Study of Maize Inbreds and Hybrids for Resistance to Fusarium graminearum Schw. Infection via the Silk
Bibliographic record
Abstract
Within the maize breeding program, 63 inbreds and 62 maize hybrids were tested, using for the first time in 1998 a new method of artificial ear infection with Fusarium graminearum into the silk channel (1). In 7 trials significant differences in resistance degree among the tested lines and hybrids were obtained. Estimates obtained by a 1-7 scale varied from 1.0 to 5.1 for the lines and from 1.4 to 4.4. for the hybrids. Mean values of 27 single cross hybrids to Fusarium ear rot was compared to mean values of the parents resistance. Correlation coefficient of r=0.72 was obtained, which indicates that only approximate hybrid resistance can be predicted from line resistance. Therefore, testing for resistance needs to be conducted with both lines and hybrids. In 1999, the second year of investigation, 37 inbred lines were tested. The ratings ranged from 1.6 to 6.5 and the differences were statistically significant. Also, screening of 1121 maize hybrids, mostly testcrosses, was made for resistance to F. graminearum ear rot and ratings ranged from 1.0 to 6.2. Susceptible hybrid combinations were identified, as well as inbred lines which need to be improved for their degree of resistance to F. graminearum ear rot. 1. Reid, L.M., Hamilton, R.I., Mathev, D.E. 1996. Screening Maize for Resistance to Gibberella Ear Rot. Technical Bulletin 1996-5E. Research Branch, Agriculture and Agri-Food Canada.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".