Archives of Current Research International

Green synthesis of silver nanoparticles (AgNPs) using plant-derived phytochemicals has emerged as a viable alternative to traditional chemical approaches. The present study optimised AgNP production using Cassia fistula stem, bark, and leaf extracts by evaluating the influence of key process parameters through statistical optimisation tools. A total of 36 experiments were conducted by varying AgNO₃ concentration (1, 2, and 3 mM), plant extract volume (2.5, 5, and 10 mL), pH (4, 7, and 8), and temperature (40, 60, and 80°C). The synthesised nanoparticles were purified, and their formation was confirmed by UV–Visible spectroscopy using characteristic surface plasmon resonance (SPR) bands. Exploratory data analysis (EDA) using box plots and UV–Vis spectral visualisation in R, followed by one-way ANOVA, was performed to assess the significance of the process variables. Response Surface Methodology (RSM) was used to model the relationship between synthesis parameters and nanoparticle yield, with absorbance as the response variable. The RSM model showed a highly significant overall fit (F = 363.6, p < 2.2 × 10⁻¹⁶) and identified significant interactions between AgNO₃ concentration and plant part (p = 3.644 × 10⁻⁷), plant extract and plant part (p = 4.477 × 10⁻⁴), and temperature and plant part (p < 2.2 × 10⁻¹⁶), confirming variation in synthesis efficiency among stem, leaf, and bark extracts. The optimised conditions were 3 mM AgNO₃, 5 mL extract, pH 8, and 80°C for leaf and bark extracts, while the stem extract showed maximum absorbance at 3 mM AgNO₃, 2.5 mL extract, pH 8, and 40°C. SPR peaks between 420 and 470 nm confirmed successful AgNP formation. Overall, leaf and bark extracts exhibited higher nanoparticle production efficiency. The integrated EDA-RSM approach provides a statistical framework for optimising green AgNP synthesis using Cassia fistula extracts.