Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&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
Genetic evaluations in beef cattle have evolved over the past 50 years relative to the hardware or software used, the statistical methodology underpinning them, and the traits evaluated. However, the underlying premise has remained the same; to generate predictions of genetic merit such that selection decisions can be made that materialize as phenotypic changes in commercial animals. The wide-spread availability and adoption of genomic technology has enabled more accurate genetic predictions of young animals albeit with the requirement of continual collection and reporting of phenotypic data.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.cvfa.2024.05.002 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!