Yield and uptake of nitrogen and phosphorus in soybean, pea, and lentil, and effects on soil nutrient supply and crop yield in the succeeding year in Saskatchewan, Canada
Bibliographic record
Abstract
There is little information on soybean [Glycine max (L.) Merr.] grown in western Canada despite its expanding acreage in this region. This study quantified the yield and uptake of nitrogen (N) and phosphorus (P) in three short-season soybean varieties (in 2014) and their impact on following wheat and canola crops, as well as soil nutrient supplies in 2015 in comparison to three pea and three lentil varieties at four sites in Saskatchewan. In 2014, soybean had comparable grain yield (929–3534 kg ha−1) and higher grain N (39–48 g kg−1) and P (5.1–6.8 g kg−1) concentrations compared with pea and lentil. In 2015, although soil N and P supplies showed some responses to different stubbles during the growing season, cumulative soil nutrient supplies were similar in soybean, pea, and lentil stubbles at the end of the season. Overall, soybean, pea, and lentil stubbles had similar impact on the yield and uptake of N and P in the wheat or canola crop grown in the subsequent year. The findings suggest promising potential for soybean production to achieve rotational benefits similar to other grain legumes grown under western Canadian soil–climatic conditions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".