Experimental Demonstration of Masking Phenomena between Competing Odorants via an Air Dilution Sensory Test

To simulate the occurrence of masking phenomena with the aid of an air dilution sensory (ADS) test, two types of odorant mixtures were prepared: (1) M2 with two individual odorants [H2S and acetaldehyde (AA)] and (2) M6 with six individual odorants (H2S and five aldehydes). The test results derived for samples containing single individual odorants at a wide range of concentrations are initially used to define the empirical relationship between the dilution-to-threshold (D/T) ratio and odor intensity (OI) scaling. Based on these relationships, the D/T ratios were estimated for each odorant with the same intensity as the synthetic mixture. The relative contribution of each odorant to such mixture is then assessed by comparing the estimated and measured D/T values. This stepwise test confirmed the dominance of certain compounds at a given OI rating. In the case of M2, H2S showed sensitive detection at high OI range, while AA did so at low end. The pattern of a competing relationship is also seen consistently from M6 between AA (low) and iso-valeraldehyde (IA: high OI range). The overall results thus suggest that the masking phenomena between strong odorants should proceed under competing relationships, if released at the same time

The Averaging Effect of Odorant Mixing as Determined by Air Dilution Sensory Tests: A Case Study on Reduced Sulfur Compounds

To learn more about the effects of mixing different odorants, a series of air dilution sensory (ADS) tests were conducted using four reduced sulfur compounds [RSC: hydrogen sulfide (H2S), methanethiol (CH3SH), dimethylsulfide (DMS), and dimethyldisulfide (DMDS)] at varying concentration levels. The tests were initially conducted by analyzing samples containing single individual RSCs at a wide range of concentrations. The resulting data were then evaluated to define the empirical relationship for each RSC between the dilution-to-threshold (D/T) ratio and odor intensity (OI) scaling. Based on the relationships defined for each individual RSC, the D/T ratios were estimated for a synthetic mixture of four RSCs. The effect of mixing was then examined by assessing the relative contribution of each RSC to those estimates with the aid of the actually measured D/T values. This stepwise test confirmed that the odor intensity of the synthetic mixture is not governed by the common theoretical basis (e.g., rule of additivity, synergism, or a stronger component model) but is best represented by the averaged contribution of all RSC components. The overall results of this study thus suggest that the mixing phenomenon between odorants with similar chemical properties (like RSC family) can be characterized by the averaging effect of all participants

Effect of Functional Group and Carbon Chain Length on the Odor Detection Threshold of Aliphatic Compounds

Odor detection thresholds (ODTs) are used for assessing outdoor and indoor air quality. They are obtained experimentally by olfactometry and psychophysical methods, and large compilations are available in the literature. A non-linear regression equation was fitted to describe the ODT variability of 114 aliphatic compounds based on the alkyl chain length for different homologous series (carboxylic acids, aldehydes, 2-ketones, esters, 1-alcohols, amines, thiols, thioethers and hydrocarbons). The resulting equation reveals an effect of the functional group, molecular size and also an interaction between both factors. Although the mechanistic interpretation of results is uncertain, the relatively high goodness-of-fit (R2 = 0.90) suggests that ODT values of aliphatic compounds can be predicted rather accurately, which is not the case for rigid molecules. This equation may serve as a basis for the development of more complex ODT models taking into account diverse structural features of odorants. The variability of power-law exponents was also investigated for the homologous series

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

Recovery of Agricultural Odors and Odorous Compounds from Polyvinyl Fluoride Film Bags

Accurate sampling methods are necessary when quantifying odor and volatile organic compound emissions at agricultural facilities. The commonly accepted methodology in the U.S. has been to collect odor samples in polyvinyl fluoride bags (PVF, brand name Tedlar®) and, subsequently, analyze with human panelists using dynamic triangular forced-choice olfactometry. The purpose of this research was to simultaneously quantify and compare recoveries of odor and odorous compounds from both commercial and homemade PVF sampling bags. A standard gas mixture consisting of p-cresol (40 μg m−3) and seven volatile fatty acids: acetic (2,311 μg m−3), propionic (15,800 μg m−3), isobutyric (1,686 μg m−3), butyric (1,049 μg m−3), isovaleric (1,236 μg m−3), valeric (643 μg m−3), and hexanoic (2,158 μg m−3) was placed in the PVF bags at times of 1 h, 1 d, 2 d, 3 d, and 7 d prior to compound and odor concentration analyses. Compound concentrations were quantified using sorbent tubes and gas chromatography/mass spectrometry. Odor concentration, intensity, and hedonic tone were measured using a panel of trained human subjects. Compound recoveries ranged from 2 to 40% after 1 h and 0 to 14% after 7 d. Between 1 h and 7 d, odor concentrations increased by 45% in commercial bags, and decreased by 39% in homemade bags. Minimal changes were observed in intensity and hedonic tone over the same time period. These results suggest that PVF bags can bias individual compound concentrations and odor as measured by dynamic triangular forced-choice olfactometry

Expression of multidisciplinary flavour science : proceedings of the 12th Weurman Symposium

The 12th Weurman Flavour Research Symposium contributed 177 lectures and posters to the wealth of flavor knowledge; these were presented in eight sessions: biology, retention and release, psychophysics, quality, thermal generation, bioflavors, impact molecules, and analytics. Emerging topics were discussed in three workshops dealing with flavor and health, in vivo flavor research, and flavor metabolomics. It has been an excellent forum for passionate exchange of recent results obtained in traditional and emerging fields of flavor research. The symposium allowed coverage of the broad diversity of flavor-related topics: comprising odor and taste; applying targeted and holistic approaches; using sensorial, chemical, biological, physical, and chemometric techniques; as well as considering nutrition and health aspects

Expression of multidisciplinary flavour science : proceedings of the 12th Weurman Symposium

The 12th Weurman Flavour Research Symposium contributed 177 lectures and posters to the wealth of flavor knowledge; these were presented in eight sessions: biology, retention and release, psychophysics, quality, thermal generation, bioflavors, impact molecules, and analytics. Emerging topics were discussed in three workshops dealing with flavor and health, in vivo flavor research, and flavor metabolomics. It has been an excellent forum for passionate exchange of recent results obtained in traditional and emerging fields of flavor research. The symposium allowed coverage of the broad diversity of flavor-related topics: comprising odor and taste; applying targeted and holistic approaches; using sensorial, chemical, biological, physical, and chemometric techniques; as well as considering nutrition and health aspects

Intelligent classification of ammonia concentration based on odor profile

This thesis presents the intelligent classification of ammonia concentration based on the standard of oil and gas industries wastewater discharge. The intelligent classification using signal processing is a well-known technique in many applications and as well in the oil and gas industry. The intelligent classification technique for ammonia concentration classification is a demanding technique especially in the environmental sector. Ammonia solution properties and ammonia solution preparations were studied in this thesis which commonly used in industry. The objectives of this thesis are to develop an intelligence classification of ammonia concentration based on the oil and gas industry wastewater discharge schedule and to analyze performance of the intelligent classification of ammonia concentration based on the oil and gas industry wastewater discharge schedule. In this thesis the ammonia odor profile has been pre-identified by chemist using four sensor array. The ammonia concentration was validated using a commercialized gas sensor and spectrophotometer to cross-validated e-nose instrument. The odor profile from two different samples; high (20 ppm and 25 ppm) and low (5 ppm, 10 ppm and 1 5ppm) concentration that have been normalized and visualized in a 2D plot to extract the unique patterns. The variance of the low and high concentration of ammonia odor profile has been identified as different group samples. This group samples have been analyzed statistically using Boxplot, calibration curve and proximity matrix, The thesis describes the statistical techniques to visualize the pattern and using mean features to classify between the low and high concentration. Two intelligent classification techniques have been used which are Artificial Neural Network (ANN) using the back-propagation approaches and then, the result of ANN model was cross-validated.using CBR. Both ANN model and CBR classifier have been measured using several performance measures. From the results, it is observed that ANN model and CBR classifier are capable of classifying 100% of ammonia concentration odor profile from the water. The results can also significantly reduce the cost and time, and improve product reliability and customer confidence

Development of a Portable Electronic Nose System for the Detection and Classification of Fruity Odors

In this study, we have developed a prototype of a portable electronic nose (E-Nose) comprising a sensor array of eight commercially available sensors, a data acquisition interface PCB, and a microprocessor. Verification software was developed to verify system functions. Experimental results indicate that the proposed system prototype is able to identify the fragrance of three fruits, namely lemon, banana, and litchi