Predicting Odor Pleasantness with an Electronic Nose

A primary goal for artificial nose (eNose) technology is to report perceptual qualities of novel odors. Currently, however, eNoses primarily detect and discriminate between odorants they previously “learned”. We tuned an eNose to human odor pleasantness estimates. We then used the eNose to predict the pleasantness of novel odorants, and tested these predictions in naïve subjects who had not participated in the tuning procedure. We found that our apparatus generated odorant pleasantness ratings with above 80% similarity to average human ratings, and with above 90% accuracy at discriminating between categorically pleasant or unpleasant odorants. Similar results were obtained in two cultures, native Israeli and native Ethiopian, without retuning of the apparatus. These findings suggest that unlike in vision and audition, in olfaction there is a systematic predictable link between stimulus structure and stimulus pleasantness. This goes in contrast to the popular notion that odorant pleasantness is completely subjective, and may provide a new method for odor screening and environmental monitoring, as well as a critical building block for digital transmission of smell.     

Fruit Volatile Analysis Using an Electronic Nose

Numerous and diverse physiological changes occur during fruit ripening, including the development of a specific volatile blend that characterizes fruit aroma. Maturity at harvest is one of the key factors influencing the flavor quality of fruits and vegetables¹. The validation of robust methods that rapidly assess fruit maturity and aroma quality would allow improved management of advanced breeding programs, production practices and postharvest handling. Over the last three decades, much research has been conducted to develop so-called electronic noses, which are devices able to rapidly detect odors and flavors^2-4. Currently there are several commercially available electronic noses able to perform volatile analysis, based on different technologies. The electronic nose used in our work (zNose, EST, Newbury Park, CA, USA), consists of ultra-fast gas chromatography coupled with a surface acoustic wave sensor (UFGC-SAW). This technology has already been tested for its ability to monitor quality of various commodities, including detection of deterioration in apple⁵; ripeness and rot evaluation in mango⁶; aroma profiling of thymus species⁷; C₆ volatile compounds in grape berries⁸; characterization of vegetable oil⁹ and detection of adulterants in virgin coconut oil¹⁰. This system can perform the three major steps of aroma analysis: headspace sampling, separation of volatile compounds, and detection. In about one minute, the output, a chromatogram, is produced and, after a purging cycle, the instrument is ready for further analysis. The results obtained with the zNose can be compared to those of other gas-chromatographic systems by calculation of Kovats Indices (KI). Once the instrument has been tuned with an alkane standard solution, the retention times are automatically converted into KIs. However, slight changes in temperature and flow rate are expected to occur over time, causing retention times to drift. Also, depending on the polarity of the column stationary phase, the reproducibility of KI calculations can vary by several index units¹¹. A series of programs and graphical interfaces were therefore developed to compare calculated KIs among samples in a semi-automated fashion. These programs reduce the time required for chromatogram analysis of large data sets and minimize the potential for misinterpretation of the data when chromatograms are not perfectly aligned.We present a method for rapid volatile compound analysis in fruit. Sample preparation, data acquisition and handling procedures are also discussed.     

Analysis of Medication Off-odors Using an Electronic Nose

Packaging materials have been implicated as a source for off-odorsin pharmaceutical products. A new instrumentation method employingan array of conducting polymer gas sensors was used to identifythe offending packaging components in the canister of a pharmaceuticalinhalant. A case study is described in which tainted inhalersas well as elastomeric components of the canisters were ‘sniffed’by the electronic nose. The electronic nose was able to differentiatebetween tainted and untainted canisters. Signal processing algorithmsperformed on the raw data from the sensors suggested that specificelastomeric components were responsible for the off-odor. Afurther experiment suggested that the propellant (Freon) extractedthe odor from the elastomeric components as the medication wasexpelled from the canister. These data indicate that the electronicnose is a potential tool to solve odor problems in which humanodor assessment is not feasible due to excess exposure to themedically active ingredient. Chem. Senses 22: 119–128,1997.     

Identification of Stink Bugs Using an Electronic Nose

Stink bugs are recognized as pests of several economically important crops, including cotton, soybean and a variety of tree fruits. The Cyranose 320 was used for the classified investigation of stink bug. Stink bugs including males and females of the southern green stink bugs, Nezara viridula, were collected from crop fields around College Station, TX. Results show that the released chemicals and chemical intensity are both critical factors, which determine the rate that the Cyranose 320 correctly identified the stink bugs. The Cyranose 320 shows significant potential in identifying stink bugs, and can classify stink bug samples by species and gender.     

利用电子鼻评价桃果实香气

为了明确不同桃品种资源果实香气差异,对桃果实香气评价和品质改良提供参考,本研究利用电子鼻系统对桃品种资源果实整果香气进行测定和区分.通过PEN 3.5电子鼻系统采集74份不同品种资源桃果实芳香成分并得到了不同传感器的响应值,采用主成分(PCA)、线性判别法(LDA)和负荷加载(LO)方法分析数据.LO分析结果显示,硫化...     

Rapid Identification of Rice Samples Using an Electronic Nose

Four rice samples of long grain type were tested using an electronic nose (Cyranose-320).Samples of 5 g of each variety ofrice were placed individually in vials and were analyzed with the electronic nose unit consisting of 32 polymer sensors.TheCyranose-320 was able to differentiate between varieties of rice.The chemical composition of the rice odors for differentiatingrice samples needs to be investigated.The optimum parameter settings should be considered during the Cyranose-320 trainingprocess especially for multiple samples,which are helpful for obtaining an accurate training model to improve identificationcapability.Further,it is necessary to investigate the E-nose sensor selection for obtaining better classification accuracy.A re-duced number of sensors could potentially shorten the data processing time,and could be used to establish an application pro-cedure and reduce the cost for a specific electronic nose.Further research is needed for developing analytical procedures thatadapt the Cyranose-320 as a tool for testing rice quality.     

Comparison of Algorithms for an Electronic Nose in Identifying Liquors

When the electronic nose is used to identify different varieties of distilled liquors, the pattern recognition algorithm is chosen on the basis of the experience, which lacks the guiding principle. In this research, the different brands of distilled spirits were identified using the pattern recognition algorithms （principal component analysis and the artificial neural network）. The recognition rates of different algorithms were compared. The recognition rate of the Back Propagation Neural Network （BPNN） is the highest. Owing to the slow convergence speed of the BPNN, it tends easily to get into a local minimum. A chaotic BPNN was tried in order to overcome the disadvantage of the BPNN. The convergence speed of the chaotic BPNN is 75.5 times faster than that of the BPNN.     

Electronic Nose with an Air Sensor Matrix for Detecting Beef Freshness

China is one of the largest meat producing countries in the wodd. With the growing concern for food safety more attention has been paid to meat quality. The application of conventional test methods for meat quality is limited by many factors, and subjectiveness, such as longer time to prepare samples and to test. A sensor matrix was constructed with several separate air sensors, and tests were conducted to detect the freshness of the beef. The results show that the air sensors TGS2610, TGS2600, TGS2611, TGS2620 and TGS2602 made by Tianjin Figaro Electronic Co, Ltd could be used to determine the degree of freshness but TGS2442 is not suitable. This study provides a foundation for designing and making an economical and practical detector for beef freshness.     

Physiologically Motivated Monitoring of Fermentation Processes by Means of an Electronic Nose

An on‐line approach of non‐invasive monitoring of the physiological changes in fermentation processes is presented. In yeast batch and bacterial fed‐batch fermentations it is shown that metabolic state changes can be revealed using an electronic nose. The transient responses of the gas sensors to the changes in the composition of the volatiles emitted from the cell cultures during fermentation are used to retrieve a semi‐quantitative representation of the physiological state of the cultures. With the sensor responses of the electronic nose it is shown that physiological variables such as rates of growth, substrate uptake and product formation can be depicted. The non‐invasive method thus seems as a pertinent alternative to conventional bioreactor monitoring methods.     

Using the Electronic Nose to Identify Airway Infection during COPD Exacerbations

Background

The electronic nose (e-nose) detects volatile organic compounds (VOCs) in exhaled air. We hypothesized that the exhaled VOCs print is different in stable vs. exacerbated patients with chronic obstructive pulmonary disease (COPD), particularly if the latter is associated with airway bacterial infection, and that the e-nose can distinguish them.

Methods

Smell-prints of the bacteria most commonly involved in exacerbations of COPD (ECOPD) were identified in vitro. Subsequently, we tested our hypothesis in 93 patients with ECOPD, 19 of them with pneumonia, 50 with stable COPD and 30 healthy controls in a cross-sectional case-controlled study. Secondly, ECOPD patients were re-studied after 2 months if clinically stable. Exhaled air was collected within a Tedlar bag and processed by a Cynarose 320 e-nose. Breath-prints were analyzed by Linear Discriminant Analysis (LDA) with “One Out” technique and Sensor logic Relations (SLR). Sputum samples were collected for culture.

Results

ECOPD with evidence of infection were significantly distinguishable from non-infected ECOPD (p = 0.018), with better accuracy when ECOPD was associated to pneumonia. The same patients with ECOPD were significantly distinguishable from stable COPD during follow-up (p = 0.018), unless the patient was colonized. Additionally, breath-prints from COPD patients were significantly distinguished from healthy controls. Various bacteria species were identified in culture but the e-nose was unable to identify accurately the bacteria smell-print in infected patients.

Conclusion

E-nose can identify ECOPD, especially if associated with airway bacterial infection or pneumonia.     

Bioactive Attributes and Analysis of Electronic Nose Feature Signals of Colombian Stingless Bees Propolis

The volatile and non-volatile chemical composition and bioactivity of propolis from the species Apis mellifera has been widely studied, but there is very little knowledge regarding propolis of other bee species, which ultimately hinders their differentiation and potential use. In this work, 53 propolis samples of A. mellifera and four stingless bee species (Frieseomielitta sp., Melipona eburnea, Melipona sp., and Trigona sp.) were collected in Colombia. An electronic nose with 10 metal oxide semiconductor sensors (MOS) was used to generate a pattern of the representative volatile compounds of the samples. Ethanolic extracts were obtained to assess their antioxidant activity towards DPPH radical and ABTS radical cation, total phenolics, and color (CIELAB space). The results showed an overall similarity of the aromatic profiles between species. The antioxidant activity of Frieseomielitta sp. propolis was higher than that of A. mellifera and the other species, in correspondence with a higher phenolic content. CIELAB color parameter b* was the most differentiating variable among samples, indicating a variation of propolis colors between red and yellow. By combining the data from physico-chemical analysis and aromatic profile, it was possible to differentiate the propolis from each bee species, with the exception of those from Melipona sp. and Trigona sp., indicating their similarity. These results have practical significance since they are a starting point to recognizing and valuing native stingless bee propolis and their bioactive potential, which, in addition to geographical differentiation and further quality parameters evaluation, will enhance their commercial exploitation.     

Bionic Layout Optimization of Sensor Array in Electronic Nose for Oil Shale Pyrolysis Process Detection

In order to meet the requirements for miniaturization detection of oil shale pyrolysis process and solve the problem of low sensitivity of oil and gas detection...     

Using an Electronic Nose to Rapidly Assess Grandlure Content in Boll Weevil Pheromone Lures

Samples of pheromone lures used in boll weevil,Anthonomus grandis (Boheman),eradication programs are routinely analyzed by Gas Chromatography (GC) to ensure lures are adequately dosed with grandlure,the synthetic aggregation pheromone produced by male weevils.However,preparation of GC samples is tedious,time consuming,and requires a moderate level of experience.We examined the use of a commercially-available electronic nose (e-nose) for rapidly assessing the grandlure contents of lures.The e-nose was trained to recognize headspace collections of grandlure emitted from new lures and after lures were aged under field conditions for 4 d,7 d,10 d,and 14 d.Based on cross-validation of the training set,the e-nose was 82％accurate in discriminating among the different age classes of lures.Upon sampling headspace collections of pheromone from a different set of field-aged lures,the e-nose was ＜50％ accurate in discriminating 4 d,7 d,and 10 d aged lures from the other ageclasses of lures.However,the e-nose identified new and 14 d aged lure samples with 100％ accuracy.In light of these findings,e-nose technology shows considerable promise as an alternative approach for rapidly assessing the initial grandlure contents of lures used in boll weevil eradication programs.     

On-Line Detection of Microbial Contaminations in Animal Cell Reactor Cultures Using an Electronic Nose Device

An electronic nose (EN) device was used to detect microbial and viral contaminations in a variety of animal cell culture systems. The emission of volatile components from the cultures accumulated in the bioreactor headspace, was sampled and subsequently analysed by the EN device. The EN, which was equipped with an array of 17 chemical gas sensors of varying selectivity towards the sampled volatile molecules, generated response patterns of up to 85 computed signals. Each 15 or 20 min a new gas sample was taken generating a new response pattern. A software evaluation tool visualised the data mainly by using principal component analysis. The EN was first used to detect microbial contaminations in a Chinese hamster ovary (CHO) cell line producing a recombinant human macrophage colony stimulating factor (rhM-CSF). The CHO cell culture was contaminated by Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus and Candida utilis which all were detected. The response patterns from the CHO cell culture were compared with monoculture references of the microorganisms. Second, contaminations were studied in an Sf-9 insect cell culture producing another recombinant protein (VP2 protein). Contaminants were detected from E. coli, a filamentous fungus and a baculovirus. Third, contamination of a human cell line, HEK-293, infected with E. coli exhibited comparable results. Fourth, bacterial contaminations could also be detected in cultures of a MLV vector producer cell line. Based on the overall experiences in this study it is concluded that the EN method has in a number of cases the potential to be developed into a useful on-line contamination alarm in order to support safety and economical operation for industrial cultivation.     

Rapid and Accurate Detection of Urinary Pathogens by Mobile IMS-Based Electronic Nose: A Proof-of-Principle Study

Urinary tract infection (UTI) is a common disease with significant morbidity and economic burden, accounting for a significant part of the workload in clinical microbiology laboratories. Current clinical chemisty point-of-care diagnostics rely on imperfect dipstick analysis which only provides indirect and insensitive evidence of urinary bacterial pathogens. An electronic nose (eNose) is a handheld device mimicking mammalian olfaction that potentially offers affordable and rapid analysis of samples without preparation at athmospheric pressure. In this study we demonstrate the applicability of ion mobility spectrometry (IMS) –based eNose to discriminate the most common UTI pathogens from gaseous headspace of culture plates rapidly and without sample preparation. We gathered a total of 101 culture samples containing four most common UTI bacteries: E. coli, S. saprophyticus, E. faecalis, Klebsiella spp and sterile culture plates. The samples were analyzed using ChemPro 100i device, consisting of IMS cell and six semiconductor sensors. Data analysis was conducted by linear discriminant analysis (LDA) and logistic regression (LR). The results were validated by leave-one-out and 5-fold cross validation analysis. In discrimination of sterile and bacterial samples sensitivity of 95% and specificity of 97% were achieved. The bacterial species were identified with sensitivity of 95% and specificity of 96% using eNose as compared to urine bacterial cultures. In conclusion: These findings strongly demonstrate the ability of our eNose to discriminate bacterial cultures and provides a proof of principle to use this method in urinanalysis of UTI.     

A Simple,Low-Cost Conductive Composite Material for 3D Printing of Electronic Sensors

3D printing technology can produce complex objects directly from computer aided digital designs. The technology has traditionally been used by large companies to produce fit and form concept prototypes (‘rapid prototyping’) before production. In recent years however there has been a move to adopt the technology as full-scale manufacturing solution. The advent of low-cost, desktop 3D printers such as the RepRap and emoH@baF has meant a wider user base are now able to have access to desktop manufacturing platforms enabling them to produce highly customised products for personal use and sale. This uptake in usage has been coupled with a demand for printing technology and materials able to print functional elements such as electronic sensors. Here we present formulation of a simple conductive thermoplastic composite we term ‘carbomorph’ and demonstrate how it can be used in an unmodified low-cost 3D printer to print electronic sensors able to sense mechanical flexing and capacitance changes. We show how this capability can be used to produce custom sensing devices and user interface devices along with printed objects with embedded sensing capability. This advance in low-cost 3D printing with offer a new paradigm in the 3D printing field with printed sensors and electronics embedded inside 3D printed objects in a single build process without requiring complex or expensive materials incorporating additives such as carbon nanotubes.     

Smelling the Diagnosis: The Electronic Nose as Diagnostic Tool in Inflammatory Arthritis. A Case-Reference Study

Objective

To investigate whether exhaled breath analysis using an electronic nose can identify differences between inflammatory joint diseases and healthy controls.

Methods

In a cross-sectional study, the exhaled breath of 21 rheumatoid arthritis (RA) and 18 psoriatic arthritis (PsA) patients with active disease was compared to 21 healthy controls using an electronic nose (Cyranose 320; Smiths Detection, Pasadena, CA, USA). Breathprints were analyzed with principal component analysis, discriminant analysis, and area under curve (AUC) of receiver operating characteristics (ROC) curves. Volatile organic compounds (VOCs) were identified by gas chromatography and mass spectrometry (GC-MS), and relationships between breathprints and markers of disease activity were explored.

Results

Breathprints of RA patients could be distinguished from controls with an accuracy of 71% (AUC 0.75, 95% CI 0.60–0.90, sensitivity 76%, specificity 67%). Breathprints from PsA patients were separated from controls with 69% accuracy (AUC 0.77, 95% CI 0.61–0.92, sensitivity 72%, specificity 71%). Distinction between exhaled breath of RA and PsA patients exhibited an accuracy of 69% (AUC 0.72, 95% CI 0.55–0.89, sensitivity 71%, specificity 72%). There was a positive correlation in RA patients of exhaled breathprints with disease activity score (DAS28) and number of painful joints. GC-MS identified seven key VOCs that significantly differed between the groups.

Conclusions

Exhaled breath analysis by an electronic nose may play a role in differential diagnosis of inflammatory joint diseases. Data from this study warrant external validation.