Effects of different wheat straw returning modes on soil organic carbon sequestration in a rice–wheat rotation
Bibliographic record
Abstract
Straw ditch-buried returning is a new straw returning mode; however, the different effect of straw ditch-buried returning and frequently used straw returning modes on soil organic carbon (SOC) sequestration is still unclear. A 2 yr field experiment was conducted and four treatments (CK: no straw returning; WR: wheat straw returning with rotary tillage; WP: wheat straw returning with plowing; WD: wheat straw ditch-buried returning) were set to assess the effects on SOC fractions and sequestration in rice–wheat rotation. Results indicated that WD had significantly higher total organic carbon than did WP and CK in wheat season. Soil dissolved organic carbon and easily oxidizable carbon contents were significantly increased by 21.3%, 24.3%, 38.6%, and 43.5% under WR than that under CK in rice and wheat seasons, respectively. Soil microbial biomass carbon (MBC) content was highest under WP in rice season, but in wheat season, WR had significantly higher MBC than WP and WD. Soil carbon pool management index was significantly higher in WR than CK, with the increase of 41.0% and 108.6%. After 2 yr rotation, WD had a significant higher SOC stock and sequestration than WP. Therefore, WD could be an available mode to increase SOC sequestration in rice–wheat rotation system.
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 | 0.000 |
| 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) | 0.001 | 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".