Rice Root Fe Plaque-Induced Hydroxyl Radicals Increase Paddy Soil CO<sub>2</sub> Emissions
Bibliographic record
Abstract
Poorly crystalline iron (Fe) oxides often accumulate on rice root surfaces, forming Fe plaque. While this plaque has been implicated in soil organic carbon (SOC) transformation, its specific role in regulating SOC mineralization is still insufficiently understood. In this study, we hypothesize that Fe plaque induces the generation of hydroxyl radicals (•OH), which disrupt the “enzyme latch” mechanism and promote CO 2 emissions. The results showed that seedlings with Fe plaque showed a 150% higher •OH concentration, 50% higher laccase activity, 25% higher SOC mineralization rate, and 20% lower phenolic concentration in comparison to those without Fe plaque. These effects disappeared when a •OH scavenger was applied or oxygen availability was reduced. Moreover, the exogenous addition of Fe(II) in Fe plaque-free soils reproduced the increases in •OH, laccase activity, and SOC mineralization, confirming the role of Fe-driven •OH production. These findings demonstrate that Fe plaque-induced •OH simultaneously disrupts phenolic inhibition and accelerates SOC mineralization. This study identifies a previously underappreciated oxidative mechanism by which Fe plaque destabilizes SOC in paddy soils and highlights the role of mineral–radical interactions in controlling carbon turnover.
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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) | 0.001 | 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".