Genotype and environment effect on canning quality of kabuli chickpea
Bibliographic record
Abstract
Chickpea (Cicer arietinum) has become an important pulse crop in Saskatchewan where both the large-seeded (kabuli) and small-seeded (desi) market classes are grown. In North America, kabuli chickpea is mainly used for canning and in salad bars. Both the genotype and the environment affect the canning quality. This study was conducted to determine the effect of genotype, environment and genotype × environment interactions on canning quality traits of three kabuli chickpea cultivars. The three cultivars were grown in 17 environments in Saskatchewan and Alberta during 1996, 1997 and 1998. The genotype, environment and genotype × environment interactions were significant for most canning quality traits. Significant genotype × environment interactions suggest that chickpea cultivars did not perform consistently relative to each other in different environments. This suggests that breeders must give due consideration to quality traits of both the dry and the canned product during the selection process. The results make apparent the magnitude of genotype × environment interactions that chickpea breeders must confront and indicate that extensive testing of chickpea for canning quality traits over different environments is required. Key words: Cicer arietinum, kabuli chickpea, genotype, environment, canning quality
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".