Dry fractionation methods for plant protein, starch and fiber enrichment: A review

By Andrew Assatory, Michael Vitelli, A. Rajabzadeh, R. Legge. Trends in Food Science & Technology, 2019

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Abstract Background Conventional methods for extraction of plant protein, starch and fiber use solvents and intensive drying. These processes are energy intensive and can alter the native structure and function of isolates. Dry fractionation methods have been investigated as solvent-free means for the production of protein-, starch- and fiber-enriched products. Two widely studied methods for dry fractionation of plant flours are air classification and electrostatic separation. Scope and approach Several aspects of both air classification and electrostatic separation are reviewed: basic operating principles; the effect of milling conditions; physical factors that influence separation efficiency; isolate structure and function; and advantages and disadvantages with respect to traditional wet processes. Quantitative approaches in the design and analysis of dry fractionation are also reviewed, in addition to recent patent developments and future prospects of the technology. Key findings and conclusions Dry fractionation methods exhibit lower energy and water consumption relative to wet extraction and retain native structure and function of components. However, these technologies are not yet suitable for the production of high-purity isolates (>90%). Physical limitations of these technologies, such as powder fouling and low process yield, may pose problems for commercialization. Increases in product concentration have been achieved by recycling fractions and by combining different separation techniques in series, such as air classification followed by electrostatic separation. Recent patents show a trend in the development of technologies that integrate elements of milling, sieving, air classification and electrostatic separation.

Subfields: Computational Mechanics, Physiology

View Paper: https://www.semanticscholar.org/paper/2a35f6f70f4eea22f7a2d10ac15618ab4dab3cbb

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