Genetic Analysis of Yield and its Components in Wheat (Triticum aestivum L.) using Generation Mean Analysis
Bibliographic record
Abstract
Abstract In this study, the six generational clans (P1, P2, F1, F2, B1, and B2) were used for two crosses of bread wheat. (Triticum aestivum. L), (the first cross was between the two cultivars (Milan * Abu Ghraib 3) and the second cross between (Milan * Sham 6). The six generations of the two crosses were cultivated according to the randomized complete block design in three replications for each of them. The averages of the generations were analyzed for the studied quantitative traits. For the six generations in the two crosses, the arithmetic averages and their standard errors showed that the values of the generations differed significantly from zero and in both crosses. F2 clans outperformed P1 in their performance and for some traits, and this indicates more frequency of the alleles responsible for this trait in the second generation clan and thus the expression of this trait. Through superior dominance as well as ultra-border genetic isolations, as well as the superiority of BC2 over F2 clans, which indicates more frequency of the alleles responsible for this trait in the second generation clan and for some traits. This means the dominance of the dominant variance that controls the inheritance of traits, and heritability in the narrow sense was low due to the low additional genetic variance.was significant in all traits except for the number of grains per spike and yield efficiency in the first cross, while the values of [d] were significant and positive for leaf area and protein content, which makes early selection beneficial for these traits, and were significant and negative for the traits of number of grains per spike and grain yield, and the dominance effects were [h] Positive and significant values for the characteristics of plant height, total number of tillers, number of spikes per plant, number of grains per spike, biological yield, grain yield, weight of 1000 grains, protein content and gluten content, while significant did not appear in the rest of the studied traits, in the first cross, and in the characteristics of plant height and total number of tillers The number of grains per spike, grain yield, harvest index, weight of 1000 grains, yield efficiency, protein content and gluten content, the second cross, and the superior effects (i) were the first contributors to the inheritance of these traits, followed by the part of the superior genetic action dominant x dominant (l) and then the superior genetic action additional × dominant (j) followed by the dominant genetic act and then the additive genetic action were significant in most of the traits studied in both crosses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".