Characterization of Odorants in Clustered Mountain Mint <i>Pycnanthemum muticum</i>
Bibliographic record
Abstract
The clustered mountain mint, Pycnanthemum muticum, is a pleasant-smelling, native North American plant. Despite its wide geographical presence across the United States and Canada, little is known about the specific odorants responsible for its pleasing aroma. Herein, 42 odorants were identified in the plant through solvent-assisted flavor evaporation (SAFE), gas chromatography–olfactometry (GC-O), and gas chromatography–mass spectrometry (GC-MS). Subsequent analysis involved determining flavor dilution (FD) factors using aroma extract dilution analysis (AEDA), quantitating 14 odorants through stable isotope dilution assays (SIDA), and calculating their odor activity values (OAVs). Several noteworthy odorants with OAV ≥ 1 included pulegone (mint, medicinal; OAV 276), 1-octen-3-one (mushroom; OAV 149), menthofuran (mint, petrol; OAV 139), nonanal (citrus; OAV 21), γ-nonalactone (coconut; OAV 13), 1,8-cineole (eucalyptus; OAV 12), mintlactone (mint, coconut; OAV 12), menthone (mint, fresh; OAV 7.3), α-pinene (pine; OAV 4), and piperitenone (mint; OAV 1.9). The study also determined the stereochemistry of various chiral odorants. An aroma simulation model was developed to validate the identification and quantitative results; upon evaluation using olfactory profile analysis, no significant differences were found between the aroma model and an aqueous infusion of P. muticum ( P > 0.05). These findings lay the foundation for future investigations into the diversity of P. muticum selections and can provide valuable insights for studies on plant hybridization for food and flavor applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".