Physiological and Agronomic Performance of the Coffee Crop in the Context of Climate Change and Global Warming: A Review

DaMatta, Fábio M.; Ávila, Rodrigo T.; Cardoso, A. A.; Martins, Samuel C. V.; Ramalho, José C.

doi:10.1021/acs.jafc.7b04537

Cited by 135 publications

(111 citation statements)

References 98 publications

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“…Concerning the precipitation levels, the precipitation in 2014 was much lower than expected, according to the historical mean. The water potential is a crucial water relation parameter that describes the energy state of water; low Cw is associated with the extent of plant dehydration [31]. Therefore, according to the values of Cw, the region has favorable climatic conditions to maintain coffee hydration, but the occurrence of low rainfall in 2014 resulted in a moderate water deficit to the plants.…”

Section: Variability Of Remote Sensing Ph and Precipitation For Thementioning

confidence: 99%

Leaf water potential of coffee estimated by landsat-8 images

et al. 2020

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Traditionally, water conditions of coffee areas are monitored by measuring the leaf water potential (Ψ W) throughout a pressure pump. However, there is a demand for the development of technologies that can estimate large areas or regions. In this context, the objective of this study was to estimate the Ψ W by surface reflectance values and vegetation indices obtained from the Landsat-8/OLI sensor in Minas Gerais-Brazil Several algorithms using OLI bands and vegetation indexes were evaluated and from the correlation analysis, a quadratic algorithm that uses the Normalized Difference Vegetation Index (NDVI) performed better, with a correlation coefficient (R 2) of 0.82. Leave-One-Out Cross-Validation (LOOCV) was performed to validate the models and the best results were for NDVI quadratic algorithm, presenting a Mean Absolute Percentage Error (MAPE) of 27.09% and an R 2 of 0.85. Subsequently, the NDVI quadratic algorithm was applied to Landsat-8 images, aiming to spatialize the Ψ W estimated in a representative area of regional coffee planting between September 2014 to July 2015. From the proposed algorithm, it was possible to estimate Ψ W from Landsat-8/OLI imagery, contributing to drought monitoring in the coffee area leading to cost reduction to the producers.

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Section: Variability Of Remote Sensing Ph and Precipitation For Thementioning

confidence: 99%

Leaf water potential of coffee estimated by landsat-8 images

et al. 2020

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“…Finding cultivars that can adapt to different environments and present stable and high quality production has become a priority for breeders, especially given the current climate change predictions (Damatta et al 2018). Therefore, it is necessary to evaluate how the genotype and environment interaction (G 9 E) affects agronomic performance and coffee quality.…”

Section: Introductionmentioning

confidence: 99%

G × E interactions on yield and quality in Coffea arabica: new F1 hybrids outperform American cultivars

et al. 2020

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Conventional American cultivars of coffee are no longer adapted to global warming. Finding highly productive and stable cultivars in different environments without neglecting quality characteristics has become a priority for breeders. In this study, new Arabica F1 hybrids clones were compared to conventional American varieties in seven contrasting environments, for yield, rust incidence and volume of the canopy. The quality was assessed through size, weight of 100 beans, biochemical analysis (24 aroma precursors and 31 volatiles compounds) and sensory analysis. Conventional varieties were the least productive, producing 50% less than the best hybrid. The AMMI model analysis pointed out five hybrids as the most stable and productive. Two F1 hybrids clones, H1-Centroamericano and H16-Mundo Maya, were superior to the most planted American cultivar in Latin and Central America showing a high yield performance and stability performance. H1-Centroamerica and Starmaya contain more D-limonene than Caturra, while Starmaya contain more 3-methylbutanoic acid than the control. Those two latter volatiles compounds are linked with good cup quality in previous studies. In terms of sensory analysis, Starmaya and H1-Centroamericano scored better than control.

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“…Furthermore, Arabica coffee is generally grown under rainfed conditions. Given this reliance on rainfall, growth and yield of C. arabica can be affected by water stress caused by a shortage of water in the soil (Baca et al, 2014;DaMatta et al, 2018;Meinzer et al, 1992;Wang et al, 2015). In terms of climatic control, the amount of soil water available for crop use depends on the balance between rainfall and evapotranspiration (ET; Monteith & Moss, 1977).…”

Section: 1029/2018jg004911mentioning

confidence: 99%

Soil Evaporation in a Shaded Coffee Plantation Derived From Eddy Covariance Measurements

Holwerda

Meesters

2019

JGR Biogeosciences

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Little is known about soil evaporation (Esoil) in shaded coffee plantations. In this study, Esoil and its proportion to total evapotranspiration and rainfall (P) were quantified for a densely shaded Arabica coffee plantation (~80% tree cover) in central Veracruz, Mexico, using eddy covariance (EC) measurements made above the tree canopy and at the boundary between the stem space and canopy of the coffee crop. While measurements above the canopy were made continuously during the 1‐year study period (October 2016 to September 2017), this was not possible for the above‐soil level due to logistical considerations, and hence, annual Esoil was calculated from a relationship between the ratio of the actual to the equilibrium Esoil and surface soil water content. This empirical model was calibrated using 31 days of EC measurements, representing the range in surface soil water content observed during the study period. Examining the above‐canopy and above‐soil EC measurements for quality yielded similar results with regard to stationarity (99% and 85% of the time, respectively) and degree of energy balance closure (81% and 96%, respectively). The permanent and relatively dense vegetation cover provided by the shade trees and coffee plants reduced net radiation at the soil surface to only about 12% of the above‐canopy value. Consequently, Esoil was a minor fraction of evapotranspiration (10–13%) and P (8–9%), with the spread reflecting uncertainties related to the failure to close the energy balance. In addition to the low‐energy availability, Esoil may have been reduced by the presence of a litter layer.

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Physiological and Agronomic Performance of the Coffee Crop in the Context of Climate Change and Global Warming: A Review

Cited by 135 publications

References 98 publications

Leaf water potential of coffee estimated by landsat-8 images

Leaf water potential of coffee estimated by landsat-8 images

G × E interactions on yield and quality in Coffea arabica: new F1 hybrids outperform American cultivars

Soil Evaporation in a Shaded Coffee Plantation Derived From Eddy Covariance Measurements

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