Green Synthesis of Silver Nanoparticles Using Leaf Extract of Rosmarinus officinalis and Its Effect on Tomato and Wheat Plants
Bibliographic record
Abstract
Biological green synthesis of silver nanoparticles (AgNPs) from silver salts is a growing advanced approach to avoid the requirement of costly instruments and involvement of hazardous chemicals as well. However, increasing use of AgNPs raises potential toxicity level in the environment. In this investigation, leaf extract of rosemary (Rosmarinus officinalis) used as a reducing and stabilizing agent for biosynthesis of AgNPs. The biosynthesized AgNPs were authorized by UV-vis spectrophotometer and X-ray diffraction (XRD) analysis. The shape and size of the biosynthesized AgNPs were studied using high resolution transmission electron microscope (TEM). The toxicity of the biosynthesized silver nanoparticles on wheat and tomato plants was studied by soaking wheat grains and tomato seeds in 100 mg/L AgNPs and follow its effect on seedling growth of wheat (at 10 days) and on vegetative growth of tomato and wheat plants (at 35 days). Some physiological parameters as germination percentage of wheat seedling, length of seedling, dry weight, pigment fractions (chl.a, chl.b and caroteinoids), soluble proteins, lipid peroxidation (MDA) and antioxidant enzymes (catalase and peroxidase) of two plants were measured. AgNPs has a non-significant inhibitory effect on germination percentage of wheat, dry weight and pigment fractions. The biosynthesized AgNPs has a noticeable stress effect on tomato plant as reduced chlorophyll a and dry weight. Generally, AgNPs stimulate MDA accumulation in tomato and wheat plants. There was a noticeable different effect of AgNPs on soluble proteins and antioxidant enzymes as catalase and peroxidase among tomato and wheat plants.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 |
| 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 teacher head, 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".