Etude de la résistance du colza (Brassica napus) au Phoma (Leptosphaeria maculans) : étude des populations du pathogène et cartographie génétique des QTL impliqués dans la résistance
Bibliographic record
Abstract
Leptosphaeria maculans est l’agent responsable de la Necrose du collet du colza. Il est l’agent de la maladie la plus grave des Brassica spp. . L’utitlisation de genes majeurs de resistance a permis de controler cette maladie, mais cet Ascomycete s’adapte tres rapidement. Une collection de souches a ete analysees pour connaitre la structure des races presentes au Canada. Durant mes travaux de recherche, j’ai construis une carte genetique du colza avec un taux de saturation de 50%. Les evaluations phenotypiques ont ete faite en conditions controlees et au champ au Canada et Australia. L’analyse QTLs a ete faite par deux methodes a l’aide MapQTL. Le gene majeur de resistance a ete identifiee avec un R2 variant entre 30 et 50%. De nombreux QTLs ont ete observees pour la resistance commune entre le champ et le laboratoire et d’autres specifiques du champs. C’est la premiere fois que de la cartographie de la resistance pour L. Maculans a ete faite entre le Canada et l’Australie et entre le resistance au champ et au laboratoire. Les futures travaux sont orientes l’extension de la carte genetique. Une cartographie de la resistance a Sclerotinia sclerotiorum a aussi ete realisees.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".