Papermill biosolids and alkaline residuals affect crop yield and soil properties over nine years of continuous application
Bibliographic record
Abstract
Gagnon, B. and Ziadi, N. 2012. Papermill biosolids and alkaline residuals affect crop yield and soil properties over nine years of continuous application. Can. J. Soil Sci. 92: 917-930. Residues from paper and wood mills are a valuable source of nutrients for field crops, but little is known about the effectiveness of repeated applications over many years. A study was initiated at Yamachiche, QC, to assess the effect of continuous applications over 9 yr of combined papermill biosolids (PB), applied alone or with several liming by-products, on grain yield, plant nutrient accumulation, and soil fertility in a loamy soil cropped to grain corn, dry bean, and soybean. The PB treatments (0, 30, and 60 Mg wet ha−1) and liming by-products [calcitic lime (CL), lime mud (LM), wood ash (WA)], and two magnesium residuals, each at 3 Mg wet ha−1 along with 30 Mg PB ha−1) were surface applied annually at post-seeding. In the last 6 yr, the two treatments receiving magnesium residuals were replaced with 90 Mg wet PB ha−1 and mineral N fertilizer (MIN), respectively. Repeated annual applications of LM followed by CL increased soil pH the most (up to 1.4 unit). Crop yields were not significantly affected by treatments in the first 3 yr but subsequent applications of PB at 90 Mg ha−1 increased yields in grain corn (+1.9 Mg ha−1) and dry bean (+0.77 Mg ha−1) relative to the control, while PB with WA increased yield in soybean (+0.85 Mg ha−1). The PB at 30 Mg wet ha−1 with supplemental N (average of 45 kg N ha−1), or at 60 Mg wet ha−1 applied alone, achieved yields comparable with MIN treatment under corn. The PB applications increased soil organic matter and all major soil nutrients except K and Mg. The results of this study indicate that PB and alkaline residuals can be effectively applied to agricultural soils over many years although PB exceeding 60 Mg wet ha−1 yr−1 induce significant nitrate leaching.
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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 | 0.001 | 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".