|Author||Yan, Luchun ♦ Liu, Jiemin ♦ Qu, Chen ♦ Gu, Xingye ♦ Zhao, Xia|
|Source||World Health Organization (WHO)-Global Index Medicus|
|Publisher||Multidisciplinary Digital Publishing Institute|
|File Format||HTM / HTML|
|Subject Domain (in DDC)||Philosophy & psychology ♦ Psychology ♦ Natural sciences & mathematics ♦ Chemistry & allied sciences ♦ Life sciences; biology ♦ Biochemistry ♦ Technology ♦ Medicine & health ♦ Incidence & prevention of disease ♦ Pharmacology and therapeutics ♦ Diseases ♦ Manufacture for specific uses ♦ Precision instruments & other devices|
|Subject Domain (in MeSH)||Organic Chemicals ♦ Chemicals and Drugs ♦ Investigative Techniques ♦ Analytical, Diagnostic and Therapeutic Techniques and Equipment ♦ Psychological Phenomena and Processes ♦ Psychiatry and Psychology|
|Subject Keyword||Discipline Biotechnology ♦ Aldehydes ♦ Isolation & Purification ♦ Models, Theoretical ♦ Odors ♦ Analysis ♦ Chemistry ♦ Sensory Thresholds ♦ Smell ♦ Journal Article ♦ Research Support, Non-u.s. Gov't|
|Abstract||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.|
|Description||Country affiliation: China
Author Affiliation: Yan L ( School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Xueyuan Road 30, Haidian District, Beijing 100083, China. email@example.com.); Liu J ( School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Xueyuan Road 30, Haidian District, Beijing 100083, China. firstname.lastname@example.org.); Qu C ( School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Xueyuan Road 30, Haidian District, Beijing 100083, China. email@example.com.); Gu X ( School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Xueyuan Road 30, Haidian District, Beijing 100083, China. firstname.lastname@example.org.); Zhao X ( School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Xueyuan Road 30, Haidian District, Beijing 100083, China. email@example.com.)
|Educational Role||Student ♦ Teacher|
|Age Range||above 22 year|
|Educational Use||Reading ♦ Research ♦ Self Learning|
|Education Level||UG and PG|
|Learning Resource Type||Article|
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