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• W2893180798 abstract "For the preparation of nanoemulsions, the correct choice of emulsifiers, together with the emulsification methods, directly influences the final product quality. The present study reports the ultrasound-assisted preparation of oil-in-water nanoemulsions produced with mucilage extracted from leaves of Pereskia aculeata Miller (ora-pro-nobis; OPN). The OPN mucilage (%) and soybean oil (%) concentration range, and the process operating parameters, ultrasonic power amplitude (%) and sonication time (min), were optimized based on the mean droplet diameter (d32). The effect of the mucilage and oil concentrations was also investigated by the response variables such as polydispersity, density, turbidity, viscosity, zeta-potential, and interfacial tension. The higher OPN mucilage concentrations (%) with lower amounts of soybean oil (%) favored nanoemulsion formations (116 ≤ d32 ≤ 171 nm) and increased polydispersity, density, and zeta-potential. On increasing OPN mucilage and soybean oil the turbidity of the dispersions increased. All colloidal systems showed Newtonian behavior, and the viscosity in the systems increased due to the greater OPN mucilage concentration in the aqueous phase at a certain oil concentration. In addition, lower values of equilibrium interfacial tension were found with increasing OPN mucilage concentrations. Finally, from the stability test, it can be pointed out that the OPN mucilage concentration should be between 1.0 and 1.5% and the oil concentration should be less than 5%, so that lower d32 values are maintained over time. Therefore, mucilage extracted from OPN and the ultrasound technique can be used in the preparation of nanoemulsions." @default.
• W2893180798 created "2018-10-05" @default.
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• W2893180798 date "2019-01-01" @default.
• W2893180798 modified "2023-10-17" @default.
• W2893180798 title "Ultrasound-assisted oil-in-water nanoemulsion produced from Pereskia aculeata Miller mucilage" @default.
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• W2893180798 doi "https://doi.org/10.1016/j.ultsonch.2018.09.036" @default.
• W2893180798 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30287179" @default.
• W2893180798 hasPublicationYear "2019" @default.
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