Acid–base properties of humic acid from soils amended with different organic amendments over 17 years in a long‐term soil experiment
Bibliographic record
Abstract
Abstract The acid–base properties of soil organic matter are crucial in regulating plant nutrient availability in agricultural soils. This study examined the effect of long‐term application of different forms of manure: liquid swine manure (LSM), solid swine manure (SSM), and swine manure compost (SMC), applied biennially over 17 years, on the intrinsic charge characteristics of humic acid (HA) extracted from soils. Potentiometric titration and a continuous distribution p Ka model assessed buffer intensity, surface charge excess, p Ka distribution, and proton binding site capacities. The HA formed in soils amended with SMC (SMC‐HA) showed higher proton neutralization, particularly in the pH range critical for plant nutrient availability, correlating with phenol content. Variations in p Ka distribution highlighted stronger acidic sites in SMC‐HA, attributed to phenols and sulfur content, while LSM‐HA (HA formed in soils amended with LSM) and SSM‐HA (HA formed in soils amended with SSM) displayed weaker acid strength due to lower phenol content and molecular configurations. Acidic/basic site ratios revealed dominance of acidic functional groups in LSM‐HA and SSM‐HA, whereas SMC‐HA exhibited relatively higher basic site content and a lower acid/basic ratio. These findings underscore the heterogeneity of binding sites and differences in binding strengths among HA samples from various manure forms. The enhanced buffering capacity and distinct charge characteristics of SMC‐HA suggest a greater potential to improve nutrient availability and overall soil health. SMC amendment produces HAs with properties conducive to improved nutrient management in agricultural 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".