ANOVA-Based Evaluation of a Box-Behnken Design for Total Phenolic Content in Morus alba var. shalun

Abstract

This study optimized the extraction of total phenolic content (TPC) from Morus alba var. shalun leaves using Response Surface Methodology (RSM) with a Box–Behnken Design (BBD). Ethanol concentration, extraction temperature, and extraction time were evaluated as independent variables affecting TPC extraction. A total of 17 experimental runs were conducted, and the data were analyzed using Analysis of Variance (ANOVA) and regression modeling. Prior to analysis, the response data were transformed using natural logarithm transformation based on Box–Cox analysis to improve model adequacy. The developed model was highly significant (p < 0.0001) with a high coefficient of determination (R² = 0.9953), indicating excellent agreement between predicted and experimental values. Ethanol concentration was identified as the most influential factor, followed by extraction time and temperature. Diagnostic analyses confirmed good model stability and predictive capability. Overall, the developed RSM model effectively optimized TPC extraction from Morus alba var. shalun.