Effect of de-inking paper sludge compost application on soil chemical and biological properties
Bibliographic record
Abstract
A 2-yr field study evaluated the effect of applying compost of de-inking paper residues and poultry manure (DSPC) on the chemical and biological properties of Tilly silt loam (Gleyed Humo-Ferric Podzol) in Sainte-Croix de Lotbinière, Qué bec, Canada. The experiment began in 1996 with snap bean ( Phaseolus vulgaris L. ‘Centralia’) and continued in 1997 on the same plots with potato ( Solanum tuberosum L. ‘Gold Rush’). In 1996, treatments included three rates of mineral fertilizer (MF) (60, 120 and 180 kg P2O5-K2O ha-1), three rates of DSPC (14, 28 and 42 Mg ha-1 on a dry matter basis) alone or in combination with MF, and an untreated control. In the spring of 1997, main plots were divided into four subplots and P fertilizer was applied at 0, 44, 88 and 132 kg ha-1. The DSPC increased soil pH and water content. Soil inorganic N increased just after DSPC application, but this effect lasted only 1 yr. Soil Mehlich-3 extractable P showed a significant increase due to DSPC application and the increase was much larger when DSPC was applied in combination with P fertilizer. Soil phosphatase and urease activities were also increased by DSPC. Application of DSPC increased soil Mehlich-3 extractable K and Mg contents. Except for Mn and Zn, soil Mehlich-3 extractable heavy metal contents were not influenced by DSPC. This experiment indicates that compost derived from a mixture of de-inking papermill sludges and poultry manure is a potential source of nutrients for crops and can effectively improve chemical and biological properties of low fertility or degraded soils. Key Words: De-inking sludge, paper biosolids, poultry manure, phosphorus, potassium, enzyme activity
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".