Heterosis Estimation in Okra [Abelmoschus esculentus (L.) Moench) for Yield and Contributing Traits
Bibliographic record
Abstract
AbstractThe analysis of variance revealed significant differences among all the 51 genotypes for all the fourteen quantitative characters studied indicating a high degree of variability in the materials during both the respective years. The magnitude of heterosis varied from cross to cross for all the characters studied. For fruit yield per plant, among 36 cross combinations, maximum relative heterosis was observed in EC169506 × Arka Anamika (43.13% and 37.13%) followed by EC169400 × Arka Anamika (25.55% and 30.10%), IC117351 × Arka Anamika (25.00% and 30.20%) and EC169430 × Parbhani Kranti (244.39% and 29.48%) during both the respective years consistently. Whereas, only two cross combinations viz., EC169400 × Arka Anamika (23.70% and 24.27%) and IC117351 × Arka Anamika (23.36% and 29.25%) exhibited consistent significant positive heterosis over better parent in desirable direction during both the respective years for fruit yield per plant. The high heterotic response in these hybrids for fruit yield per plant resulted mainly due to substantial heterosis for number of fruits per plant, fruit length, plant height, and inter-nodal length.
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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 | 0.002 | 0.001 |
| 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) | 0.000 | 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".