Anthracnose Risk Establishment Based on Age-Related Susceptibility of Grape Leaves, Flowers, and Berries to Infection by <i>Elsinoë ampelina</i>
Bibliographic record
Abstract
, but detailed and seasonal development of age-related susceptibility remains unclear. Experiments were conducted under greenhouse and vineyard conditions by inoculating 1- to 19-day-old leaves, flowers, and berries at different phenological stages of three grapevine cultivars (Vandal-Cliche, Marquette, and Vidal). Leaf susceptibility was highest when inoculated at 1 to 2 days old, and inoculated leaves were moderately susceptible at 3 to 6 days old and almost resistant when older than 6 days. The influence of leaf age on anthracnose relative severity was adequately described by an exponential decay model. The susceptibility of the inflorescences was high when inoculated from their initiation to the full flowering (50% fall of the caps), and the inflorescences/flowers were moderately susceptible until veraison, after which the berries were practically resistant. The flower/berry susceptibility as a function of degree-days accumulated since 1 April was modeled using a sigmoid model. Based on this model, 50% disease incidence is reached when 656, 543, and 550 degree days are accumulated for the cultivars Vandal-Cliche, Marquette, and Vidal, respectively. These results suggest that the risk of anthracnose development is high from bud-break to fruit set, and on newly emerged leaves either early in the season or following pruning. More knowledge on anthracnose epidemiology is needed, but these results could be used to improve timing of fungicide applications and pruning activities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".