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
Studies have demonstrated that plant phenophases (e.g. budburst, flowering, ripening) are occurring increasingly earlier in the season across diverse ecologies globally. Despite much interest that climate change impacts have on coffee (Coffea arabica), relatively little is known about the driving factors determining its phenophases. Using high-resolution microclimatic data, this study provides initial insights on how climate change is impacting C. arabica phenophases in Tanzania. In particular, we use generalized additive models to show how warming nocturnal temperatures (T), as opposed to day-time or maximum temperatures, have a superseding effect on the ripening of coffee and subsequent timing of harvest. A warm night index (WNI), generated from mean nocturnal temperature, permits accurate prediction of the start of the harvest season, which is superior to existing methods using growing degree days (GDD). The non-linear function indicates that a WNI of 15 °C is associated with the latest ripening coffee cherries (adjusted R = 0.95). As the WNI increases past the inflection point of ~ 16 °C, ripening occurs earlier and progresses more or less linearly at a rate of ~ 17 ± 1.95 days for every 1 °C increase in WNI. Using the WNI will thus not only allow farmers to more accurately predict their harvest start date, but also assist with identifying the most suitable adaptation strategies which may reduce harvest-related costs and buffer potential losses in quality and production.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1007/s00484-020-02016-6 | DOI Listing |
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