RESUMEN
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.
Asunto(s)
Coffea , Cambio Climático , Café , Tanzanía , TemperaturaRESUMEN
Stomatal regulation is a key process in the physiology of Coffea arabica (C. arabica). Intrinsically linked to photosynthesis and water relations, it provides insights into the plant's adaptive capacity, survival and growth. The ability to rapidly quantify this parameter for C. arabica under different agroecological systems would be an indispensable tool. Using a Flir E6 MIR Camera, an index that is equivalent to stomatal conductance (Ig) was compared with stomatal conductance measurements (gs) in a mature coffee plantation. In order to account for varying meteorological conditions between days, the methods were also compared under stable meteorological conditions in a laboratory and Ig was also converted to absolute stomatal conductance values (g1). In contrast to typical plant-thermography methods which measure indices once per day over an extended time period, we used high resolution hourly measurements over daily time series with 9 sun and 9 shade replicates. Eight daily time series showed a strong correlation between methods, while the remaining 10 were not significant. Including several other meteorological parameters in the calculation of g1 did not contribute to any stronger correlation between methods. Total pooled data (combined daily series) resulted in a correlation of ρ=0.66 (P≤2.2e-16), indicating that our approach is particularly useful for situations where absolute values of stomatal conductance are not required, such as for comparative purposes, screening or trend analysis. We use the findings to advance the protocol for a more accurate methodology which may assist in quantifying advantageous microenvironment designs for coffee, considering the current and future climates of coffee growing regions.