Rootstocks Impact Vine Performance and Fruit Composition of Grapes in British Columbia
Bibliographic record
Abstract
Nine wine grape cultivars [`Chardonnay', `Gewurztraminer', `Ortega', `Riesling', `De Chaunac', `Marechal Foch', `Okanagan Riesling', `Seyval blanc', and Verdelet'], own rooted or grafted to four rootstocks [`Couderc 3309' ( Vitis riparia × V. rupestris ); `Kober 5BB' (5BB), `Teleki 5C', and `Selektion Oppenheim 4' (SO4) ( V. riparia × V. berlandieri )] were planted into a randomized complete block experiment in 1985. Data were collected on yield components, weight of cane prunings (vine size), and fruit composition between 1989 and 1996. Yield per vine, clusters per vine, cluster weight, and berry weight were not affected by rootstock, but SO4 tended to produce lowest berries per cluster. Lowest vine size was associated with 5BB and own-rooted vines were usually largest; 5BB was also associated with highest crop load (yield to vine size ratio). Own-rooted vines tended to produce berries with lowest percentage soluble solids (%SS) while 5BB led to highest %SS. Titratable acidity was not strongly affected and pH differences between rootstocks were very small. These data suggest that rootstocks may not provide significant advantage over own-rooted vines under conditions found in the arid regions of the Pacific northwestern U.S. and British Columbia.
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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 | 0.001 | 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".