Effectiveness of wood ash and paper sludge as liming and nutrient sources for annual ryegrass grown in podzolic soils of Newfoundland
Bibliographic record
Abstract
Abstract The acidic soils of western Newfoundland require liming for successful production of most crops. Locally sourced paper mill waste wood ash (WA) and paper sludge (SL) have potential as cheaper alternatives to limestone (LIME). Two greenhouse experiments evaluated WA and SL as liming and soil conditioning amendments for annual ryegrass ( Lolium multiflorum ) production. At 55 days after seeding, soil pH in WA (6.2 and 6.3) and wood ash and paper sludge (WASL) (6.0 and 6.3) were not different from that in LIME (6.0 and 6.5) for Experiments 1 and 2, respectively. However, pH in SL was 0.4 and 0.3 points lower than in LIME. Compared to LIME, WA, SL, and WASL produced 31%–52% and 57%–74% greater biomass yield in Experiments 1 and 2, respectively. N uptake was greater in WA (60 and 129 kg N ha −1 ) and WASL (51 and 97 kg N ha −1 ) compared to LIME (40 and 85 kg N ha −1 ), in Experiments 1 and 2, respectively. SL did not differ from LIME in Experiment 1, but reduced N uptake by 57% in Experiment 2. The results show significant potential of WA as an alternative amendment for liming and yield improvement of annual ryegrass grown in NL podzolic soils. However, SL has limited potential due to the risk of increasing N immobilization and residual soil mineral N when growing conditions are limiting. Combining SL with WA or biochar seemed to alleviate these risks. Overall, the adoption of these amendments for field production systems warrants serious consideration, following supplemental field studies to determine optimal application rates and timing.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".