Soil microbiological properties during decomposition of crop residues under conventional and zero tillage
Bibliographic record
Abstract
Field experiments were conducted to correlate decomposition of red clover (Trifolium pratense) green manure (GM), field pea (Pisum sativum), canola (Brassica rapa) and wheat (Triticum aestivum) residues, and soil organic C (SOC), under zero tillage and conventional tillage, with soil microbial biomass C (MBC), bacterial functional diversity and microbial activity (CO2 evolution). A greenhouse experiment was also conducted to relate crop residue quality to soil microbial characteristics. Zero tillage increas ed MBC only in the 0- to 5-cm soil layer. Soil MBC decreased more with soil depth than either microbial diversity or total SOC. Legume GM residues induced greater initial CO2 evolution than the other residues. This means that results that do not include the initial flush of microbial activity, e.g., by sampling only in the season(s) following residue placement, probably underestimate gas evolution from legume crop residues. Residue N, P and K contents were positively correlated with microbial functional diversity and activity, which were positively correlated with crop residue decomposition. Therefore, microbial functional diversity and activity were good indicators of microbial decomposition processes. Residue C/N and C/P ratios (i.e., high C content) were positively correlated with MBC, which was positively correlated with SOC. Therefore, soil MBC was a good indicator of soil quality (soil organic matter content). Key words: Biological soil quality, crop residues, crop rotation, microbial activity, microbial biomass, microbial diversity
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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".