Impacts of Porous Silica-Nanoencapsulated Pesticide Applied to Soil on Plant Growth and Soil Microbial Community
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Porous silica nanocarriers have the potential to improve agricultural crop productivity. However, the impacts of nanoencapsulated pesticides on soil health and plant growth, and how they compare with conventional pesticide have not been systematically elucidated. In this study, we investigated how applying azoxystrobin encapsulated in porous hollow SiO2 nanocarriers to agricultural soil impacted the soil microbial community and plant development, using Solanum lycopersicum grown in the laboratory in soil microcosms. The data show that plant growth was heavily inhibited by the non-encapsulated pesticide treatment compared to that with encapsulated pesticide yielding 3.85-fold less plant biomass, while the soil microbial community experienced few to no changes regardless of the treatment. There was a 2.7-fold higher azoxystrobin uptake per unit dry plant biomass after 10 days of exposure for the non-encapsulated pesticide treatment when compared to that of nanoencapsulated pesticide, but only 1.5-fold increase in total uptake. After 20 days of exposure, however, the total uptake and uptake per unit of dry biomass were 3-fold and 10-fold higher, respectively, for the nanopesticide treatment. The differences in uptake can be attributed to phytotoxicity caused by the high the bioavailability of the non-encapsulated pesticide. The nanocarrier promoted slow release of the pesticide over days, which prevented phytotoxicity, and allowed healthy plant growth.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 it