all machine learning algorithms evaluated, the maximum classification accuracies for days 3, 14, and 28 were 94, 87, and 83% for PT; 86, 85, 92% for SSF; 87, 82, and 95 for WBF; 85, 84, and 86% for juiciness; and 87, 89, and 81% for flavor classes, respectively. FS performed the best as a dimensionality reduction method for all PT, juiciness, flavor, and SSF on day 3 and WBF on days 3 and 14. PCA-FS was the best dimensionality reduction method for SSF on days 14 and 28, and WBF on day 28. Extreme gradient boosting machine learning algorithm was the highest performing algorithm for all juiciness models, flavor model on day 28, PT on days 3 and 14, SSF on days 14 and 28, and WBF on days 3. Partial least squared discriminant analysis (PLSDA) performed better for PT day 28 and flavor day 14, while elastic-net regularized generalized linear model, random forest, and support vector machine were the highest performing algorithms for SSF day 3, and WBF days 14 and 28, respectively. Results demonstrated that the chemical fingerprints obtained with REIMS could potentially be used as in situ and real-time technique to sort carcasses by flavor, juiciness, and tenderness. However, overlaps between classes affected REIMS results, and unbalanced data negatively affected model accuracies. Therefore, exploring the full potential of REIMS will require increasing the sample size and developing a sampling method that allows increased separation between sensory evaluations. Study II was performed with REIMS data from all LM and PM samples from the six aging periods (n=1008), two sets of GR samples (n=168, N=84), and quality control (QC) samples (n=29) made from homogenized ground beef. Except for the second set of GR samples, REIMS analysis of all samples was performed at Colorado State University (CSU) using a meat probe as the sampling device. Analysis of all samples was performed over 5 days, including two batches per day. GR samples were evaluated on the first day, and LM and PM data were randomly analyzed on the remaining days. QC samples were analyzed at the beginning, middle, and end of each batch. The second set of GR samples was analyzed at Texas Tech University (TTU) using different mass spectrometry (MS) instruments, technicians, and an iKnife as the sampling device. The stability of REIMS data between burns, batches, and days was evaluated with QC data. Day effect and robustness of REIMS data were evaluated with data from LM and PM samples, and interlab reproducibility was evaluated with data from GR samples. Multiple classification models of muscle type and aging were built with LM and PM data to evaluate the robustness of REIMS and day-to-day variability. Models to predict sensory attributes of beef were used to assess the robustness of REIMS with respect to interlab variability. Coefficients of variation (CV) between burns of the mass bins representing 90% of the total ion current were between 0.7 to 0.98, while the most relevant mass bins showed CV less than 0.3. Variances between batches and collection days were not significant (P < 0.05). PCA of LM and PM showed that data variability by collection day was stronger than muscle type and aging time variability. However, data could classify samples into muscle types and two distant aging times with accuracies higher than 95.6% and 91.0%, respectively. PCA of GR samples showed that data collected in both labs differed, and the predictive models developed with the CSU data did not appropriately predict the quality classes with the TTU data. REIMS collected with the meat probe provides a chemometric profile of beef samples with good repeatability and interday reproducibility but low interlab reproducibility. Consequently, optimization and standardization of sampling methods will be required to improve the interlab reproducibility of REIMS