Green synthesis of antimicrobial metal oxide nanostructures for bovine mastitogen

Bovine mastitis is known to be a serious ailment that has a major economic impact on dairy industry throughout the world. Mastitis is typified by physical, microbiological, and chemical alterations in milk along with pathological modifications in udder glandular tissues. Primary etiology of disease is manifested by contagious agents such as viruses, bacteria, and fungi. Among these, more crucial are bacteria, split into 2 groups: major pathogens (Streptococci, S. aureus, C. pyogenes and Coliform) and minor pathogens (C. bovis and coagulase negative Staphylococci). The advent of medication resistant G +ve and G -ve bacterial strains presents substantial danger to communal well-being. Recent advances in nano-biotechnology, especially the potential to synthesize metal oxide nanomaterials of specific shape and size are leading toward the development of new antimicrobial agents. In the proposed study, metal oxide nanostructures will be synthesized using green process and characterization for appropriate analysis. Zinc nitrate, cupric nitrate, nickel nitrate and titanium ethoxide of analytical grade will be acquired along with fresh roots of Zingiber officinale (Ginger) and Allium sativum (Garlic). Optimization of green synthesized nanostructures will be undertaken with various ratios of aqueous extracts, pH and reaction temperature The synthesized nanostructures will be characterized with UV-vis, FTIR, XRD, EDX, SEM and TEM. The bovine milk samples will be cultured on 5% sheep blood agar and will be incubated at 37 C for 24 to 48 hrs. Bacterial colonies will be confirmed by typical morphology, Grams staining and various biochemical tests such as coagulase test and catalase test for MDR isolates of S. aureus. In-vitro antimicrobial efficacy of green synthesized metal oxide nanostructures will be analyzed. Efficacy of plant extract will be compared by t-test, while combination groups and hemato-biochemical changes will be analyzed by repeated measures ANOVA technique. Means will be compared for significance using post hoc tests at 5% probability (p