Soil Fertility in Crop-Livestock System Subjected to Nitrogen Fertilization and Grazing
Bibliographic record
Abstract
The aim of this study was to evaluate the effects of sheep grazing and increasing rates of nitrogen fertilization on oats + ryegrass at winter on the soil K, Ca, H + Al, Mg and P concentrations in a crop-livestock system with beans and corn crop succession during summer after four years (2006-2009) of the experiment establishment. Treatments consisted of different nitrogen levels (0, 75, 150 and 225 kg ha-1) with and without sheep grazing Lolium multiflorum Lam and Avena spp. Soil chemical traits were evaluated at depths of 0-5, 5-10, and 10-15 cm. The experiment was laid out as random block design in a split-plot scheme with three replications. Soil K content were higher at the superficial soil layer and at the treatment with 150 kg ha-1 N and remained high along the four years of assessment. Animal grazing at winter results in better soil chemical traits in relation to the soil Ca and H + Al. There were no nutrient (K, Ca, P and Mg) losses or extraction when under overgrazing, a fact that confirms the possibility of using animals in the crop-livestock areas without affecting its chemical traits. There was also an increase in Ca and SB concentrations with grazing, including in subsurface soil.
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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".