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Functional Performance of Plant Proteins
Increasingly, consumers are moving towards a more plant-based diet. However, some consumers are avoiding common plant proteins such as soy and gluten due to their potential allergenicity. Therefore, alternative protein sources are being explored as functional ingredients in foods, including pea, chi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8871229/ https://www.ncbi.nlm.nih.gov/pubmed/35206070 http://dx.doi.org/10.3390/foods11040594 |
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author | Ma, Kai Kai Greis, Maija Lu, Jiakai Nolden, Alissa A. McClements, David Julian Kinchla, Amanda J. |
author_facet | Ma, Kai Kai Greis, Maija Lu, Jiakai Nolden, Alissa A. McClements, David Julian Kinchla, Amanda J. |
author_sort | Ma, Kai Kai |
collection | PubMed |
description | Increasingly, consumers are moving towards a more plant-based diet. However, some consumers are avoiding common plant proteins such as soy and gluten due to their potential allergenicity. Therefore, alternative protein sources are being explored as functional ingredients in foods, including pea, chickpea, and other legume proteins. The factors affecting the functional performance of plant proteins are outlined, including cultivars, genotypes, extraction and drying methods, protein level, and preparation methods (commercial versus laboratory). Current methods to characterize protein functionality are highlighted, including water and oil holding capacity, protein solubility, emulsifying, foaming, and gelling properties. We propose a series of analytical tests to better predict plant protein performance in foods. Representative applications are discussed to demonstrate how the functional attributes of plant proteins affect the physicochemical properties of plant-based foods. Increasing the protein content of plant protein ingredients enhances their water and oil holding capacity and foaming stability. Industrially produced plant proteins often have lower solubility and worse functionality than laboratory-produced ones due to protein denaturation and aggregation during commercial isolation processes. To better predict the functional performance of plant proteins, it would be useful to use computer modeling approaches, such as quantitative structural activity relationships (QSAR). |
format | Online Article Text |
id | pubmed-8871229 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88712292022-02-25 Functional Performance of Plant Proteins Ma, Kai Kai Greis, Maija Lu, Jiakai Nolden, Alissa A. McClements, David Julian Kinchla, Amanda J. Foods Review Increasingly, consumers are moving towards a more plant-based diet. However, some consumers are avoiding common plant proteins such as soy and gluten due to their potential allergenicity. Therefore, alternative protein sources are being explored as functional ingredients in foods, including pea, chickpea, and other legume proteins. The factors affecting the functional performance of plant proteins are outlined, including cultivars, genotypes, extraction and drying methods, protein level, and preparation methods (commercial versus laboratory). Current methods to characterize protein functionality are highlighted, including water and oil holding capacity, protein solubility, emulsifying, foaming, and gelling properties. We propose a series of analytical tests to better predict plant protein performance in foods. Representative applications are discussed to demonstrate how the functional attributes of plant proteins affect the physicochemical properties of plant-based foods. Increasing the protein content of plant protein ingredients enhances their water and oil holding capacity and foaming stability. Industrially produced plant proteins often have lower solubility and worse functionality than laboratory-produced ones due to protein denaturation and aggregation during commercial isolation processes. To better predict the functional performance of plant proteins, it would be useful to use computer modeling approaches, such as quantitative structural activity relationships (QSAR). MDPI 2022-02-18 /pmc/articles/PMC8871229/ /pubmed/35206070 http://dx.doi.org/10.3390/foods11040594 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Ma, Kai Kai Greis, Maija Lu, Jiakai Nolden, Alissa A. McClements, David Julian Kinchla, Amanda J. Functional Performance of Plant Proteins |
title | Functional Performance of Plant Proteins |
title_full | Functional Performance of Plant Proteins |
title_fullStr | Functional Performance of Plant Proteins |
title_full_unstemmed | Functional Performance of Plant Proteins |
title_short | Functional Performance of Plant Proteins |
title_sort | functional performance of plant proteins |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8871229/ https://www.ncbi.nlm.nih.gov/pubmed/35206070 http://dx.doi.org/10.3390/foods11040594 |
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