Genetic analysis for seed size in three crosses of chickpea (<i>Cicer arietinum</i>L.)
Bibliographic record
Abstract
Sharma, S., Upadhyaya, H. D., Gowda, C. L. L., Kumar, S. and Singh, S. 2013. Genetic analysis for seed size in three crosses of chickpea (Cicer arietinum L.). Can. J. Plant Sci. 93: 387–395. Seed size (determined by 100-seed weight) is an important component of trade and yield in chickpea (Cicer arietinum L.). The present investigation was undertaken to study the possibility of maternal inheritance for seed size and to estimate relative importance of additive and non-additive gene effects on seed size in three chickpea crosses involving two desi (ICC 5002 and ICC 7672) and two kabuli (ICC 11255 and ICC 17109) genotypes. The study included parents, F 1 , F 2 , backcross generations, and their reciprocals. Differences in the reciprocal mean 100-seed weight of F 1 , F 2 , and backcross generations were not detected in any cross. No definite major gene segregation pattern was observed in the F 2 generation, and the continuous variation observed indicated quantitative inheritance. Generation mean analysis indicated the presence of additive gene effects controlling seed size in three crosses. Additive×additive type of non-allelic interactions were found significant in desi×kabuli crosses, ICC 5002×ICC 17109 and ICC 7672×ICC 11255. The selection and breeding procedure may be modified for maximum exploitation of the fixable additive×additive epistasis by delaying selection in later generations and by maintaining large populations prior to selection for maximum recombination of genes to occur.
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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 | 0.001 |
| 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".