Odor Interactions Research Articles

Synergism of Pheromone and Host-Plant Volatile Blends in the Attraction of Leucinodes orbonalis Guenee Males

Brinjal Fruit and shoot borer, Leucinodes orbonalis Guenee is considered to be the key insect pest that attacks brinjal plant. Insects such as L. orbonalis, which has extremely diverse adaptations such as hidden and protected lifestyles in the adult stage and concealed habits in the larval stage cannot be easily controlled with cover sprays of insecticides. Moreover, Pheromone-host plant odour interactions might also play a pivotal role in the evolution of mating communication and host-finding behaviour. The objective of the present work was to evaluate whether host plant volatiles synergise male L. orbonalis attraction to sex pheromone. Steam distillation method and super Q entrapment technique were used for the extraction of volatiles from brinjal plant leaves, shoots and fruits and sex pheromone from the insects respectively. Preliminary laboratory studies have shown that the male insects attracted to the host plant volatiles. Bioassay using Y-shaped olfactometer with different doses of the combination of sex pheromone and host plant volatiles were used to test the synergism. Two Whatman no. 1 filter papers (2.5 cm×2.5 cm) were used, one treated with a known amount of sex pheromone+host plant volatile and the other treated with equal amount of sex pheromone. In each experiment, the dose of sex pheromone was not changed and peak dose identified from the bioassay conducted previously was used. The dose of each host plant volatile was prepared by decreasing and increasing from the peak dose identified from the previous bioassays. Six doses of sex pheromone+fruit volatiles (25 μg+(8-48 mg)), sex pheromone+leaf volatile (25 μg+(12-42 mg)) and sex pheromone+shoot volatile (25 μg+(8-48 mg)) were tested using 15 male insects separately and each dose was replicated 5 times. The number of insects that moved into the sex pheromone+host plant volatile treated and sex pheromone treated arms within 5 minutes were recorded. This assay was carried out between 20.00–24.00 h and the test insects were not used repeatedly. Results revealed that all three types of volatiles from the host plant increased the attraction of male insects to the sex pheromone. In addition, the volatiles from brinjal fruits significantly increased the male attraction to the pheromone blend (p<0.05). The observed enhanced male attraction to the mixtures of pheromone and plant volatiles will facilitate the development of effective pest control programs for L. orbonalis. Keywords: Sex pheromone, Host plant volatiles, Synergism, Leucinodes orbonalis, Pest management

Determination of Odor Intensity of Binary Gas Mixtures Using Perceptual Models and an Electronic Nose Combined with Fuzzy Logic.

Measurement and monitoring of air quality in terms of odor nuisance is an important problem. From a practical point of view, it would be most valuable to directly link the odor intensity with the results of analytical air monitoring. Such a solution is offered by electronic noses, which thanks to the possibility of holistic analysis of the gas sample, allow estimation of the odor intensity of the gas mixture. The biggest problem is the occurrence of odor interactions between the mixture components. For this reason, methods that can take into account the interaction between components of the mixture are used to analyze data from the e-nose. In the presented study, the fuzzy logic algorithm was proposed for determination of odor intensity of binary mixtures of eight odorants: n-Hexane, cyclohexane, toluene, o-xylene, trimethylamine, triethylamine, α-pinene, and β-pinene. The proposed algorithm was compared with four theoretical perceptual models: Euclidean additivity, vectorial additivity, U model, and UPL model.

Real-time In Vitro Monitoring of Odorant Receptor Activation by an Odorant in the Vapor Phase.

Olfactory perception begins with the interaction of odorants with odorant receptors (OR) expressed by olfactory sensory neurons (OSN). Odor recognition follows a combinatorial coding scheme, where one OR can be activated by a set of odorants and one odorant can activate a combination of ORs. Through such combinatorial coding, organisms can detect and discriminate between a myriad of volatile odor molecules. Thus, an odor at a given concentration can be described by an activation pattern of ORs, which is specific to each odor. In that sense, cracking the mechanisms that the brain uses to perceive odor requires the understanding odorant-OR interactions. This is why the olfaction community is committed to "de-orphanize"these receptors. Conventional in vitro systems used to identify odorant-OR interactions have utilized incubating cell media with odorant, which is distinct from the natural detection of odors via vapor odorants dissolution into nasal mucosa before interacting with ORs. Here, we describe a new method that allows for real-time monitoring of OR activation via vapor-phase odorants. Our method relies on measuring cAMP release by luminescence using the Glosensor assay. It bridges current gaps between in vivo and in vitro approaches and provides a basis for a biomimetic volatile chemical sensor.

Elucidating Olfactory Receptor - Odorant Interactions: Leveraging Drug-Design Ideations

Elucidating Olfactory Receptor - Odorant Interactions: Leveraging Drug-Design Ideations

Oxytocin is indispensable for conspecific-odor preference and controls the initiation of female, but not male, sexual behavior in mice

Oxytocin (OT) has been demonstrated to be involved in various social behaviors in mammals. However, OT gene knockout (OTKO) mice can conceive and deliver successfully, though females cannot rear their pups because of lack of lactation. Here, we investigated the sociosexual behavior of both sexes in two experimental setups: olfactory preference for sexual partner’s odor and direct social interaction in an enriched condition. In the preference test, mice were given a choice of two airborne odors derived from intact male and receptive female mice, or from intact or castrated male mice. Wild-type (WT) mice significantly preferred opposite-sex odors, whereas OTKO mice showed vigorous but equivalent exploration to all stimuli. In social interactions in the enriched condition, no difference in sexual behavior was found between WT and OTKO males. In contrast, WT female initiated sexual behavior at the second week test, while OTKO females required 4 weeks to receive successful mounts. Neuronal activation by odor stimulation was compared between WT and OTKO mice. The numbers of cFos-immunoreactive cells increased in the medial amygdala and the preoptic area after exposure to opposite-sex odors in WT mice, whereas the increase was suppressed in OTKO mice. We conclude that OT plays an important role in the regulation of olfactory-related social behavior in both male and female mice. The influence of OT was greater in female mice, especially during social interactions involving the acquisition of sexual experience.

Vapor detection and discrimination with a panel of odorant receptors

Olfactory systems have evolved the extraordinary capability to detect and discriminate volatile odorous molecules (odorants) in the environment. Fundamentally, this process relies on the interaction of odorants and their cognate olfactory receptors (ORs) encoded in the genome. Here, we conducted a cell-based screen using over 800 mouse ORs against seven odorants, resulting in the identification of a set of high-affinity and/or broadly-tuned ORs. We then test whether heterologously expressed ORs respond to odors presented in vapor phase by individually expressing 31 ORs to measure cAMP responses against vapor phase odor stimulation. Comparison of response profiles demonstrates this platform is capable of discriminating between structural analogs. Lastly, co-expression of carboxyl esterase Ces1d expressed in olfactory mucosa resulted in marked changes in activation of specific odorant-OR combinations. Altogether, these results establish a cell-based volatile odor detection and discrimination platform and form the basis for an OR-based volatile odor sensor.

Analysis of Odour Interactions in Model Gas Mixtures using Electronic Nose and Fuzzy Logic

Measurement and monitoring of air quality in terms of odour nuisance is an important problem. Although the source of these nuisances is different (e.g. wastewater treatment plants, municipal landfills), their common feature is that they are a complex mixture of odorants with different odour thresholds. An additional problem is occurrence of the odour interactions between mixture components. From a practical point of view, it would be most valuable to directly link the odour intensity with the results of analytical air monitoring. This would allow the on-line odour monitoring using electronic noses, which perform a holistic analysis of the gas mixtures composition (like olfactometric methods). The paper presents the possibility of application of fuzzy logic to determine the odour intensity and indicate odour interactions in model, five-component gas mixtures (acetone, a-pinene, formaldehyde, toluene and triethylamine) using electronic nose prototype. As the results of the studies, it was found the electronic nose prototype along with the fuzzy logic pattern recognition system can be successfully used for this application. The results obtained using fuzzy logic are consistent with sensory analysis results in 80%.

Determination of Odour Interactions in Gaseous Mixtures Using Electronic Nose Methods with Artificial Neural Networks.

This paper presents application of an electronic nose prototype comprised of eight sensors, five TGS-type sensors, two electrochemical sensors and one PID-type sensor, to identify odour interaction phenomenon in two-, three-, four- and five-component odorous mixtures. Typical chemical compounds, such as toluene, acetone, triethylamine, α-pinene and n-butanol, present near municipal landfills and sewage treatment plants were subjected to investigation. Evaluation of predicted odour intensity and hedonic tone was performed with selected artificial neural network structures with the activation functions tanh and Leaky rectified linear units (Leaky ReLUs) with the parameter . Correctness of identification of odour interactions in the odorous mixtures was determined based on the results obtained with the electronic nose instrument and non-linear data analysis. This value (average) was at the level of 88% in the case of odour intensity, whereas the average was at the level of 74% in the case of hedonic tone. In both cases, correctness of identification depended on the number of components present in the odorous mixture.

Determination of Odour Interactions of Three-Component Gas Mixtures Using an Electronic Nose.

The paper presents an application of an electronic nose prototype comprised of six TGS-type sensors and one PID-type sensor to identify odour interaction phenomena in odorous three-component mixtures. The investigation encompassed eight odorous mixtures—toluene-acetone-triethylamine and formaldehyde-butyric acid-pinene—characterized by different odour intensity and hedonic tone. A principal component regression (PCR) calibration model was used for evaluation of predicted odour intensity and hedonic tone. Correctness of identification of odour interactions in the odorous three-component mixtures was determined based on the results obtained with the electronic nose. The results indicated a level of 75–80% for odour intensity and 57–73% for hedonic tone. The average root mean square error of prediction amounted to 0.03–0.06 for odour intensity determination and 0.07–0.34 for hedonic tone evaluation of the odorous three-component mixtures.

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.

The Investigation of Odor Contribution by sub-Threshold Odorants based on Odor Interaction among Odors Mixture

The Investigation of Odor Contribution by sub-Threshold Odorants based on Odor Interaction among Odors Mixture

Odor-taste convergence in the nucleus of the solitary tract of the awake freely licking rat.

Flavor is produced by the integration of taste, olfaction, texture, and temperature, currently thought to occur in the cortex. However, previous work has shown that brainstem taste-related nuclei also respond to multisensory inputs. Here, we test the hypothesis that taste and olfaction interact in the nucleus of the solitary tract (NTS; the first neural relay in the central gustatory pathway) in awake, freely licking rats. Electrophysiological recordings of taste and taste + odor responses were conducted in an experimental chamber following surgical electrode implantation and recovery. Tastants (0.1 m NaCl, 0.1 m sucrose, 0.01 m citric acid, and 0.0001 m quinine) were delivered for five consecutive licks interspersed with five licks of artificial saliva rinse delivered on a VR5 schedule. Odorants were n-amyl acetate (banana), acetic acid (vinegar), octanoic acid (rancid), and phenylethyl alcohol (floral). For each cell, metric space analyses were used to quantify the information conveyed by spike count, by the rate envelope, and by individual spike timing. Results revealed diverse effects of odorants on taste-response magnitude and latency across cells. Importantly, NTS cells were more competent at discriminating taste + odor stimuli versus tastants presented alone for all taste qualities using both rate and temporal coding. The strong interaction of odorants and tastants at the NTS underscores its role as the initial node in the neural circuit that controls food identification and ingestion.

Research on odor interaction between aldehyde compounds via a partial differential equation (PDE) model.

In order to explore the odor interaction of binary odor mixtures, a series of odor intensity evaluation tests were performed using both individual components and binary mixtures of aldehydes. Based on the linear relation between the logarithm of odor activity value and odor intensity of individual substances, the relationship between concentrations of individual constituents and their joint odor intensity was investigated by employing a partial differential equation (PDE) model. The obtained results showed that the binary odor interaction was mainly influenced by the mixing ratio of two constituents, but not the concentration level of an odor sample. Besides, an extended PDE model was also proposed on the basis of the above experiments. Through a series of odor intensity matching tests for several different binary odor mixtures, the extended PDE model was proved effective at odor intensity prediction. Furthermore, odorants of the same chemical group and similar odor type exhibited similar characteristics in the binary odor interaction. The overall results suggested that the PDE model is a more interpretable way of demonstrating the odor interactions of binary odor mixtures.

Assessment of odor activity value coefficient and odor contribution based on binary interaction effects in waste disposal plant

Odor activity value (OAV) has been widely used for the assessment of odor pollution from various sources. However, little attention has been paid to the extreme OAV variation and potential inaccuracies of odor contribution assessment caused by odor interaction effects. The objective of this study is to assess the odor interaction effect for precise assessment of odor contribution. In this paper, samples were collected from a food waste disposal plant, and analyzed by instrumental and olfactory method to conclude odorants' occurrence and OAV. Then odor activity value coefficient (γ) was first proposed to evaluate the type and the level of binary interaction effects based on determination of OAV variation. By multiplying OAV and γ, odor activity factor (OAF) was used to reflect the real OAV. Correlation between the sum of OAF and odor concentration reached 80.0 ± 5.7%, which was 10 times higher than the sum of OAV used before. Results showed that hydrogen sulfide contributed most (annual average 66.4 ± 15.8%) to odor pollution in the waste disposal plant. However, as odor intensity of samples in summer rising, odor contribution of trimethylamine increased to 48.3 ± 3.7% by the strong synergistic interaction effect, while odor contribution of phenol decreased to 0.1 ± 0.02% for the increasing antagonistic interaction effect.

An odor interaction model of binary odorant mixtures by a partial differential equation method.

A novel odor interaction model was proposed for binary mixtures of benzene and substituted benzenes by a partial differential equation (PDE) method. Based on the measurement method (tangent-intercept method) of partial molar volume, original parameters of corresponding formulas were reasonably displaced by perceptual measures. By these substitutions, it was possible to relate a mixture's odor intensity to the individual odorant's relative odor activity value (OAV). Several binary mixtures of benzene and substituted benzenes were respectively tested to establish the PDE models. The obtained results showed that the PDE model provided an easily interpretable method relating individual components to their joint odor intensity. Besides, both predictive performance and feasibility of the PDE model were proved well through a series of odor intensity matching tests. If combining the PDE model with portable gas detectors or on-line monitoring systems, olfactory evaluation of odor intensity will be achieved by instruments instead of odor assessors. Many disadvantages (e.g., expense on a fixed number of odor assessors) also will be successfully avoided. Thus, the PDE model is predicted to be helpful to the monitoring and management of odor pollutions.

Preferential binding of an odor within olfactory receptors: a precursor to receptor activation.

Using computational methods, which allow mechanistic insights at a molecular level, we explored the olfactory receptor (OR)-odor interactions for 2 mouse ORs, S79 and S86. Both ORs have been previously experimentally, functionally characterized. The odors used were mostly carboxylic acids, which differed in chain length, substituents on the primary carbon atom-chain and degree of unsaturation. These odors elicited varied activation responses from both ORs. Our studies revealed that both receptors have 2 distinct binding sites. Preferential binding in 1 of the 2 sites is correlated with OR activation. The activating odorants: nonanedioic acid, heptanoic acid, and octanoic acid for OR S79 and nonanoic acid for OR S86 preferentially bind in the region bound by transmembranes (TMs [helical domains]) III, IV, V, and VI. The non excitatory odorants heptanol for S79 and heptanoic acid for S86 showed a greater likelihood of binding in the region bound by TMs I, II, III, and VII. Nanosecond-scale molecular dynamics simulations of the physiologically relevant conditions of docked OR-odorant complexes enabled us to quantitatively assess the roles of individual OR amino acids in odor binding. Amino acid-odorant contact maps and distance determinations over the course of the simulations lend support to our conclusions.

The role of congruency in taste–odor interactions

The present study investigated the role that congruency between tastes and odors plays in two types of taste–odor interactions: retronasal odor enhancement by taste and retronasal odor referral to the mouth. In the first experiment, subjects rated (1) the intensities of sweetness, sourness, bitterness, and specific odor of aqueous samples of 3 tastants (sucrose, citric acid, caffeine) and 2 odorants (citral, coffee odor), both alone and in taste–odor mixtures, and (2) the degree of congruency of all possible taste–odor pairs. The results showed that only sucrose significantly enhanced the perceived intensities of citrus and coffee odors (Tukey’s test, p<0.05), while citric acid and caffeine failed to enhance or even suppressed the odors. In the second experiment, the returning subjects were asked (1) to report the perceived locations of the odors after inhaling 3 odorants (citral, “sweet” and “bitter” coffee odors) through the mouth alone or in the presence of either water or various tastes in the mouth, and (2) to rate the degree of congruency between tastes and odors. The data showed that a highly congruent taste or taste mixture significantly increased localization of odors to the mouth (χ2, p<0.05). These findings suggest that taste–odor congruency is a necessary but not sufficient condition for retronasal odor enhancement. In contrast, taste–odor congruency is a critical component for retronasal odor referral, and the degree of congruency modulates the degree of odor referral to the mouth. The results and implications of the study findings are discussed in terms of cognitive and perceptual factors of flavor perception.

The Interaction of Mixing Odorants with Similar Chemical Properties: A Case Study on Ketone Compounds

To investigate more about the interaction of mixing odorants, a series of sensory tests were conducted using five ketones [butanone (Bu), 2-Pentanone (Pe), 2-Hexanone (Hex), 2-Heptanone (Hep), 2-Octanone (Oc)] at varying concentration levels. The determination of odor threshold (OT) was initially conducted by the triangle odor bag method (GB/T 14675, China). The odor activity values (OAVs) of individual odorants at a wide range of concentrations were derived from concentration-to-odor threshold ratios. The resulting data were then evaluated to define the empirical relationship for each ketone between the OAV and odor intensity (OI) scaling. Based on the relationships defined for each individual ketone, the OI values were estimated for a synthetic mixture of five ketones. The effect of mixing was then examined by assessing those estimated OI values with the actually measured OI values. The overall results of this study confirmed that the OI values 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 ketone components. Thus, the odor intensity (OI) of a given mixture sample containing odorants with similar chemical properties can be accessed through the conversion from its concentration value with the application of empirical equations instead of direct measurement by the human test panel.

Expanding the olfactory code by in silico decoding of odor-receptor chemical space

Coding of information in the peripheral olfactory system depends on two fundamental : interaction of individual odors with subsets of the odorant receptor repertoire and mode of signaling that an individual receptor-odor interaction elicits, activation or inhibition. We develop a cheminformatics pipeline that predicts receptor-odorant interactions from a large collection of chemical structures (>240,000) for receptors that have been tested to a smaller panel of odorants (∼100). Using a computational approach, we first identify shared structural features from known ligands of individual receptors. We then use these features to screen in silico new candidate ligands from >240,000 potential volatiles for several Odorant receptors (Ors) in the Drosophila antenna. Functional experiments from 9 Ors support a high success rate (∼71%) for the screen, resulting in identification of numerous new activators and inhibitors. Such computational prediction of receptor-odor interactions has the potential to enable systems level analysis of olfactory receptor repertoires in organisms. DOI:http://dx.doi.org/10.7554/eLife.01120.001.

Color–Odor Interactions: A Review and Model

Certain colors are seen as corresponding to, and thus appropriate to, certain odors (e.g., red for cherry odor). When colors accompany odors, our perceptions of the odors are changed. Appropriate colors often affect our perception of the odors differently from inappropriate colors. This paper discusses the literature on color–odor correspondences including possible causes of these correspondences. It then reviews findings on the influence of color on odor identification, odor discrimination, odor intensity, and odor pleasantness. Color's effect on both orthonasal and retronasal olfaction is discussed. A model for how color exerts its effects on odor is proposed.