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Development of zein/soluble soybean polysaccharide nanoparticle-stabilized Pickering emulsions.

Jin GaoHongshan LiangShugang LiBin Zhou
Published in: Journal of food science (2021)
Pickering emulsions have received wide attention due to their "surfactant-free" character and the ability of delivery bioactive compounds. In the current work, zein and soluble soybean polysaccharide (SSPS) food-grade composite nanoparticles (NPs) were fabricated as Pickering stabilizers. The particle size of the composite NPs varied with the concentration of zein and SSPS, consequently leading to larger hydrodynamic diameters compared with zein nanoparticles (ZPs) in all formulations, also seen from the scanning electron microscopy (SEM) images. At pH 4.0, the dispersions of ZPs exhibited a positive ζ-potential (around at +12 mV); however, zein/SSPS NPs obtained at the same pH had much lower ζ-potential (about -2 mV) further proving that there was electrostatic interaction between SSPS and zein. The composite nanoparticles (NPs) were well dispersed through the results of polydispersity index (PDI). The physical properties and stability of zein/SSPS NPs stabilized Pickering emulsions were evaluated at a fixed oil phase volume (30%, v/v). On the surface of the oil droplets, a densely packed interface layer was observed by confocal laser scanning microscopy (CLSM), which could prevent oil droplets from coalescence and Ostwald ripening. At zein concentration of 6 mg/mL and SSPS concentration of 1 mg/mL, the formed Pickering emulsions had higher stability at 25 °C. PRACTICAL APPLICATION: The findings of this study can be utilized and integrated to further extend the application of zein in foods, medicine, or cosmetics field. This study showed that the food-grade composite colloidal particles formed by electrostatic interaction can significantly improve the emulsification properties of zein and soluble soybean polysaccharides, and stability. The Pickering emulsions have been observed in long-term testing.
Keyphrases
  • electron microscopy
  • physical activity
  • human health
  • single molecule
  • high throughput
  • molecular dynamics simulations
  • convolutional neural network