Soil Quality Indicators After Sequential Applications of Poultry Litter
Bibliographic record
Abstract
Application of poultry litter may lead to major changes in the structural and functional properties of soil. Understanding these alterations is crucial for assessing the effect of organic wastes on the soil quality and attributes. The purpose of this study was to assess the influence of use of poultry litter on increased organic matter, microbiological activity and physicochemical properties of soils in the Brazilian Cerrado and identify a group of expressive indicators of changes for the assessed attributes. The research was conducted in Fazenda Alvorada, a farm located in Portelândia/GO (Brazil), consisting of the following accumulated doses of turkey litter: T0 (without application); T1 (26.32 Mg ha-1); T2 (43.15 Mg ha-1); T3 (57.6 Mg ha-1). The experimental design consisted of randomized blocks and four replications. Sequential applications of poultry litter provide increases in the variables related to organic matter, mainly in particulate nitrogen and total nitrogen stocks. Applications of lower doses resulted in increases of microbial biomass carbon and microbial quotient. Concerning soil physicochemical properties, available phosphorus, the sum of bases and base saturation were the variables that exhibited the most significant changes with increased doses of poultry litter. The metabolic quotient was the most expressive indicator to represent soil alterations resulting from application of poultry litter.
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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 | 0.001 |
| 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) | 0.000 | 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".