Anatomic and genetic factors associated with the susceptibility of grapevine cultivars to <i>Plasmopara viticola</i> clade <i>aestivalis</i> and clade <i>riparia</i>
Bibliographic record
Abstract
The susceptibility of commonly grown grapevine cultivars in the province of Quebec to Plasmopara viticola (Berk. & M.A. Curtis) Berl. & De Toni clades riparia and aestivalis was compared. The relationship between anatomic (density and size of stomata and type of leaf hairs) and genetic composition (percentages of Vitis vinifera L., Vitis riparia Michx. and Vitis aestivalis Michx.) factors of the grapevine cultivars and their susceptibility to the two clades was investigated. The grapevine cultivars were classified according to their susceptibility to each clade. The aggressiveness of the clade riparia was positively correlated with stomata size and negatively correlated with type of leaf hairs. However, the aggressiveness of clade aestivalis was positively correlated with stomata size and density, estimated percentage of V. vinifera ancestry, and the published downy mildew susceptibility of grapevine cultivars; and negatively correlated with estimated percentage of V. riparia ancestry. Furthermore, the grapevine cultivar classification showed that, for P. viticola clade riparia, 44.4%, 44.4%, and 11.1% of the grapevine cultivars were classified as minimally susceptible, moderately susceptible, and highly susceptible, respectively. Alternatively, for P. viticola clade aestivalis, 11.1%, 22.2%, and 66.7% of the grapevine cultivars were classified as minimally susceptible, moderately susceptible, and highly susceptible, respectively. Although some grapevine cultivars fell in the same susceptibility groups for both clades, 78% of grapevine cultivars were classified in different susceptibility groups. The findings of this study provide new information on grapevine and P. viticola interactions, and highlight the importance of knowing which clade of P. viticola is present so that downy mildew control measures can be adapted accordingly.
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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 | 0.001 | 0.001 |
| 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".