Oilseed Crops for Semiarid Cropping Systems in the Northern Great Plains
Bibliographic record
Abstract
Oilseed crops are grown throughout the semiarid region of the northern Great Plains of North America for use as vegetable and industrial oils, spices, and birdfeed. In a region dominated by winter and spring wheat (Triticum aestivum L. emend. Thell.), the acceptance and production of another crop requires that it both has an agronomic benefit to the cropping system and improve the farmers’ economic position. In this review, we compare the adaptation and rotational effects of oilseed crops in the northern Great Plains. Canola (Brassica sp.), mustard (B. juncea and Sinapis alba L.), and flax (Linum usitatissimum L.) are well adapted to cool, short‐season conditions found on the Canadian prairies and northern Great Plains border states of the USA. Sunflower (Helianthus annuus L.) and safflower (Carthamus tinctorius L.) are better adapted to the longer growing season and warmer temperatures found in the northern and central Great Plains states. Examples are presented of how agronomic practices have been used to manipulate a crop's fit into a local environment, as demonstrated with the early spring and dormant seeding management of canola, and of the role of no‐till seeding systems in allowing the establishment of small‐seeded oilseed crops in semiarid regions. Continued evaluation of oilseed crops in rotation with cereals will further expand our understanding of how they can be used to strengthen the biological, economic, and environmental role of the region's cropping systems. Specific research needs for each oilseed crop have been recommended.
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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 | 0.001 |
| 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) | 0.004 | 0.001 |
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".