Nitrogen and phosphorus fertility management for desi and kabuli chickpea
Bibliographic record
Abstract
Chickpea (Cicer arietinum L.) is a relatively new crop in Saskatchewan and acreage has undergone a rapid expansion during the past decade. However, uncertainty remains regarding growth and yield responses of this grain legume to N and P fertilization under the semiarid environment of Saskatchewan. Field experiments were conducted at various locations in Saskatchewan to investigate chick pea response to starter N (0, 15, 30, and 45 kg N ha-1) and P (0, 20 and 40 kg P2O5 ha-1) using desi cv. Myles and kabuli cv. Sanford. Starter N was side banded (2.5 cm to the side and 4 cm below the seed) and the P was placed in the seed row or side banded. Starter N promoted early vegetative growth of both desi and kabuli chickpea, but kabuli seed yield was unaffected by N application. Application of 30 or 45 kg N ha-1 enhanced desi yield by as much as 221 kg ha-1. Starter N reduced N2 fixation by kabuli chickpea whereas N2 fixation by desi apparently was not as sensitive to inorganic N. Phosphorus (40 kg P2O5 ha-1) enhanced chickpea vegetative growth, although only desi seed yield was significantly enhanced (121 kg ha-1). Shoot N and P accumulation in both chickpea types generally increased with P application, but N2 fixation was unaffected. The results suggest that although N and P application had no effect on kabuli seed yield, desi yields may be optimized by the application of low rates of starter N (i.e., 30 kg N ha-1) and P (20 kg P2O5 ha-1). Key words: Chickpea, nitrogen, phosphorus, N2 fixation
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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 | 0.001 | 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 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".