Encapsulation of bioactive compounds extracted from Cucurbita moschata pumpkin waste: the multi-objective optimisation study

Aim Artificial neural network (ANN) development to find optimal carriers (pea protein-P, maltodextrin-M, and inulin-I) mixture for encapsulation of pumpkin waste bioactive (beta-carotene and phenolics). Methods Freeze-drying encapsulation and encapsulates characterisation in terms of bioactive contents and encapsulation efficiencies, water activity, hygroscopicity, densities, flowability, cohesiveness, particle size (laser diffraction), solubility, colour (CIELab), morphological (SEM), stability and release properties. Results Optimal encapsulates, OE-T (with highest total bioactive contents; P, M, and I of 53.9, 46.1, and 0%w/w) and OE-EE (with highest bioactive encapsulation efficiencies; P, M, and I of 45.5, 32.0, and 22.5%w/w) had particle diameters of 94.561 +/- 1.341 mu m and 90.206 +/- 0.571 mu m, the span of 1.777 +/- 0.094 and 1.588 +/- 0.089, highest release at pH 7.4 of phenolics of 71.03%w/w after 72 h and 66.22%w/w after 48 h, and beta-carotene of 43.67%w/w after 8 h and 48.62%w/w after 6 h, respectively. Conclusion ANN model for prediction of encapsulates' preparation, showed good anticipation properties (with gained determination coefficients of 1.000).