Strategies to prevent spread of <i>Leptosphaeria maculans</i> (phoma stem canker) onto oilseed rape crops in China; costs and benefits
Bibliographic record
Abstract
Field experiments in Europe have shown that Chinese cultivars of winter oilseed rape ( Brassica napus ) are very susceptible to the pathogen Leptosphaeria maculans (cause of phoma stem canker). Climatic and agronomic conditions in China are suitable for L. maculans since the closely related but less damaging pathogen L. biglobosa occurs on the winter and spring oilseed rape crops there. Major gene resistance to L. maculans is not durable; when introduced into commercial oilseed rape cultivars it is rapidly rendered ineffective by changes in the pathogen population. The threat to Chinese oilseed rape production from L. maculans is illustrated by the way in which L. maculans has spread into other areas of the world where previously only L. biglobosa was present, such as Canada and Poland. Models were developed to describe the spread (in space and time) of L. maculans across Alberta province, Canada, based on survey data collected over a 15‐year period. These models were used to estimate the potential spread of L. maculans across the Yangtze river oilseed rape growing areas of China and its associated costs. Short‐term strategies to prevent occurrence of severe phoma stem canker epidemics in China include training of extension workers to recognise symptoms of the disease and use of PCR‐based diagnostics to detect the pathogen on imported seed. Long‐term strategies include the introduction of durable resistance to L. maculans into Chinese oilseed rape cultivars as a component of an integrated disease management programme. The costs of such strategies in relation to costs of a phoma stem canker epidemic are discussed.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".