Green Synthesis of Zinc Oxide Nanoparticles Using Conocarpus lancifolius Extract and Their Antibacterial Activity Against Xanthomonas citri
Bibliographic record
Abstract
The increasing resistance of pathogenic bacteria to conventional antibiotics poses a serious threat to both human health and agriculture, prompting the search for alternative antimicrobial strategies.This study aimed to investigate the antibacterial potential of zinc oxide nanoparticles (ZnO-NPs) synthesized through a green method.Xanthomonas citri, a bacterial pathogen, was isolated from infected plant leaves collected from Baghdad, Babylon, and Kut in Iraq.Zinc oxide nanoparticles were biologically synthesized using Conocarpus lancifolius leaf extract.The biologically synthesized nanoparticles were characterized using Fourier-transform infrared spectroscopy (FTIR), ultraviolet-visible spectroscopy (UV-Vis), and atomic force microscopy (AFM).The antimicrobial activity of the biologically synthesized nanoparticles against Xanthomonas citri was evaluated using the streaking technique.The results of the characterization of the ZnO-NPs revealed an absorption peak at 292 nm and an average particle size of 73.55 nm.Furthermore, the ZnO-NPs demonstrated an 18 mm clear zone against the test bacterial pathogen.At 100 mg/mL, however, the crude C. lancifolius extract had no inhibitory effect, suggesting that the formulation of the nanoparticles greatly increased the antimicrobial activity.These findings highlight the promising role of biologically synthesized ZnO-NPs as an effective alternative approach to combat bacterial resistance, with potential applications in both medical and agricultural fields.
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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) | 0.000 | 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 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".