Diallel Analyses of Agronomic Traits Using Chinese and U.S. Maize Germplasm
Why this work is in the frame
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Bibliographic record
Abstract
Added genetic diversity among commercial maize ( Zea mays L ) hybrids may further increase yields and safeguard against vulnerability. Introducing exotic germplasm into breeding programs would increase the genetic base from which elite commercial inbreds are derived. Ten populations of maize, created from Chinese and/or U.S. inbreds or strains, were evaluated by Griffing's diallel analysis for combining ability of grain yield, stalk lodging, ear height, flowering time, and European corn borer (ECB; Ostrinia nubilalis Hübner) resistance to estimate their potential as sources of exotic germplasm for U.S. breeding programs. Grain yield general combining ability was largest for the population Mo17 Syn.(H14)C5, a synthetic improved by half‐sib selection using US13 as a tester. Grain yield specific combining ability was largest in the cross Chinese Mix 2 × Mo17 Syn.(H14)C5. Chinese Mix 2 × Mo17 Syn.(H14)C5 had more stalk lodging than the B73 × Mo17 and Pioneer Brand 3394 checks. Because of the high yield potential and other moderate‐to‐good agronomic traits of the cross combination, Chinese Mix 2 was selected as the best population for selection. Its large specific combining ability effect with Lancaster type material, which is commonly known in breeding programs, shows potential for further improvement. No native ECB resistance in Chinese germplasm was detected (two environments in 1 yr) compared with the resistant check Pioneer Brand 3184.
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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 it