Soil Structural Behavior as a Function of the Amount of Coverage of Maize and Oat Straw on Oxisol on Subtropical Region
Bibliographic record
Abstract
It is undeniable which soil management systems with intensive use of machines and with little formation of organic matter result in the deterioration of the soil structure. The relation among the values of organic matter in the soil profile as function of the quantity of residue left on the soil surface during the harvest has been little documented. This evaluation will be very important to provide and to apply the best optimization model of the soil management system. The objective of this work was to value the contribution of the mulch cover of maize and oat straw, applied in the soil surface at different quantities and of the soil textural porosity at the change of the soil structural porosity. The experiment was carried out from August to November 2005 on a Oxisol, with clay texture, located at the Experiment Farm of Agricultural Engineering from the UNIOESTE, Cascavel, Paraná, Brazil (24°54′ S; 53°31′ W). The average soil texture in top 20 cm was 126, 195 and 679 g kg-1 of sand, silt and clay respectively. Aggregates sizes distribution, soil bulk density, particles density and textural density and soil organic matter were determined at the laboratory for evaluation of the soil structural parameters. For all conditions: application rates, and distribution in the layers of soil depth, the cover with oat straw produced more organic matter and presented a positive effect faster on the soil structural voids ratio than the coverage with maize straw.
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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 | 0.000 | 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".