Cattle Manure Amendments Can Increase the pH of Acid Soils
Bibliographic record
Abstract
Crop production on acid soils can be improved greatly by adjusting the pH to near neutrality. While soil acidity is commonly corrected by liming, there is evidence that animal manure amendments can increase the pH of acid soils. The effect of fresh cattle manure on soil acidity and nutrient availability was determined in the laboratory for two acid soils from Beaverlodge and Fort Vermillion in the Peace River region of Alberta, Canada. The effect of manure on soil pH was immediate and persisted during an 8‐wk incubation. Manure‐amended soil had significantly higher pH than unamended soil, and the highest rate (40 g manure kg −1 , dry weight basis) increased the pH of Beaverlodge and Fort Vermillion soils from 4.8 to 6.0 and 5.5 to 6.3, respectively. The higher pH in manure‐amended than unamended soils was attributed to buffering from bicarbonates and organic acids in cattle manure. Mineral N (NH 4 –N + NO 3 –N), available P, K, Ca, and Mg increased immediately after manure application, and available P and K remained significantly higher in manure‐amended than unamended soil after the 8‐wk incubation. Soils amended with 40 g manure kg −1 had three to four times more plant‐available P and K than unamended soils after incubation. Available S concentrations did not differ significantly in manure‐amended and unamended soils. Extractable Al and Fe declined slightly after manure application, but did not differ in manure‐amended or unamended soils after incubation. No change in the cation‐exchange capacity (CEC) of manure‐amended soils compared to unamended soils was observed in this study, and it appears that appreciable changes in Al, Fe, and CEC from manure application do not occur in the short‐term (weeks). Our results indicate that, in the short‐term, cattle manure amendments can increase the pH and the quantity of plant‐available P and K in acid soils.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".