Optimization of Pinhão Extract Encapsulation by Solid Dispersion and Application to Cookies as a Bioactive Ingredient

Food and Bioprocess Technology(2022)

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Abstract
Pinhão residues have a wide range of bioactive compounds and encapsulation can be one of the alternatives to increase their bioavailability. Thus, this work aimed to apply pinhão extract, pure and encapsulated by solid dispersion, in the formulation of cookies as a bioactive ingredient. For that, pinhão extract was encapsulated in different biopolymers (sodium caseinate, gelatin, and gum arabic) and with different shear mechanisms (sonication, Ultra-Turrax, and magnetic stirring). The best encapsulation procedure has been defined by a chemometric analysis (hierarchical cluster analysis), considering thermal properties (DSC) of particles and ( +)-catechin encapsulation efficiency (HPLC). The optimized conditions were gelatin as encapsulation agent and Ultra-Turrax as shear mechanism (70.1 ± 2.8 °C maximum endothermic peak temperature and 96.0 ± 2.3% ( +)-catechin encapsulation efficiency). The phenolic profile of the encapsulated extract showed the presence of ( +)-catechin (0.31 ± 0.01 (mg/g particle ), protocatechuic acid (0.29 ± 0.00 mg/g particle ), and ( −)-epicatechin (0.11 ± 0.00 mg/g particle ). Both the pure and encapsulated extracts were incorporated into the cookie formulation, which was characterized in terms of centesimal composition, color parameters, texture, and sensory aspects. It was found that cookies with the pure and the encapsulated extract showed significant differences concerning the centesimal composition, products added with pinhão extract and encapsulated extract presented higher values when compared to the control, probably influenced by the mineral content of the pinhão. In addition, higher hardness values were detected for cookies formulated with the encapsulated extract, which possibly negatively affected the consumer’s sensory perception.
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Key words
Araucaria angustifolia (Bertol.) Kuntze, Solid dispersion, Encapsulation, Hierarchical cluster analysis
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