An economic review of conservation tillage practices: select case studies from the eastern Prairies of Canada
Bibliographic record
Abstract
This study reviewed the literature on soil conservation practices and analyzed four case studies in different soil zones and diverse cropping systems of Manitoba (MB), western Canada, to show the potential impacts of no-till/reduced tillage practices on field crop economic performance. Primary and secondary data, such as tillage type, input cost, crop price, crop yield, and net revenue (NR), were used to assess the tillage practices in each of the case studies. Based on crop economic analysis, over 9 years (1998–2006) in southern Manitoba, cereal-based (spring wheat ( Triticum aestivum L.) and barley ( Hordeum vulgare L .)) cropping systems were more profitable under conservation tillage than conventional tillage practices, whereas the opposite was true for oilseed crops (e.g., canola, Brassica napus L.). In plot-scale studies at Portage, MB, low intensity tillage increased NR for soybean ( Glycine max L.) in 1 of 3 years when compared to high intensity tillage, and there appeared to be lower NRs for canola as tillage intensity increased. However, in studies near Brandon, MB, NRs for a 4-year wheat-pea ( Pisum sativum L .) rotation were lower in low disturbance seeding than high disturbance seeding systems for a clay loam soil but similar for a loam soil. While no single tillage system was found to consistently provide the highest NR based on these case studies, these findings provide insights into some of the factors behind decisions surrounding tillage management and the rationale for the continued use of a combination of conventional, reduced, and zero-till systems in the eastern Prairies of Canada.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.036 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 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".