Short-Term Effects of Maize Rhizosphere and N-Fertilization on Stable Organic Matter in a Tropical Soil
Bibliographic record
Abstract
The objective of this study was to investigate the effect of maize rhizosphere in the dynamics of soil organic matter (SOM) fractions (particulate organic matter—POM and mineral associated organic matter—MAOM) under different soil nitrogen (N) availability. The experiment was laid out as a factorial scheme 2 × 2: (i) without (-Plant) and with maize plant (+Plant); (ii) without (-N) and with N fertilization (+N) throughout 56 d under greenhouse conditions. Soil surface CO2-C efflux was monitored by static PVC chambers, and soil- and root-derived CO2-C efflux was determined using the mass-balance approach. In the absence of plants, N addition reduced total soil CO2-C efflux over the 56-d experiment and increased MAOM-C. This was followed by an increase of 366% in microbial biomass (MB-C), indicating a high C assimilation by soil microbes. In the presence of plants, there was evidence of positive rhizosphere priming effect (RPE) at 42-d after planting when N was applied. The new C input by rhizodeposition promoted an increase of 495% and 50% in MB-C under -N and +N addition, respectively. The short-term effect of maize rhizosphere appeared to preserve native SOM and allowed higher incorporation of microbial residues-derived C into the MAOM.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".