Odor prediction of whiskies based on their molecular composition

Odor prediction of whiskies based on their molecular composition | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Odor prediction of whiskies based on their molecular composition Satnam Singh*, Doris Schicker*, Helen Haug, Tilman Sauerwald, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4641419/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Dec, 2024 Read the published version in Communications Chemistry → Version 1 posted You are reading this latest preprint version Abstract Aroma compositions are usually complex mixtures of odor-active compounds exhibiting diverse molecular-structure. Due to the chemical interactions of the compounds in the olfactory system, assessing or even predicting the olfactory quality of such mixtures is a difficult problem, not only for statistical models, but even for trained assessors. Here, we combine fast automated analytical assessment tools with human sensory data of 11 trained panelists and machine learning algorithms. Using 16 previously analyzed whisky samples (American or Scotch origin), we use the linear classifier OWSum to distinguish the samples based on their detected molecules and to gain insights into the key molecular structure characteristics and odor descriptors for sample type. Moreover, we use OWSum and a Convolutional Neural Network (CNN) architecture to classify the five most relevant odor attributes of each sample and predict their sensory scores with promising accuracies (up to F1: 0.66, MCC: 0.65, ROCAUC: 0.76). The predictions outperform the panel and thus demonstrate previously impossible data-driven sensory assessment in mixtures. *Satnam Singh and Doris Schicker contributed equally to the work and are shared first authors. Physical sciences/Chemistry/Cheminformatics Physical sciences/Chemistry/Analytical chemistry/Mass spectrometry Full Text Additional Declarations There is NO Competing Interest. Supplementary Files 20240626Supplementary.pdf Cite Share Download PDF Status: Published Journal Publication published 19 Dec, 2024 Read the published version in Communications Chemistry → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4641419","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":327204129,"identity":"14a03992-d4eb-4482-b687-b6bbc0dcf741","order_by":0,"name":"Satnam Singh*","email":"","orcid":"","institution":"Department of Sensory Analytics and Technologies, Fraunhofer Institute for Process Engineering and Packaging IVV, Giggenhauser Str. 35, 85354 Freising, Germany; Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Schwabachanlage 6, 91054 Erlangen, Germany","correspondingAuthor":false,"prefix":"","firstName":"Satnam","middleName":"","lastName":"Singh*","suffix":""},{"id":327204130,"identity":"d40c6c1f-7c66-47ff-9990-3e57da843121","order_by":1,"name":"Doris Schicker*","email":"","orcid":"","institution":"Department of Sensory Analytics and Technologies, Fraunhofer Institute for Process Engineering and Packaging IVV, Giggenhauser Str. 35, 85354 Freising, Germany","correspondingAuthor":false,"prefix":"","firstName":"Doris","middleName":"","lastName":"Schicker*","suffix":""},{"id":327204131,"identity":"fc812259-f818-4711-ab05-b9b36844acef","order_by":2,"name":"Helen Haug","email":"","orcid":"","institution":"Department of Sensory Analytics and Technologies, Fraunhofer Institute for Process Engineering and Packaging IVV, Giggenhauser Str. 35, 85354 Freising, Germany; Department of Chemistry and Pharmacy, Chair of Aroma and Smell Research, Friedrich-Alexander-Universität Erlangen-Nürnberg, Henkestraße 9, 91054 Erlangen, Germany","correspondingAuthor":false,"prefix":"","firstName":"Helen","middleName":"","lastName":"Haug","suffix":""},{"id":327204132,"identity":"3241ffb3-1ba0-42e2-87e0-d6f7ee7d0ea0","order_by":3,"name":"Tilman Sauerwald","email":"","orcid":"","institution":"Department of Sensory Analytics and Technologies, Fraunhofer Institute for Process Engineering and Packaging IVV, Giggenhauser Str. 35, 85354 Freising, Germany","correspondingAuthor":false,"prefix":"","firstName":"Tilman","middleName":"","lastName":"Sauerwald","suffix":""},{"id":327204128,"identity":"5e95a61c-7efa-4658-9a8c-2214d3831c99","order_by":4,"name":"Andreas T. 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