Optimizing harvest schemes to improve yield and feeding quality in chickpea
Bibliographic record
Abstract
Late maturity often causes substantial losses in yield and quality of chickpea (Cicer arietinum L.) in the short growing season in western Canada. This study determined optimum harvest management practices to minimize losses due to late maturity. Kabuli chickpea was grown in southwestern Saskatchewan from 2002 to 2004, and seed and straw were harvested with various harvest management practices. Seed yield in 2004 was higher compared with 2002 and 2003, but the 2004 seed samples had a high percentage of shrivelled and green seeds. Seed yield, weight per seed and harvest index (HI) were highest when the crop was directly combined at natural maturity either before or after a killing (-5°C) frost. On average, swathing at early or late maturity stages decreased seed yield, weight per seed and HI significantly compared with direct combine practices. Seeds from the swathing treatments had high percentages of green and shrivelled seeds with high levels of fungal colonization. Both seed and straw from swathing had the poorest feeding quality measured as neutral detergent fibre, acid detergent fibre, and organic matter content and digestibility. Desiccation of chickpea plants with Reglone or low dosages of glyphosate when 80% of pods had turned colour did not advance plant maturity, nor did they affect seed yield or HI compared with direct combine practices. It is concluded that in the short growing season in western Canada, harvest of chickpea at natural maturity either prior to or after a killing frost may optimize the seed yield and quality. Regardless of harvest practices, the quality of both seed and straw in chickpea may be suitable as salvage feed materials for beef livestock. Key words: Cicer arietinum, desiccation, direct-combine, maturity, glyphosate stress, swath, salvage feed
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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".