The influence of grapevine cultivar, clone, and rootstock on cold hardiness and dehydrin proteins
Bibliographic record
Abstract
Grapevine cold hardiness is a critical phenotype that is impacted by genetic and environmental factors. The extent of intra- and inter-cultivar differences within the Vitis vinifera L. specie are not well characterized. The dehydrins are a family of proteins that is upregulated by cold temperatures and have seldom been studied in overwintering grapevines. This thesis contains four research articles on these topics. First, cold hardiness of different cultivars was compared using the Vine Alert database containing data from ten winters from more than twenty vineyards. We report average and maximum mid-winter hardiness for Cabernet franc, Cabernet Sauvignon, Chardonnay, Merlot, Pinot noir, Riesling, Sauvignon blanc and Syrah, showing that cultivar and year have a larger impact than site within a viticultural region. Acclimation and deacclimation rates were weakly influenced by cultivar and site, but significantly influenced by the time of the year and the year itself. Cold hardiness was then studied for different clone and rootstock combinations of Riesling (clones 49 and 239 on Riparia gloire and SO4, and 239 on 3309) and Sauvignon Blanc (clones 242, 297, 376, 530) over three winters (2016 to 2019). We demonstrated that clone and clone x rootstock interaction can influence cold hardiness to a greater extent than rootstock alone. We then studied the presence and relative concentration of dehydrin proteins. We identified six new dehydrin bands (23 kDa, 26 kDa, 35 kDa, 41 kDa, 48 kDa, 90 kDa), showed that their concentration peaked either mid-winter or immediately before deacclimation, and demonstrated that they were all correlated to cold hardiness. For the final chapter, we demonstrated intra- and inter-cultivar differences in the hardiness-dehydrin correlations, particularly for the 23 kDa band which is negatively correlated to the % maximum hardiness in Riesling but not in Sauvignon blanc. Riesling cold hardiness was strongly correlated to temperature before sampling, but dehydrin accumulation was strongly correlated to the temperature before sampling in Sauvignon blanc, a key difference in cold-exposure response. This thesis contains findings that are actionable for the industry and relevant for the ongoing research efforts in the field of cold hardiness.
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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".