Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 144
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 144
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 212
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3106
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
Increased adoption of improved agricultural technologies is considered an essential step to address global poverty and hunger, and agronomic trials suggest intensification in developing countries could result in large yield gains. Yet the promise of new technologies does not always carry over from trials to real-life conditions, and diffusion of many technologies remains limited. We show how parcel and farmer selection, together with behavioural responses in agronomic trials, can explain why yield gain estimates from trials may differ from the yield gains of smallholders using the same inputs under real-life conditions. We provide quantitative evidence by exploiting variation in farmer selection and detailed data collection from research trials in Western Kenya on which large yield increments were observed from improved input packages for maize and soybean. After adjusting for selection, behavioural responses, and other corrections, estimates of yield gains fall to being not significantly different from zero for the input package tested on one of the crops (soybean), but remain high for the other (maize). These results suggest that testing new agricultural technologies in real-world conditions and without researcher interference early in the agricultural research and development process might help with identifying which innovations are more likely to be taken up at scale.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7459313 | PMC |
http://dx.doi.org/10.1038/s41598-020-71155-y | DOI Listing |
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