Nine cycle of mass section to increased oil content in the two synthetics populations of maize (Zea mays L.)
Bibliographic record
Abstract
The objectives of this study were to estimate changes in oil content and grain yield in the maize populations DS7u and YuSSSu. As estimations were performed at CO and C9 for both populations, it was possible to observe changes occurring following long-term mass selection for high oil content. The synthetic population DS7u was developed by recombination of 29 inbreeds of Yugoslav, Canadian and US origin. The synthetic population YuSSSu is an Iowa Stiff Stalk Synthetic - BSS(R)C5. The following statistical and genetic parameters were analyzed: means, frequency distribution, components of genetic variance and heritability. Progenies were derived according to the North Carolina Design II. Results were indicated that nine cycles of selection led to statistically significant increase in oil content and statistically significant decrease for grain yield in both populations. Estimates of additive and dominance variances for grain oil content were highly significant in CO and C9 of the population DS7u. Dominance variance showed significance in the initial cycle of the population YuSSSu, but it disappeared in the course of nine cycles of mass selection. Additive and dominance variances for grain yield were highly significant in both initial populations. Loss of significance did not result from selection, while the proportion of dominance vs. additive variance became greater. High narrow-sense heritability was detected for grain yield and oil content in the initial cycles of both populations. Mass selection resulted in increased heritability for oil content in the DS7u population. .
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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 | 0.000 | 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) | 0.001 | 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".