2000
DOI: 10.1002/1097-461x(2000)79:2<109::aid-qua6>3.0.co;2-g
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Molecular orbital approach to possible discrimination of musk odor intensity

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Cited by 8 publications
(4 citation statements)
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“…One enduring puzzle of structure-odor relations is the relationship between musk odor [typically very similar from musk to musk] and molecular structure [very diverse] [32][33][34][35][36]. To this puzzle we tentatively offer a novel solution.…”
Section: Discussionmentioning
confidence: 99%
“…One enduring puzzle of structure-odor relations is the relationship between musk odor [typically very similar from musk to musk] and molecular structure [very diverse] [32][33][34][35][36]. To this puzzle we tentatively offer a novel solution.…”
Section: Discussionmentioning
confidence: 99%
“…One enduring puzzle of structure-odor relations is the relationship between musk odor [typically very similar from musk to musk] and molecular structure [very diverse] [32][33][34][35][36]. To this puzzle we tentatively offer a novel solution.…”
Section: Discussionmentioning
confidence: 99%
“…This relatively new approach has been applied by a number of researchers for estimation of odour properties. Ishikawa and Kishi [25] studied 203 musk-related molecules and established a relationship between the electronic parameters of the molecules and their odour intensities by performing a discriminative function analysis and multi-linear regression analysis. Korichiet al [26] developed a QSPR model showing the importance of molecular descriptors to predict the odour quality of 121 molecules of balsamic odour employing artificial neural networks and discriminant analysis after reducing the number of descriptors through a variable selection approach.…”
Section: Introductionmentioning
confidence: 99%
“…This relatively new approach has been applied by a number of researchers for estimation of odour properties. Ishikawa and Kishi studied 203 musk‐related molecules and established a relationship between the electronic parameters of the molecules and their odour intensities by performing a discriminative function analysis and multi‐linear regression analysis. Korichi et al .…”
Section: Introductionmentioning
confidence: 99%