Soil Compaction from Wheel Traffic under Three Tillage Systems
Bibliographic record
Abstract
Agricultural fields are usually subjected to high amounts of traffic from field operations. The influence of traffic on sandy loam soil in three tillage systems were investigated in a field experiment. The field was located in a Canadian prairie region. In the experiment, the treatments were three tillage systems: no-tillage, disc tillage, and spring-tine tillage. Following tillage operations, field plots were trafficked with one pass of a sub-compact tractor. Soil properties were measured before and after the traffic to examine the effects of tillage systems and wheel traffic. For the effects of the tillage systems on the soil bulk density, soil shear strength, soil surface resistance, and soil cone index, the no-tillage system had higher values for all the soil properties when compared with the disc and spring-tine tillage systems. The plant (canola) population density ranged from 18.2 plants/m2 to 34.9 plants/m2, with the no-tillage having the lowest plant densities. For the effects of wheel traffic, one pass of the tractor in the disc and spring-tine tillage plots resulted in a 2.7% and 17.4% reduction in soil moisture content, respectively. After wheel traffic, the average soil shear strength for the disc and spring-tine systems were still significantly lower than the no-tilled system. Sinkages of 40 and 50 mm were observed for the spring-tine and disc tillage systems, respectively. The results of this study highlight the importance of preventing the demerits of soil compaction induced by wheel traffic after tillage operations.
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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 | 0.001 | 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".