Impact of natural or industrial liming materials on soil properties and microbial activity
Bibliographic record
Abstract
Soil acidity is a major problem in agriculture because it limits plant growth and reduces crop productivity. The neutralizing potential of industrial by-products and their impact on soil properties were evaluated in two acidic soils characterized by contrasting textures, and submitted to intensive agriculture practices. Soil pH, microbial (dehydrogenase and alkaline phosphatase) activity, and Mehlich-3 extractable P, K, Ca and Mg were monitored in the year of soil incorporation of eight liming products and in the following 2 yr. In the sandy loam, liming products did not result in significant increases in soil pH in the 0- to 7.5-cm soil layer. Lime mud (LM) significantly increased soil pH by 0.4 units in the 7.5- to 20-cm layer compared with cement kiln dust (CKD). In the silty clay, calcium-phosphate-magnesium (CalPoMag) significantly raised pH by 0.65 units over both natural calcitic lime (NCa) and the magnesium dissolution product (MgD) in the first soil layer, and by 0.5 units over carbide lime (CL) treatment in the second soil layer. Activities of dehydrogenase and alkaline phosphatase were increased to various degrees by all liming materials, especially on the silty clay; LM and CalPoMag were the most beneficial materials. The exception was MgD, which did not result in any impact on microbial activity relative to the control. Both enzymatic activities were related to the increase in soil pH, particularly the alkaline phosphatase. Ion leaching was more pronounced in the sandy loam than in the silty clay soil, where large differences in the Ca and Mg ion levels were still detected in the 20- to 40-cm layer of the sandy loam. In this study, LM and CalPoMag are interesting liming products, particularly in the silty clay soil. Key words: Enzymatic activity, soil pH, lime, soil cations
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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 | 0.001 |
| 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".