Genetic value of maize self-pollinated lines by the level of combining ability
Bibliographic record
Abstract
Aim. Evaluation of maternal forms in terms of morphological and economic characteristics, assessment of their combination ability. Results and Discussion. 175 maize self-pollinated lines of different geographical origin were explored. The level of the combining ability of maize lines was determined by the main quantitative characteristics: plant productivity, ear length, grain number on ear, row number on ear, weight of 1000 grains, representing their breeding suitability. Donor properties were revealed in 14 lines of their own breeding, in which a high level of characters manifests itself in hybrid combinations. Among the studied simple hybrids with the participation of these lines, productive combinations were highlighted: UHI 5/Kharkivska 126, UFF 4/Kharkivska 164; UHF 175/Kharkivska 164; UHK 568/Kharkivska 164; UHK 579 / Kharkivska 164 with a yield capacity of 9.4-11.1t/ha with a standard yield of 6.8-7.8t/ha. Among the lines of foreign origin, high combining ability in crosses with domestic lines was found in the lines RF 90 from the Illinois University (USA), lines SK 543/18, SK 591/18 from the University of Manitoba (Canada), 1028 SPT from the Liaoning Academy of Agriculture (China). Conclusions. The self-pollinated lines of maize are identified, which are a valuable source material for creating new promising hybrids with a complex of valuable economic traits. Their use will increase the efficiency of the breeding process and ensure its acceleration by 4-5 years.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".