Genotype and growing environment influence chickpea (<i>Cicer arietinum</i> L.) seed composition
Bibliographic record
Abstract
Abstract BACKGROUND: As a first step towards genetic improvement of seed quality in chickpea ( Cicer arietinum L.), seven desi and nine kabuli varieties were grown at multiple sites to assess the affect of environment on seed yield, weight and selected seed constituents. The sites were chosen to represent a range of environments in chickpea production areas of the Canadian prairies. RESULTS: Genotype × environment interaction effects on starch, amylose and protein (desi only) concentrations and seed yield were significant, suggesting that the varieties did not perform consistently relative to each other in the different environments. Starch concentration was negatively correlated ( r kabuli = −0.25, P < 0.05; r desi = −0.16, P < 0.05) with protein concentration in both chickpea market classes. However, repeatability estimates of starch, amylose and protein concentrations were low and inconsistent across chickpea market classes, possibly owing to complex biosynthetic pathways for these constituents. CONCLUSION: The results suggest that testing for seed constituent traits over a range of environments will be required to improve seed quality in individual chickpea varieties. The best selection strategies for seed constituent improvement in chickpea will be influenced by genotype and genotype × environment interaction for these traits. The negative relationship between seed constituents and yield indicates that selection for chickpea cultivars with desired seed composition may require compromise and indirect selection. Copyright © 2009 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".