Abstract
Current studies reveal the antimicrobial activity effectiveness of various nanoparticles (NPs) towards numerous microorganism. The present study reports on statistical models which define suitable parameters to improve the efficacy of NPs antimicrobial activity. Data on NPs antimicrobial activity were collected, focusing on parameters such as the NPs type and size (nm), bacterial strains and its initial density (O.D.600nm), inhibition zone (IZ) size (mm), contact time (h), well and disc diffusion size (mm) and Minimum Inhibitory Concentration (MIC) (μg/mL). Correlation between these parameters were modelled by using multiple correspondence analysis (MCA) and principal component analysis (PCA) for qualitative and quantitative analyses, respectively. Results showed a significant positive correlation between the IZ size and the following parameters: MIC, well size and disc diffusion size with a Pearson ratio 95.98 %, 93.99 % and 94.82 % (α = 0.5), respectively. Antibacterial affinity between Ag, SiO2 and ZnO NPs with the IZ of strain bacteria gram-positive was obtained. In addition, bacteria gram negative and Fungi have an affinity with the La-ZnO and Ag NPs. Antimicrobial tests with NPs could be improved by varying not only the NPs concentration but also the well or disc diffusion size. The NPs type should be chosen as a function of the bacteria gram stain type for higher efficacy.