New Sources of Temperature-Sensitive Resistance to <i>Wheat streak mosaic virus</i> in Wheat
Bibliographic record
Abstract
Expressing temperature-sensitive resistance (TSR) protects wheat against yield losses from infection with Wheat streak mosaic virus (WSMV). In examining how 2,429 wheat accessions from the National Small Grains Collection responded to inoculation with the Sid81 isolate of WSMV, 20 candidate TSR sources were discovered. To differentiate their relative effectiveness, accession responses over 21 days to inoculation with GH95, Sid81, and PV57 virus isolates in regimes of 18 and 20°C were observed. At 18°C, all 20 candidate TSR sources were uniformly or nearly uniformly asymptomatic 21 days after inoculation with the PV57 isolate, resistance indistinguishable from resistant checks KS96HW10-3 and RonL. By contrast, the Sid81 isolate induced symptoms in low but significant proportions of plants of two candidates, and the GH95 isolate in high proportions for four candidates and low but significant proportions for two others. In the more stringent 20°C regime, the uniform or near-uniform induction of symptoms in response to inoculation with GH95 failed to differentiate among the 20 candidate TSR sources and two resistant checks, while PV57 and Sid81 identified several candidates that performed similarly to KS96HW10-3 and significantly better than RonL. By identifying new sources of resistance, this study contributes to the control of WSMV.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".