Odor Detection Research Articles

Examining shaping of two odor detection dogs

Examining shaping of two odor detection dogs

Canine detection of explosives under adverse environmental conditions with and without acclimation training.

Canines are one of the best biological detectors of energetic materials available; however, canine detection of explosives is impacted by a number of factors, including environmental conditions. The objectives of this study were: 1) determine how canine detection limits vary when both the canine and odorant are tested in varying temperature and humidity conditions (canine and odor interactive effects); and 2) determine if an acclimatization plan can improve detection limits in an adverse environmental condition. Eight working line canines were trained to detect four energetics: prill ammonium nitrate (AN), Composition 4 (C4), trinitrotoluene (TNT) and double base smokeless powder (SP). In Experiment 1, canines completed a 3-alternative forced choice 3-down-1-up staircase threshold assessment in five environmental conditions: 40°C and 70% relative humidity (RH), 40°C and 40% RH, 0°C and 90% RH, 0°C and 50% RH and 21°C and 50% RH. Canines showed a 3.5-fold detection limit increase (poorer detection) for C4 in 40°C and 70% RH compared to their detection limit at 21°C and 50% RH. In Experiment 2, the eight canines were split into two groups (n = 4), control and acclimation groups. The control group completed the threshold assessment for C4 at 21°C and 50% RH each day for 20 days, with 5 minutes of petting prior to testing. The acclimation group completed the same assessment daily starting at 21°C and 50% RH but temperature and RH were incremented daily over the course of 6 days to the 40°C and 70% RH condition. After the initial six days, the acclimation group completed daily assessments at 40°C and 70% RH condition for the remainder of the experiment. All acclimatization group canines started their session with 5 minutes of toy or food retrieves. Detection limits for C4 for all dogs were tested in 40°C and 70% RH on day 11 and day 22. The acclimatization plan improved detection limits in the 40°C and 70% RH condition for C4 compared to the non-acclimated group. In this set of experiments, canine detection limits for four explosive odorants were found to vary based on environmental condition and were mostly driven by impacts on the canine rather than odor availability. The acclimatization plan did result in lower detection limits (i.e., increased performance). Future work should determine what factor (exercise or environmental exposure) is more effective in acclimatization for odor detection work.

Marinade injection of pork as a possible technological strategy to reduce boar taint: Response and attitude of the consumer

Sensory evaluation by consumers allows validation of a solution for the food industry to overcome boar taint and market entire male pork with high levels of boar taint considered “unfit for human consumption”. One possible technological strategy for improvement is the injection marination of entire male pork to help minimise the impact of boar taint and improve its marketability. The responses of 120 regular pork consumers, to entire males with high levels of boar taint and castrated pork, both injection-marinated, were evaluated. The results showed a similar response between entire and castrated male pork regardless of sex, and the detection of unpleasant odours and flavours (as farm/animal), thus offering a new alternative to the pork sector to mask the boar taint and revalue this pork. However, it was observed that consumer information on castration and animal welfare of entire male pork is scarce, and it is important to increase their knowledge so that they can place a value on this technological strategy with entire male pork and thus increase their purchase intention.

Dogs can detect an odor profile associated with Staphylococcus aureus biofilms in cultures and biological samples.

The study investigated the utilization of odor detection dogs to identify the odor profile of Staphylococcus aureus (S. aureus) biofilms in pure in vitro samples and in in vivo biosamples from animals and humans with S. aureus periprosthetic joint infection (PJI). Biofilms form when bacterial communities aggregate on orthopedic implants leading to recalcitrant infections that are difficult to treat. Identifying PJI biofilm infections is challenging, and traditional microbiological cultures may yield negative results even in the presence of clinical signs. Dogs were trained on pure in vitro S. aureus biofilms and tested on lacrimal fluid samples from an in vivo animal model (rabbits) and human patients with confirmed S. aureus PJI. The results demonstrated that dogs achieved a high degree of sensitivity and specificity in detecting the odor profile associated with S. aureus biofilms in rabbit samples. Preliminary results suggest that dogs can recognize S. aureus volatile organic compounds (VOCs) in human lacrimal fluid samples. Training odor detection dogs on in vitro S. aureus, may provide an alternative to obtaining clinical samples for training and mitigates biosecurity hazards. The findings hold promise for culture-independent diagnostics, enabling early disease detection, and improved antimicrobial stewardship. In conclusion, this research demonstrates that dogs trained on in vitro S. aureus samples can identify the consistent VOC profile of PJI S. aureus biofilm infections. The study opens avenues for further investigations into a retained VOC profile of S. aureus biofilm infection. These advancements could revolutionize infectious disease diagnosis and treatment, leading to better patient outcomes and addressing the global challenge of antimicrobial resistance.

Making sense of scents: Structural insights into odor detection

Making sense of scents: Structural insights into odor detection

Effect of wearing masks on odor detection and recognition

Background The effect of wearing masks on olfaction remains unclear. Objectives This study aimed to clarify the differences between the effects of no masks, surgical masks, and N95 respirator masks by conducting both identification and threshold olfaction tests. Methods Young, healthy volunteers aged ≥ 18 years and < 30 years without awareness of apparent olfactory disorder were included. All participants filled out a questionnaire on olfaction and completed an acuity smell identification test (Open Essence test) and an olfactory threshold test (T&T olfactometry) while wearing no masks, surgical masks, or N95 respirator masks. Results In the Open Essence tests, the no-mask group score was significantly higher than those of the surgical- and N95-mask groups. Using T&T olfactometry, the median-detection threshold of the no-mask group was significantly lower than that of the surgical-mask group, and the surgical-mask group threshold was significantly lower than that of the N95-mask group. Similar patterns were observed for the median-recognition threshold. Conclusions Wearing masks, especially an N95 mask, reduces the ability to detect and identify odors. This disadvantage should be considered by professionals such as healthcare workers, who require proper olfaction to perform appropriate tasks.

Electronic nose coupled with artificial neural network for classifying of coffee roasting profile

Coffee known for its diverse aromas shaped by postharvest treatments, particularly the roasting process, plays a pivotal role in determining the quality of the brewed beverage. This study focuses on classifying the aroma of Arabica coffee beans based on roasting temperature, employing an electronic nose equipped with a TGS gas array sensor. The classification methodology integrates deep learning through an artificial neural network (ANN), along with a calculation analysis utilizing the Pearson correlation coefficient. Raw Robusta coffee beans were subjected to five distinct roasting treatments (185 °C, 195 °C, 205 °C, 215 °C, and 225 °C), resulting in light roasts, light to medium roasts, medium to dark roasts, medium to dark roasts, and dark roasts. The repeatability test affirms the TGS sensor's reliability, exhibiting a standard deviation (STD) below 20%. Notably, the TGS 2612 and TGS 2611 sensors, dedicated to odor detection, demonstrated excellent validity with an STD below 10% across various roasting temperatures. Classification results from deep learning cross-validation showcase impressive accuracy: 98.2% for Light Roasts, 98.4% for Light to Medium Roasts, 98.8% for Medium Roasts, 97.8% for Medium Roasts, and 95.9% for Dark Roasts. In conclusion, this study reveals that the E-nose, utilizing the TGS gas sensor array with deep learning analysis, effectively detects and classifies coffee types based on roasting time with high accuracy.

Efficient Multifeature Extraction and Embedded Array Optimization for Drift-Calibrated Multisensor Odor Detection System

Efficient Multifeature Extraction and Embedded Array Optimization for Drift-Calibrated Multisensor Odor Detection System

Magnolol-driven microbiota modulation elicits changes in tryptophan metabolism resulting in reduced skatole formation in pigs

Skatole of gut origin has garnered significant attention as a malodorous pollutant due to its escalating emissions, recalcitrance to biodegradation and harm to animal and human health. Magnolol is a health-promoting polyphenol with potential to considerably mitigate the skatole production in the intestines. To investigate the impact of magnolol and its underlying mechanism on the skatole formation, in vivo and in vitro experiments were conducted in pigs. Our results revealed that skatole concentrations in the cecum, colon, and faeces decreased by 58.24% (P = 0.088), 44.98% (P < 0.05) and 43.52% (P < 0.05), respectively, following magnolol supplementation. Magnolol supplementation significantly decreased the abundance of Lachnospira, Faecalibacterium, Paramuribaculum, Faecalimonas, Desulfovibrio, Bariatricus, and Mogibacterium within the colon (P < 0.05). Moreover, a strong positive correlation (P < 0.05) between skatole concentration and Desulfovibrio abundance was observed. Subsequent in silico studies showed that magnolol could dock well with indolepyruvate decarboxylase (IPDC) within Desulfovibrio. Further in vitro investigation unveiled that magnolol addition led to less indole-3-pyruvate diverted towards the oxidative skatole pathway by the potential docking of magnolol towards IPDC, thereby diminishing the conversion of substrate into skatole. Our findings offer novel targets and strategies for mitigating skatole emission from the source.

Development of a modified C-BARQ for evaluating behavior in working dogs.

Current high demand for effective odor detection dogs calls for the development of reliable methods for measuring performance-related behavioral phenotypes in these highly specialized working animals. The Canine Behavioral Assessment & Research Questionnaire (C-BARQ) is a widely used behavioral assessment tool among working dog organizations with a demonstrated ability to predict success/failure of dogs in training. However, this instrument was developed originally to study the prevalence of behavior problems in the pet dog population, and it therefore lacks the capacity to measure specific behavioral propensities that may also be important predictors of working dog success. The current paper examines the factor structure, internal reliability, and content validity of a modified version of the C-BARQ designed to evaluate four new domains of canine behavior in addition to those encompassed by the original C-BARQ. These domains, labeled Playfulness, Impulsivity, Distractibility, and Basophobia (fear of falling), respectively, describe aspects of canine behavior or temperament which are believed to contribute substantially to working dog performance. Exploratory factor analysis (EFA) of owner/handler questionnaire responses based on a sample of 1,117 working odor detection dogs. A total of 15 factors were extracted by EFA, 10 of which correspond to original C-BARQ factors. The remaining 5 comprise the four new domains- Playfulness, Impulsivity, Distractibility, and Basophobia- as well as a fifth new factor labeled Food focus. The resulting Working Dog Canine Behavioral Assessment & Research Questionnaire (WDC-BARQ) successfully expands the measurement capacities of the original C-BARQ to include dimensions of behavior/temperament of particular relevance to many working dog populations.

Numerical Investigation of Odor-Guided Navigation in Flying Insects: Impact of Turbulence, Wingbeat-Induced Flow, and Schmidt Number on Odor Plume Structures.

Odor-guided navigation is fundamental to the survival and reproductive success of many flying insects. Despite its biological importance, the mechanics of how insects sense and interpret odor plumes in the presence of complex flow fields remain poorly understood. This study employs numerical simulations to investigate the influence of turbulence, wingbeat-induced flow, and Schmidt number on the structure and perception of odor plumes by flying insects. Using an in-house computational fluid dynamics solver based on the immersed-boundary method, we solve the three-dimensional Navier-Stokes equations to model the flow field. The solver is coupled with the equations of motion for passive flapping wings to emulate wingbeat-induced flow. The odor landscape is then determined by solving the odor advection-diffusion equation. By employing a synthetic isotropic turbulence generator, we introduce turbulence into the flow field to examine its impact on odor plume structures. Our findings reveal that both turbulence and wingbeat-induced flow substantially affect odor plume characteristics. Turbulence introduces fluctuations and perturbations in the plume, while wingbeat-induced flow draws the odorant closer to the insect's antennae. Moreover, we demonstrate that the Schmidt number, which affects odorant diffusivity, plays a significant role in odor detectability. Specifically, at high Schmidt numbers, larger fluctuations in odor sensitivity are observed, which may be exploited by insects to differentiate between various odorant volatiles emanating from the same source. This study provides new insights into the complex interplay between fluid dynamics and sensory biology and behavior, enhancing our understanding of how flying insects successfully navigate using olfactory cues in turbulent environments.

Scent on the wing: exploring flight effects on insect odor detection

Simulating the complex odor detection of fruit flies and the influence of flight speed and flapping frequency.

Odorant detection in a locust exhibits unusually low redundancy

Olfactory coding, from insects to humans, is canonically considered to involve considerable across-fiber coding already at the peripheral level, thereby allowing recognition of vast numbers of odor compounds. We show that the migratory locust has evolved an alternative strategy built on highly specific odorant receptors feeding into a complex primary processing center in the brain. By collecting odors from food and different life stages of the locust, we identified 205 ecologically relevant odorants, which we used to deorphanize 48 locust olfactory receptors via ectopic expression in Drosophila. Contrary to the often broadly tuned olfactory receptors of other insects, almost all locust receptors were found to be narrowly tuned to one or very few ligands. Knocking out a single receptor using CRISPR abolished physiological and behavioral responses to the corresponding ligand. We conclude that the locust olfactory system, with most olfactory receptors being narrowly tuned, differs from the so-far described olfactory systems.

Biosensors for Odor Detection: A Review.

Animals can easily detect hundreds of thousands of odors in the environment with high sensitivity and selectivity. With the progress of biological olfactory research, scientists have extracted multiple biomaterials and integrated them with different transducers thus generating numerous biosensors. Those biosensors inherit the sensing ability of living organisms and present excellent detection performance. In this paper, we mainly introduce odor biosensors based on substances from animal olfactory systems. Several instances of organ/tissue-based, cell-based, and protein-based biosensors are described and compared. Furthermore, we list some other biological materials such as peptide, nanovesicle, enzyme, and aptamer that are also utilized in odor biosensors. In addition, we illustrate the further developments of odor biosensors.

Gas-phase odor mixture quantification based on relative comparison method using multiple olfactory receptors

The gas-phase odor biosensors exhibit outstanding sensitivity and selectivity towards target ligands. Current odor detections, however, were only operated under one or multiple separated olfactory receptors (ORs) stimulated by a single component odor. Meanwhile, the nonlinear characteristic, drift, and aging problems in biosensors were the main barriers for better quantification performance. Here, we proposed a gas-phase odor biosensor for odor mixture quantification based on relative comparison method using cell expressing ORs, the liquid thickness control and liquid exchange maintained repeatable OR responses. We repeatedly compared the known and its adjacent unknown odor response thus mitigating the biosensor drift interference and sensor nonlinearity characteristic. We first conducted the odor quantification of one odor component in a mixture of five odors. The existence of other odors did not influence the quantification of Or56a towards geosmin component in the mixture. Then, two types of OR were utilized for quantifying odor mixture with or without adding the OR label information to the individual cells. With-label quantification was more precise and efficient than without-label one. Lastly, we simultaneously expressed two ORs on one cell line for wider detection range and quantified the mixture even if OR has cross sensitivity. We believe the odor mixture quantification methods established in this study will extend the application scenarios of odor biosensors especially in rapid on-site odor detection.

Drug-detecting bioelectronic nose based on odor cue memory combined with a brain computer interface

The international drug situation is increasingly, various new drugs are hidden in public places through changing forms and packaging, which brings new challenges to drug enforcement. This study proposes a drug-detecting bioelectronic nose based on odor cue memory combined with brain-computer interface and optogenetic regulation technologies. First, the rats were trained to generate positive memories of drug odors through food reward training, and multichannel microelectrodes were implanted into the DG region of the hippocampus for responsible memory retrieval, the spike signals of individual neurons and the local field potential signals of population neurons in the brain region were collected for pattern recognition and analysis. Preliminary experimental results have shown that when low-dose drugs are buried in a hidden area, rats can find the location of the drugs in a very short time, and when close to the relevant area, there is a significant change in the energy value and time-frequency spectrum signal coupling of the returned data, which can be extracted to indicate that the rats have found the drugs. Second, we labled the neuronal activity marker c-fos and revealed more robust activation in the DG region following odor detection. We modulated these neurons through neuroregulatory technology, so that the rats could recognize drugs by retrieving memories more quickly. We conceive that the drug-detecting rat robot can detect trace amounts of various drugs in complex terrain and multiple scenes, which is of great significance for anti-drug work in the future.

A versatile odor detection system based on automatically trained rats for chemical sensing

We report a versatile odor detection system that employs rats trained through automated operant conditioning paradigms. While detection animals possess remarkable olfactory capabilities, their practical use has been limited by non-automated training methods, which involve lengthy training periods, high costs, handler dependency, and low reliability. Our primary research goal was to develop detection animals using a fully automated system. To achieve this, we employed four distinct operant conditioning approaches to train four rats (Numbers 3, 7, 10, and 12) in an automated apparatus for detecting 2,4-dinitrotoluene (DNT). Our system performed exceptionally well, with DNT-trained rats achieving a 95 % accuracy rate, 99 % sensitivity, 91 % specificity, 92 % positive predictive value (PPV), and 99 % negative predictive value (NPV) across 380 tests. Additionally, we observed a linear decrease in response time as DNT concentration increased from 20 parts per billion (ppb) to 1000 ppb, indicating the system's potential for quantitative odor concentration measurement. Impressively, the rats retained their odor discrimination skills for up to four months after their last training session, underscoring the durability of their olfactory memory. Our study introduces a novel, highly effective system for specific odorant component detection, offering a faster, more reliable, and accurate method for distinguishing between various odors.

An electronic nose based on adaptive fusion of transformer-ELM with active temperature modulation algorithm for accurate odor detection in refrigerators

Accurate detection of food spoilage in refrigerators is crucial for ensuring food freshness and safety. However, due to the wide variety of gases emitted by decaying food and their uneven distribution of gases within the refrigerator, current mixed odor detection methods are not satisfactory. This study proposes a dedicated algorithm for a refrigerator electronic nose that enables precise classification of mixed food odors and prediction of their intensity. To achieve this objective, a dataset of food odor samples was collected from refrigerators, and sensory identification as well as gas chromatography-mass spectrometry analysis were performed to obtain freshness and intensity labels. The developed electronic nose algorithm incorporates key techniques, including active temperature modulation and an adaptive fusion model of lightweight Transformer-ELM, to enhance sensitivity, selectivity, and global modeling capabilities for identifying abnormal odors in volatile compounds of mixed gases. Experimental evaluations on a large-scale dataset demonstrate the effectiveness of the proposed method in classifying refrigerated food freshness and predicting odor intensity. This research contributes to the field of electronic nose technology and has potential for applications beyond refrigerator odor detection.

Identification, Quantitation, and Sensory Evaluation of Thiols in Bordeaux Red Wine with Characteristic Aging Bouquet.

Great Bordeaux red wines are known for their distinctive aging bouquet. However, the nature of volatile chemicals underpinning this sensory expression is not fully understood. This work investigated the empyreumatic aging bouquet of a collection of premium Bordeaux red wines using silver-ion (Ag+) solid-phase extraction, cryogenic heart-cutting multidimensional gas chromatography mass spectrometry/olfactometry, and comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry. In doing so, a substantial number of "meaty" odors were revealed. Three detected "meaty" notes were tentatively or unequivocally attributed to furan thiols. Among them, 2-methyltetrahydrofuran-3-thiol (1) with a pleasant "meaty" aroma was reported in wine for the first time. Its trans isomer (trans-1a) was resolved from its racemate by chemical modification, which confirmed its presence in wine. The odor detection threshold of trans-1a in the model wine was determined at 55 ng/L. Moreover, an additive effect between 1 and literature-known 2-methyl-3-furanthiol was observed. By a new ultra high-performance liquid chromatography quadrupole Orbitrap high-resolution mass spectrometry method, the concentration of trans-1a, in addition to those of 2-methyl-3-furanthiol and 2-furfuryl thiol, was measured in the wines at ng/L levels.

Method Comparison for the Identification and Characterization of Odorants from Scots Pine (Pinus sylvestris L.) and Oriented Strand Boards (OSB) Made Thereof by GC-MS and GC-FID/O Using Different Headspace Techniques

Volatile organic compounds (VOCs) from wood and wood composites are important contributors to odor profiles of indoor environments and can significantly influence human health and well-being. GC-MS/FID and gas chromatography (GC) with olfactometric detection (GC-O) are employed for the identification and characterization of odorants. Four different sample preparation methods are evaluated on wood strands and isocyanate adhesive–based oriented strand boards (OSBs) made from Pinus sylvestris L.: among these, dynamic headspace extraction thermal desorption ((dynamic) HS-TD), head space solid phase microextraction (HS-SPME), head space solid phase microextraction Arrow (HS-SPME Arrow), and liquid injection of a CH2Cl2 solvent extract. The olfactometric investigation revealed over 30 odor-active substances of cyclic and acyclic monoterpene, monoterpenoid ketone, monoterpenoid aldehyde, monoterpenoid alcohol, monoterpenoid ester, aliphatic aldehyde, alcohol, and acid and phenolic chemistry. Compared to liquid injection, (dynamic) HS-TD was found to result in a similar number of odorants (20 vs. 24), whereas HS SPME Arrow shows good performance with minimal instrumental effort, notably for monoterpene and aldehyde compounds. Native wood vs. OSB showed high concentrations of saturated and unsaturated aldehydes for the wood board sample. These findings demonstrate the capability of headspace methods for odorant detection and their suitability for standardization towards a database for wood and wood composites.