Estimation of Heterosis, Heterobeltiosis and Potence Ratio Over Environments Among Pre and Post Green Revolution Spring wheat in Pakistan
Bibliographic record
Abstract
Globally wheat trade has a major and impacting role in political and economic relationships between nations. Twelve pre-green revolution and post green revolution wheat genotypes viz., Sehr-06, Pasban-90, C-273, Pari-73, SA-42, Fsd-08, Chenab-70, Blue Silver, Lasani-08, Pak-81, Uqab-2000, and Pothowar-73 and their direct and reciprocal crosses were evaluated. The study concluded significant differences and highest values in heterosis, heterobeltiosis and potence ratio were found among genotypes and their cross combinations for pollen viability (Sehr-06 × Blue Silver), flag leaf area (SA-42 × Fsd-08), number of grains per spike (Pak-81× Lasani-08) and grain yield plant-1 (Chenab-70 × Fsd-08). Under changing climatic condition and limited water provision an amalgamation of pre-green revolution and post green revolution may provide a genetic diversity to break the stagnant yield barrier to ensure food security.
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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 | 0.000 | 0.000 |
| 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".