Genetic combining ability of coriander genotypes for agronomic and phytochemical traits in response to contrasting irrigation regimes
Bibliographic record
Abstract
Knowledge of genetic combining ability and gene action would help breeders to choose suitable parents and devise an appropriate breeding strategy for coriander. In the present study, six diverse genotypes of coriander, their 15 F1s and 15 F2s were evaluated through randomized complete block design with three replications to study genetic combining ability for agronomic and phytochemical traits in coriander. Plants were subjected to well-watered (WW), mild water-deficit stress (MWDS) and severe water-deficit stress (SWDS) irrigation regimes. The results indicate that water-deficit stress decreased all of the measured traits in both the F1 and F2 generations. General combining ability and specific combining ability effects were highly significant for all of the traits in both the F1 and F2 generations. Additive gene action was predominant for phonology and fruit yield component traits in all irrigation regimes in both the F1 and F2 generations. For fatty acid content and total lipid yield, non-additive gene action was predominant in the F1 generation while additive gene action was predominant in the F2 generation under MWDS and SWDS conditions. The P4 parent had the highest general combining ability for fruit yield components in both the F1 and F2 generations. The P6 parent had the highest general combining ability for phenological and phytochemical traits. The P4 and P6 parents are promising material to develop early flowering and early maturing genotypes coupled with high total lipids in advanced generations of segregation.
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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".