SUBSURFACE AND SURFACE TILLAGE PRACTICES AND THEIR EFFECTS ON STRUCTURE, PERMEABILITY AND CROP YIELD IN A CHERNOZEMIC AND SOLONETZIC SOIL
Bibliographic record
Abstract
Fall tillage on the Canadian prairies may involve subsurface tillage (subsoiling) and surface tillage operations. These tillage practices alter soil physical properties such as aggregation, strength, bulk density, air and water permeability that can subsequently affect growth and yield of following crops. Reclaiming compacted Chernozemic and Solonetzic soils with hardpan B horizons may be possible through subsoiling operations to loosen the soil to depth e.g. ~30cm, while surface tillage operations such as tandem disc and vertical tillage can be used to get rid of recalcitrant crop residues like flax straw by incorporation to ~ 10cm. The objective of this study was to evaluate the effect of subsurface and surface tillage on soil physical properties and subsequent crop yield. Subsoiling treatments were applied to wheel traffic compacted and non-compacted Chernozemic and Solonetzic soils at a site in south-central Saskatchewan, Canada. Subsoiling increased air permeability in the compacted Chernozemic soil from 4.5x10-7 m sec-1 to 2.9x10-6 m sec-1. The subsoiler also significantly reduced soil bulk density and soil strength in both soil types. Subsoiling increased crop production on only one soil type; the long-term wheel traffic compacted Solonetzic soil, which had the highest soil strength (> 2000 kPa), where canola grain yield was increased by 1,100 kg ha-1. Effects of the subsoiling on soil physical properties and crop yield diminished greatly in the second year after subsoiling. Vertical tillage in the Chernozemic soil to incorporate flax straw tended to decrease water infiltration and air permeability compared to the raking and burning treatment and the no-till, no-burn control. Surface tillage of the flax stubble using tandem disk or vertical tillage implement, raking and burning, and direct seeding into the flax stubble all had similar wheat and pea yields in the in the first and second year of the study. When considering fall tillage, subsoiling may be most effectively applied to long-term wheel traffic compacted areas of a field with identified high soil strength. Surface tillage, raking and burning to reduce perceived residue interference may not be required if residue chopping and spreading by the combine at harvest is effective.
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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 | 0.001 | 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".