Genetic Evaluation and Correlation Analysis Among Various Quantitative Traits in Maize Single-Cross Hybrids Under Diverse Environments
Bibliographic record
Abstract
Genetic variation abundance, high genetic advance coupled with high heritability estimates presents the most suitable condition for selection. Ninety-five hybrids generated from elite and new inbred lines crossed using half diallel mating design were evaluated under diverse environments. The objectives were to estimate genetic variances, heritability of traits and genetic advance and to determine correlations of grain yield and its component characters in maize hybrids. Analysis of variance revealed significant differences among genotypes for all traits studied except for ear rots. Estimates of phenotypic coefficient of variation were slightly higher than genotypic coefficient of variation for all traits suggesting low influence of environment in the expression of these traits. High heritability and genetic estimates were recorded for grain yield (79%; 30.27%), plant height (85%; 102.42%) and ear height (86%; 117.15%) whilst high heritability and low genetic advance were observed for anthesis date (87%; 5.8%), texture (75%; 8%) and ear position (71%; 0.23%). Correlation between environments using grain yield data revealed existence of a very strong positive correlation between CIMMYT2 and RARS2 suggesting that the sites have the same discriminating effect. Correlation among traits revealed that grain yield had significant (P < 0.05) positive correlation with plant height and ear height. Similarly, plant height had significant and positive correlation with ear height while ear position was positively correlated to ear height. Path analysis showed that plant height, ears per plant and ear position had positive direct effects on grain, while anthesis date, ear height, ear position, grain moisture content at harvest and texture indirectly influenced grain yield. These characters’ contribution to grain yield is important and the strong association with grain yield implied that these can be used as secondary traits to indirectly select for grain yield performance in this set of germplasm across all the environments.
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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 | 0.000 | 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".