Insights into the chemosensory basis of flavor in table grapes
Bibliographic record
Abstract
BACKGROUND: The full flavor of grape berries is determined by the interaction of sugars, acids, volatile compounds, and other berry properties, such as astringency. Sugars and acids are important for berry taste, whereas volatile compounds are important for the unique berry flavors, e.g., monoterpenes for the Muscat varieties. RESULTS: We explored the basis for 'fruity' flavor perception in table grapes. Samples were collected from 134 new table grape lines and commercial varieties and tested chemically for their volatile profiles and organoleptically by tasting panels. At the sensory level, flavor impression was strongly correlated with berry preference, whereas among 'fruity', 'neutral', 'herbaceous,' and 'Muscat', only the 'fruity' flavor was correlated with berry preference. At the chemical level, 114 volatile compounds were detected in the 81 breeding lines and cultivars examined, and grouped into 'core' and 'unique' categories. The typical berry flavor seemed to depend on the major volatile aldehydes - 1-hexanal and (E)-2-hexenal - accounting for up to an average 85% of the berry's core volatile concentration. We found four volatile compounds - α-bergamotene, geranyl formate, aristolene and α-penansinene - previously undetected, to our knowledge, in fresh grape berries. CONCLUSIONS: High 'fruity' flavor scores were related to three independent factors: (i) presence of unique volatile compounds, such as the sesquiterpene α-copaene, (ii) higher total concentration of volatile compounds, (iii) optimal maturity associated to high total soluble solids (TSS) levels, interacting with berry volatile composition. These combined sensory and analytical data on the flavor of table grapes improve our understanding of the complex interface between chemical and sensory perception in fruit. © 2019 Society of Chemical Industry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".