Mixed Paper Mill Sludge Effects on Corn Yield, Nitrogen Efficiency, and Soil Properties
Bibliographic record
Abstract
Large quantities of mixed paper mill sludges (PMS) are applied annually to agricultural soils in North America. However, little information exists in the literature delineating the impact of land application of PMS on crop N nutrition and soil properties. In a 3‐yr field study, (1997–1999), we evaluated PMS effects on corn ( Zea mays L.) yields and soil property changes. The study included annual and biennial PMS applications of 20, 40, and 60 Mg ha −1 on wet basis, applied alone or in combination with N fertilizer at reduced rates (90 and 135 kg N ha −1 for 40 and 20 Mg PMS ha −1 , respectively), complete N fertilizer for corn (180 kg N ha −1 ) and a control. Plots were split beginning with the second year for annual and biennial PMS and N fertilizer application. Annual or biennial applications of PMS alone resulted in grain yield increase of 1500 to 3000 kg ha −1 as compared to the unfertilized control. The applications of 20 to 40 Mg ha −1 . PMS with N fertilizer at reduced rates (135 and 90 kg ha −1 respectively) achieved higher corn yields compared to PMS applied alone. The PMS applications combined with N fertilizer at reduced rates produced highest corn yields, similar to those obtained with complete N fertilization for corn (180 kg N ha −1 ). Corn apparent N recoveries (ANR) ranged from 17 to 21% in year of application and from 15 to 22% in residual year, depending of PMS rates. Three PMS applications at 40 to 60 Mg ha −1 yr −1 significantly increased the soil C content by 22 and 26%, and by 18 and 22%, compared to the control and N fertilizer, respectively. Those PMS applications also significantly increased the mean‐weight diameter (MWD) of aggregates, and reduced soil bulk density as compared to the control and fertilizer alone treatment. The soil microbial biomass C and the alkaline phosphatase and urease activities were also increased in soils that received PMS. Our results suggest that the applications of PMS with low C/N (19–24) benefit corn growth possibly due to a combination of the higher nutrient availability and the improvement of the soil properties.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".