Cereal crop following organic intercrops and their respective monocultures in the semiarid Canadian Prairie
Bibliographic record
Abstract
Abstract Organic crop production relies mostly on legumes for N input. Intercropping of organic legumes with more competitive crops might provide an alternative to the poor weed suppression and disease susceptibility of legumes. It might also be expected that such intercropping could be of benefit to crops grown in the subsequent year through increased N from the preceding intercropped legume, and lower weed growth due to the more competitive companion. The objective of this study, conducted under drier than average conditions in a semiarid region of the Canadian Prairies, was to determine how organic intercrops of legumes with a cereal or oilseed at different ratios would affect soil nutrients the next spring, weed levels, and the productivity and quality of the following durum wheat [ Triticum turgidum L. ssp. durum (Desf.) Husn.]. Results from 2018 to 2019 showed that intercropping had a negligible impact on Olsen P and extractable K. Soil NO 3 ‐N (>15‐cm deep) was lowest following the lentil ( Lens culinaris Medik.)–mustard ( Sinapis alba L.) intercrops and mustard monoculture, which was reflected in lower growth of the durum wheat. Conversely, some of the pea ( Pisum sativum L.)–oat ( Avena sativa L.) intercrops and the oat and all legume monocultures resulted in higher durum wheat biomass and grain yield, with their highest values observed after the checks summerfallow and forage pea manure. Weeds tended to have lower densities after the intercrops than the grain legume monocultures. Nutrient concentration in plant tissue suggested that weeds could be a greater source of soil nutrients than crops.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".