Warm nights drive Coffea arabica ripening in Tanzania
Autor: | Laurence Jassogne, Alessandro Craparo, P.J.A. van Asten, Stefan W. Grab, Peter Läderach |
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Rok vydání: | 2020 |
Předmět: |
030203 arthritis & rheumatology
Driving factors Atmospheric Science 010504 meteorology & atmospheric sciences Ecology Harvest season Phenology Health Toxicology and Mutagenesis Coffea arabica Climate change Ripening Growing degree-day Nocturnal Biology 01 natural sciences 03 medical and health sciences Horticulture 0302 clinical medicine 0105 earth and related environmental sciences |
Zdroj: | International Journal of Biometeorology. 65:181-192 |
ISSN: | 1432-1254 0020-7128 |
DOI: | 10.1007/s00484-020-02016-6 |
Popis: | 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 (Tnight), 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 R2 = 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. |
Databáze: | OpenAIRE |
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