Economic analysis of organic cropping systems under different tillage intensities and crop rotations
Bibliographic record
Abstract
Abstract Costs of production and organic price premiums are defining factors influencing the economic viability of organic crop production systems. Different agronomic practices, such as crop rotation and tillage intensity, are known to affect the economic performance of the production systems. The aim of this study was to compare the impact of two crop rotation sequences (simplified and diversified) and two levels of tillage intensity (high and low) on the cost of production, gross return and gross margin of crops when grown under organic management in the semi-arid Brown soil zone of the Canadian Prairies. The 2-year simplified rotation sequence consisted of forage pea (Pisum sativum L.) grown as a green manure followed by hard red spring wheat (HRSW) (Triticum aestivum L.), while the 4-year diversified rotation sequence was forage pea green manure followed by flax (Linum usitatissimum L.) or yellow mustard (Sinapis alba L.), field pea or lentil (Lens culinaris L.) and HRSW. Our hypothesis that a more diversified crop rotation would increase profitability over a traditional simplified crop rotation was supported by the findings. However, the findings did not support our hypothesis that reducing tillage intensity, and the combination of tillage reduction and diversified crop rotation through a synergetic response, would further enhance profitability. Analysis of the breakeven prices and breakeven yields for crops indicated the importance of adopting diversified crop rotations and choosing crops with high organic price premiums as means to maximize the long-term profitability of organic cropping systems.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".