A Model to Estimate the Amount of Primary Inoculum of <i>Elsinoë ampelina</i>
Bibliographic record
Abstract
In Eastern Canada, anthracnose, caused by the fungus Elsinoë ampelina, is a serious disease on susceptible grape cultivars. In the absence of management tools, anthracnose management relies almost exclusively on fungicide applications programmed at fixed intervals. Therefore, a better understanding of the factors affecting primary inoculum release and abundance would help in the timing of the first fungicide applications. The temporal dynamics of airborne primary inoculum released from cane cankers were investigated from 2007 to 2010. One to three times per week, starting in the first week of April, six 12-cmlong cane pieces were randomly selected from diseased canes that had overwintered on a vineyard floor. The concentration of E. ampelina conidia was expressed as the number of conidia per square millimeter of canker. In total, 27, 32, 33, and 118 samplings were conducted in 2007, 2008, 2009, and 2010, respectively, with the 118 samplings conducted on three sites at 49, 35, and 34 samplings for site 1, 2, and 3, respectively. Each year, the number of conidia per square millimeter of canker was expressed as the proportion of seasonal inoculum (PSI) at the same site and analyzed as a function of degree-days (DD; base temperature = 0°C) accumulated since 1 April (cumulative degreedays [CDD]). The nonlinear sigmoid model in the form PSI = 1.003/(1 + e –((CDD – 566.133)/139.204) ) provided adequate fit to the observed data (P < 0.0001, R 2 = 0.97). When the model was validated against independent data, the model adequately predicted PSI; however, reliability was improved by adding a “dry days” threshold of 6 days during which accumulation of DD is stopped. This study shows that primary inoculum of grape anthracnose is available early in the season before bud break; meaning that emerging leaves could be infected provided that weather conditions are favorable. The results also show that there is an overlap in the availability of primary and secondary inoculum, mainly during the period of rapid leaf growth, a situation that may explain the explosive nature of the disease. The results suggest that, on susceptible cultivars and when there is a history of anthracnose in the vineyard, a fungicide spray program should be initiated early in the season, as soon as leaves are present.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".