Comparison of Three Methods for Measurement of Soil Organic Carbon
Bibliographic record
Abstract
Quantification of soil organic carbon (SOC) is an important element in the assessment of the carbon sequestration potential of soils in tree-based intercropping (TBI) systems. The organic carbon (OC) concentrations of soils in TBI systems often differ from those in conventional agricultural systems due to the additional C inputs from litter fall and roots. However, the presence of soil inorganic carbon (SIC) can confound the measurements of SOC. This study compared three methods of measuring SOC: (i) measurement of the total soil C (TC) in one subsample and, after treatment in a muffle furnace (575 °C) for 24 h, measurement of SIC in another subsample; (ii) SOC measured after fumigation with 12 M hydrochloric acid (HCl) to remove SIC; and (iii) SOC measured after digestion with 0.73 M H2SO3 to remove SIC. The TC, SOC, and SIC concentrations were determined by combustion. A correction factor was applied to express SIC and SOC concentrations on an original, untreated soil basis. Measurement of SOC by the muffle furnace method resulted in the greatest SOC concentrations for Populus spp. (hybrid poplar) for samples from two of the three depths (0–10 and 20–40 cm). Measurement of SOC by the HCl fumigation and H2SO3 digestion methods were highly correlated, suggesting complete removal of SIC with minimal oxidation of SOC. These results have implications for the method of measuring SOC in calcareous soils under coniferous and deciduous tree species to a depth of 40 cm.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".