An overview of an artificial nose system

Nanotechnology and E-Sensing for Food Chain Quality and Safety

Nowadays, it is well known that sensors have an enormous impact on our life, using streams of data to make life-changing decisions. Every single aspect of our day is monitored via thousands of sensors, and the benefits we can obtain are enormous. With the increasing demand for food quality, food safety has become one of the main focuses of our society. However, fresh foods are subject to spoilage due to the action of microorganisms, enzymes, and oxidation during storage. Nanotechnology can be applied in the food industry to support packaged products and extend their shelf life. Chemical composition and sensory attributes are quality markers which require innovative assessment methods, as existing ones are rather difficult to implement, labour-intensive, and expensive. E-sensing devices, such as vision systems, electronic noses, and electronic tongues, overcome many of these drawbacks. Nanotechnology holds great promise to provide benefits not just within food products but also around food products. In fact, nanotechnology introduces new chances for innovation in the food industry at immense speed. This review describes the food application fields of nanotechnologies; in particular, metal oxide sensors (MOS) will be presented.

Advances in the Production of Olfactory Receptors for Industrial Use

In biological olfactory systems, olfactory receptors (ORs) can recognize and discriminate between thousands of volatile organic compounds with very high sensitivity and specificity. The superior properties of ORs have led to the development of OR-based biosensors that have shown promising potential in many applications over the past two decades. In particular, newly designed technologies in gene synthesis, protein expression, solubilization, purification, and membrane mimetics for membrane proteins have greatly opened up the previously inaccessible industrial potential of ORs. In this review, gene design, expression and solubilization strategies, and purification and reconstitution methods available for modern industrial applications are examined, with a focus on ORs. The limitations of current OR production technology are also estimated, and future directions for further progress are suggested.

Recent Advances in Transistor-Based Bionic Perceptual Devices for Artificial Sensory Systems

The sensory nervous system serves as the window for human beings to perceive the outside world by converting external stimuli into distinctive spiking trains. The sensory neurons in this system can process multimodal sensory signals with extremely low power consumption. Therefore, new-concept devices inspired by the sensory neuron are promising candidates to address energy issues in nowadays’ robotics, prosthetics and even computing systems. Recent years have witnessed rapid development in transistor-based bionic perceptual devices, and it is urgent to summarize the research and development of these devices. In this review, the latest progress of transistor-based bionic perceptual devices for artificial sense is reviewed and summarized in five aspects, i.e., vision, touch, hearing, smell, and pain. Finally, the opportunities and challenges related to these areas are also discussed. It would have bright prospects in the fields of artificial intelligence, prosthetics, brain-computer interface, robotics, and medical testing.

Sensors for Volatile Organic Compounds

This paper provides an overview of recent developments in the field of volatile organic compound (VOC) sensors, which are finding uses in healthcare, safety, environmental monitoring, food and agriculture, oil industry, and other fields. It starts by briefly explaining the basics of VOC sensing and reviewing the currently available and quickly progressing VOC sensing approaches. It then discusses the main trends in materials' design with special attention to nanostructuring and nanohybridization. Emerging sensing materials and strategies are highlighted and their involvement in the different types of sensing technologies is discussed, including optical, electrical, and gravimetric sensors. The review also provides detailed discussions about the main limitations of the field and offers potential solutions. The status of the field and suggestions of promising directions for future development are summarized.

Electronic nose application for the discrimination of sterilization treatments applied to Californian-style black olive varieties

BACKGROUND

Olive oil continues to be the main destination for olives. The production of table olives is increasing. 'Californian-style' processes are among the most frequently employed to produce oxidized olives. Sensory evaluation requires the development of an instrumental detection method that can be used as an adjunct to traditional tasting panels.

RESULTS

An electronic nose (E-nose) was used to classify two varieties of olives following exposure to different sterilization. Principal component analysis (PCA) revealed that both varieties had different volatile profiles. Sensory panel evaluations were similar for both. Partial least squares-discriminant analysis (PLS-DA) obtained from the E-nose was able to separate the two varieties and explained 82% of total variance. Moreover, volatile profiles correctly classified olives according to sterilization times recorded up to 121 °C . The only exception was at F₀  ≥ 22 min, at which a plot of PCA outcomes failed to differentiate scores. E-nose data showed similar results to those produced from the volatile analysis when grouping samples were sterilized to F₀  ≥ 18 min, at the same time distinguishing these samples from those subjected to less intense thermal treatments. A partial least squares (PLS) chemometric approach was evaluated for quantifying important olive quality parameters. With regards to validation parameters, R P 2 pertaining to perceived defect was 0.88, whilst R P 2 pertaining to overall assessment was 0.78.

CONCLUSIONS

E-nose offers a fast, inexpensive and non-destructive method for discriminating between varieties and thermal treatments up to a point at which cooking defects are highly similar (from F₀  = 18 onwards). © 2021 Society of Chemical Industry.

Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose

The organoleptic profile of a Virgin Olive Oil is a key quality parameter that is currently obtained by human sensory panels. The development of an instrumental technique capable of providing information about this profile quickly and online is of great interest. This work employed a general purpose e-nose, in lab conditions, to predict the level of fruity aroma and the presence of defects in Virgin Olive Oils. The raw data provided by the e-nose were used to extract a set of features that fed a regressor to predict the level of fruity aroma and a classifier to detect the presence of defects. The results obtained were a mean validation error of 0.5 units for the prediction of fruity aroma using lasso regression; and 88% accuracy for the defect detection using logistic regression. Finally, the identification of two out of ten specific sensors of the e-nose that can provide successful results paves the way to the design of low-cost specific electronic noses for this application.

Application of a Low-Cost Electronic Nose for Differentiation between Pathogenic Oomycetes Pythium intermedium and Phytophthora plurivora

Compared with traditional gas chromatography-mass spectrometry techniques, electronic noses are non-invasive and can be a rapid, cost-effective option for several applications. This paper presents comparative studies of differentiation between odors emitted by two forest pathogens: Pythium and Phytophthora, measured by a low-cost electronic nose. The electronic nose applies six non-specific Figaro Inc. metal oxide sensors. Various features describing shapes of the measurement curves of sensors' response to the odors' exposure were extracted and used for building the classification models. As a machine learning algorithm for classification, we use the Support Vector Machine (SVM) method and various measures to assess classification models' performance. Differentiation between Phytophthora and Pythium species has an important practical aspect allowing forest practitioners to take appropriate plant protection. We demonstrate the possibility to recognize and differentiate between the two mentioned species with acceptable accuracy by our low-cost electronic nose.

Peptides, DNA and MIPs in Gas Sensing. From the Realization of the Sensors to Sample Analysis

Detection and monitoring of volatiles is a challenging and fascinating issue in environmental analysis, agriculture and food quality, process control in industry, as well as in 'point of care' diagnostics. Gas chromatographic approaches remain the reference method for the analysis of volatile organic compounds (VOCs); however, gas sensors (GSs), with their advantages of low cost and no or very little sample preparation, have become a reality. Gas sensors can be used singularly or in array format (e.g., e-noses); coupling data output with multivariate statical treatment allows un-target analysis of samples headspace. Within this frame, the use of new binding elements as recognition/interaction elements in gas sensing is a challenging hot-topic that allowed unexpected advancement. In this review, the latest development of gas sensors and gas sensor arrays, realized using peptides, molecularly imprinted polymers and DNA is reported. This work is focused on the description of the strategies used for the GSs development, the sensing elements function, the sensors array set-up, and the application in real cases.

Electrochemical biosensing with odorant binding proteins

The development of sensors that mimic the natural smell sensing mechanism and selectively recognizes the odorants remains highly challenging. Electrochemical based sensing approaches aiming at monitoring molecular recognition events between surface receptors and analytes in solution or in the gas phase, are one possible transduction platforms among others for the construction of an artificial nose. The principle of electrochemical detection lies on the shift of the potential/current during the recognition event, which is proportional to the concentration of the analyte, in our case the odorant. A tremendous amount of efforts has been put into making electrochemical sensors sensitive and selective to the analyte of interest through the use of nanomaterials, development of different detection schemes and application of innovative receptor ligands for selective detection of the analyte. There have been significant advances in electrochemical based odorant sensing by using odorant binding proteins (OBP) as surface receptors, small soluble proteins present in nasal mucus at millimolar concentrations where the hydrophobic binding pocket gives the ability to reversibly bind odorant molecules. As OBPs are robust and easy to produce receptors, they are good candidates for the design of biosensors. In this chapter, we focus on the progress made on the detection of odorant molecules using OBPs as a bioreceptor and electrochemistry as a transduction method.

Classification and Identification of Industrial Gases Based on Electronic Nose Technology

Rapid detection and identification of industrial gases is a challenging problem. They have a complex composition and different specifications. This paper presents a method based on the kernel discriminant analysis (KDA) algorithm to identify industrial gases. The smell prints of four typical industrial gases were collected by an electronic nose. The extracted features of the collected gases were employed for gas identification using different classification algorithms, including principal component analysis (PCA), linear discriminant analysis (LDA), PCA + LDA, and KDA. In order to obtain better classification results, we reduced the dimensions of the original high-dimensional data, and chose a good classifier. The KDA algorithm provided a high classification accuracy of 100% by selecting the offset of the kernel function c = 10 and the degree of freedom d = 5. It was found that this accuracy was 4.17% higher than the one obtained using PCA. In the case of standard deviation, the KDA algorithm has the highest recognition rate and the least time consumption.

Critical review of electronic nose and tongue instruments prospects in pharmaceutical analysis

Electronic nose (enose, EN) and electronic tongue (etongue, ET) have been designed to simulate human senses of smell and taste in the best possible way. The signals acquired from a sensor array, combined with suitable data analysis system, are the basis for holistic analysis of samples. The efficiency of these instruments, regarding classification, discrimination, detection, monitoring and analytics of samples in different types of matrices, is utilized in many fields of science and industry, offering numerous practical applications. Popularity of both types of devices significantly increased during the last decade, mainly due to improvement of their sensitivity and selectivity. The electronic senses have been employed in pharmaceutical sciences for, among others, formulation development and quality assurance. This paper contains a review of some particular applications of EN and ET based instruments in pharmaceutical industry. In addition, development prospects and a critical summary of the state of art in the field were also surveyed.

Use of Electronic Noses for Diagnosis of Digestive and Respiratory Diseases through the Breath

The increased occurrence of chronic diseases related to lifestyle or environmental conditions may have a detrimental effect on long-term health if not diagnosed and controlled in time. For this reason, it is important to develop new noninvasive early diagnosis equipment that allows improvement of the current diagnostic methods. This, in turn, has led to an exponential development of technology applied to the medical sector, such as the electronic nose. In addition, the appearance of this type of technology has allowed the possibility of studying diseases from another point of view, such as through breath analysis. This paper presents a bibliographic review of past and recent studies, selecting those investigations in which a patient population was studied with electronic nose technology, in order to identify potential applications of this technology in the detection of respiratory and digestive diseases through the analysis of volatile organic compounds present in the breath.

Protein- and Peptide-Based Biosensors in Artificial Olfaction

Animals' olfactory systems rely on proteins, olfactory receptors (ORs) and odorant-binding proteins (OBPs), as their native sensing units to detect odours. Recent advances demonstrate that these proteins can also be employed as molecular recognition units in gas-phase biosensors. In addition, the interactions between odorant molecules and ORs or OBPs are a source of inspiration for designing peptides with tunable odorant selectivity. We review recent progress in gas biosensors employing biological units (ORs, OBPs, and peptides) in light of future developments in artificial olfaction, emphasizing examples where biological components have been employed to detect gas-phase analytes.