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: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
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
Remote sensing technology offers an opportunity to significantly increase the amount of site-specific information about field characteristics such as pest populations. Coupled with variable rate application technologies, this added information has the potential to provide environmental benefits through reduced pesticide applications. However, producers face a complicated adoption decision because output prices and crop yields are uncertain. A model is developed to examine the potential value of remote sensing information to pesticide applications in an option-value framework under uncertainty. Simulations suggest that remote sensing information could decrease pesticide use, but uncertainty and irreversibility are likely to limit technological adoption by farmers. Potential cost-share subsidies are discussed.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1016/j.jenvman.2005.01.024 | DOI Listing |
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