The Influence of <i>Harmonia axyridis</i> on Wine Composition and Aging
Bibliographic record
Abstract
ABSTRACT: This study sought to further characterize the effects of Harmonia axyridis (HA ) on white and red wine quality, including determining the influence of bottle aging on the composition and sensory attributes of HA‐affected wines and examining the hypothesis that methoxypyrazines are responsible for the characteristic sensory profiles of these wines. Vinification in the presence of HA beetles had little effect on basic physical and chemical attributes of white and red wine, either at bottling or after 10‐mo of aging. 2‐Isopropyl‐3‐methoxypyrazine (IPMP) was detected at relatively high concentrations and at levels above sensory threshold in wines fermented in the presence of HA . In addition, significant positive correlations were found between IPMP concentration in wines and sensory attributes that characterize HA “taint.” After aging, the aroma and flavor profiles of HA‐ treated wines were similar to those of newly bottled wines. White wines showed a trend, as beetle numbers increased, of higher intensities of peanut, bell pepper, asparagus, and bitterness attributes and lower scores for fruit and floral descriptors. Red wines showed a trend of higher scores for peanut and asparagus/bell pepper aroma intensity and lower scores for fruit attributes as the number of beetles increased.
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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 | 0.000 | 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) | 0.001 | 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".