Primary hexaploid synthetics: Novel sources of wheat disease resistance
Bibliographic record
Abstract
Climate change is leading to increased occurrence of and yield losses to wheat diseases. Managing these diseases by introducing new, effective and diverse resistance genes into cultivars represents an important component of sustainable wheat production. In 2016 and 2017 a set of primary hexaploid synthetic wheat was studied under high disease pressure: powdery mildew, leaf and stem rust in Omsk; Septoria tritici and S. nodorum in Moscow. A total of 28 synthetics (19 CIMMYT synthetics and 9 Japanese synthetics) were selected as having combined resistance to at least two diseases in both years of testing. Two synthetics (entries 13 and 18) originating from crosses between winter durum wheat Ukrainka odesskaya-1530.94 and various Aegilopes taushii accessions, and four synthetics (entries 20, 21, 23 and 24) from cross between Canadian durum wheat Langdon and Ae. taushii were resistant to all four pathogens. Pathological and molecular markers evaluation of resistance suggests presence of new genes and diverse types of resistance. The novel genetic sources of disease resistance identified in this study can be successfully utilized in wheat breeding.
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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 | 0.000 |
| 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) | 0.003 | 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".