Cultivation Affects Soil Organic Nitrogen: Pyrolysis‐Mass Spectrometry and Nitrogen K‐edge XANES Spectroscopy Evidence
Bibliographic record
Abstract
Elucidating molecular–chemical changes that the soil organic N (SON) pool has undergone following long‐term cultivation remains a challenge. Our objective was to examine SON compounds in paired native and long‐term cultivated soils using three independent analytical methods. Curie‐point pyrolysis‐gas chromatography/mass spectrometry revealed approximately 60 different organic N‐containing molecules of which 11, 13, and 14 were less and 8, 16, and 11 more abundant in the cultivated than in the native soils from Lethbridge, Macklin, and St. Denis, respectively. Pyrolysis‐field ionization mass spectrometry (Py‐FIMS) revealed that heterocyclic N compounds such as substituted pyrroles and pyridines contributed to the overall cultivation‐induced changes. Furthermore, Py‐FIMS showed that cultivated sites preferentially lost thermally labile peptides and, to a lesser extent, other labile N‐containing compounds. The magnitude of losses decreased in the order Lethbridge (80 yr cultivation) > Macklin (85 yr cultivation) > St. Denis (57+ yr cultivation). Relative gains in thermally stable N‐containing compounds (all sites) and peptides (Macklin only) followed the same order. The weaker cultivation effect at St. Denis probably reflects a greater inherent stability of SON compounds in the native soil, as indicated by onsets and peaks in the thermal volatilization curves at 40 K higher pyrolysis temperature. Synchrotron‐based N K‐edge x‐ray near‐edge fine structure spectroscopy confirmed the enrichment of nitriles and N‐heterocycles in the cultivated Lethbridge soil at the expense of amide N. Our multimethodological approach provided evidence for the enrichment of a relatively stable nonproteinaceous pool of SON on cultivation.
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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".