Monitoring blackleg (Leptosphaeria spp.) ascospore release timing and quantity enables optimal fungicide application to improved oilseed rape yield and seed quality
Bibliographic record
Abstract
Stem canker is a damaging disease of winter oilseed rape, caused by ascomycetous fungi Leptosphaeria maculans and L. biglobosa. The initial source of plant infection is ascospores, formed in pseudothecia on stubble from the previous growing season. The aim of this work was to evaluate the effectiveness of fungicide treatments at different times of application in the autumn on quality and quantity of seed yield, in relation to the concentration of ascospores of L. maculans and L. biglobosa in the air. Field experiments were done in Lower Silesia, the region of intensive oilseed rape cultivation, located in south-west Poland. We have demonstrated that, in case of high disease pressure, fungicide treatment against stem canker was most efficient when done 4–11 days after the highest concentration of pathogen ascospores in air. The seed yield, oil and protein content increased by 17.7–18.8 %, 1.60–1.72 % and 0.8–0.9 % respectively. In low disease pressure the optimal spray time was more flexible, but the highest yield was always following the maximum ascospore release. In some cases it also coincided with the increase of oil, without adverse effect on protein content. Furthermore, it coincided with the increase of indole glucosinolates, such as glucobrassicine and 4-hydroxyglucobrassicine, and – besides one studied year – it was also connected with decreased amounts of alkenyl glucosinolates. Both Leptosphaeria species were present in air and in infected plants during their vegetation. The ratio between both species depended on seasons; L. maculans prevailed on leaves in the autumn, whereas L. biglobosa dominated on stems before harvest.
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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".