Effective Resources in Wheat and Wheat–<i>Thinopyrum</i> Derivatives for Resistance to <i>Heterodera filipjevi</i> in China
Bibliographic record
Abstract
ABSTRACT Cereal cyst nematode (CCN) is becoming one of the important soil‐borne pathogens in wheat (Triticum aestivum L.) monocropping or wheat–maize (Zea mays L.)–wheat cropping systems of central China. Heterodera filipjevi (Madzhidov, 1981) Stelter, 1984 was recently recognized as a causal agent of CCN in China, but little information is available on sources of resistance against this nematode species. The present study was initiated to determine the current status of resistance in wheat cultivars against H. filipjevi and to identify effective resources for improvement of CCN resistance in China. A 3‐yr field study of CCN resistance that involved 174 wheat cultivars or wheat–Thinopyrum derivatives was conducted in a wheat field in Xuchang, Henan Province, China, where H. filipjevi had been present for years. Greenhouse experiments were conducted with representative resistant entries from each group of accessions. None of the 78 wheat cultivars and breeding lines from China was resistant in field tests. Wheat cultivar Madsen from Washington State was most resistant among the entries tested both in field and under controlled environment. New sources of resistance to H. filipjevi were identified in some wheat–intermediate wheatgrass [Thinopyrum intermedium (Host) Barkworth & D. R. Dewey] and wheat–tall wheatgrass [Thinopyrum ponticum (Podp.) Barkworth & D. R. Dewey] partial amphiploids, which will diversify resistance resources in enhancing resistance of wheat against CCN.
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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 | 0.001 | 0.001 |
| 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".