Biological nitrogen fixation by pulse crops on the semiarid Canadian Prairie
Bibliographic record
Abstract
Pulses play a significant role in nitrogen cycling as they fix atmospheric N2 through symbiosis. However, it is unknown whether there are differences in the ability of biological nitrogen fixation (BNF) among pulse species and individual cultivars. Here, we quantified the BNF ability of selected pulse cultivars and determined the effect on crop yield. A total of 25 species-cultivar combinations of chickpea (Cicer arietinum L.), dry bean (Phaseolus vulgaris L.), faba bean (Vicia faba L.), field pea (Pisum sativum L.), and lentil (Lens culinaris Medik.) were tested in 2008–2010. Pulses had a higher BNF in the wetter 2010 season, and a lower BNF in the drier 2009 season. In 2010, faba bean and chickpea had the highest BNF at 106 kg N ha−1, followed by lentil, field pea, and dry bean at 87, 69, and 12 kg N ha−1, respectively. Across years, field pea had the most stable BNF ability, fixing 55 kg N ha−1 with an average seed yield of 2418 kg ha−1. There are large differences in BNF and yield among cultivars within a species and the magnitude of the difference varied with years. Large genetic variability in BNF and yield suggest the possibility that pulse cultivars with a higher N2-fixing ability and seed yield can be developed through selection of the N2-fixing trait.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".