Determination of Ortho‐ and Retronasal Detection Thresholds and Odor Impact of 2,5‐Dimethyl‐3‐Methoxypyrazine in Wine
Bibliographic record
Abstract
2,5-Dimethyl-3-methoxypyrazine (DMMP) has been recently identified in both Coccinellidae-tainted (by either Coccinella septempunctata or Harmonia axyridis beetles) and untainted wines; however, little is known regarding its impact on wine aroma and flavor. The aims of this study were to obtain an accurate estimate of both the ortho- and retronasal detection thresholds of DMMP in red wine and to understand how DMMP contributes to the aroma profile of red wine. In the first study, thresholds were determined for 21 individuals using the ASTM E679 ascending forced choice method of limits. The orthonasal group best estimate threshold (BET) was 31 ng/L and the retronasal group BET was 70 ng/L. A moderate variation in individual thresholds was observed for the orthonasal modality (standard deviation (SD) = 19.8) and a larger variation was noted for retronasal thresholds (SD = 111.8). In the second study, a panel of 8 assessors performed descriptive sensory analysis on 3 red wines containing various concentrations of added DMMP (0, 50, and 120 ng/L). Results show significant changes in aroma characteristics in the 120 ng/L wine and smaller effects at the 50 ng/L level. Overall, wines spiked with DMMP generated lower intensity ratings for cherry and red berry descriptors and higher ratings for earthy/musty and green/vegetal descriptors. When considered with other recent results on DMMP concentrations found in wine, DMMP can be considered a hitherto undescribed impact odorant in some wine styles.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".