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Towards predicting the emulsion properties of plant protein extracts from sugar beet (Beta vulgaris L.) leaf and soybean (Glycine max)
- Source :
- Colloids and Surfaces A: Physicochemical and Engineering Aspects, 646, Colloids and Surfaces A: Physicochemical and Engineering Aspects 646 (2022)
- Publication Year :
- 2022
-
Abstract
- To apply (novel) proteins such as sugar beet leaf proteins (LSPC) as emulsifier their emulsion properties need to be tested over a wide range of conditions, which is impractical. Recently, a model was proposed to predict the efficiency of proteins to form and stabilize an emulsion -based on the protein molecular properties (e.g. size, charge) and system parameters-. In this model, the critical protein concentration (Ccr), to prevent coalescence during emulsion formation and flocculation induced by changes in system conditions, is the key descriptor. This study investigates whether the model, developed for single protein systems, can be applied to more complex systems containing multiple proteins, i.e. LSPC and soy protein isolate (SPI). Despite the complexity of LSPC and SPI, Ccr for emulsion formation and salt-induced flocculation (at ζ ≥ ζcr) were in close agreement with the predictions. At ζ < ζcr (i.e. pH close to pI), the critical energy barrier of 5 kBT and surface coverage were found to be the most important parameters to predict emulsion stability. As experimental values for Ccr were close to the theoretical Ccr calculated using the model, it was concluded that protein mixtures behave similar as single protein systems. This shows that the model developed to predict the emulsion properties of single protein systems can also be applied, at least to get decent estimations, to more complex (plant) protein systems containing multiple proteins.
Details
- Language :
- English
- ISSN :
- 09277757
- Database :
- OpenAIRE
- Journal :
- Colloids and Surfaces A: Physicochemical and Engineering Aspects, 646, Colloids and Surfaces A: Physicochemical and Engineering Aspects 646 (2022)
- Accession number :
- edsair.doi.dedup.....a3cd70fefec24a6e2efdeb752f2944f4