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Odor mixtures

All animals exhibit innate behaviors in response to specific sensory stimuli that are likely to result from the activation of developmentally programmed neural circuits. Even the activation of single classes of olfactory neurons can trigger complex behaviors [10]. The authors observed that Drosophila exhibit robust avoidance to odors released by stressed flies. When stressed, the flies emit an odorant mixture that elicits avoidance in other flies. C02 is the active component of this mixture. Specific blockade of the activation of a particular odorant receptor... [Pg.65]

In addition to the simultaneous impact of an odor mixture, differential evaporation may alter the signal over time, indicating the age of a scent. As an example, the major component of the chest gland secretion of the thick-tailed galago. Galago crassicaudatus, is benzylcyanide. It evaporates rapidly and is present for only about 1 hour. The other two identified compounds last for several days. In a behavioral corollary, galagos retreat from a scent mark that is less than 1 hour old, while older marks have no such effect (Katsir and Crewe, 1980). [Pg.28]

Chandra S. and Smith B. H. (1998) An analysis of synthetic processing of odor mixtures in the honeybee (Apis mellifera). J. Exp. Biol. 201, 3113-3121. [Pg.644]

Streschnak, B. 1991. Support materials for odorant mixtures. In Perfumes Art, Science, and Technology, P. M. Muller and D. Lamparsky, eds. Elsevier, London/New York, pp. 347-362. [Pg.325]

Propylene Carbonate (PC) PC is prepared by reacting propylene chlorohydrin with sodium bicarbonate. It is available as a clear liquid with a faint odor. Mixtures of PC and propylene glycol are good solvents for corticosteroids in topical preparations. It is incompatible with strong acids, bases, and amines. The pH of 10% aqueous dispersion is 6.0-7.5 [34],... [Pg.300]

Le Berre, E., Atanasova, B., Langlois, D., Etievant, R, Thomas-Danguin, T. (2007). Impact of ethanol on the perception of wine odorant mixtures. Food Qual. Prefer., 18, 901-908... [Pg.434]

Livermore, A., Laing, D. G. 1998. "The Influence of Chemical Complexity on the Perception of Multicomponent Odor Mixtures." Perception and Pschophysics, 60 650-661. [Pg.271]

The study of the perception of compounds present in odor mixtures is also fraught with the sorts of nonlinear "contextual effects" with which vision and auditory scientists are all too familiar. At present, most studies use human subjects to examine the way that odor compounds affect perception in complex mixtures such studies show that perceived odor similarity between two complex blends is likely to be mediated both by the types of compounds found in the mixtures and the relative... [Pg.210]

In complex odor mixtures, the ratios of odorant concentrations may be important features that animals use to discriminate. This has been shown to be especially true of pheromone blends, where the ratio of the concentration of each pheromone compound in the blend may affect several behaviors, from anemotaxis to contact with the source of emission. Variability of emission of the ratios of odorants in pheromone blends can occur within individuals and across populations or between species. The strength of the effects of variation on behavior appears to be dependent upon the species involved, however. In non-pheromonal odors, the ratios of odor compounds in scent may also be useful for discriminating among odor-emitting objects. Differences attributed to scent as a function of the ratios of odorant compounds may be more subtle than perceptual differences that occur from the subtraction or addition of different odorant compounds to an odor mixture. As these differences may be hard to detect, the extent to which animals use differences in the ratios of compounds may be governed by the cost of making a mistake between scents with different ratios. [Pg.213]

A recent study by Wright and Smith (2004a) showed that multiple features of odor mixtures influence which features are used by honeybees to identify previously experienced odors. In particular, the study observed that both variation in the concentration of individual odorants in a mixture and the overall intensity of an odor mixture affected what honeybees learned about odors during conditioning. They conditioned honeybees with mixtures of odorants where the concentration of one odorant remained the same throughout conditioning and the concentration of the... [Pg.214]

LASKA, M HUDSON, R., Discriminating parts from the whole - determinants of odor mixture perception in squirrel-monkeys, Saimiri-sciureus. J. Comp. Phys. A, 1993, 173, 249-256. [Pg.224]

LASKA, M., HUDSON, R., Ability to discriminate between related odor mixtures. Chem. Sens., 2002,17, 403-415. [Pg.224]

Linster, C., Masson, C., Kerszberg, M., Personnaz, L., Dreyfus, G. Computational diversity in a formal model of the insect olfactory macroglomerulus. Neural Comput. 5, 228-241 (1993) Linster, C., Smith, B.H. A computational model of the response of honey bee antennal lobe circuitry to odor mixtures Overshadowing, blocking and unblocking can arise from lateral inhibition. Behav. Brain Res. 87, 1-14 (1997)... [Pg.32]

A given animal will produce both pheromones and signature mixtures (Fig. 2.3). In addition to its sex pheromone(s), each lobster has its own highly individual odor mixture and this complex bouquet can be used by other lobsters for recognition (see Atema and Steinbach 2007). [Pg.31]

Previous studies of odor mixture have often reported rules for the addition of odor intensities, which conform to a vector model, at least in binary mixtures (1,2,3,4). Higher order mixtures moy or may not generate a total odor intensity which conforms to a vector model (Mixture A +... [Pg.23]

Scaling of the simple odors and their binary mixtures on a variety of characteristics, including measures of overall odor strength, odor liking/disliking, odor mixture complexity, and 12 additional descriptor characteristics appropriate for the particular odorants studied. [Pg.24]

Tables I, II, III and IV show the data base for the four sets of experiments reported there. Note that in each experiment a group of non-expert panelists evaluated each of the sets of odor mixtures twice, using magnitude estimation scaling. Thus, the tables each present numbers which are averages of approximately 32-36 ratings, depending upon the particular study. Furthermore, note that in Tables l-IV, the panelists profiled each stimulus on a variety of sensory characteristics. Tables I, II, III and IV show the data base for the four sets of experiments reported there. Note that in each experiment a group of non-expert panelists evaluated each of the sets of odor mixtures twice, using magnitude estimation scaling. Thus, the tables each present numbers which are averages of approximately 32-36 ratings, depending upon the particular study. Furthermore, note that in Tables l-IV, the panelists profiled each stimulus on a variety of sensory characteristics.
The first analysis of the ratings concerns their validity. Can panelists actually scale the relative sensory impressions of these odor stimuli by magnitude estimation Correct scaling of overall odor Intensity provides a validating measure of the panelist s sensory capabilities in this complicated study. Since panelists had the opportunity to scale unmixed odorants as well as the odor mixtures, and since the unmixed odorants comprised a graded intensity series (albeit presented at random in the set of 2k stimuli) it becomes a straightforward matter to determine whether panelists could pick out the k levels of each unmixed odorant, and scale them in the correct order of concentration. Panelists should do so. Table V shows linear and log-log (viz., power functions) relations between odor concentration in air, and rated overall odor intensity, for each pair of odorants in each study. Linear and power functions fit the data adequately. For power functions, the exponents are less than 1.0, confirming previously reported results in the literature. (2, 3)... [Pg.25]

The foregoing data suggests that it is possible to develop odor mixtures which reproduce a sensory profile if the components possess their specific odor characteris+ics Four observations are in order, however. [Pg.37]

The optimization of liking in odor mixtures, subject to engineering specific sensory characteristics to lie within pre-specified values (e.g., maximize liking, with overall odor intensity lower than a prespecified level). [Pg.42]

For some, but not all of the odor mixtures, the relation between overall liking vs concentration can be improved if one uses the non-linear quadratic equation, discussed previously (Equation 2). This non-linear equation allows liking of the odor mixture to increase, peak at an intermediate bliss point of concentrations, and then to drop bock down with further increases in concentration. [Pg.42]

One can also constrain the odorant mixtures to maximize acceptance, while at the same time maintaining a perceptual characteristic within pre-set boundaries. Recall that overall liking or acceptability grew according to a quadratic function of odor combinations, of the form ... [Pg.43]


See other pages where Odor mixtures is mentioned: [Pg.309]    [Pg.172]    [Pg.8]    [Pg.484]    [Pg.155]    [Pg.227]    [Pg.2142]    [Pg.407]    [Pg.1068]    [Pg.224]    [Pg.224]    [Pg.322]    [Pg.1]    [Pg.23]    [Pg.23]    [Pg.25]    [Pg.27]    [Pg.29]    [Pg.31]    [Pg.33]    [Pg.35]    [Pg.36]    [Pg.37]    [Pg.39]    [Pg.41]    [Pg.41]    [Pg.42]    [Pg.43]   
See also in sourсe #XX -- [ Pg.210 , Pg.213 , Pg.214 ]




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