Effect of Cultivation on Soil Organic Matter and Aggregate Stability
Bibliographic record
Abstract
Agricultural sustainability relates directly to maintaining or enhancing soil quality. Soil quality studies in Canada during the 1980's showed that loss of soil organic matter (SOM) and soil aggregate stability was standard features of non-sustainable land management in agroecosystems. In this study total soil organic carbon (SOC), particulate organic matter (POM), POM-C as a percentage of total SOC, and aggregate stability were determined for three cultivated fields and three adjacent grassland fields to assess the impact of conventional agricultural management on soil quality. POM was investigated using solid-state 13C nuclear magnetic resonance (NMR) to determine any qualitative differences that may be attributed to cultivation. Results show a highly significant loss in total SOC, POM and aggregate stability in the cultivated fields as compared to the grassland fields and a significant loss of POM-C as a percentage of total SOC.Integrated results of the NMR spectra of the POM show a loss in carbohydrate-C and an increase in aromatic-C in the cultivated fields, which translates to a loss of biological lability in the organic matter. Conventional cultivation decreased the quantity and quality of SOM and caused a loss in aggregate stability resulting in an overall decline in soil quality.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".