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The probing for nanoparticles in soybean protein isolate solutions.
Weichun Pan1, Wenhan Wu1, Shuang Ma1
1School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou 310018, China.
Food Chemistry
|December 8, 2024
Summary
Soybean protein isolates (SPI) form nanoparticles (NPs) with distinct properties based on molecular weight. These differences influence NP behavior during processing, aiding raw material selection for the food industry.
Area of Science:
- Food Science
- Biochemistry
- Materials Science
Background:
- Soybean protein isolates (SPI) are widely used in the food industry.
- Understanding the behavior of SPI at a molecular level is crucial for optimizing food processing.
- Nanoparticle (NP) formation within SPI solutions can significantly impact their functional properties.
Purpose of the Study:
- To investigate the structural and behavioral differences between nanoparticles (NPs) formed from high (GN) and low (DN) molecular weight soybean protein isolates (SPI).
- To elucidate how NP properties affect their stability and behavior upon dilution.
- To provide insights into selecting appropriate SPI raw materials for extrusion processes.
Main Methods:
- Preparation and characterization of two types of SPI: high molecular weight (GN) and low molecular weight (DN).
- Analysis of nanoparticle (NP) size, shape, charge, and stability in SPI solutions using various biophysical techniques.
- Investigation of NP structural changes upon dilution via fluorescence spectroscopy and measurements on filtered samples.
Main Results:
- Both GN and DN SPI formed heterogeneous nanoparticles (NPs).
- GN NPs were larger, more compact, more stable, and more negatively charged than DN NPs.
- Dilution induced NP swelling and disassembly, with tryptophan and tyrosine residues shifting to hydrophobic environments, indicating bond disruption.
Conclusions:
- Differences in NP properties between GN and DN SPI are linked to their molecular weight and affect their behavior during processing.
- Understanding these NP characteristics is vital for predicting SPI performance in applications like extrusion.
- This research provides a basis for establishing criteria for selecting SPI raw materials in the food industry.

