An algorithm for 353 odor detection thresholds in humans

Predicting odor profile of food from its chemical composition: Towards an approach based on artificial intelligence and flavorists expertise

Odor is central to food quality. Still, a major challenge is to understand how the odorants present in a given food contribute to its specific odor profile, and how to predict this olfactory outcome from the chemical composition. In this proof-of-concept study, we seek to develop an integrative model that combines expert knowledge, fuzzy logic, and machine learning to predict the quantitative odor description of complex mixtures of odorants. The model output is the intensity of relevant odor sensory attributes calculated on the basis of the content in odor-active comounds. The core of the model is the mathematically formalized knowledge of four senior flavorists, which provided a set of optimized rules describing the sensory-relevant combinations of odor qualities the experts have in mind to elaborate the target odor sensory attributes. The model first queries analytical and sensory databases in order to standardize, homogenize, and quantitatively code the odor descriptors of the odorants. Then the standardized odor descriptors are translated into a limited number of odor qualities used by the experts thanks to an ontology. A third step consists of aggregating all the information in terms of odor qualities across all the odorants found in a given product. The final step is a set of knowledge-based fuzzy membership functions representing the flavorist expertise and ensuring the prediction of the intensity of the target odor sensory descriptors on the basis of the products' aggregated odor qualities; several methods of optimization of the fuzzy membership functions have been tested. Finally, the model was applied to predict the odor profile of 16 red wines from two grape varieties for which the content in odorants was available. The results showed that the model can predict the perceptual outcome of food odor with a certain level of accuracy, and may also provide insights into combinations of odorants not mentioned by the experts.

Nontargeted Metabolite Profiling of the Most Prominent Indian Mango (Mangifera indica L.) Cultivars Using Different Extraction Methods

Aroma has a crucial role in assessing the quality of fresh fruit and its processed versions, which serve as reliable indications for advancing local cultivars in the mango industry. The aroma of mango is attributed to a complex of hundreds of volatile, polar, and nonpolar metabolites belonging to different chemical classes like monoterpenes, sesquiterpenes, nonterpene hydrocarbons (alkanes), alcohols, esters, fatty acids, aldehydes, lactones, amides, amines, ethers, and many more. This study looked at the volatile, nonpolar, and polar metabolites from 16 mango cultivars to determine their relative quantities and intervarietal changes using hexane, ethanol, and solid-phase microextraction (SPME), followed by gas chromatography-mass spectrometry (GC-MS) analysis. In total, 58 volatile compounds through SPME, 50 nonpolar metabolites from hexane extract, and 52 polar metabolites from ethanol extract were detected from all of the cultivars, belonging to various chemical classes. Through the SPME method, all 16 mango cultivars except Dashehari and Neelum exhibited abundant monoterpenes with maximum concentration in Kesar (91.00%) and minimum in Amrapali (60.66%). However, the abundance of fatty acids and sesquiterpenes was detected in Dashehari (37.91%) and Neelum (74.80%), respectively. In the hexane extract, 23 nonterpene hydrocarbons exhibited abundance in all 16 mango cultivars except Baneshan, with a higher concentration in Dashehari (95.45%) and lower in Ratna (77.63%). The ethanol extraction of 16 mango cultivars showed a higher concentration of esters, aldehydes, alcohols, and amides in Jamadar (52.16%), Dadamio (74.30%), Langra (64.38%), and Kesar (37.10%), respectively. There have been a lot of metabolite variations observed and analyzed using hierarchical cluster analysis (HCA) and principal component analysis (PCA) based on the similarity of various chemical compounds. Cluster analysis revealed the true similarity and pedigree of different mango cultivars, viz., Neeleswari, Dashehari, Neelum, Alphonso, Baneshan, Sonpari, and Neeleshan. They occupied the same cluster during analysis.

A principal odor map unifies diverse tasks in olfactory perception

Mapping molecular structure to odor perception is a key challenge in olfaction. We used graph neural networks to generate a principal odor map (POM) that preserves perceptual relationships and enables odor quality prediction for previously uncharacterized odorants. The model was as reliable as a human in describing odor quality: On a prospective validation set of 400 out-of-sample odorants, the model-generated odor profile more closely matched the trained panel mean than did the median panelist. By applying simple, interpretable, theoretically rooted transformations, the POM outperformed chemoinformatic models on several other odor prediction tasks, indicating that the POM successfully encoded a generalized map of structure-odor relationships. This approach broadly enables odor prediction and paves the way toward digitizing odors.

Indoor Air Quality-An Overview of Methods for Measuring Odor Detection Thresholds of Single Substances

Odor evaluation is an important topic in the field of indoor air quality. Odor detection threshold (ODT) values are used to derive limit values like odor guide values or odor activity value. However, ODT values for the same substance available in compilations or published before 2003 rarely have an accuracy of less than three orders of magnitude. Stimulus preparation, including analytical verification, stimulus presentation, as well as selection and training of test subjects have been identified as major sources of variability. ODT values obtained by validated standardized methods are now considered objective, reliable, and reproducible. They exhibit a variability of one or two orders of magnitude and are lower than traditionally assumed and reported. This review presents the essential criteria for a well-performed ODT determination. It is intended to assist health and safety professionals in assessing whether the methodological approach of a study was appropriate for determining a valid and reliable ODT value.

Research on odor characteristics of typical odorants of railway vehicle products

Odor annoyance was a kind of environmental air pollution. Compared to other indoor environments, vehicle interior materials were not well studied. Especially, there had been little research on odor character of the railway vehicles. This study applied the OAV method to identify the key odorants of railway vehicle materials and discussed the characteristics of these odorants through Weber Fechner law and a dual variable method. The result showed that for single odorant, Weber Fechner law can be used to estimate the perceived intensity of an odor gas sample at different concentration levels. The odorant with smaller slope had significant tolerance to human. For the mixtures of odorants, the overall intensity of the mixture is generally dominated by the strongest odor intensity of the individual substance in the mixture, and positive interaction effect can be observed in mixtures whose intensities had little difference. But there was a kind of odorants, such as methacrylate, in which a very small variation in the concentration of mixtures can affect its odor intensity largely. Meanwhile, the odor intensity modification coefficient was an effective way to identify and evaluate odor interaction effect. The interaction potential of the studied odorants from strong to weak was methacrylate, dibutyl-amine, nonanal, 2-ethyl hexanol. The odor interaction potential and odor nature should be paying much attention in the improvement of odor in railway vehicle product.

Parameter Mapping Sonification of Human Olfactory Thresholds

An objective of chemical ecology is to understand the chemical diversity across and within species, as well as the bioactivity of chemical compounds. We previously studied defensive volatiles from phytophagous insects that were subjected to parameter mapping sonification. The created sounds contained information about the repellent bioactivity of the volatiles, such as the repellence from the volatiles themselves when tested against live predators. Here, we applied a similar sonification process to data about human olfactory thresholds. Randomized mapping conditions were used and a peak sound pressure, Lpeak, was calculated from each audio file. The results indicate that Lpeak values were significantly correlated with the olfactory threshold values (e.g., r_S = 0.72, t = 10.19, p < 0.001, Spearman rank-order correlation; standardized olfactory thresholds of 100 volatiles). Furthermore, multiple linear regressions used the olfactory threshold as a dependent variable. The regressions revealed that the molecular weight, the number of carbon and oxygen atoms, as well as the functional groups aldehyde, acid, and (remaining) double bond were significant determinants of the bioactivity, while the functional groups ester, ketone, and alcohol were not. We conclude that the presented sonification methodology that converts chemicals into sound data allows for the study of their bioactivities by integrating compound characteristics that are easily accessible.

Phytochemical Profile of Trigonella caerulea (Blue Fenugreek) Herb and Quantification of Aroma-Determining Constituents

The herb of Trigonella caerulea (Fabaceae), commonly known as blue fenugreek, is used for the production of traditional cheese and bread varieties in the Alpine region. Despite its frequent consumption, only one study so far has focused on the constituent pattern of blue fenugreek, revealing qualitative information on some flavor-determining constituents. However, with regard to the volatile constituents present in the herb, the applied methods were insufficient and did not take relevant terpenoids into account. In the present study, we analyzed the phytochemical composition of T. caerulea herb applying a set of analytical methods, such as headspace-GC, GC-MS, LC-MS, and NMR spectroscopy. We thus determined the most dominant primary and specialized metabolites and assessed the fatty acid profile as well as the amounts of taste-relevant α-keto acids. In addition, eleven volatiles were quantified, of which tiglic aldehyde, phenylacetaldehyde, methyl benzoate, n-hexanal, and trans-menthone were identified as most significantly contributing to the aroma of blue fenugreek. Moreover, pinitol was found accumulated in the herb, whereas preparative works led to the isolation of six flavonol glycosides. Hence, our study shows a detailed analysis of the phytochemical profile of blue fenugreek and provides an explanation for its characteristic aroma and its health-beneficial effects.

Reliable prediction of sensory irritation threshold values of organic compounds using new models based on linear free energy relationships and GC×GC retention parameters

The human sensory irritation threshold (SIT) is an important biochemical parameter for the exposure assessment of organic air pollutants. First, we recalibrated the Abraham solvation models (ASMs) for 9 SIT endpoints by curating 720 individual experimental SIT values to find an accurate and parsimonious ASM variant, which exhibited root mean square error (RMSE) = 0.174-0.473 log unit. Second, we report linear free energy relationships - henceforth called partition models (PMs) - which exploit the correlations of 9 SIT endpoints with the linear combinations of partition coefficients for octanol-water and air-water systems showing RMSE = 0.221-0.591 log unit. These PMs can easily be integrated into widely used EPI-Suite™ screening tool. The explanatory and predictive performance of PMs were like parameter-intensive ASMs. Third, we present GC × GC models that are based on the retention times of the nonpolar analytes on the comprehensive two-dimensional gas chromatography (GC × GC), which successfully described the SIT variance (R²=0.959-0.996) and depicted a strong predictive power (RMSE = 0.359-0.660 log unit) for an independent set of nonpolar analytes. Taken together, PMs allow easy SIT screening of organic chemicals compared to ASMs. Unlike ASMs, our GC × GC models can be applied to estimate SIT of complex nonpolar mixtures.

Utilisation of QSPR ODT modelling and odour vector modelling to predict Cannabis sativa odour

Cannabis flower odour is an important aspect of product quality as it impacts the sensory experience when administered, which can affect therapeutic outcomes in paediatric patient populations who may reject unpalatable products. However, the cannabis industry has a reputation for having products with inconsistent odour descriptions and misattributed strain names due to the costly and laborious nature of sensory testing. Herein, we evaluate the potential of using odour vector modelling for predicting the odour intensity of cannabis products. Odour vector modelling is proposed as a process for transforming routinely produced volatile profiles into odour intensity (OI) profiles which are hypothesised to be more informative to the overall product odour (sensory descriptor; SD). However, the calculation of OI requires compound odour detection thresholds (ODT), which are not available for many of the compounds present in natural volatile profiles. Accordingly, to apply the odour vector modelling process to cannabis, a QSPR statistical model was first produced to predict ODT from physicochemical properties. The model presented herein was produced by polynomial regression with 10-fold cross-validation from 1,274 median ODT values to produce a model with R2 = 0.6892 and a 10-fold R2 = 0.6484. This model was then applied to terpenes which lacked experimentally determined ODT values to facilitate vector modelling of cannabis OI profiles. Logistic regression and k-means unsupervised cluster analysis was applied to both the raw terpene data and the transformed OI profiles to predict the SD of 265 cannabis samples and the accuracy of the predictions across the two datasets was compared. Out of the 13 SD categories modelled, OI profiles performed equally well or better than the volatile profiles for 11 of the SD, and across all SD the OI data was on average 21.9% more accurate (p = 0.031). The work herein is the first example of the application of odour vector modelling to complex volatile profiles of natural products and demonstrates the utility of OI profiles for the prediction of cannabis odour. These findings advance both the understanding of the odour modelling process which has previously only been applied to simple mixtures, and the cannabis industry which can utilise this process for more accurate prediction of cannabis odour and thereby reduce unpleasant patient experiences.

Heterofermentative lactic acid bacteria such as Limosilactobacillus as a strong inhibitor of aldehyde compounds in plant-based milk alternatives

Reduction of greenhouse gas emissions is important to limit climate change. Because ruminant animals emit greenhouse gases, the worldwide plant-based alternative market is an emerging trend for eating less meat and dairy products. To produce plant-based dairy products such as yogurt alternatives, certain lactic acid bacterial species, which are used for cow's milk fermentation, are often used. Substrate changes from cow's milk to plant-based milk caused nutritional changes, and unsaturated fatty acids are more enriched in plant-based milk alternatives than in cow's milk. Unsaturated fatty acids can lead to the formation of aldehydes, some of which are off-flavors; therefore, substrate changes have the potential to alter the suitable lactic acid bacterial species used for fermentation to control flavor formation, such as aldehyde compounds. However, differences in the effect of the fermentation processes on aldehyde compounds have not been evaluated among lactic acid bacterial species. In this study, we comprehensively evaluated the effect of lactic acid bacterial fermentation on aldehyde compounds in synthetic medium and plant-based milk alternatives using 20 species of lactic acid bacteria. Heterofermentative lactic acid bacteria such as strains belonging to Limosilactobacillus had a strong aldehyde-reducing ability, likely from differences in alcohol dehydrogenase function. Because the odor detection threshold of ethanol compounds was lower than that of their equivalent aldehyde compounds, our findings are valuable for the fermentation of plant-based milk alternatives with lactic acid bacteria with the goal of decreasing off-flavors derived from aldehyde compounds.

Cabin air quality on non-smoking commercial flights: A review of published data on airborne pollutants

We reviewed 47 documents published 1967-2019 that reported measurements of volatile organic compounds (VOCs) on commercial aircraft. We compared the measurements with the air quality standards and guidelines for aircraft cabins and in some cases buildings. Average levels of VOCs for which limits exist were lower than the permissible levels except for benzene with average concentration at 5.9 ± 5.5 μg/m3 . Toluene, benzene, ethylbenzene, formaldehyde, acetaldehyde, limonene, nonanal, hexanal, decanal, octanal, acetic acid, acetone, ethanol, butanal, acrolein, isoprene and menthol were the most frequently measured compounds. The concentrations of semi-volatile organic compounds (SVOCs) and other contaminants did not exceed standards and guidelines in buildings except for the average NO2 concentration at 12 ppb. Although the focus was on VOCs, we also retrieved the data on other parameters characterizing cabin environment. Ozone concentration averaged 38 ppb below the upper limit recommended for aircraft. The outdoor air supply rate ranged from 1.7 to 39.5 L/s per person and averaged 6.0 ± 0.8 L/s/p (median 5.8 L/s/p), higher than the minimum level recommended for commercial aircraft. Carbon dioxide concentration averaged 1315 ± 232 ppm, lower than what is permitted in aircraft and close to what is permitted in buildings. Measured temperatures averaged 23.5 ± 0.8°C and were generally within the ranges recommended for avoiding thermal discomfort. Relative humidity averaged 16% ± 5%, lower than what is recommended in buildings.

Assessment of olfactory information in the human brain using 7-Tesla functional magnetic resonance imaging

Olfaction could prove to be an early marker of neurodegenerative diseases, including Alzheimer's and Parkinson's diseases. To use olfaction for disease diagnosis, elucidating the standard olfactory functions in healthy humans is necessary. However, the olfactory function in the human brain is less frequently assessed because of methodological difficulties associated with olfactory-related cerebral areas. Using ultra-high fields (UHF), functional magnetic resonance imaging (fMRI) with high spatial resolution and sensitivity may allow for the measurement of activation in the cerebral areas. This study aimed to apply 7-Tesla fMRI to assess olfactory function in the human brain by exposing individuals to four different odorants for 8 s. We found that olfactory stimulation mainly activated the piriform and orbitofrontal cortex in addition to the amygdala. Among these regions, univariate fMRI analysis indicated that subjective odor intensity significantly correlated with the averaged fMRI signals in the piriform cortex but not with subjective hedonic tone in any region. In contrast, multivariate fMRI analysis showed that subjective hedonic tone could be discriminated from the fMRI response patterns in the posterior orbitofrontal cortex. Thus, the piriform cortex is mainly associated with subjective odor intensity, whereas the posterior orbitofrontal cortex are involved in the discrimination of the subjective hedonic tone of the odorant. UHF-fMRI may be useful for assessing olfactory function in the human brain.

Non-carcinogenic occupational exposure risk related to foundry emissions: focus on the workers involved in olfactometric assessments

The scope of this work is the evaluation of the non-carcinogenic occupational risk related to foundry emissions, focusing on the category of workers involved in olfactometric assessments. Odor pollution from industrial activities such as foundries is a serious environmental concern. Sensorial techniques (e.g. dynamic olfactometry, EN13725:2003) currently represent the preferred method for odor emission characterization. During olfactometric analyses, human assessors are directly exposed to the odor at increasing concentrations, thus requiring the assessment of the associated exposure risk to guarantee workers' safety. This paper presents an investigation aiming to produce an inventory of compounds emitted from foundries together with their odor thresholds and toxicological limits (TLVs), with the final objective to propose a procedure for ensuring workers' safety during olfactometric analyses. Looking at the database resulting from this study, among the >100 compounds emitted by foundries, 8 have a maximum concentration above their TLV. Among those, ammonia, H₂S, phenol, toluene and trimethylamine, produce an odor stimulus before they reach a toxic concentration, thus not representing a risk for olfactometric workers. Benzene, formaldehyde and SO₂ are identified as the most critical compounds because they may reach toxic concentrations in foundry emissions, and they start being perceived by humans above their TLV. The proposed procedure entails a minimum dilution factor of 27'000 to be applied to odor samples analyzed by olfactometry, which however might result inapplicable in practical cases, thus pointing out the necessity to adopt chemical measurements to investigate specifically the concentration of the most critical compounds identified in this study.

Physical and chemical indicators of transformations of poultry carcass parts and broiler litter during short term thermophilic composting

Short-term on-site composting of poultry carcasses and broiler litter (BL) is considered as a feasible technology for pathogen elimination during events of mass mortality in poultry houses. However, factors related to mass losses and physical transformation of the poultry carcass, and associated emissions of volatile organic compounds (VOCs) and odors, have not been thoroughly evaluated. This study aims to characterize the degradation of separated carcass parts co-composted with BL and the associated air emissions during 30 days of enclosed composting at 50 °C with constant aeration. The study was carried out in lab-scale simulators using five mixtures containing feathers, rib bones, skins, breast muscles, and hearts and livers, prepared at a 1:2 volumetric ratio (carcass:BL). Dry mass losses reached 59.5, 41.1, 60.8 and 103.5% (based on weight) or 48.4, 29.6, 49.7, and 94.8% (based on CO₂-C and NH₃-N emissions), for rib bones, skins, breast muscles, and hearts and livers, respectively. Visually, most of the carcass parts were degraded, and the typical carcass odor had disappeared by the end of the 30 days. Out of 24 VOCs, dimethyl disulfide (DMDS) and dimethyl trisulfide (DMTS) contributed 80.7-88.3% of the total VOC flux, considering the partial contribution of each part to the emissions involved with the whole carcass. DMDS, DMTS, benzaldehyde, methanethiol, pentanoic acid, and NH₃, contributed 90.5-97.9% of the odor activity values during composting. DMDS/DMTS ratio is suggested as a potential biomarker of stabilization and readiness of the compost for transportation toward further treatment or safe burial.

Descriptors for terpene esters from chromatographic and partition measurements: Estimation of human odor detection thresholds

We have used gas chromatographic retention data together with other data to obtain Abraham descriptors for 30 terpene esters. These include the air-water partition coefficient, as log Kw, for which no experimental values are available for any terpene ester. The other descriptors are the ester dipolarity, S, the hydrogen bond basicity, B, (the ester hydrogen bond acidity is zero for the esters studied), and L the logarithm of the air-hexadecane partition coefficient. Both S and B are larger than those for simple aliphatic esters, as expected from the terpene ester structures that include ring systems and ethylenic double bonds. These descriptors can then be used to obtain a large number of physicochemical and environmental properties of terpene esters. We have analyzed experimental results on human odor detection thresholds and have constructed another equation for the calculation of these thresholds, to go with a previous equation that we have reported. Then the descriptors for terpene esters can be used to estimate the important odor detection thresholds.

Scents in the stack: olfactometric proficiency testing with an emission simulation apparatus

Olfactometry is globally acknowledged as a technique to determine odor concentrations, which are used to characterize odors for regulatory purposes, e.g., to protect the general public against harmful effects of air pollution. Although the determination procedure for odor concentrations is standardized in some countries, continued research is required to understand uncertainties of odor monitoring and prediction. In this respect, the present paper strives to provide answers of paramount importance in olfactometry. To do so, a wealth of measurement data originating from six large-scale olfactometric stack emission proficiency tests conducted from 2015 to 2017 was retrospectively analyzed. The tests were hosted at a unique emission simulation apparatus-a replica of an industry chimney with 23 m in height-so that for the first time, conventional proficiency testing (no sampling) with real measurements (no reference concentrations) was combined. Surprisingly, highly variable recovery rates of the odorants were observed-no matter, which of the very different odorants was analyzed. Extended measurement uncertainties with roughly 30-300% up to 20-520% around a single olfactometric measurement value were calculated, which are way beyond the 95% confidence interval given by the widely used standard EN 13725 (45-220%) for assessment and control of odor emissions. Also, no evidence has been found that mixtures of odorants could be determined more precisely than single-component odorants. This is an important argument in the intensely discussed topic, whether n-butanol as current reference substance in olfactometry should be replaced by multi-component odorants. However, based on our data, resorting to an alternative reference substance will not solve the inherent problem of high uncertainty levels in dynamic olfactometry. Finally, robust statistics allowed to calculate reliable odor thresholds, which are an important prerequisite to convert mass concentrations to odor concentrations and vice versa.

Influence of two yeast strains in free, bioimmobilized or immobilized with alginate forms on the aromatic profile of long aged sparkling wines

Production of sparkling wines involve a second alcoholic fermentation and contact with yeast less over an extended period of time, which influences the aroma composition and sensory quality of the resulting wines. Sparkling wines obtained with two yeast strains inoculated as free cells, immobilized in alginate bed and bioimmobilized as biocapsules, were aged during 32 months. Among the volatile compounds, high Odor Activity Values were obtained with isoamyl acetate, ethyl propanoate, ethyl butanoate, ethyl 3-methylbutanoate, ethyl hexanoate, ethyl octanoate, hexanol, 2-methoxy-4-vinylphenol, decanal, octanoic acid, decanoic acid and TDN. Taken together these contribute more than 70% of the overall aromatic series value. Although some results rely more on the yeast strain than the inoculation format, specific aroma compounds were associated with the immobilization format, allowing the classification of sparkling wines by PCA. As a result the aroma quality of sparkling wines could be improved using immobilized yeasts.

Human symptom responses to bioeffluents, short-chain carbonyls/acids, and long-chain carbonyls in a simulated aircraft cabin environment

Occupants of aircraft have reported an array of symptoms related to general discomfort and irritation. Volatile organic compounds (VOCs) have been suggested to contribute to the reported symptoms. VOCs are from products used, bioeffluents from people and oxidation reaction products. Thirty-six healthy, young female subjects rated symptoms and environmental quality during an eight-hour exposure to groups of compounds often present in aircraft: (i) long-chain carbonyls, (ii) simulated bioeffluents, and (iii) short-chain carbonyls/organic acids. Statistically more symptoms were identified for the simulated bioeffluents and, to a lesser extent, short-chain carbonyls/organic acids compared to a control condition, although they remained in the acceptable range. There were three temporal patterns in the environmental quality and symptom reports: (i) an adaptive response (immediate increases followed by a decline); (ii) an apparent physiological effect (increases one to three hours into the exposure that remained elevated); and (iii) no statistical differences in reported environmental quality or symptom severity compared to the control air conditions. Typical concentrations found in aircraft can cause transitory symptoms in healthy individuals questioning the adequacy of current standards. Understanding the effects on individuals sensitive to air pollutants and methods to remove the compounds causing the greatest symptom responses are needed.

The Regular Interaction Pattern among Odorants of the Same Type and Its Application in Odor Intensity Assessment

The olfactory evaluation function (e.g., odor intensity rating) of e-nose is always one of the most challenging issues in researches about odor pollution monitoring. But odor is normally produced by a set of stimuli, and odor interactions among constituents significantly influenced their mixture’s odor intensity. This study investigated the odor interaction principle in odor mixtures of aldehydes and esters, respectively. Then, a modified vector model (MVM) was proposed and it successfully demonstrated the similarity of the odor interaction pattern among odorants of the same type. Based on the regular interaction pattern, unlike a determined empirical model only fit for a specific odor mixture in conventional approaches, the MVM distinctly simplified the odor intensity prediction of odor mixtures. Furthermore, the MVM also provided a way of directly converting constituents’ chemical concentrations to their mixture’s odor intensity. By combining the MVM with usual data-processing algorithm of e-nose, a new e-nose system was established for an odor intensity rating. Compared with instrumental analysis and human assessor, it exhibited accuracy well in both quantitative analysis (Pearson correlation coefficient was 0.999 for individual aldehydes (n = 12), 0.996 for their binary mixtures (n = 36) and 0.990 for their ternary mixtures (n = 60)) and odor intensity assessment (Pearson correlation coefficient was 0.980 for individual aldehydes (n = 15), 0.973 for their binary mixtures (n = 24), and 0.888 for their ternary mixtures (n = 25)). Thus, the observed regular interaction pattern is considered an important foundation for accelerating extensive application of olfactory evaluation in odor pollution monitoring.

Odor threshold prediction by means of the Monte Carlo method

A large set of organic compounds (n=906) has been used as a basis to build up a model for the odor threshold (mg/m(3)). The statistical characteristics of the best model are the following: n=523, r(2)=0.647, RMSE=1.18 (training set); n=191, r(2)=0.610, RMSE=1.03, (calibration set); and n=192, r(2)=0.686, RMSE=1.06 (validation set). A mechanistic interpretation of the model is presented as the lists of statistical promoters of the increase and decrease in the odor threshold.

Equations for water-triolein partition coefficients for neutral species; comparison with other water-solvent partitions, and environmental and toxicological processes

Linear free energy relationships, LFERs, have been constructed for water-triolein partition coefficients for neutral species. It is shown that separate equations are required for wet and dry triolein. From a comparison of the equation coefficients for water-wet triolein with those for 52 other water-solvent systems it is shown that there is little correspondence between triolein and any of the 52 other solvents - only the water-isopropyl myristate system is close to the water-wet triolen system. A comparison of equation coefficients for the water-wet triolein system with LFER coefficients of 16 environmentally important processes shows that wet triolein is not a suitable model for any of the processes, although a number of other water-solvent systems are possible models for some of the environmental processes. A comparison of LFER coefficients with those of 17 aqueous toxicological processes reveals that most of the water-solvent systems, including water-wet triolein, will be poor models for any of the toxicological systems, but the water-lower alcohol systems show promise as models for a number of the toxicological systems. Our method of comparison of coefficients for LFERs that have exactly the same independent variables can be extended to various other types of system.

Receptor arrays optimized for natural odor statistics

Natural odors typically consist of many molecules at different concentrations. It is unclear how the numerous odorant molecules and their possible mixtures are discriminated by relatively few olfactory receptors. Using an information theoretic model, we show that a receptor array is optimal for this task if it achieves two possibly conflicting goals: (i) Each receptor should respond to half of all odors and (ii) the response of different receptors should be uncorrelated when averaged over odors presented with natural statistics. We use these design principles to predict statistics of the affinities between receptors and odorant molecules for a broad class of odor statistics. We also show that optimal receptor arrays can be tuned to either resolve concentrations well or distinguish mixtures reliably. Finally, we use our results to predict properties of experimentally measured receptor arrays. Our work can thus be used to better understand natural olfaction, and it also suggests ways to improve artificial sensor arrays.

An assessment of air quality reflecting the chemosensory irritation impact of mixtures of volatile organic compounds

We present a method to assess the air quality of an environment based on the chemosensory irritation impact of mixtures of volatile organic compounds (VOCs) present in such environment. We begin by approximating the sigmoid function that characterizes psychometric plots of probability of irritation detection (Q) versus VOC vapor concentration to a linear function. First, we apply an established equation that correlates and predicts human sensory irritation thresholds (SIT) (i.e., nasal and eye irritation) based on the transfer of the VOC from the gas phase to biophases, e.g., nasal mucus and tear film. Second, we expand the equation to include other biological data (e.g., odor detection thresholds) and to include further VOCs that act mainly by "specific" effects rather than by transfer (i.e., "physical") effects as defined in the article. Then we show that, for 72 VOCs in common, Q values based on our calculated SITs are consistent with the Threshold Limit Values (TLVs) listed for those same VOCs on the basis of sensory irritation by the American Conference of Governmental Industrial Hygienists (ACGIH). Third, we set two equations to calculate the probability (Qmix) that a given air sample containing a number of VOCs could elicit chemosensory irritation: one equation based on response addition (Qmix scale: 0.00 to 1.00) and the other based on dose addition (1000*Qmix scale: 0 to 2000). We further validate the applicability of our air quality assessment method by showing that both Qmix scales provide values consistent with the expected sensory irritation burden from VOC mixtures present in a wide variety of indoor and outdoor environments as reported on field studies in the literature. These scales take into account both the concentration of VOCs at a particular site and the propensity of the VOCs to evoke sensory irritation.

Dose-Response Functions for the Olfactory, Nasal Trigeminal, and Ocular Trigeminal Detectability of Airborne Chemicals by Humans

We gathered from the literature 47 odor and 37 trigeminal (nasal and ocular) chemesthetic psychometric (i.e., detectability or dose-response) functions from a group of 41 chemicals. Vapors delivered were quantified by analytical methods. All functions were very well fitted by the sigmoid (logistic) equation: y = 1 / (1 + e({-(x-C)/D})), where parameter C quantifies the detection threshold concentration and parameter D the steepness of the function. Odor and chemesthetic functions showed no concentration overlap: olfactory functions grew along the parts per billion (ppb by volume) range or lower, whereas trigeminal functions grew along the part per million (ppm by volume) range. Although, on average, odor detectability rose from chance detection to perfect detection within 2 orders of magnitude in concentration, chemesthetic detectability did it within one. For 16 compounds having at least 1 odor and 1 chemesthetic function, the average gap between the 2 functions was 4.6 orders of magnitude in concentration. A quantitative structure-activity relationship (QSAR) using 5 chemical descriptors that had previously described stand-alone odor and chemesthetic threshold values, also holds promise to describe, and eventually predict, olfactory and chemesthetic detectability functions, albeit functions from additional compounds are needed to strengthen the QSAR.

Compilation and analysis of types and concentrations of airborne chemicals measured in various indoor and outdoor human environments

The main purpose of this article is to summarize and illustrate the results of a literature search on the types, levels, relative concentrations, concentration spread of individual chemicals, and number of airborne compounds (mostly volatile organic compounds, VOCs) that have been found, measured, and reported both indoors and outdoors. Two broad categories of indoor environments are considered: (1) home/school, and (2) commercial spaces. Also, two categories of outdoor environments are considered: (1) non-industrial and (2) industrial (the latter represented by the vicinity of a pig farm and the vicinity of an oil refinery). The outcome is presented as a series of graphs and tables containing the following statistics: geometric mean, arithmetic mean, median, standard deviation, variance, standard error, interquartile distance, minimum value, maximum value, and number of data (data count) for the air concentration of each reported compound in a given environment. A Supplementary Table allows interested readers to match each single value included in this compilation with its corresponding original reference.

Use of a modified vector model for odor intensity prediction of odorant mixtures

Odor intensity (OI) indicates the perceived intensity of an odor by the human nose, and it is usually rated by specialized assessors. In order to avoid restrictions on assessor participation in OI evaluations, the Vector Model which calculates the OI of a mixture as the vector sum of its unmixed components’ odor intensities was modified. Based on a detected linear relation between the OI and the logarithm of odor activity value (OAV—a ratio between chemical concentration and odor threshold) of individual odorants, OI of the unmixed component was replaced with its corresponding logarithm of OAV. The interaction coefficient (cosα) which represented the degree of interaction between two constituents was also measured in a simplified way. Through a series of odor intensity matching tests for binary, ternary and quaternary odor mixtures, the modified Vector Model provided an effective way of relating the OI of an odor mixture with the lnOAV values of its constituents. Thus, OI of an odor mixture could be directly predicted by employing the modified Vector Model after usual quantitative analysis. Besides, it was considered that the modified Vector Model was applicable for odor mixtures which consisted of odorants with the same chemical functional groups and similar molecular structures.

Applications of polyparameter linear free energy relationships in environmental chemistry

Partitioning behavior of organic chemicals has tremendous influences on their environmental distribution, reaction rates, bioaccumulation, and toxic effects. Polyparameter linear free energy relationships (PP-LFERs) have been proven to be useful to characterize the equilibrium partitioning of organic chemicals in various environmental and technical partitioning systems and predict the respective partition coefficients. Over the past decade, PP-LFER solute descriptors for numerous environmentally relevant organic chemicals and system parameters for environmentally important partitioning systems have been determined, extending substantially the applicability of the PP-LFER approaches. However, the information needed for the use of PP-LFERs including descriptors and parameters is scattered over a large number of publications. In this work, we review the state of the art of the PP-LFER approaches in environmental chemical applications. The solute descriptors and system parameters reported in the literature and the availability of their database are summarized, and their calibration and prediction methods are overviewed. We also describe tips and pitfalls associated with the use of the PP-LFER approaches and identify research needs to improve further the usefulness of PP-LFERs for environmental chemistry.

Fatty acid composition of subcutaneous adipose tissue from entire male pigs with extremely divergent levels of boar taint compounds--an exploratory study

This exploratory study investigated the variability of fatty acid composition in entire male pigs with extremely divergent levels of boar taint compounds. Fatty acids were quantified in back fat samples from 20 selected carcasses of Pietrain*F1 sired boars (average carcass weight 84 kg) with extremely low (LL) or extremely high (HH) levels of androstenone, skatole, and indole. Concentrations of polyunsaturated fatty acids (PUFA) were significantly (p<0.05) increased in LL boars (23.4%) compared to HH boars (19.7%). This was mainly due to increased levels of linoleic acid (C18:2 n-6) and α-linolenic acid (C18:3 n-3). Correspondingly, unsaturated fatty acids (SFA) were significantly lower (p<0.05) in LL boars (35.2%) compared to HH boars (37.7%). The findings are discussed with respect to potential effects on flavor formation in boar fat and meat. Further research is needed to study the gender specificity and the interplay of the synthesis and the metabolism of steroids, lipids, and the clearance of skatole in pigs.

From molecule to mind: an integrative perspective on odor intensity

A fundamental problem in systems neuroscience is mapping the physical properties of a stimulus to perceptual characteristics. In vision, wavelength translates into color; in audition, frequency translates into pitch. Although odorant concentration is a key feature of olfactory stimuli, we do not know how concentration is translated into perceived intensity by the olfactory system. A variety of neural responses at several levels of processing have been reported to vary with odorant concentration, suggesting specific coding models. However, it remains unclear which, if any, of these phenomena underlie the perception of odor intensity. Here, we provide an overview of current models at different stages of olfactory processing, and identify promising avenues for future research.

Predicting odor perceptual similarity from odor structure

To understand the brain mechanisms of olfaction we must understand the rules that govern the link between odorant structure and odorant perception. Natural odors are in fact mixtures made of many molecules, and there is currently no method to look at the molecular structure of such odorant-mixtures and predict their smell. In three separate experiments, we asked 139 subjects to rate the pairwise perceptual similarity of 64 odorant-mixtures ranging in size from 4 to 43 mono-molecular components. We then tested alternative models to link odorant-mixture structure to odorant-mixture perceptual similarity. Whereas a model that considered each mono-molecular component of a mixture separately provided a poor prediction of mixture similarity, a model that represented the mixture as a single structural vector provided consistent correlations between predicted and actual perceptual similarity (r≥0.49, p<0.001). An optimized version of this model yielded a correlation of r = 0.85 (p<0.001) between predicted and actual mixture similarity. In other words, we developed an algorithm that can look at the molecular structure of two novel odorant-mixtures, and predict their ensuing perceptual similarity. That this goal was attained using a model that considers the mixtures as a single vector is consistent with a synthetic rather than analytical brain processing mechanism in olfaction.

Indoor air pollutants in office environments: assessment of comfort, health, and performance

Concentrations of volatile organic compounds (VOCs) in office environments are generally too low to cause sensory irritation in the eyes and airways on the basis of estimated thresholds for sensory irritation. Furthermore, effects in the lungs, e.g. inflammatory effects, have not been substantiated at indoor relevant concentrations. Some VOCs, including formaldehyde, in combination may under certain environmental and occupational conditions result in reported sensory irritation. The odour thresholds of several VOCs are low enough to influence the perceived air quality that result in a number of acute effects from reported sensory irritation in eyes and airways and deterioration of performance. The odour perception (air quality) depends on a number of factors that may influence the odour impact. There is neither clear indication that office dust particles may cause sensory effects, even not particles spiked with glucans, aldehydes or phthalates, nor lung effects; some inflammatory effects may be observed among asthmatics. Ozone-initiated terpene reaction products may be of concern in ozone-enriched environments (≥0.1mg/m(3)) and elevated limonene concentrations, partly due to the production of formaldehyde. Ambient particles may cause cardio-pulmonary effects, especially in susceptible people (e.g. elderly and sick people); even, short-term effects, e.g. from traffic emission and candle smoke may possibly have modulating and delayed effects on the heart, but otherwise adverse effects in the airways and lung functions have not been observed. Secondary organic aerosols generated in indoor ozone-initiated terpene reactions appear not to cause adverse effects in the airways; rather the gaseous products are relevant. Combined exposure to particles and ozone may evoke effects in subgroups of asthmatics. Based on an analysis of thresholds for odour and sensory irritation selected compounds are recommended for measurements to assess the indoor air quality and to minimize reports of irritation symptoms, deteriorated performance, and cardiovascular and pulmonary effects.