The Economics of Alternative Crops in the Brown and Dark Brown Soil Zones of Saskatchewan
Bibliographic record
Abstract
The purpose of this study was to investigate the sustainability of alternative cropping systems in the Brown and Dark Brown soil zones of Saskatchewan. Three components of sustainability are examined; economic effects, environmental effects and social acceptance. The primary objective of this project is to investigate the short and long-term economic effects of introducing pulses and oilseeds into existing cereal crop rotations. Representative farms were developed and used in the assessment of profitability and risk for four competing alternative rotations including a cereal based benchmark system. Production costs, financial linkages and stochastic prices and yields are used to simulate farm income, expenses, cash flows and net worth for a 15 year period. Stochastic dominance testing is used to determine the profitability and risk for each of the competing rotations based on annualized net returns. The second objective was to identify the change in soil productivity and resource use efficiency from the widespread use of these new cropping systems. The EPIC model is used to simulate a 30 year cropping pattern for each of the alternative crop rotations. The simulation results indicate that there are rotational benefits in short-term off-site resource usage. The results of the whole farm production model support the following conclusions. (1) Rotations that include lentil, with low price and yield correlations, produce higher net farm income and lower have economic risk. (2) Market risk is reduced by increasing cropping diversity. (3) Production risk is highest in the early adoption phase. (4) There is a cost savings in nitrogen fertilizer usage for crop rotations that include lentil; however, this cost savings is diminished by increased chemical and equipment costs. (5) Extended rotations that include lentil and canola are preferred over 2-year and 3-year wheat-fallow rotations by risk averse producers in the Brown and Dark Brown soil zones.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".