Systematic agronomic farm management for improved coffee quality

Läderach, Peter; Oberthür, Thomas; Cook, Simon; Iza, Marcela Estrada; Pohlan, Jürgen; Fisher, Myles J.; Lechuga, Raul Rosales

doi:10.1016/j.fcr.2010.10.006

Cited by 55 publications

(51 citation statements)

References 21 publications

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“…With coffee-growing altitudes ranging from 1000 masl to over 2000 masl, the Mt. Elgon region can be used as a field laboratory to anticipate climate change and evaluate its impact on coffee, as suitable areas will shift upwards with time (Bunn et al 2015a, b;Läderach et al 2011).…”

Section: Introductionmentioning

confidence: 99%

Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda

et al. 2017

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Arabica coffee (Coffea arabica) is economically important for many smallholder farmers in the Mount Elgon region of East Uganda, but its production is increasingly threatened by climate change. However, ecosystem services (ES) provided by companion trees in coffee agroforestry systems (AFS) can help farmers adapt to climate change. The objectives of this research were to develop agroforestry species recommendations and tailor these to the farmers' needs and local context, taking into consideration gender. Local knowledge of agroforestry species and ES preferences was collected through farmer interviews and rankings. Using the Bradley-Terry approach, analysis was done along an altitudinal gradient in order to study different climate change scenarios for coffee suitability. Farmers had different needs in terms of ES and tree species at different altitudes, e.g. at low altitude they need a relatively larger set of ES to sustain their coffee production and livelihood. Local knowledge is found to be gender blind as no differences were observed in the rankings of species and ES by men and women. Ranking species by ES and ranking ES by preference is a useful method to help scientists and extension agents to use local knowledge for the development of recommendations on companion trees in AFS for smallholder farmers.

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Section: Introductionmentioning

confidence: 99%

Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda

et al. 2017

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“…The concept of specialty coffee is broad and involves characteristics such as superior beverage quality, rare varieties, and location of cultivation but also can be related to ecological, economic, or social sustainability [2]. Still, coffee quality is the result of complex interactions between the environment, management, and plant genetics [3].…”

Section: Introductionmentioning

confidence: 99%

Shade Trees Spatial Distribution and Its Effect on Grains and Beverage Quality of Shaded Coffee Trees

Neto

Morinigo

Guimarães

et al. 2018

Journal of Food Quality

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Shading coffee trees has gained importance, especially among smallholders, as an option to improve the products' quality, therefore acquiring place at the specialty coffee market, where consumers are willing to give bonus for quality. This work aims to evaluate the influence of shade trees' spatial distribution among coffee trees' agronomic characteristics, yield, and beans and cup quality of shaded coffee trees. The experimental design consisted of completely randomized blocks with six repetitions and four treatments: coffee trees on shade trees planting rows, distant one meter from the trunk; coffee trees on shade trees planting row, distant six meters from the trunk; and coffee plants between the rows of shade trees, parallel to the previous treatments. The parameters analyzed were plant height, canopy diameter, plagiotropic branches' length, yield, coffee fruits' phenological stage, ripe cherries' Brix degree, percentage of black, unripe, and insect damaged beans, bean size, and beverage quality. Shade trees quickened coffee fruits' phenological stage of coffee trees nearest to them. This point also showed the best beverage quality, except for overripe fruits. The remaining parameters evaluated were not affected by shade trees' spatial distribution.

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“…Shade level , fertilizer rates (Clemente et al 2015;Lara-Estrada and Vaast 2007) and genotypic differences (Avelino et al 2005;Bertrand et al 2006 ; Leroy et al 2006) are also among the major factors affecting tree growth, productivity and coffee bean quality. Agronomical measures like pruning and fruit thinning Cagliani et al 2013;Läderach et al 2011;Vaast et al 2006) and soil physical and chemical characteristics (Behailu et al 2008;Bosselmann et al 2009) were also reported to influence yield, physical and chemical properties of coffee beans.…”

Section: Factors That Determine Production and Quality Of Coffeementioning

confidence: 99%

“…Coffees with good quality from specific origins and with specific taste (i.e. 'terroir coffees') fetch higher prices than bulk bean lots (Avelino et al 2005;Läderach et al 2011). …”

Section: Introductionmentioning

confidence: 99%

“…Each of these attributes depends on factors such as shade level (Geromel et al 2008;Lara-Estrada and Vaast 2007;Muschler 2001;Vaast et al 2006), altitude (Avelino et al 2005;Bertrand et al 2006 ;Villarreal et al 2009), daily temperature (Bertrand et al 2012) and amount and distribution of rainfall (Silva et al 2005). Physical and chemical characteristics of the soil (Behailu et al 2008;Bosselmann et al 2009), fertilizers (Lara-Estrada and Vaast 2007), genotype and provenance (Avelino et al 2005;Belete et al 2014;Bertrand et al 2006 ;Leroy et al 2006;Oberthür et al 2011), agronomical measures like pruning and fruit thinning Läderach et al 2011;Vaast et al 2006) were also reported to influence coffee quality. Previous studies concluded that shade improves physical and organoleptic attributes via lowering air temperature, which in turn slows down the ripening process leading to enhanced accumulation of aroma precursors Joët et al 2010;Lara-Estrada and Vaast 2007;Vaast et al 2006).…”

Section: Introductionmentioning

confidence: 99%

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Examining growth, yield and bean quality of Ethiopian coffee trees : towards optimizing resources and tree management

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Systematic agronomic farm management for improved coffee quality

Cited by 55 publications

References 21 publications

Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda

Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda

Shade Trees Spatial Distribution and Its Effect on Grains and Beverage Quality of Shaded Coffee Trees

Examining growth, yield and bean quality of Ethiopian coffee trees : towards optimizing resources and tree management

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