Effects of soil tillage and crop rotation on the development of wheat stem base diseases
Bibliographic record
Abstract
Wheat stem base disease (WSD) is an important disease complex which can be caused by various pathogens with variable life cycles, ecological requirements and sensitivities to fungicides. Agronomic practices are considered important tools to control this disease complex and influence the spectrum of fungal communities in infected wheat stems. The aim of the present study was to determine the impact of crop rotation schemes and soil tillage methods on the development of WSD and to elucidate the spectrum of causal agents of this disease. The development of WSD was assessed in a two-factorial (soil tillage practice and crop rotation) experiment. The incidence of WSD was evaluated at the BBCH growth stages 83–85. Causal agents of WSD and other fungi were identified using molecular methods. The soil tillage method did not influence the development of WSD, but the impact of crop rotation was significant, and the cropping system where oilseed rape, barley and faba beans were included decreased disease levels. Members of the genera Oculimacula and Fusarium were the most prevalent fungi associated with WSD. Moreover, fungi from other taxonomic groups were detected, with Phaeosphaeria spp. being prevalent. An increasing occurrence of Microdochium spp. was also observed. In conclusion, agronomic practices influenced the level of WSD, but no distinct impact on the fungal spectrum was identified. Further investigation is required to clarify the roles that pathogens and fungi from other taxonomic groups play in the fungal–wheat relationship.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".