Yield and quality of hard red spring wheat cultivars following fallow and wheat
Bibliographic record
Abstract
Continuous wheat (Triticum aestivum L. emend. Thell.) and other intensive cropping systems are replacing t he wheat-fallow (WF) system in the semiarid prairie region of Canada and the northern USA. However, most wheat cultivar recommendations are based on performance in a WF system. Our objective was to determine if cultivar ranking for grain yield, grain protein concentration, and kernel weight changed for hard red spring wheat in WF compared with continuous wheat (WW) systems. Ten cultivars were seeded on a Dark Brown Chernozem loam following fallow and wheat over 3 consecutive years at Dickinson, ND, USA. Fertilizer was applied for equivalent yields in both systems based on soil test results. More grain and heavier kernels were produced during the crop phase of the WF system than the WW system, in part because soil-water content was greater after fallow than wheat in 2 of 3 yr. Grain protein concentration was unaffected by cropping system. Grain yield, grain protein concentration, and kernel weight differed among cultivars. Interactions did not occur between cropping systems and cultivars for any grain parameter. Results of this study support the hypothesis that wheat cultivar ranking based on performance in a WF system can be extended to a WW system. Key words: Crop rotation, cropping systems, fallow, monoculture, wheat
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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".