Breeding for Cold Tolerance in Chickpea
Bibliographic record
Abstract
Chickpea (Cicer arietinum L.), a winter season crop, is the 4th largest grain-legume crop in the world. In India, among various grain legumes grown chickpea ranks 1st covering 8.25 m ha area during 2008-09. Being a cool-season crop, chickpea faces low temperature to the tune of 0-5°C for about 15-20 days in the northern states. The sensitivity of varieties at flowering to chilling temperature below 10°C has adverse effect on chickpea production (15-20% yield losses). The development of varieties possessing cold/low temperature tolerance is viable option for enhancing chickpea production and productivity in low temperature environments of countries like India, Canada and Australia. In present paper, attempts have been made to define cold/low temperature stress in relation to chickpea for different growing environments/countries. Various screening techniques and scoring index in vogue, availability of donors, genetics of cold tolerance, different aspects of varieties development including problems and prospects have been discussed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".