Chemical and Microbiological Attributes of Soil Under Different Management With Application of Swine Wastewater
Bibliographic record
Abstract
We evaluated the effects of biannual surface applications of swine wastewater (SWW) for 11 years, on chemical and microbiological attributes of a clay-textured soil under no-tillage (NT) or conventional tillage (CT) in Palotina, Paraná, Brazil. The treatments consisted of SWW doses (split into autumn-winter/spring-summer seasons) totaling 30, 60, 90 or 120 m3 ha-1 year-1, and a control without application, under CT or NT soil managements (SM). The experimental design was in randomized blocks with a split-plot arrangement and four replications, with SM in the plots and the doses of SWW in the subplots. After 11 years of applications of SWW, soil samples were taken at 0-10, 10-20, 20-40, and 40-60 cm of depth by the end of the winter cover crop, 44 days after the second biannual application. The treatments had only minor effects on the assessed chemical and microbiological soil properties. Available P and NO3--N increased with the doses of SWW at the two upper soil layers, whereas NT decreased NO3--N at 10-20 cm and increased P at 0-10 cm. Zn2+ also increased with the doses of SWW, irrespectively the SM. NT increased the microbial biomass C (MBC) at 0-10 cm and 10-20 cm of soil depth, and the microbial quotient (qMic) at 0-10 cm. SM and SWW did not change the densities of heterotrophic bacteria, fungi, nitrite-oxidizers or ammonifiers at any soil depth. SM had single effects on organic C, MBC and qMic, whereas SWW had single effect only on Zn2+. Only available P and NO3--N were affected by both SM and SWW. The principal component analysis for chemical and microbiological attributes showed distinct groupings between CT and NT, and SWW rates at 0-10 cm and 10-20 cm of soil depths, the most influenced soil layers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".