The impact of grapevine red blotch disease on <scp><i>Vitis vinifera</i></scp> L. Chardonnay grape and wine composition and sensory attributes over three seasons
Bibliographic record
Abstract
BACKGROUND: Grapevine red blotch virus (GRBV) is a recently discovered DNA virus, which was demonstrated to be responsible for grapevine red blotch disease (GRBD). Its presence has been confirmed in the United States, Canada, Mexico, and South Korea in white and red Vitis vinifera cultivars, including Chardonnay. It has been shown that the three-cornered alfalfa treehopper (Spissistilus festinus) was able to both acquire the GRBV from a grapevine infected and transmit it to healthy grapevines in glasshouse conditions. Studies found that GRBD impacts fruit price, grapevine physiology, and grape berry composition and metabolism in red cultivars. This study evaluated the impact of GRBD on V. vinifera L. Chardonnay grape and wine composition and sensory properties from one vineyard during the 2014, 2015 and 2016 seasons. RESULTS: Grapes from symptomatic red blotch diseased grapevines were lower in total soluble solids, flavan-3-ol, and total phenolic content, and higher in flavonol content when compared to grapes from healthy grapevines. Wines made with grapes from symptomatic grapevines resulted mostly in lower ethanol content and higher pH when compared to wines made from healthy grapevines. Analysis of volatile compounds and descriptive analysis demonstrated that GRBD can impact wine style by altering aroma, flavor, and mouthfeel attributes. CONCLUSIONS: The impacts of GRBD on grape composition directly influenced wine chemistry. The decreased ethanol content impacted not only the levels of volatile compounds but the sensory perception during descriptive analysis. The extent of GRBD impact on the grape composition and wine composition and sensory attributes varied between seasons. © 2019 Society of Chemical Industry.
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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 | 0.001 | 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".