Odor Sensor Research Articles

A Taste and Odor Sensing by Photoluminescence Responses of Luminescent Metal Organic Frameworks

The sensors of taste and odor play important roles of recognition as well as reception. In our research, the taste and odor sensing capabilities were based on the photoluminescence (PL) responses of luminescent metal-organic frameworks (MOFs). For the sensing of taste, [In(OH)(bdc)]n(bdc = 1,4-benzenedicarboxylate) and [Tb(btc)] (MOF-76, btc = benzene-1,3,5-tricarboxylate), were tested on aqueous solutions of five basic tastants such as sucrose (sweet), caffeine (bitter), citric acid (sour), sodium chloride (salty) and monosodium glutamate (umami). The photoluminescence (PL) responses of polyacrylic acid-chelated [In(OH)bdc]n and lanthanide Tb(btc) were used to demonstrate the applicability of MOF-based biomimetic tongue through: (1) identification of five tastes: sweet, bitter, sour, salty and umami, by 3-D PCA (principle component analysis) to distinguish the corresponding tastants, (2) quantification of the strength of five tastes determined by the relationships between the PL intensity and the τ scale of taste. For the sensing of odor, [In(OH)(bdc)]nand [Zn4O(bdc)3] (MOF-5) were exposed to the odorants such as cumin, cinnamon, vanillin, p-xylene, m-xylene, o-xylene, water, and ethanol. Similarly, the MOF-based biomimetic nose could distinguish the odors of the analytes based on a pattern recognition method (i.e., principal component analysis) constructed by the 2-D map of PL emission responses.

Development of a fluorescent imaging sensor for the detection of human body sweat odor

An odor sensor based on a fluorescent imaging system was developed to detect the sweat odor of human body. Volatile organic acid substances with low molecular weight were supposed to be one of the key contributors to the odor of a sweat sample collected from the human body. Quinine sulfate, a pH-dependent fluorescent compound that shows fluorescent enhancing in the presence of organic acids, was utilized to prepare an agarose-gel supported fluorescent film. The existence of organic acid components with high abundance in the collected sweat sample was confirmed by the analysis of SPME-GC/MS. Sequence images of the fluorescent film in the absence and presence of odors were recorded by a high-resolution CCD camera. The response of the sensor to typical organic acids in sweat odor, such as acetic acid, isovaleric acid, hexanoic acid and octanoic acid, was evaluated by the analysis of subtraction images as well as the real-time change of mean gray value (MGV). The odor of the sweat sample after incubation was successfully visualized, which indicates the application potential of the developed fluorescent imaging sensor in the detection of human body odor.

Preface to the Special Issue on “Advances in Odor Sensing and Odor Presentation Technologies”

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Practical discrimination of good and bad cooked food using metal oxide semiconductor odour sensor

An increasing concentration of ammonia in cooked food is in direct proportion to the extent of decay. This fact is used to design an electronic nose (e-nose) based on metal oxide semiconductor odour sensor circuit capable of discriminating good and bad cooked food. On the basis of the data produced by the e-nose circuit, a feedforward multilayer neural network is designed and trained to recognize varying concentrations of ammonia in the food. Test results of the prototype e-nose system show that it is capable of classifying cooked food as being good or bad with over 92% average success rate.

Analysis of the Relationship between Odor Sensor and the Air Dilution Olfactory Method in Industrial Complex Odor

Analysis of the Relationship between Odor Sensor and the Air Dilution Olfactory Method in Industrial Complex Odor

Detection of Metabolic Gas Emitted by Termites Using Semiconductor Gas Sensors

ABSTRACT The feasibility of using three types of semiconductor gas sensors to detect the metabolic gas generated by termites was investigated. Odor, methane, and hydrogen sensors made of a tin oxide semiconductor were tested. A polypropylene container was prepared with three sensors in the lid to investigate the relationship between the number of termites and food material on gas concentration over time. Worker and soldier termites (Coptotermes formosanus), collected from a laboratory colony, were put into the container with and without food material (wood specimen). The variation in the electrical resistance of the sensors during the detection of gas components was monitored, and the detected voltage was converted into gas concentration. The hydrogen concentration increased with an increase in the number of termites and was not influenced by gases released from the wood specimen. Similar findings were obtained for the odor sensor, even though it detected odor components from both termites and the wood specimen. The methane sensor did not detect any significant increase in gas concentration. The results showed that the hydrogen emission depended on the feeding activity of worker termites, whereas soldier termites that were supplied with food material by worker termites made a small contribution to hydrogen emission. These findings suggest that because of the high selectivity and sensitivity of the hydrogen sensor, its performance is better than that of the odor and methane sensors for the detection of termite attacks.

Pattern Recognition for Selective Odor Detection with Gas Sensor Arrays

This paper presents a new pattern recognition approach for enhancing the selectivity of gas sensor arrays for clustering intelligent odor detection. The aim of this approach was to accurately classify an odor using pattern recognition in order to enhance the selectivity of gas sensor arrays. This was achieved using an odor monitoring system with a newly developed neural-genetic classification algorithm (NGCA). The system shows the enhancement in the sensitivity of the detected gas. Experiments showed that the proposed NGCA delivered better performance than the previous genetic algorithm (GA) and artificial neural networks (ANN) methods. We also used PCA for data visualization. Our proposed system can enhance the reproducibility, reliability, and selectivity of odor sensor output, so it is expected to be applicable to diverse environmental problems including air pollution, and monitor the air quality of clean-air required buildings such as a kindergartens and hospitals.

Meat and Fish Freshness Inspection System Based on Odor Sensing

We propose a method for building a simple electronic nose based on commercially available sensors used to sniff in the market and identify spoiled/contaminated meat stocked for sale in butcher shops. Using a metal oxide semiconductor-based electronic nose, we measured the smell signature from two of the most common meat foods (beef and fish) stored at room temperature. Food samples were divided into two groups: fresh beef with decayed fish and fresh fish with decayed beef. The prime objective was to identify the decayed item using the developed electronic nose. Additionally, we tested the electronic nose using three pattern classification algorithms (artificial neural network, support vector machine and k-nearest neighbor), and compared them based on accuracy, sensitivity, and specificity. The results demonstrate that the k-nearest neighbor algorithm has the highest accuracy.

Evaluation of the Masking of Dimethyl Sulfide Odors by Citronellal, Limonene and Citral through the Use of Trained Odor Sensor Mice

Previous studies indicate that the most common result of mixing two odors is the decreased olfactory perception of one or both components in the mixture. An excellent example of this phenomenon is provided by the masking of an unpleasant odor by a pleasant odor. This study hypothesized that dimethyl sulfide (DS; a major chemical component of oral malodor) might be masked by citronellal, a monoterpene aldehyde that produces an intense lemon aroma. To investigate this hypothesis, mice were chosen as odor sensor animals. Mice were trained in a Y maze to discriminate between DS (10 ppm in aqueous solution) and water. A series of generalization tests revealed that these trained "odor sensor" mice could also distinguish between 1 ppm DS and water, but not between 0.1 ppm DS and water. The mice were then confronted with the original choice of 10 ppm DS and water, but now in the presence of various concentrations of citronellal. The mice failed to detect the odor of DS when confronted with 30 ppm citronellal. The mice were similarly confused when confronted with citral (90 ppm) or limonene (3000 ppm). This study is the first to show that citrus odorants can mask the odor of DS, altering the behavioral responses of trained odor sensor mice.

Stabilization of coating for QCM odor sensors with liquid GC materials supported by lipopolymers and lipids

The paper reports on development of a method for stabilization of coatings for QCM odor sensors that use liquid GC stationary phase materials. The liquid materials tend to be easily removed from the sensor's surface when coated directly onto its surface. The proposed method employs chemisorbed lipopolymers and lipids to form a matrix into which the liquid GC materials are encapsulated. The fabrication method is relatively simple as the sensing films are formed in a sorption process from a single solution. The obtained experimental results show significantly enhanced stability of the fabricated sensing films. The obtained sensors reproducibly show high sensitivities to vapors of selected odorants with detection limits in sub-ppm range. They also showed a good capability to discriminate among the odorant samples.

An improved bioluminescence‐based signaling assay for odor sensing with a yeast expressing a chimeric olfactory receptor

The goal of this work was to improve the bioluminescence-based signaling assay system to create a practical application of a biomimetic odor sensor using an engineered yeast-expressing olfactory receptors (ORs). Using the yeast endogenous pheromone receptor (Ste2p) as a model GPCR, we determined the suitable promoters for the firefly luciferase (luc) reporter and GPCR genes. Additionally, we deleted some genes to further improve the sensitivity of the luc reporter assay. By replacing the endogenous yeast G-protein α-subunit (Gpa1p) with the olfactory-specific Gα(olf), the optimized yeast strain successfully transduced signal through both OR and yeast Ste2p. Our results will assist the development of a bioluminescence-based odor-sensing system using OR-expressing yeast.

Dissociated neuronal culture expressing ionotropic odorant receptors as a hybrid odorant biosensor—proof-of-concept study

Artificial odorant sensors generally perform poorer than olfactory systems in living organisms. The excellent performances of living odorant systems are achieved by the molecular recognition abilities of odorant receptors and the neuronal information processing that follows. To take advantages of this, here we propose a novel hybrid odorant biosensor by means of expressing ionotropic odorant receptors of insects into dissociated neuronal cultures of rodents. This combination of materials brings significant advantages such as easy functional expression, prolonged lifetime, and an ability to amplify the weak ionic currents of odorant receptors. In the present work, pheromone receptors and co-receptors of silkmoth, i.e., BmOR1 and BmorOrco, were expressed in neuronal cultures via liposome transfection. Consequently, BmOR1 and BmorOrco were co-expressed in 8% of neuronal cells, and both receptors were co-localized on a cell membrane. In Ca++ imaging experiments, synchronous increase of calcium signals at the presentation of BOL was found in both transfected cells and non-transfected cells in a dose-dependent manner. These results provide the proof-of-concept of the proposed hybrid odorant biosensor.

Effects of Manufacturing Process Conditions on Sensory Attributes and Microstructure of Ice Cream

The primary process parameters of the homogenization pressure and freezing process (drawing temperature and overrun) for ice cream manufacture were examined to determine their impact on the sensory attributes and odor sensor response of ice cream. Fifteen process conditions were selected using a Box-Behnken design, while 12 sensory attributes were obtained as assessment items based on sensory evaluations using quantitative descriptive analysis (QDA). Eleven of these sensory attributes changed significantly according to process conditions, suggesting that such conditions can have a major impact on ice cream's sensory attributes, even for a fixed make-up of ingredients. Furthermore, observed correlations between the sensory attributes and microstructural attributes of the ice cream led to the conjecture that the sensory attributes were influenced by changes to the ice cream's structural conditions resulting from the process conditions. A correlation was also observed between the odor sensor response and the overrun condition, but no clear correlations were found to exist within the ice cream structure or the sensory attributes.

Development of a Pattern Recognition System Based on Image Processing Implemented on a Safety Critical Embedded System for Accident Prevention

Irresponsible driving is one of the leading causes of mishaps & deaths in the world today. The present work aims at developing a preventive solution to this problem in the form of a driving aid for drunk drivers or people who are not in a fit state to drive. The said system proposes to enhance certain existing frameworks using image processing. Haar-wavelet classifiers & Speeded Up Robust Features (SURF) algorithm are used to analyze images of the drivers' eyes & patterns of movement to judge if they are eligible to drive. These complement the existing sensors, like the odor sensor, and help the system reach a confident decision. We plan to take this system further by creating collaborative MANETs among vehicles for preventing potential harm to other drivers as well.

The N‐terminal replacement of an olfactory receptor for the development of a Yeast‐based biomimetic odor sensor

For the development of a biomimetic odor-sensing system, we investigated the effects of replacing the N-terminus of an olfactory receptor (OR) on its functional expression in the budding yeast, Saccharomyces cerevisiae. Using the mouse olfactory receptor OR226 (mOR226), three types of chimeric ORs were constructed by replacing N-terminal regions of mOR226 with the corresponding regions of the rat I7 receptor, which is known to be functionally expressed in yeast. The replacement of the N-terminal region of mOR226 dramatically affected the expression and localization of the receptor and improved the sensing ability of the yeast cells for the odorant. Furthermore, the replacement of the endogenous yeast G-protein α subunit (Gpa1) by the OR-specific G(olf) drastically elevated the odorant-sensing ability of the yeast cells and caused the cells to display a dose-dependent responsiveness to the odorant. Because of the suitability of yeast cells for screening large-scale libraries, the strategy presented here would be useful for the establishment of advanced biomimetic odor-sensing systems.

Feasibility of Odor Sensors on the Odorous Compounds Evolved from Eutrophicated Waters

Feasibility of Odor Sensors on the Odorous Compounds Evolved from Eutrophicated Waters

Pollination biology of Lilium japonicum var. abeanum and var. japonicum: evidence of adaptation to the different availability of diurnal and nocturnal pollinators

AbstractFloral traits such as color and size are highly diversified in lilies, but their adaptive significance remains uncertain. In the present study, we compared pollination processes between Lilium japonicum var. abeanum and var. japonicum to clarify how the two varieties are adapted to different pollinators. Lilium japonicum var. japonicum is known to be pollinated by moths, and we hypothesized from its flower traits that var. abeanum is pollinated by diurnal insects. Using waterproof digital cameras set to a recording interval of 10–30 s, we recorded flower visitors for 7–9 flowers of var. japonicum and 4–6 flowers of var. abeanum over 24‐h periods. We also recorded the number of versatile (T‐shaped) and rigid (I‐shaped) anthers per flower. For var. abeanum, we observed flowers at 05.00 and 17.00 hours to determine flower opening time and measured the intensity of floral scent using a metal‐oxide semi‐conductor odor sensor. Both diurnal and nocturnal insects visited flowers of the two varieties, but visitation of diurnal insects was more frequent in var. abeanum. Anthers of var. abeanum are usually rigid, as in many bee‐pollinated flowers, whereas those of var. japonicum are mostly versatile. Although flowers of var. japonicum are known to open in the evening, 32% of the flowers of var. abeanum started to flower during the day. Lilium japonicum var. abeanum emitted scent at night, with a maximum intensity at 20.00 hours, just as in var. japonicum. These findings suggest that the floral traits of the two varieties are adapted to the different relative availabilities of nocturnal versus diurnal pollinators. The flower of var. abeanum is more adapted to diurnal pollinators, but retains adaptations to nocturnal pollinators, particularly with regard to its scent.

Highly sensitive alkane odour sensors based on functionalised gold nanoparticles

We deposit dense, ordered, thin films of Au–dodecanethiol core/shell nanoparticles by the Langmuir–Schäfer (LS) printing method, and find that their resistance at ambient temperature responds selectively and sensitively to alkane odours. Response is a rapid resistance increase due to swelling, and is strongest for alkane odours where the alkane chain is similar in length to the dodecane shell. For decane odours, we find a response to concentrations as low as 15 ppm, about 600 times below the lower explosive limit. Response is weaker, but still significant, to aromatic odours (e.g. Toluene, Xylene), while potential interferants such as polar and/or hydrogen-bonding odours (e.g. alcohols, ketones, water vapour) are somewhat rejected. Resistance is weakly dependent on temperature, and recovers rapidly and completely to its original value within the error margin of measurement.

The response characteristics of odor sensor based on organic thin-film transistor for environment malodor measurements

This paper studies the response characteristics of an odor sensor based on organic thin-film transistors (OTFTs) obtained from spin-coated poly-3-hexylthiophene (P3HT) on a thermally grown SiO 2/Si wafer. The response characteristics of the odor sensor based on OTFTs are measured for odor gases generated from liquid fumes of 2-mercaptoethanol and 3-methylindole, such as are typically emitted by pig slurry in ambient air conditions. The experiments show that the response characteristics of the OTFT, when exposed to the 2-mercaptoethanol and 3-methylindole gases, result in a threshold voltage shift, a change in drain current, and a change in mobility with the gate bias.

Highly sensitive QCM odor sensors with lipopolymeric nanocomposites and physisorbed amphiphilic GC materials

Purpose – This work has been motivated by the authors' long‐term research on odor‐sensing systems using acoustic wave‐based sensors and pattern recognition techniques. The sensors should be fabricated in such a way that they mimic performance of the olfactory receptors. In these terms, the purpose of this paper is to test a simple method for fabrication of quartz crystal microbalance (QCM) sensors by using nanocomposites and amphiphilic gas chromatography (GC) materials. The obtained sensors were intended to be highly sensitive to odorants at low concentrations and in high‐humidity conditions, as well as contributing to discrimination among odorant samples.