Immediate and second‐year effects of preceding crops on wheat production in the Northern Great Plains
Bibliographic record
Abstract
Abstract Growers in the Northern Great Plains (NGP) are increasingly adopting winter wheat (WW; Triticum aestivum L.) into their crop rotations in years of ideal fall planting conditions due to its high yield potential. Our study evaluated WW responses to rotational crops, soybean ( Glycine max L.) and lentil ( Lens culinaris L.), field peas ( Pisum sativum L.), faba bean ( Vicia faba L.), canola ( Brassica napus L.), flax ( Linum usitatissimum L.), and oats ( Avena sativa L.), and to different wheat rotational schemes following the rotational crop: WW‐WW, hard red spring wheat (HRSW)‐WW, and WW‐HRSW. Although canola is traditionally favored for its snow‐trapping benefits, soybean and lentil can achieve similar or superior results, enhancing both WW grain yields and protein concentrations when grown immediately after these two rotational crops. These benefits persisted in the second wheat phase in the WW–WW and HRSW–WW systems, albeit with increased variability. Canola stubble, while not offering immediate advantages for WW, contributed to high and stable yields in WW and HRSW when planted in the second year. However, a wheat yield drag was noted in the second year, especially affecting HRSW, indicating that monoculture cereal rotations are more detrimental to HRSW than to WW. In‐crop growth patterns aligned with yield responses, with leguminous stubbles, especially lentil, promoting superior in‐season growth compared to canola, flax, and oats. This study underscores WW as a viable option for cereal phases in the NGP cropping systems, contributing to enhanced ecological benefits in the local environment. By adopting WW in their cropping systems, growers can accrue synergistic benefits with multiple rotational 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 | 0.001 |
| 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".