Leveraging factorial design and chemometrics for the optimization of Coffea arabica L. microcapsules in functional beverages

Abstract

Coffea arabica L. contains valuable bioactive compounds with antioxidant properties, yet their susceptibility to environmental degradation limits industrial applications. This study presented an innovative integrated approach combining factorial experimental design and chemometric analysis to optimize coffee microencapsulation, addressing key gaps in the current literature. Using a 2-level factorial design, the effects of maltodextrin and gum arabic concentrations on microcapsule characteristics were investigated, identifying an optimal formulation with maltodextrin at 30% and gum arabic at 17.462%. This formulation achieved a yield of 50.4%, ash content of 1.23%, moisture content of 4.45%, solubility of 99.73 g/mol, solubility time of 79.11 s, compressibility index of 22.887%, particle size of 254.118 µm, solubility stability of 1345, and water absorption capacity of 1.236 mL/g, with the closest to 1 desirability value. Principal Component Analysis (PCA) revealed nine principal components explaining 99.7% of the total variance, with PC1 (72.3%) and PC2 (27.4%) as primary determinants of formulation performance. Cluster analysis identified four distinct formulation groups, providing a rational framework for selection. While further stability studies are needed to validate long-term performance, this work represents a significant advancement in microencapsulation technology for industrial applications.