Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
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).
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8871229 | PMC |
http://dx.doi.org/10.3390/foods11040594 | DOI Listing |
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