Irrigation Targeted to Provoke Ejection of Ascospores of <i>Venturia inaequalis</i> Shortens the Season for Ascospore Release and Results in Less Apple Scab
Bibliographic record
Abstract
Trials were carried out in apple orchards of Emilia-Romagna and Trentino-Alto Adige in northern Italy to investigate the effects of sprinkler irrigation on possible reduction in inoculum and subsequent disease pressure of Venturia inaequalis, the ascomycete causing apple scab. In spring, volumetric spore traps were placed above apple leaf litter containing pseudothecia with ascospores of the fungus. Pseudothecia matured more rapidly in irrigated plots, and 95% of the total number of spores trapped in a season was reached on average 164 degree days (base temperature 0°C) earlier in irrigated compared with nonirrigated plots. On average for seven location/year combinations, more than 50% of the ascospores were trapped following irrigations carried out for 2 h on sunny days before a forecasted rainfall. Subsequently, a much lower number of spores were trapped on rainy days following irrigation. Field trials with scab-susceptible apple cultivars were carried out in the two regions to evaluate the efficacy of sprinkler irrigation on disease. Irrigated and nonirrigated plots were either treated with different fungicide control strategies or not treated. Irrigation significantly reduced the incidence of apple scab at both sites, and the overall number of infected leaves and fruit was reduced by more than 50%. Midday sprinkler irrigation can significantly reduce the inoculum pressure of V. inaequalis in apple orchards. This may be a sustainable management strategy, especially in areas with extended dry periods.
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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 | 0.000 | 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".