In recent years, varietal honey has been a massive target of adulteration through mislabeling and the addition of other sugars. Unethical companies do this to cut production costs while still charging the consumer full price. Previous studies have used nuclear magnetic resonance (NMR) to unravel possible adulteration in honey, but currently, there are no standard rapid methods to authenticate varietal honey. In our research, we collected NMR signatures (“fingerprints”) and combined them with linear discriminant analysis (LDA) to predict the varietal, country, and region of varietal honey. As a part of the project, we investigated whether an adjustment to the spectral data based on a signal-to-noise cutoff would provide better predictive ability. Our results are inconclusive as to whether a signal-to-noise adjustment provides a meaningful advantage; however, they demonstrate that combining NMR data with LDA enables prediction of honey varietal, country, and region at rates significantly better than random chance.
","abstract_html":"<p>In recent years, varietal honey has been a massive target of adulteration through mislabeling and the addition of other sugars. Unethical companies do this to cut production costs while still charging the consumer full price. Previous studies have used nuclear magnetic resonance (NMR) to unravel possible adulteration in honey, but currently, there are no standard rapid methods to authenticate varietal honey. In our research, we collected NMR signatures (“fingerprints”) and combined them with linear discriminant analysis (LDA) to predict the varietal, country, and region of varietal honey. As a part of the project, we investigated whether an adjustment to the spectral data based on a signal-to-noise cutoff would provide better predictive ability. Our results are inconclusive as to whether a signal-to-noise adjustment provides a meaningful advantage; however, they demonstrate that combining NMR data with LDA enables prediction of honey varietal, country, and region at rates significantly better than random chance.</p>","abstract_has_math":false,"creators":["Mac, Taylor"],"institution":null,"degree_name":"Master of Science (MS)","degree_level":"Open Access Thesis","degree_discipline":"Chemistry","degree_department":null,"school":null,"contributors":["Cory Emal, Ph.D.","Heather Holmes, Ph.D.","Gregg Wilmes, Ph.D."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026-01-01T08:00:00Z","date_published":"2026-01-01T08:00:00Z","updated_at":"2026-07-24T02:17:53Z","subjects":["Chemistry","Organic Chemistry"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.emich.edu/theses/1335","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Cory Emal, Ph.D.","Heather Holmes, Ph.D.","Gregg Wilmes, Ph.D."]},{"key":"dc:creator","label":"Author","values":["Mac, Taylor"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2026-06-22T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Chemistry"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Chemistry","Organic Chemistry"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.emich.edu/theses/1335"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In recent years, varietal honey has been a massive target of adulteration through mislabeling and the addition of other sugars. Unethical companies do this to cut production costs while still charging the consumer full price. Previous studies have used nuclear magnetic resonance (NMR) to unravel possible adulteration in honey, but currently, there are no standard rapid methods to authenticate varietal honey. In our research, we collected NMR signatures (“fingerprints”) and combined them with linear discriminant analysis (LDA) to predict the varietal, country, and region of varietal honey. As a part of the project, we investigated whether an adjustment to the spectral data based on a signal-to-noise cutoff would provide better predictive ability. Our results are inconclusive as to whether a signal-to-noise adjustment provides a meaningful advantage; however, they demonstrate that combining NMR data with LDA enables prediction of honey varietal, country, and region at rates significantly better than random chance.
"]},{"key":"dc:title","label":"Title","values":["Using NMR spectroscopy and linear discriminant analysis to molecular profile varietal honey"]}]}],"canonical_facts":{"dc:contributor":["Cory Emal, Ph.D.","Heather Holmes, Ph.D.","Gregg Wilmes, Ph.D."],"dc:creator":["Mac, Taylor"],"dc:date.available":["2026-06-22T07:00:00Z"],"dc:description.abstract":["In recent years, varietal honey has been a massive target of adulteration through mislabeling and the addition of other sugars. Unethical companies do this to cut production costs while still charging the consumer full price. Previous studies have used nuclear magnetic resonance (NMR) to unravel possible adulteration in honey, but currently, there are no standard rapid methods to authenticate varietal honey. In our research, we collected NMR signatures (“fingerprints”) and combined them with linear discriminant analysis (LDA) to predict the varietal, country, and region of varietal honey. As a part of the project, we investigated whether an adjustment to the spectral data based on a signal-to-noise cutoff would provide better predictive ability. Our results are inconclusive as to whether a signal-to-noise adjustment provides a meaningful advantage; however, they demonstrate that combining NMR data with LDA enables prediction of honey varietal, country, and region at rates significantly better than random chance.
"],"dc:identifier":["https://commons.emich.edu/theses/1335"],"dc:subject":["Chemistry","Organic Chemistry"],"dc:title":["Using NMR spectroscopy and linear discriminant analysis to molecular profile varietal honey"],"thesis:degree_discipline":["Chemistry"],"thesis:degree_level":["Open Access Thesis"],"thesis:degree_name":["Master of Science (MS)"]},"updated_at":"2026-07-24T02:17:53Z"}