Clone and Rootstock Interactions Influence the Cold Hardiness of <i>Vitis vinifera</i> cvs. Riesling and Sauvignon blanc
Bibliographic record
Abstract
Cold damage is a threat to grapegrowers worldwide. Cold hardiness varies across <i>Vitis vinifera</i> cultivars, but the influence of clone and rootstock selection on this trait is unclear. Five clone × rootstock combinations of Riesling (clone 49 × Riparia Gloire [RG], 49 × SO4 Teleki, clone 239 × RG, 239 × SO4, and 239 × Couderc 3309) and four clones of Sauvignon blanc (clone 242, 297, 376, and 530 on SO4 Teleki rootstock) were evaluated over three dormant seasons (2016/17, 2017/18, and 2018/19). Bud cold hardiness was quantified every two to four weeks by differential thermal analysis and reported as low temperature exotherms. Yield and pruning weights were determined every year. Rootstock did not influence the cold hardiness of Riesling buds consistently, although clone 239 was generally hardier than clone 49. Significant clone × rootstock interactions were observed more frequently in the first year of the study. No consistent differences were observed between Sauvignon blanc clones, although clone 242 and 297 were often among the least-hardy clones. Differences in hardiness were not consistently related to yield, pruning weight, or crop load in the prior growing season. This study demonstrates the importance of both clone and rootstock selection in cool climate regions where freeze injury may occur. Future research should consider the clone identity and the possibility of a clone × rootstock interaction when comparing the cold hardiness of different cultivars.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".