Nodulation and nitrogen accumulation in pulses vary with species, cultivars, growth stages, and environments
Bibliographic record
Abstract
Biological N2-fixation underpins the role of pulse crops in the development of sustainable cropping systems, but it is uncertain how nodulation and N accumulation may differ with pulse species, cultivars, and environments. This 3 yr field study investigated nodulation at the early and late flowering stages and seed and straw N uptake for chickpea (Cicer arietinum L.), dry bean (Phaseolus vulgaris L.), faba bean (Vicia faba L.), field pea (Pisum sativum L.), and lentil (Lens culinaris Medik.). At early flowering, all pulses except dry bean had more nodules in the wetter (2010) than drier year (2009). Faba bean had the most nodules followed by field pea and chickpea, while the nodulation varied with plant growth stages and environments. For both pea and lentil, more nodules were observed at early flowering, but higher nodule biomass was obtained at late flowering. Chickpea had higher nodule biomass at late than early flowering but number of nodules varied with year. Seed N uptake was highest in field pea, whereas straw N uptake was highest in faba bean. Our results suggest a possibility of improving pulse N2-fixation by targeting nodule numbers and nodule biomass, although the outcome of plant N uptake will vary with environments.
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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 | 0.000 | 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) | 0.001 | 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".