Fertilizer and rhizobial inoculant responses of chickpea on fallow and stubble sites in southern Alberta
Bibliographic record
Abstract
Agronomic practices for chickpea (Cicer arietinum L.) production on the Canadian prairies are not well established. The objective of this study was to evaluate the impact of fallow on chickpea yield and response to rhizobia inoculation and fertilization. Field trials were conducted at nine fallow sites and nine stubble sites in southern Alberta over a 4-yr period (2000–2003). In the N experiment, N fertilizer was applied to rhizobia-inoculated and uninoculated desi (cv. Myles) and kabuli (cv. Sanford) chickpea at five N rates (0, 20, 40, 60 and 80 kg N ha-1). In the P experiment, P fertilizer was applied to desi chickpea at 0, 6.5 and 13 kg P ha-1. Growing season precipitation was well below normal during 3 of the 4 yr of this study, and fallow yields were more than double stubble yields. Desi seed yield increased 15.8 kg ha-1 for each millimetre increase in water use above a minimum requirement of 84 mm. Although nodulation of uninoculated chickpea was absent or very low at all sites, the benefits of inoculation were modest. On average, inoculation increased seed yield by 12%, seed protein concentration by 11%, and seed N yield by 24%. Inoculation responses were similar for fallow and stubble sites. Yield gains due to application of N fertilizer were also small at most sites, with no difference in yield gain between fallow and stubble sites. Yield benefits due to inoculation and N fertilization were often small because either moisture availability was low or soil N availability was high. Desi was more responsive to N fertilization than kabuli. Phosphorus fertilizer had a minimal impact on desi chickpea yield. Fallow had a large impact on chickpea yields, but did not affect rhizobia or fertilizer response. Key words: Cicer arietinum, yield, nitrogen, phosphorus, water use efficiency
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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 | 0.001 | 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 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".