Influence of management practices on soil organic matter composition evaluated by complementary analytical techniques: XANES and mass spectrometry
Bibliographic record
Abstract
The impact of soil management practices on carbon (C) sequestration in soil organic matter (SOM) is insufficiently known. We studied relevant treatments, including manure application, legumes incorporation, their combination, conventional and no-tillage systems, as well as tillage with and without catch crops, at three long-term experimental sites in Poland. Bulk soil and humin fractions were analyzed by X-ray absorption near edge structure (XANES) spectroscopy and thermochemolysis-gas chromategraphy/mass spectrometry (TC-GC/MS). XANES and TC-GC/MS revealed treatment-specific molecular enrichments. Legume cropping enhanced total organic carbon (TOC) and enriched aromatic and aliphatic C structures, particularly at Skierniewice, contributing significantly to SOM stabilization. At Chylice, no-tillage preserved a higher aromatic C content, indicating a contribution of relatively stable compounds to SOM enrichment. At Swojec, the application of catch crops resulted in a balanced C profile with aliphatic C enrichments. Humin consistently exhibited greater aromatic and carboxylic C intensities compared to bulk soil, emphasizing its role as a relatively stable C reservoir. The findings demonstrate that for comparable climatic and soil conditions, no-till management is more efficient in enriching relatively recalcitrant aromatic SOM than the addition of organic matter through manure and legumes. No-till is therefore recommended as a first, immediately effective measure for SOM enrichment under Central European conditions.
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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 | 0.001 | 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 | 0.000 |
| 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 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".