Effectiveness of Different Sources of Stem Rust Resistance in Barley
Bibliographic record
Abstract
Stem rust ( Puccinia graminis Pers. f. sp. tritici Eriks. & Henn.) pathotype QCCJ is a potential threat to barley ( Hordeum vulgare L.) production in North America. A field test was conducted for 3 yr to evaluate the effectiveness of several new sources of stem rust resistance to reduce losses. A randomized complete block design was used, with a split‐plot arrangement of treated (propiconizole fungicide) and untreated plots. Nine lines used in the test were classed as resistant (R), moderately resistant (MR), moderately susceptible (MS), and susceptible (S). The yield losses in each group were: R—Q21861 (12%), QSM‐041 (12%), BM8923‐46 (12%); MR— ‘Diamond’ (21%), SB90585 (26%); MS—‘Robust’ (30%), ‘Bonanza’ (33%), ‘Harrington’ (37%); S—‘Klages’ (53%). There were highly significant effects on 1000‐kernel weight, test weight, and percentage kernel plumpness for all entries. The losses in kernel weight ranged from 7% (Q21861) to 43% (Klages), in test weight from 3% (Q21861) to 26% (Klages), and kernel plumpness from 5% (Q21861) to 95% (Klages). There were no significant effects of rust infection on plant height and days to heading. Effects on lodging were variable, and reduced days to maturity was highly significant for all entries. Lines with combinations of genes Rpg1 / rpg4 (Q21861, Q/SM‐041) and Rpg1 / Rpg3 (BM8923‐46) provided the highest levels of protection, with a somewhat lesser level provided by Rpg1 / RpgU (Diamond). Combinations of these genes should provide effective stem rust resistance in barley breeding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".