Combining Ability Studies for Development of New Hybrids over Environments in Sunflower (Helianthus annuus L.)
Bibliographic record
Abstract
Seven CMS lines were crossed with six inbred lines in Line x Tester fashion to elucidate the information on the nature of gene action involved in the inheritance of important quantitative traits and to select the parents with good gca and crosses with good sca effects. The resultant 42 hybrids were evaluated along with their parents with three standard checks at three locations in Andhra Pradesh state viz., Hyderabad, Tandur, and Jagtial. The pooled analysis of variance for combining ability revealed that sca variance was higher in magnitude compared to gca variance for all the characters except oil content indicating the preponderance of non-additive gene action for all the characters while additive gene action for oil content. The gca effects of the parents in pooled analysis revealed that among the lines ARM 243B and CMS 17B and among the testers RHA-6D-1R, RES-834-1 and 3376R were found to be promising general combiners for seed yield and yield component characters. Based on significant sca effects in pooled analysis, five hybrids viz., CMS 89A x RES-834-1, CMS 17A x LTRR 341, ARM 243A x R 298, ARM 238A x 3376R and CMS 852A x R-649 were identified as promising for seed yield and other yield contributing characters.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".