Cattle manure and lime amendments to improve crop production of acidic soils in Northern Alberta
Bibliographic record
Abstract
Crop production on acid soils can be improved greatly by adjusting the pH to near neutrality. Although soil acidity is commonly corrected by liming, there is evidence that animal manure amendments can increase the pH of acid soils. Fresh cattle manure and agricultural lime were compared for their effects on soil acidity and the production of canola (Brassica napus L.) and wheat (Triticum aestivum L.) in a greenhouse study. Canola and wheat yield, the nutrient content of grain and straw, and selected soil properties were determined on a Gray Luvisol (pH 4.8) from the Peace Region of Alberta. Soil pH increased with lime and manure applications, and canola and wheat yields were higher in limed and manure-amended soils than unfertilized, unlimed soils. Macronutrient uptake by canola and wheat was generally improved by liming and manure applications, and micronutrient uptake was related to the effects of lime and manure on soil pH. An economic analysis compared the costs of using cattle manure and lime to increase soil pH to 6.0. The costs of applying lime and fresh cattle manure to increase soil pH were compared, based on the fees for purchasing and applying lime or loading, hauling and applying manure. The nutrient value of manure was calculated based on the quantities of plant-available N, P and K in fresh manure. At distances less than 40 km, it is economical to substitute fresh cattle manure for agricultural lime to increase soil pH of acidic soils. However, good manure management practices should be followed to minimize the risk of nutrient transport and environmental pollution from agricultural land amended with cattle manure. Key words: Agricultural economics, canola production, cattle manure, lime, soil pH, wheat prodution
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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 | 0.000 | 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".