Contact Information

(267) 519-4668
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Emily Mayhew

Affiliations

Postdoctoral Fellow, Monell Chemical Senses Center

Laboratory of

Dr. Joel Mainland

Education

Ph.D., Food Science, University of Illinois at Urbana-Champaign

Research Summary

The collection of all organic molecules comprises millions of known molecules in public databases as well as a much larger number of theoretically possible molecules. How many of these molecules have an odor? What features of the molecule most strongly influence what the molecule will smell like?

My research interest lies in using the chemical and physical properties of stimuli to explain and predict human sensory perception. At Monell, the focus of my work will be the prediction of odor characteristics of molecules based on structural characteristics of the molecules. Our first aim is to collect rich sensory data from human evaluations of the presence/absence of an odor and the sensory characteristics of the odor for a diverse set of molecules. Combining this information with a wide array of physicochemical and structural variables, we will build and train models using machine learning to predict both whether a compound is odorous or odorless and what type of odor perception a molecule elicits. These models can enable more accurate prediction of the total number of possible odorous molecules and identify key molecular features that influence odor perception.

Keywords

Olfaction, psychophysics, machine learning

Recent Publications

Mayhew EJ, Neal CH, Lee S-Y, Schmidt SJ. (2017) Glass transition prediction strategies based on the Couchman-Karasz equation in model confectionary systems. J. Food Eng. 214: 287-302. doi.org/10.1016/j.jfoodeng.2017.07.007

Mayhew EJ, Schmidt SJ, Schlich P, Lee S-Y. (2017) Correlation of consumer perception of stickiness and contributing texture attributes to trained panelist evaluations in a caramel system. Food Qual. Prefer. 65:72-80. doi.org/10.1016/j.foodqual.2017.11.009.

Mayhew EJ, Schmidt SJ, Schlich P, Lee S-Y. (2017) Temporal texture profile and identification of glass transition temperature as an instrumental predictor of stickiness in a caramel system. J. Food Sci. 82(9): 2167-76. doi.org/10.1111/1750-3841.13822.