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
In the context of data management and processing, food science needs tools to organize the results of diverse studies to make the data reusable. In sensory analysis, there are no classification or wheel of textural attributes that can be used to interpret the results of sensory studies. Research from the literature and databases was used to elaborate a list of attributes related to texture. With the help of a group of experts in food texture, work on these attributes and the related concepts was conducted to classify them into several categories, including intensity levels. The classification was represented as a texture wheel, completed by a generic lexicon of definitions of texture concepts. The work can be useful as a reference in texture attributes related to foods, and thanks to implementation in a general ontology based on food processing and observation, it can help query and interpret texture-related results from sensory studies.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9562153 | PMC |
http://dx.doi.org/10.3390/foods11193097 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!