Genetic Parameters of Some Wheat (Triticum aestivum L.) Genotypes Using Factorial Mating Design
Bibliographic record
Abstract
Using parents and mating designs appropriate in the field of conventional plant breeding are the beginning to successful plant breeding program. However, there are many factors that influence their choices of mating designs, such as genetic parameters, experimental conditions and other biological constraints used in the evaluation process. In this study, Two wheat (Triticum aestivum L.) genotypes used as males while, fifteen used as females were assessed for yield and yield associated traits using North Carolina Design II (factorial mating design). The seventeen parents and their 30 F1 progenies were planted in randomized complete block design with three replications in three sets , during the growing season 2009/2010 and 2010/2011 in Ras-Sudr Regoin , South of Sinai, Egypt. Highly significant differences among males, females and hybrids between them were observed for all traits except No. of tillers and weight of grains /spike for females and the hybrids between males and females. The dominance genetic variance was higher than additive genetic variance for all studied traits except grain and straw yield per plant. Both heritability in narrow sense and expected genetic advance as percent were relatively high for spike weight grain yield and straw yield per plant. Depending on the previous genetic parameters we can achieve a quick and easy insight to a successful assessment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".