Impact of crop sequence decisions in the Saskatchewan Parkland
Bibliographic record
Abstract
Rotations are constantly being adapted to current economic and management realities. As a result, the crop sequence used tends to depend more on the economic value of particular crop types, principally cereals, oilseeds and pulse crops in the Saskatchewan Parkland, than on the best management practices for optimizing crop productivity. A study was conducted from 1999 to 2001 at Melfort, SK, to assess the effects of growing barley, wheat, canola, flax, and field pea on their own and the other crop stubbles. When a crop was seeded on its own stubble, the poorest grain yield and quality were recorded, a difference that often was related to major pathogens affecting crop productivity. In the first 2 yr of this study, when near normal temperature and precipitation were recorded, little difference was observed in the average crop yield response when any of the crops were seeded on the other broadleaf and cereal stubbles considered in the study. The exception was flax, which performed poorer when seeded on canola than flax stubble, a reflection of the negative impact canola has on arbuscular mycorrhizae populations on subsequent flax in rotation. In 2001, a year with below-normal precipitation and above-average temperature, crops seeded into pea and flax stubble had yields that were 15–40% of the best stubble treatments. Under these drought conditions, field pea was the best crop choice for flax stubble, while wheat was the best choice for pea stubble. The results of this study indicate that for the Saskatchewan Parkland, the lowest risk crop sequence decision is to avoid seeding a crop in its own stubble. Key words: Malt barley (Hordeum vulgare L.), spring wheat (Triticum aestivum L.), canola (Brassica napus L.), flax (Linum usitatissimum L.), pea, (Pisum sativum L.), crop rotation, disease management
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".