Change and spatial variability of soil organic matter humification after long-term tillage and olive mill wastewater application in arid regions
Bibliographic record
Abstract
The changes of soil organic matter (SOM) humification induced by long-term combination of tillage and olive mill wastewater (OMW) application compared to natural and cultivated soil have been little investigated. This study aimed to compare effects of no cultivation with natural vegetation soil (NC), tillage (CT1) for 80 years and combination of tillage with OMW application (CT2) for 20 years on SOM humification degree. Fluorescence spectroscopy and UV-visible ratios (E4/E6 and CHA/CFA) were used to study soil humic acids (HAs). The SOM and humification distribution was determined for the whole field area using the Inverse Distance Weighting method. Results showed that SOM content, fluorescence emission area and E4/E6 and CHA/CFA ratios were higher in NC. Tillage reduced SOM amount, molecular size, aromatic condensation and humification degree as shown by the strong correlation between fluorescence area and CHA/CFA ratio in CT1 conversely to E4/E6. Contradictory results between fluorescence emission area and E4/E6 ratio found in NC and CT1 indicated that E4/E6 ratio was not a reliable indicator of SOM humification degree. The SOM amount, CHA/CFA ratio and emission fluorescence area increased conversely to E4/E6 ratio in CT2. This revealed a greatly humified organic matter and aromatic structure condensation with tillage and OMW application. Spatial distribution showed a progressive increase of SOM and CHA/CFA from north-west to south-east linked to the positive relationship between CHA/CFA ratio and SOM amount independent of soil management practices. Soil amended with OMW provided a favourable environment for the development of HAs which improved soil quality. The UV-visible ratio CHA/CFA with fluorescence emission area can be used as parameters to investigate SOM humification degree.
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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 | 0.000 | 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 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".