Chemical composition and thermal stability of topsoil organic carbon: Influence of cropping system and tillage practices
Bibliographic record
Abstract
Abstract Agricultural management practices play a significant role in regulating the potential for soil organic carbon (SOC) sequestration. The objective of this study was to determine the effects of cropping systems and tillage practices on the chemistry and thermal stability of topsoil SOC in a long‐term field study in Ontario, Canada. The cropping system is based on rotations including corn, alfalfa, cereals, soybeans and a red clover cover crop. Tillage practices of conventional (moldboard plow, CT) and conservation (no‐till, NT) were applied to each cropping system. A 130‐day laboratory incubation was conducted to measure the potentially mineralizable SOC. The thermal stability and molecular structure of SOC were investigated using thermal analysis‐programmed pyrolysis (PP) and solid‐state 13 C cross polarization/total sideband suppression magic angle spinning nuclear magnetic resonance (CP/TOSS MAS NMR) spectroscopy, respectively. The SOC stocks were larger under NT practices and the crop rotations incorporating alfalfa and cover crops. Under NT practices, an abundance of aromatic‐C components was observed, however, soil under CT showed an abundance of aliphatic‐C compounds ( p < 0.001), with a higher alkyl/O‐alkyl‐C ratio, indicating a higher degree of SOC decomposition. Soil under rotations that included soybeans demonstrated a significant increase in aliphatic‐C components, whereas those with cover cropping exhibited an enrichment in O‐alkyl‐C groups ( p < 0.05), representing the presence of more resistant and easily decomposable SOC constituents, respectively. The results demonstrated that the thermal stability of SOC in CT systems was higher than that of NT practices ( p < 0.05), while NT practices and crop rotations including cover crops are better capable of conserving the labile pool of SOC. Our findings confirmed the correlations among the parameters that characterize both the labile and stable pools of SOC as determined by the methods employed in this study. These results demonstrated that agricultural management practices significantly influence the chemical composition and thermal stability of soil organic matter (SOM), which can have significant impacts on soil health and C sequestration potential.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 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".