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Abstract

Coffea canephora (Robusta coffee) is the most heat tolerant and ‘robust’ coffee species and therefore considered more resistant to climate change than other types of production coffee. However, the optimum production range of Robusta has never been quantified, with current estimates of its optimal mean annual temperature range (22‐30 °C) based solely on the climatic conditions of its native range in the Congo basin, Central Africa. Using 10 years of yield observations from 798 farms across South East Asia coupled with high‐resolution precipitation and temperature data we used hierarchical Bayesian modelling to quantify Robusta’s optimal temperature range for production. Our climate based models explained yield variation well across the study area with a cross‐validated mean R2 = 0.51. We demonstrate that Robusta has an optimal temperature below 20.5 °C (or a mean minimum / maximum of ≤ 16.2/24.1 °C), which is markedly lower, by 1.5 – 9 °C than current estimates. In the middle of Robusta’s currently assumed optimal range (mean annual temperatures over 25.1 °C), coffee yields are 50% lower compared to the optimal mean of ≤ 20.5 °C found here. During the growing season every 1 °C increase in mean minimum/maximum temperatures above 16.2/24.1 °C corresponded to yield declines of ~14% or 350‐460 kg/ha (95% credible interval). Our results suggest that Robusta coffee is far more sensitive to temperature than previously thought. Current assessments, based on Robusta having an optimal temperature range over 22 °C, are likely overestimating its suitable production range and its ability to contribute to coffee production as temperatures increase under climate change. Robusta supplies 40% of the world’s coffee, but its production potential could decline considerably as temperatures increase under climate change, jeopardizing a multi‐billion dollar coffee industry and the livelihoods of millions of farmers.

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... In fact, current opinion suggests that the Robusta optimum mean annual temperature ranges from 22 to 26 ºC (Matiello, 1998) or even up to 30°C (Willson, 1999). However, a recent study has challenged this claim and suggested that the purported heat tolerance of Robusta plants could have been greatly overestimated (Kath et al., 2020). These authors used a large dataset collected over 10 years from 798 farms across Southeast Asia, encompassing farms with varying use of inputs and bean yields ranging from 0.04 to 5.0 tonnes ha −1 (mean yield = 2.05 ± 0.96 tonnes ha −1 ). ...
... For example, in South Bahia State, where the highest Brazilian Robusta yields are recorded (3.32 tonnes ha −1 over the 2020-2023 period (CONAB, 2024)), the average annual temperature is ca. 24.5°C (or minimum/maximum of 21.3/28°C), which is nearly 4°C above the optimum considered by Kath et al. (2020). Recently, Partelli et al. (2021) have launched a Robusta cultivar (composed by six clones) specifically recommended to Bahia state yielding 7.8 tonnes ha −1 averaged over the first four harvests, with one clone yielding, in one harvest, 13.0 tonnes ha −1 . ...
... Additionally, the presumably higher heat tolerance of Robusta coffee in Brazil may be linked to the higher averaged use of inputs (e.g., irrigation, fertilisation) than in Southeast Asia, allowing a better plant endurance to warmer conditions. To reconcile our observations with the findings of Kath et al. (2020), we suggest that the optimum temperature for Robusta growth and production would range from approximately 20 to 26°C. Such a relatively broad range seems to be consistent with the wide genetic diversity within C. canephora (Bertrand et al., 2024;Partelli et al., 2022) and the varying use of inputs across the Robusta-producing countries. ...
Chapter
The global coffee market is circumscribed to two species, Coffea arabica (aka. Arabica coffee) and C. canephora (aka. Robusta coffee), which account for ca. 99% of coffee production. Both species exhibit fragility to the perils of ongoing climate changes, with exacerbation of these conditions expected over the years to come. Supra-optimal temperatures and drought are the major environmental stresses impacting coffee growth and production, especially under full sunlight conditions. By contrast, growing evidence suggests that elevated atmospheric [CO2] could (at least partially) mitigate the damages caused to coffee plants by warming and droughts. Moreover, the positive effects of enhanced [CO2] on coffee photosynthesis and yields are suggested to be greater under moderate to high solar irradiances. Here, we explore (i) the role of photosynthetic gas exchanges as a key physiological driver on coffee production in a climate change context; (ii) the ecophysiological responses of shaded and unshaded coffee plantations to compare and contrast shade benefits and drawbacks in the coming years (highlighting the use of particle films as an agronomic management strategy to reduce solar energy loads); (iii) the present and forthcoming aspects associated with the coffee production, emphasising the positive role of rising atmospheric [CO2] in boosting coffee yields; (iv) some morpho-physiological aspects linked to the overall superior yield performance of Robusta to that of Arabica coffee; and finally (v) provide some guidance on the optimum temperature range for coffee production.
... This was perceived as particularly important for C. arabica, which is globally considered inherently more sensitive to heat, drought, pests, and diseases than C. canephora [36]. Yet, recent studies claim that C. canephora bean productivity and quality are also highly sensitive to high temperatures and low rainfall availability [37,38], making these issues more important than initially assumed regarding the two main producing species. ...
... Coffea genotypes usually have a limited optimal temperature range, with most C. arabica genotypes having an ideal annual mean temperature between 18 and 23 °C, while in C. canephora, this range is higher (22-30 °C) [36]. Recent studies suggest that high temperatures might have strong impacts on C. arabica production [37,40], especially under full sunlight exposure [34]. Likewise, C. canephora was recently suggested to be more sensitive to global warming than previously thought, with reports that every 1 °C increase in mean minimum/maximum temperatures above approx. ...
... Likewise, C. canephora was recently suggested to be more sensitive to global warming than previously thought, with reports that every 1 °C increase in mean minimum/maximum temperatures above approx. 24 °C can lead to yield declines of ~14% or 350-460 kg ha −1 [37]. However, despite the relevant sensitivity of most Coffea genotypes to environmental constraints, the study of elite cultivars has been quite overlooked, although some of them (as the ones studied here) can present strong intrinsic resilience to harsh conditions of water restriction and high temperatures, well above commonly believed [11,39,41]. ...
Article
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Increasing exposure to unfavorable temperatures and water deficit imposes major constraints on most crops worldwide. Despite several studies regarding coffee responses to abiotic stresses, transcriptome modulation due to simultaneous stresses remains poorly understood. This study unravels transcriptomic responses under the combined action of drought and temperature in leaves from the two most traded species: Coffea canephora cv. Conilon Clone 153 (CL153) and C. arabica cv. Icatu. Substantial transcriptomic changes were found, especially in response to the combination of stresses that cannot be explained by an additive effect. A large number of genes were involved in stress responses, with photosynthesis and other physiologically related genes usually being negatively affected. In both genotypes, genes encoding for protective proteins, such as dehydrins and heat shock proteins, were positively regulated. Transcription factors (TFs), including MADS-box genes, were down-regulated, although responses were genotype-dependent. In contrast to Icatu, only a few drought- and heat-responsive DEGs were recorded in CL153, which also reacted more significantly in terms of the number of DEGs and enriched GO terms, suggesting a high ability to cope with stresses. This research provides novel insights into the molecular mechanisms underlying leaf Coffea responses to drought and heat, revealing their influence on gene expression.
... For example, Martins et al. (2019) described high flexibility among C. canephora genotypes, with good performance in alternative environments, which includes low temperatures and high altitudes. In sharp contrast, Kath et al. (2020) have argued that C. canephora production is highly sensitive to temperature, suggesting that the species may not attain the necessary requisites for a climate-resilient crop. ...
... With global evidence of climate change, several initiatives are projecting the future of coffee cultivars. Recently, Kath et al. (2020) reported a climate-based model to associate yield performance as a function of temperature and rainfall in C. canephora. Using a historical dataset, one of the key conclusions is that Robusta coffee is highly sensitive to temperature, a fact that makes the species vulnerable and hence not ideal for future climateresilient coffee. ...
... To gain further biological interpretations, we tested the association between yield as a function of environmental factors (temperature and rainfall). Contrasting to the results reported by Kath et al. (2020), we could infer that Robusta/Conilon genotypes respond differently to variations in temperature. For example, the genotype CC8 shows a positive slope, indicating a good response on yield performance when the temperature increases. ...
Article
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Coffee is an important crop with economic and social importance in several countries. With a daily consumption estimated at 2.2 billion cups, its sustainability is facing critical challenges given the projected climate changes. Coffea arabica, which represents ∼60% of the global market coffee is a delicate crop, quite susceptible to diseases and biotic stresses. Developing climate‐resilience cultivars is necessary, and it includes coffee plants adapted to new farming conditions that can meet the demand for biotic and abiotic tolerance and quality. In this context, Coffea canephora emerges as a potential candidate if the crop combines plasticity and cupping quality. Plant plasticity refers to adjusted phenotypic performance when grown in different environments, a fact that may help mitigate the detrimental effect of climate changes. In this study, using a multiple environment trial, we combined genomic and genotype‐by‐environment analyses to answer the following main question: How the climate effects may affect the phenotypic plasticity in C. canephora? Our contributions in this paper are fourfold: (i) we draw attention to the cupping quality and yield performance of C. canephora cultivars when evaluated in high‐altitude and cold weather, (ii) we compared C. arabica and C. canephora phenotypic plasticity and highlight genotypes with broad and specific adaptation to certain environmental conditions, and finally, (iii) using stochastic simulation, we emphasize the potential of molecular breeding in the long term in coffee. Altogether, we present an emerging view on how C. canephora could be a valid alternative for climate‐smart cultivars in a projected scenario of altered climatic conditions.
... Climate change substantially threatens Tanzania's ambitious coffee production plans, as alterations in temperature and precipitation patterns impact the success of coffee cultivation (Kath et al., 2020). Recent studies demonstrate that Tanzania's temperature has increased, and rainfall has decreased in recent decades (Chang'a et al., 2017;Gebrechorkos et al., 2019;Muthoni et al., 2019). ...
... This is concerning because changes in temperature and precipitation levels and variability can lead to declining yields and increased severity and spread of coffee pests and diseases (Mbwambo et al., 2022;Wagner et al., 2021). Notably, rising minimum temperatures are considered a crucial factor for yield reduction in coffee production (Craparo et al., 2015(Craparo et al., , 2021aKath et al., 2020). The increase in minimum temperature above 1 • C is projected to lead to Arabica yield decline of about 137 ± 16.87 kg/ha in 2060 in Tanzania (Craparo et al., 2015). ...
... Similarly, at annual mean temperatures above 23 • C, coffee trees cannot produce quality coffee (Craparo et al., 2015). Precipitation is also an important factor, and excessive rainfall during the flowering season may hinder flower-bud formations, leading to yield loss (Kath et al., 2020). ...
... This species of coffee is more tolerant to heat and is more resistant to climate change. Its optimal production range is estimated with an average annual temperature between 20 and 30 °C (Magrach and Ghazoul 2015;Kath et al. 2020;Venancio et al. 2020). However, there are few studies on C. canephora in the face of climate change. ...
... In the study by Partelli et al. (2013), it was observed that the growth rate of branches of C. canephora was drastically reduced in all genotypes studied at temperatures below 17.2 °C. For Kath et al. (2020) C. canephora shows significant productivity losses at temperatures below 15.8 °C. Robusta is productive with temperatures ranging from 20 to 30 °C (Magrach and Ghazoul 2015;Kath et al. 2020;Venancio et al. 2020). ...
... For Kath et al. (2020) C. canephora shows significant productivity losses at temperatures below 15.8 °C. Robusta is productive with temperatures ranging from 20 to 30 °C (Magrach and Ghazoul 2015;Kath et al. 2020;Venancio et al. 2020). The maximum average temperature indicated as a limit for the growth of C. canephora must be below 33 °C (Covre et al. 2016;Dubberstein et al. 2017). ...
Article
Coffee is a crucial crop for the economy of several countries. It contributes substantially to the livelihoods of millions of small producers worldwide. Coffea canephora represents 40% of the world's production of beans. Coffea canephora is a perennial crop, it is sensitive to climate, and several production areas in Brazil may become unfit for C. canephora cultivation due to expected climate change. Thus, knowledge of the temporal dynamics of favorable climate conditions for C. canephora in Brazil is necessary. This work aims to elaborate the CLIMEX model to predict the climatic suitability for C. canephora in Brazil in the current climate and front of climate changes for 2030, 2050, 2070, and 2100. The model shows a good agreement between the density and the growth rate of the species, which indicates significant reliability of the results in the proposed model. Our modeling results show that there has been a reduction in the areas very favorable to C. Canephora over the years, in the North, Southeast, and the entire east coast of the Northeast regions. Compared to the current scenario, the model projection reduces by 49, 73, 82, and 88% in 2030, 2050, 2070, and 2100, respectively. The results may help long-term planning strategies to mitigate the economic effects of the climate change scenario on C. canephora production in Brazil.
... The appropriate scale at which to describe the impact of climate on coffee under the scope of varying CAFS set-ups needs, therefore, explicit investigation. When assessing climate risks and climate change impacts on coffee, studies have mostly focused on either the suitability of land areas for coffee production 2,16,26 or the assessment of potential coffee yield under projected climate conditions 4,27,28 , the exposure and vulnerability of coffee-producing regions to changes in climate hazards 29 or the proportion of variation in coffee yield explained by climate predictors (i.e., rainfall and temperature) 30,31 . However, the risks associated with climate variability at different spatial scales in CAFS under various management practices have yet to be fully investigated. ...
... At different scales, climate risks such as excess or deficit rainfall, dry spells or frosts, may differ depending on the topographical characteristics and the management practices that dominate the CAFS. If climate impacts vary considerably between scales, i.e., the particular climate driver(s) most important for yield vary, then extrapolating findings from global and country-level studies 2,4,9,31 may have limited utility for informing smaller farm-scale climate adaptation responses. Likewise, smaller experimental and farm-scale studies 32 may not be relevant for understanding the larger scale regional and global impacts of climate change. ...
... At the regional scale (pooled data for all three districts), post-flowering maximum temperature was selected as the best variable explaining the variability in robusta coffee yield, with lower maximum temperatures being associated with higher yields. These results concur with previous findings indicating that high temperatures adversely impact robusta coffee yield 7,31,46,47 . Bud development and berry filling, two key yield determinants in coffee yield, can be drastically and negatively affected under high temperature conditions 7,46 , which may explain the relationships observed in this study. ...
Article
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Agroforestry is a management strategy for mitigating the negative impacts of climate and adapting to sustainable farming systems. The successful implementation of agroforestry strategies requires that climate risks are appropriately assessed. The spatial scale, a critical determinant influencing climate impact assessments and, subsequently, agroforestry strategies, has been an overlooked dimension in the literature. In this study, climate risk impacts on robusta coffee production were investigated at different spatial scales in coffee-based agroforestry systems across India. Data from 314 coffee farms distributed across the districts of Chikmagalur and Coorg (Karnataka state) and Wayanad (Kerala state) were collected during the 2015/2016 to 2017/2018 coffee seasons and were used to quantify the key climate drivers of coffee yield. Projected climate data for two scenarios of change in global climate corresponding to (1) current baseline conditions (1985–2015) and (2) global mean temperatures 2 °C above preindustrial levels were then used to assess impacts on robusta coffee yield. Results indicated that at the district scale rainfall variability predominantly constrained coffee productivity, while at a broader regional scale, maximum temperature was the most important factor. Under a 2 °C global warming scenario relative to the baseline (1985–2015) climatic conditions, the changes in coffee yield exhibited spatial-scale dependent disparities. Whilst modest increases in yield (up to 5%) were projected from district-scale models, at the regional scale, reductions in coffee yield by 10–20% on average were found. These divergent impacts of climate risks underscore the imperative for coffee-based agroforestry systems to develop strategies that operate effectively at various scales to ensure better resilience to the changing climate.
... This climate data was also extracted for the 798 robusta farms we have ten years of yield data for , and which was the basis of our productivity model (see below). Climate variables were extracted for the flowering and growing season each year as this is when production is most sensitive to climatic variability (Craparo et al. 2015;Kath et al. 2020). To deal with potential collinearity between climate variables we assessed predictor collinearity using Pearson correlations, setting a threshold of |r|< 0.70 (Dormann et al. 2013). ...
... The phenological data sets of Taluma, Turipaná, and El Mira research centers in Colombia were used to create a phenological calendar. Climate variables were adjusted to this phenological calendar and used as input to the regression model of robusta yield response to climate adapted from Kath et al. (2020). That study identified four key climate predictors, (1) minimum growing season temperature, (2) minimum flowering season temperature, (3) total growing season rainfall, and (4) total flowering season rainfall as the key climate predictors of robusta coffee yield in South East Asia, based on the Watanabe-Akaike's Information Criteria (WAIC) and the deviation information criterion (DIC) for model selection (see Kath et al. 2020 for model selection and performance details ofthe productivity model). ...
... Climate variables were adjusted to this phenological calendar and used as input to the regression model of robusta yield response to climate adapted from Kath et al. (2020). That study identified four key climate predictors, (1) minimum growing season temperature, (2) minimum flowering season temperature, (3) total growing season rainfall, and (4) total flowering season rainfall as the key climate predictors of robusta coffee yield in South East Asia, based on the Watanabe-Akaike's Information Criteria (WAIC) and the deviation information criterion (DIC) for model selection (see Kath et al. 2020 for model selection and performance details ofthe productivity model). ...
Article
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Meeting future demand for coffee under climate change is a challenge. Approaches that can inform where coffee may grow best under current and future climate scenarios are needed. Robusta coffee (Coffea canephora P.) is planted in many tropical areas and makes up around 40% of the world’s coffee supply. However, as the climate shifts, current robusta areas may become less productive, while in other areas new growing regions for robusta may emerge. Colombia is one of the world’s most important Arabica coffee producer, famous for its high-quality coffee. Although robusta coffee is not yet a commercial crop in Colombia, it could be one of the future bastions for robusta coffee in South America contributing to meeting the increasing demand, but this remains unexplored. We aimed to identify areas with highest biophysical and socio-economic potential to grow robusta coffee in Colombia. An integrated modelling approach was used, combining climate suitability and crop-yield modelling for current and future climate scenarios, soil constraints, pest risk assessment and socio-economic constraints to identify the regions with the highest potential productivity and the lowest pest and climate change risks with good market access and low security risks which don’t further expand the agricultural frontier. Our results showed that parts of the foothills along the eastern Andean Mountain ranges, the high plains of the Orinoquía region and the wet parts of the Caribbean region are the best candidates for the potential development of robusta coffee plantations in Colombia. The crop-yield model indicated highest yields of green coffee on the foothills of the eastern Andean Mountain range with an estimated average yield of 2.6 t ha⁻¹ (under rain-fed conditions) which is projected to occur at elevations below 600 m avoiding interference with the traditional and established Arabica coffee regions in Colombia. Under a 2 °C global warming scenario climate change is projected to have the largest impacts on the Caribbean region. Therefore, larger scale irrigated production system could be an appropriate option in the Caribbean region, while diversified smallholder robusta coffee agroforestry systems are considered more favourable in the Orinoquía region.
... The other way that climate affects coffee cultivation is through the impacts of inter-annual variability on the annual production cycle and on yields (as opposed to suitability studies, which are based on the presence and/or absence of coffee farms). During any given year, climate hazards such as heatwaves, droughts, frosts and floods can each affect coffee yield [8][9][10][11][12][13][14]. Sub-optimal temperatures and precipitation deficits have negative effects on yield and bean quality, and climate acts as a control on pests and diseases [5]. The timing is also important, as the vulnerability of coffee to climate variables changes depending on the stage of the plant's life cycle [8,15]. ...
... These failures are characterised by large-scale yield deficits, and can arise as a result of widespread, spatially compounding climate anomalies [16][17][18][19][20]. For coffee productivity, however, the impacts of climate variability are typically analysed on national or regional spatial scales [5,8,10,13,14]. On a global scale, the historical variability and changes in the frequency of spatially compounding events that affect coffee production is unknown. ...
... We estimated the flowering and growing (i.e. cherry and fruit development) seasons for each country based on the literature [13,[40][41][42][43]. ...
Article
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Global coffee production is at risk from synchronous crop failures, characterised by widespread concurrent reductions in yield occurring in multiple countries at the same time. For other crops, previous studies have shown that synchronous failures can be forced by spatially compounding climate anomalies, which in turn may be driven by large-scale climate modes such as the El Niño Southern Oscillation (ENSO). We provide a systematic analysis of spatially compounding climate hazards relevant to global coffee production. We identify 12 climate hazards from the literature, and assess the extent to which these hazards occur and co-occur for the top 12 coffee producing regions globally. We find that the number of climate hazards and compound events has increased in every region between 1980 and 2020. Furthermore, a clear climate change signature is evident, as the type of hazard has shifted from overly cool conditions to overly warm. Spatially compounding hazards have become particularly common in the past decade, with only one of the six most hazardous years occurring before 2010. Our results suggest that ENSO is the primary mode in explaining annual compound event variability, both globally and regionally. El Niño-like sea-surface temperatures in the Pacific Ocean are associated with decreased precipitation and increased temperatures in most coffee regions, and with spatially compounding warm and dry events. This relationship is reversed for La Niña-like signatures. The Madden Julian Oscillation also shows a strong association with climate hazards to coffee, with increased activity in the Maritime Continent related to a global increase in the number of cold or wet hazards and a decrease in the number of warm or dry hazards. With climate change projections showing a continued rise in temperatures in the tropics is likely, we suggest that coffee production can expect ongoing systemic shocks in response to spatially compounding climate hazards.
... The appropriate scale at which to describe the impact of climate on coffee under the scope of varying CAFS set-ups needs, therefore, explicit investigation. When assessing climate risks and climate change impacts on coffee, studies have mostly focused on either the suitability of land areas for coffee production 2,16,26 or the assessment of potential coffee yield under projected climate conditions 4,27,28 , the exposure and vulnerability of coffee-producing regions to changes in climate hazards 29 or the proportion of variation in coffee yield explained by climate predictors (i.e., rainfall and temperature) 30,31 . However, the risks associated with climate variability at different spatial scales in CAFS under various management practices have yet to be fully investigated. ...
... At different scales, climate risks such as excess or deficit rainfall, dry spells or frosts, may differ depending on the topographical characteristics and the management practices that dominate the CAFS. If climate impacts vary considerably between scales, i.e., the particular climate driver(s) most important for yield vary, then extrapolating findings from global and country-level studies 2,4,9,31 may have limited utility for informing smaller farm-scale climate adaptation responses. Likewise, smaller experimental and farm-scale studies 32 may not be relevant for understanding the larger scale regional and global impacts of climate change. ...
... At the regional scale (pooled data for all three districts), post-flowering maximum temperature was selected as the best variable explaining the variability in robusta coffee yield, with lower maximum temperatures being associated with higher yields. These results concur with previous findings indicating that high temperatures adversely impact robusta coffee yield 7,31,46,47 . Bud development and berry filling, two key yield determinants in coffee yield, can be drastically and negatively affected under high temperature conditions 7,46 , which may explain the relationships observed in this study. ...
... While bioclimatic suitability for robusta production is projected to decline altogether by some global studies, there is a general lack of large-scale research on the climatesensitive flowering and growth phases of robusta. Future research is required to determine its optimal temperature ranges more precisely to enhance yields [27,42]. These results may be attributable to the fact that most of the reviewed manuscripts were conducted on the American continent, where Arabica has the most extensive diffusion. ...
... While bioclimatic suitability for robusta production is projected to decline altogether by some global studies, there is a general lack of large-scale research on the climate-sensitive flowering and growth phases of robusta. Future research is required to determine its optimal temperature ranges more precisely to enhance yields [27,42]. ...
... Intriguingly, one manuscript done in the provinces of Indonesia and Vietnam (Southeast Asia) quantified robusta's optimal temperature range for production and showed it might present losses against climate change. The data indicated a decline in the production potential of Coffea canephora, placing a multibillion-dollar coffee industry and the livelihoods of millions of farmers at risk [42]. ...
Article
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Coffee production is fragile, and the Intergovernmental Panel on Climate Change (IPCC) reports indicate that climate change (CC) will reduce worldwide yields on average and decrease coffee-suitable land by 2050. This article adopted the systematic review approach to provide an update of the literature available on the impacts of climate change on coffee production and other ecosystem services following the framework proposed by the Millenium Ecosystem Assessment. The review identified 148 records from literature considering the effects of climate change and climate variability on coffee production, covering countries mostly from three continents (America, Africa, and Asia). The current literature evaluates and analyses various climate change impacts on single services using qualitative and quantitative methodologies. Impacts have been classified and described according to different impact groups. However, available research products lacked important analytical functions on the precise relationships between the potential risks of CC on coffee farming systems and associated ecosystem services. Consequently, the manuscript recommends further work on ecosystem services and their interrelation to assess the impacts of climate change on coffee following the ecosystem services framework.
... C. canephora shows greater tolerance compared to Arabica, occupying ecological niches with temperatures ranging from 22 • C to 30 • C. However, it has been Proceedings 2024, 109, 23 2 of 6 established that the optimal growth temperature for Robusta is 20 • C, and temperature variations of 1 • C below or above a range of 16-24 • C result in a significant production loss (14%) [5]. ...
... Arabica, occupying ecological niches with temperatures ranging from 22 °C to 30 °C. However, it has been established that the optimal growth temperature for Robusta is 20 °C, and temperature variations of 1 °C below or above a range of 16-24 °C result in a significant production loss (14%) [5]. With global changes, a reduction of nearly 50% in the cultivated coffee area is projected by 2050 [3]. ...
... This can be explained scientifically that aroma is a volatile compound. Brewing using hot water is able to provide heat that can vaporize these compounds to create a fragrant aroma (Kath et al., 2020). The act of closing the container traps the aroma compounds in the container. ...
... To maintain the aroma of coffee and tea, it can be stored in cool conditions and in a closed container (Moldevaer, 2021). Also, when brewing, you should use hot water, this can give the fragrant aroma of coffee and tea a stronger flavor (Kath et al., 2020). Meanwhile, when using cold water, coffee and tea do not give a strong aroma. ...
Article
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Environmental literacy is one of the keys to support the success of sustainable development goals (SDGs). This research aims to develop an inquiry e-module with an ethno-STEM approach to the concept of volatile aromatic compounds. The research subjects involved 46 students in the chemistry education study program who took the course on organic chemistry of natural substances. Data collection was carried out using an environmental literacy questionnaire covering four domains (knowledge, cognitive skills, attitudes and behavior). The results showed that the validity of e-modules in terms of material and media was 82.5% and 93.25%, respectively, which were categorized as very valid. The results of the environmental literacy test indicate that the average scores for knowledge, attitude, cognitive skills, and behavior were 45.91, 46.46, 51.32, and 53.24. All four domains fall within the high category. The inquiry e-module with an ethno-STEM approach is very suitable for developing environmental literacy skills.
... La literatura muestra que los niveles bajos de sombra reducen la competencia por luz y nutrientes, y también facilitan el control de la roya en las hojas de café (clr, del inglés coffee leaf rust) [Avelino et al., 2020]. Los efectos interactivos de la sombra, la altitud (a medida que aumenta, la temperatura desciende), la pendiente y la roya de la hoja del café se consideran factores que disminuyen el rendimiento [Cerda et al., 2020;Kath et al., 2020]. ...
... Además de los efectos positivos de la densidad, es posible inferir un efecto negativo de los manejos menos intensificados, al mostrar mayor susceptibilidad ante la incidencia de la roya [Durand-Bessart et al., 2020;. En función de la variabilidad espacial, los efectos más severos recayeron en los sistemas con más diversificación, que se caracterizan por ubicarse en regiones de baja altitud y mayor temperatura, lo cual crea las condiciones más adecuadas para la dispersión de la roya [Vaast et al., 2016;Kath et al., 2020]. Por otro lado, la sombra en altitudes elevadas (alrededor de 1 300 metros sobre el nivel del mar) tiende a generar rendimientos más bajos, junto con los efectos de la precipitación y la temperatura más baja [Sarmiento-Soler et al., 2019]; sin embargo, mostró un efecto buffer, al evidenciar los efectos más severos de la roya en los cafetales comerciales localizados en altitudes bajas. ...
... Specifically, global warming will significantly affect coffee crop production worldwide, with a reduction in 2050 of up to 60% in southern Brazil [30], 90% in Nicaragua [19], and 30-60% in Kenya [31]. Both Robusta and Arabica will be negatively affected by increasing temperature: a 1 • C increase in minimum/maximum temperature (16.2/24 • C) could result in ≈14% or 350-460 kg ha −1 Robusta yield reduction [32], even though the Arabica favourable environment could be relocated to 300 m up the altitude gradient in Nicaragua [19]. In addition, high temperatures would make coffee farming susceptible to fungal attacks, such as coffee rust, at lower altitudes and borer damage at high elevations [33,34]. ...
... The available literature on coffee presents extensive insights and recommendations for using models and other analytical tools to study climate change impacts and adaptations in coffee production in different regions, such as [35] in Central America, [32] in Vietnam, [36] in Brazil, [37] in Colombia, [38] in Uganda, [39] in Ethiopia, and many more. While the impacts of climate change on coffee have been systematically studied [40], modelling tools still have not received enough attention in terms of systematic review and classification. ...
Article
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Several modelling tools reported the climate change impact on the coffee agrosystems. This article has adopted a systematic approach to searching out information from the literature about different modelling approaches to assess climate change impacts or/and adaptation on coffee crops worldwide. The review included all scientific publications from the date of the first relevant article until the end of 2022 and screened 60 relevant articles. Most results report research conducted in America, followed by Africa. The models assessed in the literature generally incorporate Intergovernmental Panel on Climate Change (IPCC) emission scenarios (80% of manuscripts), particularly Representative Concentration Pathways (RCP) and Special Report on Emission Scenarios (SRES), with the most common projection periods until 2050 (50% of documents). The selected manuscripts contain qualitative and quantitative modelling tools to simulate climate impact on crop suitability (55% of results), crop productivity (25% of studies), and pests and diseases (20% of the results). According to the analysed literature, MaxEnt is the leading machine learning model to assess the climate suitability of coffee agrosystems. The most authentic and reliable model in pest distribution is the Insect Life Cycle Modelling Software (ILCYM) (version 4.0). Scientific evidence shows a lack of adaptation modelling, especially in shading and irrigation practices, which crop models can assess. Therefore, it is recommended to fill this scientific gap by generating modelling tools to understand better coffee crop phenology and its adaptation under different climate scenarios to support adaptation strategies in coffee-producing countries, especially for the Robusta coffee species, where a lack of studies is reported (6% of the results), even though this species represents 40% of the total coffee production.
... La productividad del café (kg/ha) se evaluó con base en los rendimientos promedio de los dos años anteriores. Finalmente, el rendimiento en los cultivos de café fue obtenido también a través de la correlación de imágenes satelitales con datos in situ de productividad (40), se usaron los índices de vegetación NDVI y EVI para identificar zona sensible al estrés hídrico. Se determinó que un alto índice foliar en épocas lluviosas, hacia más probable un incremento en la productividad, reflejado en una mayor cobertura de área foliar, en contraste a lo sucedido, en las épocas secas donde se redujo. ...
... ;(40) se percibe la influencia de la temperatura (°C) en el rendimiento del café Robusta, determinando que cada aumento de 1°C en las temperaturas medias, mínimas o máximas por encima de 16,2/24,1 °C corresponde a una disminución del rendimiento de aproximadamente 14% o 350-460 kg/ha. la temperatura se agrega generalmente como atributo al conjunto de datos de entrenamiento para los diferentes modelos, se mide con temporalidad trimestral y se incluye con valores promedio, mínimo y máximo. ...
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Resumen Coffee is one of the most traded agricultural products internationally; in Colombia, it is the first non-mining-energy export product. In this context, the prediction of coffee crop yields is vital for the sector since it allows coffee growers to establish crop management strategies, maximizing their profits or reducing possible losses. This paper addresses crucial aspects of coffee crop yield prediction through a systematic literature review of documents consulted in Scopus, ACM, Taylor & Francis, and Nature. These documents were subjected to a filtering and evaluation process to answer five key questions: predictor variables used, target variable, techniques and algorithms employed, metrics to evaluate the quality of the prediction, and species of coffee reported. The results reveal some groups of predictor variables, including atmospheric, chemical, satellite-derived, fertilizer-related, soil, crop management, and shadow factors. The most recurrent target variable is yield, measured in bean weight per hectare or other measures, with one case considering leaf area. Predominant techniques for yield forecasting include linear regression, random forests, principal component analysis, cluster regression, neural networks, classification and regression trees, and extreme learning machines. The most common metrics to evaluate the quality of predictive models include root mean squared error, coefficient of determination (R²), mean absolute error, error deviation, Pearson's correlation coefficient, and standard deviation. Finally, robusta, arabica, racemosa, and zanguebariae are the most studied coffee varieties.
... The findigd in line with recent studies that have reached conclusions about coffee's vulnerability to increasing temperatures. Some suggest the widespread loss, in excess of 50%, of suitable growing areas [43,44]. The often cited optimal mean annual temperature range of Robusta is estimated to be between 22 and 26 or 22 and 30℃ [45][46][47]. ...
... Our study also higlight that rainfall influence climate sustainability of Robusta Coffee. Rainfall had a notable negative effect on yields in the flowering season [43]. Excessive rain and cool conditions during the quiescent growth phase can repress flowering and this has been linked to lower yields [45]. ...
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This study aims to analyze the impact of climate change on the climate suitability of Robusta coffee in five main Indonesian coffee production centers namely Aceh, North Sumatera, South Sumatera, Bengkulu and Lampung using the Maxent approach. The study used climate data, and climate projections from Worldclim and coffee location data from maps of Indonesia's main agricultural commodities. The results showed that Maxent had good performance in modeling the climatic suitability of Robusta coffee at the provincial level, and the corresponding production areas shifted with different patterns between provinces. The areas with suitable and highly suitable climates for Robusta coffee were projected to decrease in all provinces except for Bengkulu. The findings suggest a future challenge for Robusta coffee sustainability in Indonesia. Aceh, North Sumatera, South Sumatera, and Lampung need to develop adaptation strategies to anticipate the increasingly unsuitable environment. On the other hand, Bengkulu can be considered a new area for coffee plantation. The projection of the suitability of the coffee climate is crucial in determining the future coffee development areas and for the rejuvenation of the existing coffee plantations, highlighting the significance of the study's findings for policymakers, farmers, and other stakeholders.
... Robusta coffee is generally considered to be more heat-tolerant than arabica, making it more resilient to climate change (Jayakumar et al., 2017;Läderach et al., 2017). However, some studies suggest that robusta may be more temperature-sensitive than previously thought (Kath et al., 2020). Nonetheless, the global share of robusta production compared to arabica has been increasing over time (ICO, 2023), a trend expected to continue due to climate change . ...
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Robusta coffee, grown by 25 million farmers across more than 50 countries, plays an important role in smallholder farmers' livelihoods and the economies of many low-income countries. Despite robusta coffee’s growing economic importance, currently accounting for 43% of global coffee production, its association with arbuscular mycorrhizal fungus (AMF) communities and how agricultural practices affect this association remains poorly understood. To address this, we characterised the AMF community composition of robusta coffee in part of its region of origin, the Democratic Republic of Congo. AMF diversity and community composition were compared between coffee monoculture, agroforestry systems and wild robusta in its native rainforest habitat. Using Illumina sequencing on 304 root samples, we identified 307 AMF operational taxonomic units (OTUs), dominated by the genera Glomus and Acaulospora . OTU richness did not vary across the three studied systems, yet large differences in community composition were found. Many unique OTUs were only observed in the coffee in the rainforest. In general, lower available soil phosphorus (P) and lower soil bulk density increased AMF diversity, yet higher available soil P and pH increased AMF diversity in the wild forest coffee. Shifts in AMF community composition across coffee systems were driven by canopy closure, soil pH, available soil P and soil bulk density. Our study is the first to characterise mycorrhizal communities in wild robusta coffee in its region of origin and shows that even low-input agricultural practices result in major AMF community shifts as compared to a natural baseline.
... According to Navarro-Serrano et al. (2020), the spatial distribution of air temperature is controlled by altitude; in this sense, Kath et al. (2020) highlights that there are currently no estimates of ideal minimum and maximum temperatures for the flowering and growth stages of C. canephora. focused on determining the ideal temperature for coffee (C. ...
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Water balance is a tool that has various applications in agriculture, including assessing whether an environment is suitable for growing a specific crop by providing information on how water resources function in the system. This information is essential for determining whether the available water satisfies the crop’s demand. Thus, the objective of this work was to calculate the water balance of Typic Hapludults for growing coffee (Coffea canephora) crops in Cruzeiro do Sul, Acre, Brazil, using a 36-year historical series to assess the potential and limitation of the crop according to the water availability. The results showed that coffee crops are, in general, suitable for growing in the study region. Water deficit and water surplus periods are well-defined, from April to August and September to March, respectively. Flowering was the only stage of coffee crops that coincides with the water deficit period in the region; thus, irrigation is necessary to prevent compromising this stage and fruit development. The Water Requirement Satisfaction Index (WRSI), calculated on a monthly basis, indicates a low climate risk for coffee crops in the region. However, when calculated on a daily basis, the WRSI shows a medium to high climate risk for coffee crops in several periods. The WRSI proved to be an adequate tool for assisting in decision-making regarding the adoption of irrigation. Key words: water availability; irrigation; crop water use
... El 88% de los productores de café del mundo están localizados sobre la línea del Ecuador denominada "el cinturón de café" [35], con las regiones de mayor altitud siendo asociadas a café de mayor calidad [14] [36]. Por lo que poseen condiciones climáticas variables para el secado solar de café, ya sea por baja temperatura [37], alta humedad relativa [38], bajo brillo solar [39], entre otras características que terminan afectando el tiempo total del secado e influyendo en la calidad e inocuidad del producto final [40]. Por ende, en algunos países como Colombia, los caficultores consideran el uso de secadores de baja capacidad estática para reemplazar al secado solar o utilizarlo como complemento [41]. ...
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El secado es una de las etapas más cruciales para garantizar la calidad e inocuidad del café. Se ha evidenciado que diferentes tipos de superficies y técnicas utilizadas en el secado solar pueden afectar a la calidad final del café. El secado tradicional solar en particular es afectado por las condiciones climáticas del sitio donde se realiza, entre ellas la humedad y la temperatura; existen otros métodos utilizados en la industria para contrarrestar estas desventajas. En este artículo se explora la literatura existente acerca del funcionamiento de distintas maneras de aplicar el secado solar (sobre distintas superficies y con cubiertas), diferentes tipos de secado mecánico (secadoras rotativas, de capa estática, silo-secadores y secadores en lecho fluidizado); así como la posibilidad teórica de utilizar la liofilización en granos de café para el secado en lugar de café soluble instantáneo, que es la aplicación utilizada históricamente. Los métodos mecanizados de secado presentan tiempos menores de secado, sin embargo, la calidad del café comienza a disminuir si se sobrepasan los 40°C. Si bien la liofilización tiende a conservar mejor sabores y aromas, también se incurren en mayores gastos de producción, por lo que su aplicación como método alternativo de secado se ha seguido limitando al café comercial a pesar de sus ventajas respecto a la calidad del producto final.
... El 88% de los productores de café del mundo están localizados sobre la línea del Ecuador denominada "el cinturón de café" [35], con las regiones de mayor altitud siendo asociadas a café de mayor calidad [14] [36]. Por lo que poseen condiciones climáticas variables para el secado solar de café, ya sea por baja temperatura [37], alta humedad relativa [38], bajo brillo solar [39], entre otras características que terminan afectando el tiempo total del secado e influyendo en la calidad e inocuidad del producto final [40]. Por ende, en algunos países como Colombia, los caficultores consideran el uso de secadores de baja capacidad estática para reemplazar al secado solar o utilizarlo como complemento [41]. ...
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Drying is one of the most crucial stages to ensure the quality and safety of coffee. It has been evidenced that different types of surfaces and techniques used in solar drying can affect the final quality of coffee. Traditional solar drying, is particularly influenced by the climactic conditions of the site where it is carried out, including humidity and temperature; there are other methods used in the industry to counteract these advantages. This article explores existing literature on the performance of different ways of applying solar drying (on different surfaces and with covers), different types of mechanical drying (rotary dryers, static layer dryers, dryer silos and fluidized bed drying); as well as the theoretical possibility of using freeze-drying on coffee beans for drying instead of instant soluble coffee, which has been historically used. Mechanical drying methods tend to have shorter drying times; however, the quality of coffee starts to decrease if the temperature exceeds 40°C. While freeze-drying tends to better preserve flavours and aromas, it also incurs higher production costs, limiting its application as an alternative drying method in commercial coffee despite its advantages in terms of final product quality.
... At the production stage, studies have shown a possible reduction in the area suitable for coffee growing on a global scale Gruter et al. 2022;Läderach et al. 2016;Magrach and Ghazoul 2015;Ovalle-Rivera et al. 2015). Coffee yield will also be highly affected as fluctuations in temperature and precipitation, especially during the growing, blossom and backing stages affect flower bud development (Jayakumar et al. 2017;Kath et al. 2020Kath et al. , 2023. In addition, rising temperatures accelerate ripening before proper maturation, affecting the beans' size, and quality (Ahmed and Stepp 2016;dos Santos et al. 2015). ...
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Coffee, an important global commodity, is threatened by climate change. Agroforestry has been considered as one option to maintain or enhance coffee production. In this study, we use a machine learning ensemble consisting of MaxEnt, Random Forest and Boosted Regression Trees to assess climate change impacts on the suitability to grow Arabica coffee, Robusta coffee and bananas in Uganda by 2050. Based on this, the buffering potential of Cordia africana and Ficus natalensis, the two commonly used shading trees in agroforestry systems is assessed. Our robust models (AUC of 0.7–0.9) indicate temperature-related variables as relevant for Arabica coffee suitability, while precipitation-related variables determine Robusta coffee and banana suitability. Under current climatic conditions, only a quarter of the total land area is suitable for growing Arabica coffee, while over three-quarters are suitable for Robusta coffee and bananas. Our results suggest that climate change will reduce the area suitable to grow Arabica coffee, Robusta coffee and bananas by 20%, 9% and 3.5%, respectively, under SSP3-RCP7.0 by 2050. A shift in areas suitable for Arabica coffee to highlands might occur, leading to potential encroachment on protected areas. In our model, implementing agroforestry with up to 50% shading could partially offset suitable area losses for Robusta coffee—but not for Arabica coffee. The potential to produce valuable Arabica coffee thus decreases under climate change and cannot be averted by agroforestry. We conclude that the implementation and design of agroforestry must be based on species, elevation, and regional climate projections to avoid maladaptation.
... While farmers did not agree on whether or not coffee yield increased, meteorological data supported those farmers who perceived a decrease in coffee yield due to an increase in mean annual temperature and temperature during flowering. This matches previous reports that increasing temperature is associated with reduced coffee yield (Bunn et al., 2015;Kath et al., 2020;Pham et al., 2019) and that high temperatures during flowering can cause flower abortion and increase the formation of malformed star flowers (Cannell, 1985;Craparo et al., 2015;Pham et al., 2019 and disease levels and coffee leaf rust with rising temperatures but also more frequently reported such changes at locations with a higher temperature. This may suggest that a small increase in temperature might be more problematic in already warm places. ...
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Societal Impact Statement Adapting agriculture to climate change requires an understanding of the long‐term relationship between climate, disease dynamics, and yield. While some countries have monitored major crop diseases for decades or centuries, comparable data is scarce or non‐existent for many countries that are most vulnerable to climate change. For this, a novel approach was developed to reconstruct climate‐mediated changes in disease dynamics and yield. Here, a case study on Arabica coffee in its area of origin demonstrates how to combine local knowledge, climate data, and spatial field surveys to reconstruct disease and yield time series and to postulate and test hypotheses for climate–disease–yield relationships. Summary While some countries have monitored crop diseases for several decades or centuries, other countries have very limited historical time series. In such areas, we lack data on long‐term patterns and drivers of disease dynamics, which is important for developing climate‐resilient disease management strategies. We adopted a novel approach, combining local knowledge, climate data, and spatial field surveys to understand long‐term climate‐mediated changes in disease dynamics in coffee agroforestry systems. For this, we worked with 58 smallholder farmers in southwestern Ethiopia, the area of origin of Arabica coffee. The majority of farmers perceived an increase in coffee leaf rust and a decrease in coffee berry disease, whereas perceptions of changes in coffee wilt disease and Armillaria root rot were highly variable among farmers. Climate data supported farmers' understanding of the climatic drivers (increased temperature, less rainy days) of these changes. Temporal disease‐climate relationships were matched by spatial disease‐climate relationships, as expected with space‐for‐time substitution. Understanding long‐term disease dynamics and yield is crucial to adapt disease management to climate change. Our study demonstrates how to combine local knowledge, climate data and spatial field surveys to reconstruct disease time series and postulate hypotheses for disease‐climate relationships in areas where few long‐term time series exist.
... While farmers did not agree on whether or not coffee yield increased, meteorological data supported those farmers who perceived a decrease in coffee yield due to an increase in mean annual temperature and temperature during flowering. This matches previous reports that increasing temperature is associated with reduced coffee yield (Bunn et al., 2015;Kath et al., 2020;Pham et al., 2019) and that high temperatures during flowering can cause flower abortion and increase the formation of malformed star flowers (Cannell, 1985;Craparo et al., 2015;Pham et al., 2019 and disease levels and coffee leaf rust with rising temperatures but also more frequently reported such changes at locations with a higher temperature. This may suggest that a small increase in temperature might be more problematic in already warm places. ...
... While farmers did not agree on whether or not coffee yield increased, meteorological data supported those farmers who perceived a decrease in coffee yield due to an increase in mean annual temperature and temperature during flowering. This matches previous reports that increasing temperature is associated with reduced coffee yield (Bunn et al., 2015;Kath et al., 2020;Pham et al., 2019) and that high temperatures during flowering can cause flower abortion and increase the formation of malformed star flowers (Cannell, 1985;Craparo et al., 2015;Pham et al., 2019 and disease levels and coffee leaf rust with rising temperatures but also more frequently reported such changes at locations with a higher temperature. This may suggest that a small increase in temperature might be more problematic in already warm places. ...
... On the other hand, C canephora shown a greater tolerance compared to Arabica species, occupying ecological niches with temperatures ranging from 22˚C to 30˚C. However, it has been established that the optimal growth temperature for Robusta is only 20˚C, and that temperatures variations of 1˚C below or above a range of 16-24˚C result in a 14% loss of production [9]. Considering the expected global changes, estimations indicate that the arable area under cultivation will shrink by almost 50% by 2050 [6]. ...
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The wild species of the Coffea genus present a very wide morphological, genetic, and biochemical diversity. Wild species are recognized more resistant to diseases, pests, and environmental variations than the two species currently cultivated worldwide: C. arabica (Arabica) and C. canephora (Robusta). Consequently, wild species are now considered as a crucial resource for adapting cultivated coffee trees to climate change. Within the Coffea genus, 79 wild species are native to the Indian Ocean islands of Comoros, Mayotte, Mauritius, Réunion and Madagascar, out of a total of 141 taxa worldwide. Among them, a group of 9 species called "Baracoffea" are particularly atypical in their morphology and adaptation to the sandy soils of the dry deciduous forests of western Madagascar. Here, we have attempted to shed light on the evolutionary history of three Baracoffea species: C. ambongensis, C. boinensis and C. bissetiae by analyzing their chloroplast and nuclear genomes. We assembled the complete chloroplast genomes de novo and extracted 28,800 SNP (Single Nucleotide Polymorphism) markers from the nuclear genomes. These data were used for phylogenetic analysis of Baracoffea with Coffea species from Madagascar and Africa. Our new data support the monophyletic origin of Baracoffea within the Coffea of Madagascar, but also reveal a divergence with a sister clade of four species: C. augagneurii, C. ratsimamangae, C. pervilleana and C. Mcphersonii (also called C. vohemarensis), belonging to the Subterminal botanical series and living in dry or humid forests of northern Madagascar. Based on a bioclimatic analysis, our work suggests that Baracoffea may have diverged from a group of Malagasy Coffea from northern Madagascar and adapted to the specific dry climate and low rainfall of western Madagascar. The genomic data generated in the course of this work will contribute to the understanding of the adaptation mechanisms of these particularly singular species.
... However, the minimum temperature at high-elevation during flowering was lower than at low-elevation (Fig. 1). This may have influenced the size of the flowers because although there are no estimates for ideal minimum and maximum temperatures during flowering, low minimum temperatures during flowering have been related to reduced productivity of C. canephora (Kath et al., 2020). Therefore, the favorable climatic conditions for the cultivation of C. canephora at low-elevation may have contributed to better plant development and, consequently, to the production of bigger flowers than at high-elevation. ...
... Although arabica coffee dominates the market due to its high beverage quality, robusta coffee accounts for almost 40% of the world's coffee production. It is an important commodity to many developing countries and represents the income of millions of farmers (Kath et al., 2020). Brazil is the second largest robusta coffee producer of the world, and its production is concentrated in the states of Espirito Santo and Rondônia (CONAB, 2023;Moreira et al., 2021). ...
... Climate change poses serious threats to coffee production and quality Kath et al., 2020;Craparo et al., 2021) and seasonal norms are reported to be increasingly unpredictable. Even though total annual rainfall is reported to slightly increase, rainfall patterns are expected to shift with more rain in the wet season and less rain in the dry season (Baker et al., 2017) with adverse impacts on flowering and fruit setting (Koh et al., 2020). ...
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The Central Highlands of Vietnam is an important Robusta coffee growing region. However, the region is facing climate change impacts from rising temperatures and irregular rainfall, while Vietnamese coffee farmers predominantly rely on irrigation from heavily depleted aquifers. To continue productive and sustainable growth, this system requires an innovative approach to meet this hydrological challenge. Here we propose a user-friendly tool, which aims to support coffee farmers’ irrigation decisions, through the Targeted Irrigation Support Tool or ThIRST. ThIRST combines seasonal forecasts, on-farm metrics, and farmer’s expertise. The research comprises baseline ( n = 400) and endline ( n = 237) surveys of coffee farmers in Đắk Lắk and Lâm Đồng Provinces. Through the surveys, farmers’ irrigation needs and the applicability of the tool are evaluated. Despite low smartphone usage for farming advisory, the results show the tool allows coffee farmers to continually achieve water-use efficiency and adapt to climate variability. Involving farmers in the design, production and evaluation of climate services can improve the trust and uptake of agro-advisories and the way this information is communicated.
... J. G. da Silva et al., 2015). However, drought is the main environmental stress affecting coffee production in most growing areas , which together with high air temperatures -above 31.5 °C (Partelli et al., 2010) -can drastically reduce coffee growth due to physiological and biochemical changes (DaMatta & Ramalho, 2006;Kath et al., 2020) related to a decrease in photosynthetic activity and respiratory capacity and increased respiratory rate (Vara Prasad et al., 2005;Dubberstein et al., 2018;Venancio et al., 2020). ...
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Neste estudo objetivou-se avaliar o crescimento vegetativo da espécie Coffea canephora, a partir dos ramos ortotrópicos e plagiotrópicos dos cafeeiros das variedades botânicas Conilon e Robusta, em condições irrigada e não irrigadas, durante as estações de chuva e estiagem. O experimento foi conduzido no município de Ouro Preto do Oeste, Rondônia, Brasil, durante dois períodos definidos entre os meses de outubro de 2019 a outubro de 2021. As taxas de crescimentos dos ramos (mm dia-1) foram obtidas a cada quatorze dias e o crescimento sazonal foi plotado em gráficos em série. As médias das taxas de crescimento para cada tipo de ramo foram comparadas pelo teste de Tukey (p ≤ 0,05). O crescimento vegetativo foi sazonal durante os períodos de avaliação e estações do ano e, variou conforme o material genético e uso da irrigação. As taxas de crescimento foram superiores no período chuvoso, independentemente do manejo hídrico e da variedade botânica. A irrigação de cafeeiros realizada durante as épocas de altas temperaturas e forte déficit hídrico proporcionou maior crescimento em relação a plantas não irrigadas. Além disso, o crescimento dos cafeeiros não irrigados ficou represado durante o período da estiagem e foi compensado pelas altas taxas de crescimento no período das chuvas. As plantas da variedade botânica Robusta, em condições de disponibilidade hídrica, mediante chuva ou irrigação, tenderam a crescer mais do que as da variedade Conilon, considerando as condições climáticas da Amazônia Sul-Ocidental.
... Many studies have shown that coffee is highly sensitive to changes in temperature and precipitation levels (Craparo et al 2015, Kath et al 2020, Venancio et al 2020, Dinh et al 2022. According to Venancio et al 2020, droughts and high temperatures have a negative impact on coffee production, with rising temperatures having a more significant effect than decreases in annual rainfall. ...
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This research aimed to identify sensitive areas for Robusta coffee trees in Dak Lak province, Vietnam, where frequent droughts caused fluctuations in productivity. To improve yield forecasting, a mask was developed to extract potential predictive variables from satellite-derived vegetation indices (VIs). Correlation coefficients between VIs and coffee yield were analyzed to determine sensitive areas, and grid cells with high multiple correlation coefficients and a variable over time were used to build the mask for extracting VIs as predictor variables. The study found that sensitive areas had more challenging farming conditions than long-term crops, and the Vegetation Health Index was the most appropriate index for predicting coffee yield. The forecast quality for 6-8 months in advance was relatively high, with a "Willmott's index of agreement" ranging from 0.85 to 0.97 and the Mean Absolute Percentage Error ranging from 4.9% to 7.5%. Compared to previous research, the forecast quality has significantly improved. This study provides valuable insights for predicting coffee yield in Dak Lak and highlights the importance of considering sensitive areas and VIs for accurate forecasting.
... The viability of the economic aspects of the coffee agro-food industry is threatened by several factors, such as fluctuating and low prices and the lack of investment in technology. Several other factors, such as the use of child labour, forced labour, labour shortages, and lack of knowledge, are common social problems in the coffee industry (Dietz et al. 2018;Kath et al. 2020). In addition, the coffee agro-food industry also impacts the ecosystem and causes environmental problems (Ango et al. 2020;Pendrill et al. 2019). ...
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The coffee agro-food industry has great potential for economic development in tropical countries. However, the issue of agro-food sustainability in the coffee industry is a primary focus, so this industry must conduct a sustainable performance assessment (SPA). This research aims to propose a new SPA framework that incorporates the fuzzy analytical hierarchy process (AHP), rating assessment, and traffic light system (TLS) procedures. The fuzzy AHP is used to weight the indicators, and rating assessment is used to evaluate the performance of each indicator. The rating assessment results are used to evaluate the efficiency of the indicators used to calculate the sustainability score. Furthermore, the sustainability score is classified using the TLS to assess sustainability performance. A case study of the agro-food coffee industry in Indonesia is also presented, with six indicators of the economic dimension, eight of the social dimension, and four of the environmental dimension. The results show that economic factors produce good performance (green). In contrast, social factors produce performance that needs to be improved (yellow). Environmental aspects have poor performance (red). The overall sustainability score assessment results show that the agro-food coffee industry in Indonesia scored 85.71%, which is categorized as needing improvement (yellow). This study also makes strategic recommendations to improve the performance of the coffee agro-food industry.
... Recent data from Kath et al. (2020) suggests Robusta has a lower optimal temperature range than previously thought, with every 1°C increase in the mean maximum temperature above about 24°C associated with a yield reduction of ~ 14% (350-460 kg ha −1 ). Hence, there will be limits to the resilience of yields to increased temperatures when transitioning from Arabica to Robusta production. ...
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Climate change is adversely affecting coffee production, impact-ing both yields and quality. Coffee production is dominated by the cultivation of Arabica and Robusta coffee, species that represent 99% of production, but both will be affected by climate change. Sustainable management practices that can enhance the resilience of production and livelihoods to climate change are urgently needed as production supports the livelihoods of over 25 million people globally, the majority of whom are smallholder farmers located in the coffee belt spanning the tropics. These communities are already experiencing the impacts of climate change. We conducted a systematic review, identifying 80 studies that describe the direct and indirect impacts of climate change on coffee agroecosystems, or that identify agroecological practices with the potential to enhance climate resilience. Adverse environmental impacts include a reduction in area suitable for production, lower yields, increased intensity and frequency of extreme climate events, and greater incidence of pests and diseases. Potential environmental solutions include altitudinal shifts, new, resilient culti-vars, altering agrochemical inputs, and agroforestry. However, financial, environmental and technical constraints limit the availability of many of these approaches to farmers, particularly smallholder producers. There is therefore an urgent need to address these barriers through policy and market mechanisms, and stakeholder engagement to continue meeting the growing demand for coffee.
... Cool climates (higher elevations, with at least intermediate canopy cover) had a high potential to produce coffee beans possessing superior total preliminary quality, higher caffeine, total chlorogenic acid (CGA) contents, and trigonelline concentrations (Worku et al. 2018;Tolessa et al. 2017;paper in-press). Water deficits, on the other hand, during the coffee fruit expansion and filling period caused appreciable productivity loss and decreased bean quality (Kath et al. 2020;Semedo et al. 2018). In terms of soil characteristics, is especially soil pH associated with the acidity of coffee, body and cup cleanness. ...
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The biophysical drivers that affect coffee quality vary within and among farms. Quantifying their relative importance is crucial for making informed decisions concerning farm management, marketability and profit for coffee farmers. The present study was designed to quantify the relative importance of biophysical variables affecting coffee bean quality within and among coffee farms and to evaluate a near infrared spectroscopy-based model to predict coffee quality. Twelve coffee plants growing under low, intermediate and dense shade were studied in twelve coffee farms across an elevational gradient (1470–2325 m asl) in Ethiopia. We found large within farm variability, demonstrating that conditions varying at the coffee plant-level are of large importance for physical attributes and cupping scores of green coffee beans. Overall, elevation appeared to be the key biophysical variable influencing all the measured coffee bean quality attributes at the farm level while canopy cover appeared to be the most important biophysical variable driving the above-mentioned coffee bean quality attributes at the coffee plant level. The biophysical variables driving coffee quality (total preliminary and specialty quality) were the same as those driving variations in the near-infrared spectroscopy data, which supports future use of this technology to assess green bean coffee quality. Most importantly, our findings show that random forest is computationally fast and robust to noise, besides having comparable prediction accuracy. Hence, it is a useful machine learning tool for regression studies and has potential for modeling linear and nonlinear multivariate calibrations. The study also confirmed that near-infrared spectroscopic-based predictions can be applied as a supplementary approach for coffee cup quality evaluations.
... These modelling methods have been shown to provide climate metrics that are similar to those provided for coffee species in cultivation (including farmed conditions) and in the wild, produced by direct measurement and other means (Davis et al., 2021b). For validation purposes, our modelled mean annual temperatures (from Bio1), total annual precipitation (Bio12) and precipitation seasonality (Bio15), were compared against publicly available monthly mean temperature precipitation charts for Uganda and published data for cultivated C. canephora (DaMatta and Ramalho, 2006;Kath et al., 2020;Venancio et al., 2020); published data are not available for the three other species studied here. ...
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... For example, possible decreased coffee productivity due to climate change is alarming (Pham et al., 2019) and likely related to more biodiversity loss (Philpott et al., 2008). Spatial shifts in Arabica coffee producing regions are also expected (Ovalle-Rivera et al., 2015) with concerns over seemingly less resistant Robusta coffee (Kath et al., 2020). In the context of climate change, shade coffee production of planted trees in between coffee hedgerows has since been seen as a viable alternative with hydrological (in the context of reduced AET) and soil structural and biogeochemical benefits over coffee directly exposed to the sun particularly in Costa Rica (Siles et al., 2010;Harmand et al., 2007). ...
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... The amount and timing of rainfall can impact coffee bean quality. Too little rainfall during the growing season stresses plants, causing branch death and defoliation, reducing resources for fruiting, and leading to small and damaged coffee beans (DaMatta et al. 2018;Kath et al. 2020). Too much rainfall can dislodge flowers and fruits. ...
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Assessing and prescribing fertilizer use is critical to profitable and sustainable coffee production, and this is becoming a priority concern for the Robusta coffee industry. In this study, annual survey data of 798 farms across selected Robusta coffee-producing provinces in Vietnam and Indonesia between 2008 and 2017 were used to comparatively assess the fertilizer management strategies in these countries. Specifically, we aimed to characterize fertilizer use patterns in the key coffee-growing provinces and discuss the potential for improving nutrient management practices. Four types of chemical (NPK, super phosphate, potassium chloride and urea) and two of natural (compost and lime) fertilizers were routinely used in Vietnam. In Indonesia, NPK and urea were supplemented only with compost. Farmers in Vietnam applied unbalanced quantities of chemical fertilizers (i.e., higher rates than recommended) and at a constant rate between years whereas Indonesian farmers applied well below the recommended rates because of poor accessibility and financial support. The overuse of chemical fertilizers in Vietnam threatens the sustainability of Robusta coffee farming. Nevertheless, there is a potential for improvement in both countries in terms of nutrient management and sustainability of Robusta coffee production by adopting the best local fertilizer management practices.
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Species distribution models (SDM) that rely on regional‐scale environmental variables will play a key role in forecasting species occurrence in the face of climate change. However, in the Anthropocene, a number of local‐scale anthropogenic variables, including wildfire history, land‐use change, invasive species, and ecological restoration practices can override regional‐scale variables to drive patterns of species distribution. Incorporating these human‐induced factors into SDMs remains a major research challenge, in part because spatial variability in these factors occurs at fine scales, rendering prediction over regional extents problematic. Here, we used big sagebrush (Artemisia tridentata Nutt.) as a model species to explore whether including human‐induced factors improves the fit of the SDM. We applied a Bayesian hurdle spatial approach using 21,753 data points of field‐sampled vegetation obtained from the LANDFIRE program to model sagebrush occurrence and cover by incorporating fire history metrics and restoration treatments from 1980 to 2015 throughout the Great Basin of North America. Models including fire attributes and restoration treatments performed better than those including only climate and topographic variables. Number of fires and fire occurrence had the strongest relative effects on big sagebrush occurrence and cover, respectively. The models predicted that the probability of big sagebrush occurrence decreases by 1.2% (95% CI; –6.9%, 0.6%) when one fire occurs and that increasing fires from zero to at least one fire would decrease cover by 44.7% (95% CI; –47.9%, –41.3%). Restoration practices increased the probability of big sagebrush occurrence but had minimal effect on cover. Our results demonstrate the potential value of including disturbance and land management along with climate in models to predict species distributions. As an increasing number of datasets representing land use history become available, we anticipate that our modeling framework will have broad relevance across a range of biomes and species. This article is protected by copyright. All rights reserved.
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Wild coffee species are critical for coffee crop development and, thus, for sustainability of global coffee production. Despite this fact, the extinction risk and conservation priority status of the world’s coffee species are poorly known. Applying IUCN Red List of Threatened Species criteria to all (124) wild coffee species, we undertook a gap analysis for germplasm collections and protected areas and devised a crop wild relative (CWR) priority system. We found that at least 60% of all coffee species are threatened with extinction, 45% are not held in any germplasm collection, and 28% are not known to occur in any protected area. Existing conservation measures, including those for key coffee CWRs, are inadequate. We propose that wild coffee species are extinction sensitive, especially in an era of accelerated climatic change.
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Arabica coffee (Coffea arabica) is a key crop in many tropical countries and globally provides an export value of over US$13 billion per year. Wild Arabica coffee is of fundamental importance for the global coffee sector and of direct importance within Ethiopia, as a source of harvestable income and planting stock. Published studies show that climate change is projected to have a substantial negative influence on the current suitable growing areas for indigenous Arabica in Ethiopia and South Sudan. Here we use all available future projections for the species based on multiple general circulation models (GCMs), emission scenarios, and migration scenarios, to predict changes in Extent of Occurrence (EOO), Area of Occupancy (AOO), and population numbers for wild Arabica coffee. Under climate change our results show that population numbers could reduce by 50% or more (with a few models showing over 80%) by 2088. EOO and AOO are projected to decline by around 30% in many cases. Furthermore, present‐day models compared to the near future (2038), show a reduction for EOO of over 40% (with a few cases over 50%), although EOO should be treated with caution due to its sensitivity to outlying occurrences. When applying these metrics to extinction risk, we show that the determination of generation length is critical. When applying the International Union for Conservation of Nature's Red list of Threatened Species (IUCN Red List) criteria, even with a very conservative generation length of 21 years, wild Arabica coffee is assessed as Threatened with extinction (placed in the Endangered category) under a broad range of climate change projections, if no interventions are made. Importantly, if we do not include climate change in our assessment, Arabica coffee is assessed as Least Concern (not threatened) when applying the IUCN Red List criteria.
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The expanding human global footprint and growing demand for fresh water have placed tremendous stress on inland aquatic ecosystems. Aichi Target 10 of the Convention on Biological Diversity aims to minimize anthropogenic pressures affecting vulnerable ecosystems, and pressure interactions are increasingly being incorporated into environmental management and climate change adaptation strategies. In this study, we explore how climate change, overfishing, forest disturbance, and invasive species pressures interact to affect inland lake walleye (Sander vitreus) populations. Walleye support subsistence, recreational, and commercial fisheries and are one of most sought‐after freshwater fish species in North America. Using data from 444 lakes situated across an area of 475 000 km² in Ontario, Canada, we apply a novel statistical tool, R‐INLA, to determine how walleye biomass deficit (carrying capacity – observed biomass) is impacted by multiple pressures. Individually, angling activity and the presence of invasive zebra mussels (Dreissena polymorpha) were positively related to biomass deficits. In combination, zebra mussel presence interacted negatively and antagonistically with angling activity and percentage decrease in watershed mature forest cover. Velocity of climate change in growing degree days above 5°C and decrease in mature forest cover interacted to negatively affect walleye populations. Our study demonstrates how multiple pressure evaluations can be conducted for hundreds of populations to identify influential pressures and vulnerable ecosystems. Understanding pressure interactions is necessary to guide management and climate change adaptation strategies, and achieve global biodiversity targets. This article is protected by copyright. All rights reserved.
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Coffee, one of the most heavily globally traded agricultural commodities, has been categorized as a highly sensitive plant species to progressive climatic change. Here, we summarize recent insights on the coffee plant’s physiological performance at elevated atmospheric carbon dioxide concentration [CO2]. We specifically (i) provide new data of crop yields obtained under free-air CO2 enrichment conditions, (ii) discuss predictions on the future of the coffee crop as based on rising temperature and (iii) emphasize the role of [CO2] as a key player for mitigating harmful effects of supra-optimal temperatures on coffee physiology and bean quality. We conclude that the effects of global warming on the climatic suitability of coffee may be lower than previously assumed. We highlight perspectives and priorities for further research to improve our understanding on how the coffee plant will respond to present and progressive climate change.
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The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological data. Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models is not always straightforward. The ability to achieve robust biological inference requires that practitioners know how and when to apply these tools. Here, we provide a general overview of current methods for the application of LMMs to biological data, and highlight the typical pitfalls that can be encountered in the statistical modelling process. We tackle several issues regarding methods of model selection, with particular reference to the use of information theory and multi-model inference in ecology. We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding. This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions.
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We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958–2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.
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Study on variability in area, production, and productivity of coffee in India during last decade indicates that area and production of coffee is increasing whereas yield of coffee is decreasing trend during the period 1990–1991 to 2015–2016. There was increasing trend of Robusta coffee and decreasing trend of Arabica coffee yields in India with three distinct periods due to climate change. Micro-level study was conducted on variability in yield of Arabica and Robusta coffee vis-à-vis climate change, variability of parameters like rainfall (RF), maximum temperature (Tmax), minimum temperature (Tmin), and mean relative humidity (RH) was undertaken with data recorded at Regional Coffee Research Station, Chundale, Wayanad, Kerala State. The yield data for 35 years (1980 to 2014) revealed that the yield of Robusta coffee was higher than that of Arabica coffee in most of the years due to favorable climate requirements in Kerala. There was increasing trend of yield of Robusta coffee in Kerala and decreasing trend of Arabica coffee. Blossom showers had significance influence in increasing the yield of coffee rather than total annual rainfall in Robusta coffee. El Niño events have little effect on coffee production in India in general, and out of 11 El Niño years, only 3 years coffee productivity was adversely affected. However, with respect to Kerala, Arabica yield was adversely affected in strong El Niño years, which was again confirmed with NDVI anomaly too.
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Ecological data often show temporal, spatial, hierarchical (random effects), or phylogenetic structure. Modern statistical approaches are increasingly accounting for such dependencies. However, when performing cross-validation, these structures are regularly ignored, resulting in serious underestimation of predictive error. One cause for the poor performance of uncorrected (random) cross-validation, noted often by modellers, are dependence structures in the data that persist as dependence structures in model residuals, violating the assumption of independence. Even more concerning, because often overlooked, is that structured data also provides ample opportunity for overfitting with non-causal predictors. This problem can persist even if remedies such as autoregressive models, generalized least squares, or mixed models are used. Block cross-validation, where data are split strategically rather than randomly, can address these issues. However, the blocking strategy must be carefully considered. Blocking in space, time, random effects or phylogenetic distance, while accounting for dependencies in the data, may also unwittingly induce extrapolations by restricting the ranges or combinations of predictor variables available for model training, thus overestimating interpolation errors. On the other hand, deliberate blocking in predictor space may also improve error estimates when extrapolation is the modelling goal. Here, we review the ecological literature on non-random and blocked cross-validation approaches. We also provide a series of simulations and case studies, in which we show that, for all instances tested, block cross-validation is nearly universally more appropriate than random cross-validation if the goal is predicting to new data or predictor space, or for selecting causal predictors. We recommend that block cross-validation be used wherever dependence structures exist in a dataset, even if no correlation structure is visible in the fitted model residuals, or if the fitted models account for such correlations. This article is protected by copyright. All rights reserved.
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Background The coffee species Coffea canephora is commercially identified as “Conilon” when produced in Brazil, or “Robusta” when produced elsewhere in the world. It represents approximately 40 % of coffee production worldwide. While the genetic diversity of wild C. canephora has been well studied in the past, only few studies have addressed the genetic diversity of currently cultivated varieties around the globe. Vietnam is the largest Robusta producer in the world, while Mexico is the only Latin American country, besides Brazil, that has a significant Robusta production. Knowledge of the genetic origin of Robusta cultivated varieties in countries as important as Vietnam and Mexico is therefore of high interest. ResultsThrough the use of Sequencing-based diversity array technology-DArTseq method-on a collection of C. canephora composed of known accessions and accessions cultivated in Vietnam and Mexico, 4,021 polymorphic SNPs were identified. We used a multivariate analysis using SNP data from reference accessions in order to confirm and further fine-tune the genetic diversity of C. canephora. Also, by interpolating the data obtained for the varieties from Vietnam and Mexico, we determined that they are closely related to each other, and identified that their genetic origin is the Robusta Congo – Uganda group. Conclusions The genetic characterization based on SNP markers of the varieties grown throughout the world, increased our knowledge on the genetic diversity of C. canephora, and contributed to the understanding of the genetic background of varieties from very important coffee producers. Given the common genetic origin of the Robusta varieties cultivated in Vietnam, Mexico and Uganda, and the similar characteristics of climatic areas and relatively high altitude where they are grown, we can state that the Vietnamese and the Mexican Robusta have the same genetic potential to produce good cup quality.
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Coffee is grown in more than 60 tropical countries on over 11 million ha by an estimated 25 million farmers, most of whom are smallholders. Several regional studies demonstrate the climate sensitivity of coffee (Coffea arabica) and the likely impact of climate change on coffee suitability, yield, increased pest and disease pressure and farmers’ livelihoods. The objectives of this paper are (i) to quantify the impact of progressive climate change to grow coffee and to produce high quality coffee in Nicaragua and (ii) to develop an adaptation framework across time and space to guide adaptation planning. We used coffee location and cup quality data from Nicaragua in combination with the Maxent and CaNaSTA crop suitability models, the WorldClim historical data and the CMIP3 global circulation models to predict the likely impact of climate change on coffee suitability and quality. We distinguished four different impact scenarios: Very high (coffee disappears), high (large negative changes), medium (little negative changes) and increase (positive changes) in climate suitability. During the Nicaraguan coffee roundtable, most promising adaptation strategies were identified, which we then used to develop a two-dimensional adaptation framework for coffee in time and space. Our analysis indicates that incremental adaptation may occur over short-term horizons at lower altitudes, whereas the same areas may undergo transformative adaptation in the longer term. At higher elevations incremental adaptation may be needed in the long term. The same principle and framework is applicable across coffee growing regions around the world.
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Modeling studies have predicted that coffee crop will be endangered by future global warming, but recent reports highlighted that high [CO2] can mitigate heat impacts on coffee. This work aimed at identifying heat protective mechanisms promoted by CO2 in Coffea arabica (cv. Icatu and IPR108) and Coffea canephora cv. Conilon CL153. Plants were grown at 25/20°C (day/night), under 380 or 700 μL CO2 L⁻¹, and then gradually submitted to 31/25, 37/30, and 42/34°C. Relevant heat tolerance up to 37/30°C for both [CO2] and all coffee genotypes was observed, likely supported by the maintenance or increase of the pools of several protective molecules (neoxanthin, lutein, carotenes, α-tocopherol, HSP70, raffinose), activities of antioxidant enzymes, such as superoxide dismutase (SOD), ascorbate peroxidase (APX), glutathione reductase (GR), catalase (CAT), and the upregulated expression of some genes (ELIP, Chaperonin 20). However, at 42/34°C a tolerance threshold was reached, mostly in the 380-plants and Icatu. Adjustments in raffinose, lutein, β-carotene, α-tocopherol and HSP70 pools, and the upregulated expression of genes related to protective (ELIPS, HSP70, Chape 20, and 60) and antioxidant (CAT, CuSOD2, APX Cyt, APX Chl) proteins were largely driven by temperature. However, enhanced [CO2] maintained higher activities of GR (Icatu) and CAT (Icatu and IPR108), kept (or even increased) the Cu,Zn-SOD, APX, and CAT activities, and promoted a greater upregulation of those enzyme genes, as well as those related to HSP70, ELIPs, Chaperonins in CL153, and Icatu. These changes likely favored the maintenance of reactive oxygen species (ROS) at controlled levels and contributed to mitigate of photosystem II photoinhibition at the highest temperature. Overall, our results highlighted the important role of enhanced [CO2] on the coffee crop acclimation and sustainability under predicted future global warming scenarios.
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Despite the importance of coffee as a globally traded commodity and increasing concerns about risks associated with climate change, there is virtually no information about the effects of rising atmospheric [CO2] on field-grown coffee trees. This study shows the results of the first 2 years of an innovative experiment. Two commercial coffee cultivars (Catuaí and Obatã) were grown using the first free-air CO2 enrichment (FACE) facility in Latin America (ClimapestFACE). Plants of both cultivars maintained relatively high photosynthetic rates, water-use efficiency, increased growth and yield under elevated [CO2]. Harvestable crop yields increased 14.6 % for Catuaí and 12.0 % for Obatã. Leaf N content was lower in Obatã (5.2%) grown under elevated [CO2] than under ambient [CO2]; N content was unresponsive to elevated [CO2] in Catuaí. Under elevated [CO2] reduced incidence of leaf miners (Leucoptera coffeella) occurred on both coffee cultivars during periods of high infestation. The percentage of leaves with parasitized and predated mines increased when leaf miner infestation was high, but there was no effect of elevated [CO2] on the incidence of natural enemies. The incidence of rust (Hemileia vastatrix) and Cercospora leaf spot (Cercospora coffeicola) was low during the trial, with maximum values of 5.8 and 1 %, respectively, and there was no significant effect of [CO2] treatments on disease incidence. The fungal community associated with mycotoxins was not affected by the treatments.
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