The Genetic Architecture of Flowering Time and Related Traits in Two Early Flowering Maize Lines
Bibliographic record
Abstract
Flowering time is the major factor in determining maize (Zea mays L.) maturities. Genetic bases of flowering time and other agronomically important traits were examined in a set of interheterotic‐pattern recombinant inbred lines (RILs). The RILs were developed from crossing the short‐season Iodent inbred line CG60 with the short‐season Stiff Stalk inbred line CG102. Recombinant inbred lines were derived through single‐seed descent (S‐RILs) or intermated for three generations before inbreeding (I‐RILs), thereby increasing recombination. Genetic variation was high for all traits in both populations, and a large number of RILs had days to silking, days to anthesis, plant height, visual stay green, canopy reflectance, and leaf number trait values beyond the parental line ranges. Both the I‐RIL and S‐RIL populations had similar genetic variances and similar genetic and phenotypic correlations between traits. We conclude that although Northern Corn Belt Dents have been subjected to strong selection and drift and have diverged greatly from their source population, there is substantial cryptic variation for many traits. Our results also suggest that coupling and repulsion phase linkage blocks are not prevalent within parental genomes and that genetic correlations are caused by pleiotropic genes. Intermating may have little value in recovering extreme phenotypes for flowering time and other agronomically important traits.
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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 | 0.000 |
| 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".