Impact of zinc and zinc oxide nanoparticles on the physiological and biochemical processes in tomato and wheat
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
In this study, the effects of various concentrations of zinc and zinc oxide nanoparticles (nZn, nZnO) were evaluated in tomato and wheat. Results showed that at lower concentrations, nZn and nZnO augmented seed germination and growth parameters, whereas with higher concentrations, the nanoparticles reduced these traits. Zn concentrations corresponding to Zn dissolved (3–23 mg Zn·L −1 ) from nanoparticles (NPs) did not significantly affect the germination indices in either species. Compared with the bulk counterparts of ZnO, NPs exerted more toxicity on seed germination, growth parameters, and chlorophyll and carotenoid contents, and also increased Zn bioaccumulation more. More often than not, nZnO provoked more adverse symptoms than nZn at equivalent concentrations. In both species, the Zn accumulation in roots and shoots followed the order: Zn 2+ ions > nZn > nZnO > bulk ZnO > control. Exposure to 200 mg Zn·L −1 nZn and nZnO increased H 2 O 2 accumulation and malondealdehyde (MDA) levels, which were more pronounced in tomato than wheat. The results suggested that the toxicity of NPs could be due to the particle itself, or from the Zn 2+ ions dissolved from NPs. Moreover, nanotoxicity, like other stresses, caused oxidative stress in both plants, and the differences in proline accumulation and the antioxidant enzyme activities of leaves, especially APX activity, at least in part, explained the higher sensitivity of tomato to NPs than wheat.
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.
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) | 0.000 | 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 it