Production and Decomposition of Cover Crop Residues and Associations With Soil Organic Fractions
Bibliographic record
Abstract
The decomposition of plant residues, the changes in the total organic carbon (TOC) and the fractions of soil organic matter (SOM) occur differently in irrigated areas. The objective of this study was to quantify the biomass production, the decomposition of cover crops residues and relate them with the changes n the content and fractions of SOM in an irrigated area of vegetable crops. Six types of cover crop treatments were evaluated: brachiaria (B); sunn hemp (S); millet (M); B + S; B + M; S + M, plus an additional treatment (native area), with 4 repetitions. The production of fresh (FB) and dry biomass (DB), the rate of plant residue decomposition, TOC, SOM fractions and the coefficient of SOM (QSOM) were quantified. It was observed that the greatest and the lowest volume of crop residues were from the B and S cover crop, respectively. The cover crops in monoculture presented great decomposition rates and short half-life when compared to mixtures of cover crop. The TOC and QSOM were great in the 0 to 0.05 m soil layer, and in the M + S cover crop mixture, when compared to the 0.05 to 0.1 m soil layer and to other cover crops. Among the SOM fractions, the humin predominated in the most superficial soil layer (0 to 0.05 m).
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) | 0.000 | 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".