Projected shifts in Coffea arabica suitability among major global producing regions due to climate change

Breaking new ground: First AquaCrop calibration and climate change impact assessment on Arabica coffee

Climate change threatens global coffee yield stability, especially in Brazil, the largest Arabica exporter. Yield modeling is key to climate-resilient strategies and effective planning. To this end, the AquaCrop model was parameterized, calibrated, and validated for Arabica coffee in Brazil and subsequently applied to project yield under future climate scenarios. These processes were carried out across 58 municipalities in Brazil's two largest coffee-growing regions, covering the growing years from 2014 to 2019. AquaCrop accurately simulated Arabica coffee yield during calibration and validation processes, with root mean square error values of ∼0.15 t ha-1, mean bias error of ∼0.007 t ha-1, and d-index of ∼0.76. To project yield, AquaCrop used as input daily near-surface air temperature (minimum and maximum), precipitation, and reference evapotranspiration data from 9 General Circulation Models (GCMs) from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), which are derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6), under three Shared Socioeconomic Pathways scenarios (SSP2-4.5, SSP3-7.0 and SSP5-8.5). Under future climate conditions, reductions in the coffee growing cycle duration and heterogeneous yield changes are projected, with increases (between 0.25 and 0.55 t ha-1) along a belt extending from southeastern São Paulo to southern Minas Gerais, and decreases (between -0.05 and -0.15 t ha-1) in northeastern Minas Gerais. Even though yield increases are projected for much of the study region, adopting effective adaptive measures will be essential to address climate change threats.

Development of a flavour wheel for Coffea canephora using rate-all-that-apply

Improving Coffea canephora cup quality became a target for several coffee improvement programs, opening the possibility of sensory profile diversification and opportunities for the recognition of C. canephora by the specialty coffee market. Nonetheless, there is a lack of a defined descriptive tool for evaluating the sensory quality of C. canephora. The aim of this study was to identify the aroma/flavour descriptors of C. canephora samples from 13 different countries of origin and submitted to various postharvest processes (dry and wet processing), with different quality levels (specialty and non-specialty), and organize them in a aroma/flavour wheel for use as a descriptive tool in quality assessment. Altogether, 49 professional coffee graders in both exporting (Brazil) and importing (Switzerland) countries evaluated and described 67 samples in 3 cupping sessions. They used a Rate-All-That-Apply (RATA) list as well as the CQI standard cupping protocol for quality assessment of overall attributes (e.g., aroma, flavour, body, aftertaste) and the final quality score (0-100). A total of 103 descriptors were represented in the three-tiered wheel. 'Roasted' was the Tier 1 category with the highest average mean score, followed by 'sweet', 'fruity', 'cocoa', all the way to 'salty' (the Tier 1 category with the lowest average mean score). The differences between exporting and importing graders regarding (1) the use of descriptive terms, (2) the rated intensity/frequency of certain aroma/flavour categories, and (3) the final score given to both low-grade (i.e., commercial) and specialty coffee samples are discussed. The aroma/flavour wheel can be used as a tool to identify, understand, and map the sensory characteristics of C. canephora that are most important or valued in different markets. Standardizing the description of C. canephora aroma/flavours in a replicable way is important not only for the coffee industry but also for scientists working on quality improvement.

Beneficial Effects of ACC Deaminase-Producing Rhizobacteria on the Drought Stress Resistance of Coffea arabica L

Given the challenges of climate change, effective adaptation strategies for crops like coffee are crucial. This study evaluated twelve 1-aminocyclopropane-1-carboxylate deaminase-producing bacterial strains selectively isolated from the rhizosphere of Coffea arabica L. cv. Costa Rica 95 in a plantation located in Veracruz, Mexico, focusing on their potential to enhance drought resistance. The strains, representing seven genera from the Gamma-proteobacteria and Bacteroidota groups, were characterized for growth-promoting traits, including ACC deaminase activity, indole-3-acetic acid (IAA) synthesis, phosphates solubilization, siderophore production, and nitrogen fixation. Strains of the genus Pantoea exhibited higher ACC deaminase activity, phosphate solubilization, and IAA synthesis, while others, such as Sphingobacterium and Chryseobacterium, showed limited plant growth-promoting traits. A pot experiment was conducted with coffee plants subjected to either full irrigation (soil with 85% volumetric water content) or drought (soil with 55% volumetric water content) conditions, along with inoculation with the isolated strains. Plants inoculated with Pantoea sp. RCa62 demonstrated improved growth metrics and physiological traits under drought, including higher leaf area, relative water content (RWC), biomass, and root development compared to uninoculated controls. Similar results were observed with Serratia sp. RCa28 and Pantoea sp. RCa31 under full irrigation conditions. Pantoea sp. RCa62 exhibited superior root development under stress, contributing to overall plant development. Proline accumulation was significantly higher in drought-stressed, non-inoculated plants compared to those inoculated with Pantoea sp. RCa62. This research highlights the potential of Pantoea sp. RCa62 to enhance coffee plant resilience to drought and underscores the need for field application and further validation of these bioinoculants in sustainable agricultural practices.

Biodiversity and Evaluation of Genetic Resources of Some Coffee Trees Grown in Al-Baha, Saudi Arabia

The biodiversity of 12 coffee (Coffea arabica L.) cultivars collected from the Al-Baha region in the southwest of Saudi Arabia was evaluated using 25 morphological variations and genetic diversity as demonstrated by molecular polymorphism generated by eight Inter Simple Sequence Repeats (ISSRs) and nine Start Codon Targeted (SCoT) primers. Substantial variations were scored in the morphological traits reflected in the clustering of the examined cultivars in PCA of the coffee cultivars. The examined cultivars were grouped in two groups, one included the cultivars coded Y5, Y6, R113, and Y7 and the other group comprised two clusters; one comprised cultivars coded R8 and R4 and the other comprised cultivars R112, R114, and Y2. In the meantime, the cultivars coded R9 and R111 were differentiated together from other cultivars, while the Y3 cultivar was confirmed by the analysis of ISSR data and SCoT data, which also support the grouping of R9 and R111 cultivars. Principle Component Analysis (PCA) of morphological, ISSR, and SCoT data as a combined set differentiated the examined species into four groups in a scatter plot in agreement with their separation in the cluster trees. The diversity profile among the examined C. arabica cultivars proved that R111 and R4 cultivars are highly diverse, while R8 and Y5 cultivars exhibit low diversity. Alpha diversity indices indicated that R9 and R111 cultivars are the most dominant and stable C. arabica cultivars among the examined samples in the study region.

Assessing habitat selection parameters of Arabica coffee using BWM and BCM methods based on GIS

Arabica coffee, as one of the world's three native coffee species, requires rational planning for its growing areas to ensure ecological and sustainable agricultural development. This study aims to establish a decision-making framework using Geographic Information Systems (GIS) and Multi-Criteria Decision-Making (MCDM), with a focus on assessing the habitat suitability of Arabica coffee in Yunnan Province, China. The impacts of climate, topography, soil, and socio-economic factors were considered by selecting 13 criteria through correlation analysis. Indicator weights were determined using the Best-Worst Method (BWM), while weighted processing was conducted using the Base-Criterion Method (BCM). Sensitivity analysis was performed to verify the accuracy and stability of the model. Additionally, several decision models were evaluated to investigate regionalizing Arabica coffee habitats in Yunnan. The results highlighted that minimum temperature during the coldest month is crucial for evaluation purposes. The BWM-GIS model identified suitable areas comprising 13.55% of the total area as most suitable, 27.46% as suitable, and 59.00% as unsuitable, whereas corresponding values for the BCM-GIS model were 9.97%, 30.43%, and 59.59%. Despite employing different decision-making methods, both models yielded similar and consistent results. The suitable areas mainly encompass Dehong, Pu'er, Lincang, Xishuangbanna, Baoshan, southern Chuxiong, eastern Honghe, southern Yuxi, and parts of Wenshan. BWM-GIS achieved an area under curve (AUC) value of 0.891, while BCM-GIS obtained an AUC value of 0.890, indicating the stability and reliability of the models. Among them, the evaluation process of BCM-GIS was simpler and more realistic. Therefore, it has high feasibility and practical value in practical application. The findings from this study provide a significant scientific foundation for optimizing Yunnan Province.

Unveiling the Genetic Diversity and Demographic History of Coffea stenophylla in Sierra Leone Using Genotyping-By-Sequencing

Coffea stenophylla is a rare Coffea species boasting a flavor profile comparable to Arabica coffee (Coffea arabica) and has a good adaptability to lowland tropical climates. This species faces increasing threats from climate change, deforestation, and habitat fragmentation in its West African homeland. Using 1037 novel SNP markers derived from Genotyping-by-Sequencing (GBS), we revealed the presence of three distinct natural populations (mean Fst = 0.176) in Sierra Leone. Evidence of recent bottlenecks and small effective population size (118-140) was found across all three populations, reflecting the impact of recent anthropogenic disturbances on this species. Using a model-flexible inference approach, we unveiled a strong ancient bottleneck approximately 23,000 years ago, coinciding with the last glacial maximum (LGM), followed by post-glacial expansion and divergence into distinct genetic clusters. A comparative analysis between ex situ genebanks and natural populations detected a significant gap in genetic diversity, with two out of three natural populations missing from the ex situ genebank collection. These findings highlight the urgent need to improve conservation practices for C. stenophylla in Sierra Leone. The novel SNP markers developed in this study provided valuable tools to support future efforts in conservation and utilization of C. stenophylla genetic resources in West Africa.

A bitter cup of coffee? Assessing the impact of climate change on Arabica coffee production in Brazil

Brazil, the world's largest producer and exporter of Arabica coffee, faces increasing challenges from climate changes. To maintain the sustainability of this commodity, innovative management techniques will be essential. This study aimed to assess the impact of climate projections, considering two CMIP6 emission scenarios (SSP2-4.5 and SSP5-8.5) on the phenology and yield of Arabica coffee in 36 representative locations across Brazil for the periods 2041-2060, 2061-2080, and 2081-2100. Observed meteorological data from the BR-DWGD (Brazilian Daily Weather Gridded Data) and projected data from CLIMBra (Climate Change Dataset for Brazil) were employed. An agrometeorological model, calibrated for Brazilian conditions, estimated yield and phenology. Results indicate significant impacts on coffee cultivation areas, mainly due to rising temperatures and increased water deficits. Projections also suggest changes in coffee phenology, with anthesis advancing in colder regions and delaying in warmer areas, while maturation timing occurring earlier in all climates. Yield increases from CO₂ fertilization were more pronounced in category C climates (Cfa, Cfb, Cwa, and Cwb), particularly in Cwb climates, reaching 2.9 bags ha-1 (3.7 bags ha-1 with irrigation) under the SSP2-4.5 scenario and 2.5 bags ha-1 (3.5 bags ha-1 with irrigation) under SSP5-8.5. However, higher temperatures and water deficits could cause severe yield losses, especially in Aw climates and under high-emission scenarios, where losses may reach 100 %. Irrigation will play an important role in mitigating yield losses, especially in northern regions such as northern Minas Gerais and Bahia, where yields could exceed 30 bags ha-1. While southern Minas Gerais, São Paulo, and northern Paraná are projected to have the highest yields, these regions also face greater uncertainty and variability. This study underscores the need for adaptive agricultural practices, the development of resilient coffee cultivars, and supportive research policies to ensure the sustainability of coffee farming in the face of climate change.

Analysis of current and future bioclimatic suitability for C. arabica production in Ethiopia

The coffee sector in Ethiopia is the livelihood of more than 20% of the population and accounts more than 25% of the country's foreign exchange earnings. Climate change is expected to affect the climatic suitability of coffee in Ethiopia, and this would have implications for global coffee output, the national economy, and farmers' livelihoods in Ethiopia. The objective of this paper is to assess the current and future impacts of climate change on bioclimatic suitability to C.arbica production in Ethiopia. Based on the current distribution of coffee production areas and climate change predictions from HadGEM2 and CCSM2 models and using the Maximum Entropy (MaxEnt) bioclimatic modeling approach, future changes in climatic suitability for C. arabica were predicted. Coffee production sites in Ethiopia were geo-referenced and used as input in the MAXENT model. The findings indicated that climate change will increase the suitable growing area for coffee by about 44.2% and 30.37% under HadGEM2 and CCSM2 models, respectively, by 2080 in Ethiopia. The study also revealed a westward and northwestward shift in the climatic suitability to C. arabica production in Ethiopia. This indicates that the suitability of some areas will continue with some adaptation practice, whilst others currently suitable will be unsuitable, yet others that are unsuitable will be suitable for arabica coffee production. These findings are intended to support stakeholders in the coffee sector in developing strategies for reducing the vulnerability of coffee production to climate change. Site-specific strategies should be developed to build a more climate resilient coffee livelihood in the changing climate.

Contrasted agronomical and physiological responses of five Coffea arabica genotypes under soil water deficit in field conditions

Introduction

Breeding programs have developed high-yielding Coffea arabica F1-hybrids as an adaptation against adverse conditions associated with climate change. However, theresponse to drought of coffee F1 hybrids has seldom been assessed.

Methods

A trial was established with five C. arabica genotypes (2 pure lines: Catimor and Marsellesa and 3 F1 hybrids: Starmaya, Centroamericano and Mundo Maya) planted under the leguminous tree species Leuceana leucocephala. Coffee growth, yield and physiological responses were assessed under a rain-fed (control: CON) and a rainfall reduction treatment (RR) for 2 years.

Results

The RR treatment created a long-term rainfall deficit in a region with suboptimal temperature similar to those predicted by climate change scenarios. Moreover, the RR treatment reduced soil water content by 14% over 2 successive years of production and increased hydric stress of the three F1-hybrids (leaf water potentials averaged -0.8 MPa under RR compared with -0.4 MPa under CON). Under RR, coffee yields were reduced from 16 to 75% compared to CON. Mundo Maya F1 hybrid was the sole high-yielding genotype apable of sustaining its yield under RR conditions. Our results suggested that its significant increase in fine root density (CON = 300 and RR = 910 root.m-2) and its maintenance of photosynthetic rate (2.5 - 3.5 mmol CO2 m-2 s-1) at high evaporative demand might explain why this genotype maintained high yield under RR condition.

Discussion

This work highlights a possible drought tolerance mechanism in fruit bearing adult coffee trees where the plant fine root number increases to intake more water in order to preserve turgor and sustainphotosynthesis at high ETo and therefore conserves high yield in dry conditions.

Physiological and Agronomical Response of Coffee to Different Nitrogen Forms with and without Water Stress

Nitrogen (N) is the most important nutrient in coffee, with a direct impact on productivity, quality, and sustainability. N uptake by the roots is dominated by ammonium (NH4+) and nitrates (NO3-), along with some organic forms at a lower proportion. From the perspective of mineral fertilizer, the most common N sources are urea, ammonium (AM), ammonium nitrates (AN), and nitrates; an appropriate understanding of the right balance between N forms in coffee nutrition would contribute to more sustainable coffee production through the better N management of this important crop. The aim of this research was to evaluate the influences of different NH4-N/NO3-N ratios in coffee from a physiological and agronomical perspective, and their interaction with soil water levels. Over a period of 5 years, three trials were conducted under controlled conditions in a greenhouse with different growing media (quartz sand) and organic soil, with and without water stress, while one trial was conducted under field conditions. N forms and water levels directly influence physiological responses in coffee, including photosynthesis (Ps), chlorophyll content, dry biomass accumulation (DW), nutrient uptake, and productivity. In all of the trials, the plants group in soils with N ratios of 50% NH4-N/50% NO3-N, and 25% NH4-N/75% NO3-N showed better responses to water stress, as well as a higher Ps, a higher chlorophyll content, a higher N and cation uptake, higher DW accumulation, and higher productivity. The soil pH was significantly influenced by the N forms: the higher the NO3--N share, the lower the acidification level. The results allow us to conclude that the combination of 50% NH4-N/50% NO3-N and 25% NH4-N/75% NO3-N N forms in coffee improves the resistance capacity of the coffee to water stress, improves productivity, reduces the soil acidification level, and improves ion balance and nutrient uptake.

Assessing scale-dependency of climate risks in coffee-based agroforestry systems

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.

Diversity of Leaf Fungal Endophytes from Two Coffea arabica Varieties and Antagonism towards Coffee Leaf Rust

Coffee has immense value as a worldwide-appreciated commodity. However, its production faces the effects of climate change and the spread of severe diseases such as coffee leaf rust (CLR). The exploration of fungal endophytes associated with Coffea sp. has already found the existence of nearly 600 fungal species, but their role in the plants remains practically unknown. We have researched the diversity of leaf fungal endophytes in two Coffea arabica varieties: one susceptible and one resistant to CLR. Then, we conducted cross-infection essays with four common endophyte species (three Colletotrichum sp. and Xylaria sp. 1) and Hemileia vastatrix (CLR) in leaf discs, to investigate the interaction of the endophytes on CLR colonisation success and severity of infection. Two Colletotrichum sp., when inoculated 72 h before H. vastatrix, prevented the colonisation of the leaf disc by the latter. Moreover, the presence of endophytes prior to the arrival of H. vastatrix ameliorated the severity of CLR. Our work highlights both the importance of characterising the hidden biodiversity of endophytes and investigating their potential roles in the plant-endophyte interaction.

Genomic-assisted breeding for climate-smart coffee

Coffee is a universal beverage that drives a multi-industry market on a global basis. Today, the sustainability of coffee production is threatened by accelerated climate changes. In this work, we propose the implementation of genomic-assisted breeding for climate-smart coffee in Coffea canephora. This species is adapted to higher temperatures and is more resilient to biotic and abiotic stresses. After evaluating two populations, over multiple harvests, and under severe drought weather condition, we dissected the genetic architecture of yield, disease resistance, and quality-related traits. By integrating genome-wide association studies and diallel analyses, our contribution is four-fold: (i) we identified a set of molecular markers with major effects associated with disease resistance and post-harvest traits, while yield and plant architecture presented a polygenic background; (ii) we demonstrated the relevance of nonadditive gene actions and projected hybrid vigor when genotypes from different geographically botanical groups are crossed; (iii) we computed medium-to-large heritability values for most of the traits, representing potential for fast genetic progress; and (iv) we provided a first step toward implementing molecular breeding to accelerate improvements in C. canephora. Altogether, this work is a blueprint for how quantitative genetics and genomics can assist coffee breeding and support the supply chain in the face of the current global changes.

Effects of reduced rainfall on coffee quality and volatile composition

BACKGROUND

For a significant subset of agricultural products, including coffee, wine and tea, sensory perceptions of terroir (i.e., characteristic flavors imparted by the growing environment) are tightly linked to the product's value. With increasing climate change, it is critical to understand how shifts in climate, such as changes in precipitation, may interact with management practices (e.g., cultivar selection) to impact sensory quality in terroir-driven crops, and what biochemical compounds may be associated with those impacts. Here, sensory quality and volatile profile composition were assessed for four Arabica coffee (Coffea arabica) cultivars grown in a field experiment where precipitation was reduced by rainout shelters, resulting in 14% lower soil moisture on average.

RESULTS

Our results indicate an overall increase in yield coincident with a moderate decrease in sensory quality in response to reduced precipitation. The presence and magnitude of the sensory quality shift varied by cultivar and sensory attribute, though the Acidity attribute was consistently negatively impacted across cultivars, albeit with a high degree of uncertainty. Additionally, 31 volatile compounds were identified across green coffee samples that were variably impacted by reduced precipitation. Hierarchical clustering analysis identified patterns in volatile clustering associated with sensory attributes suggesting that reduced precipitation effects on sensory attributes may depend on nonlinear combinations of secondary metabolites.

CONCLUSION

Ultimately, our results advance efforts to improve predictions of climate impacts on coffee-growing landscapes and communities and highlight the value of considering indicators of harvest value beyond yield to improve economic forecasts for agroecosystems under climate change.

Climate risks and vulnerabilities of the Arabica coffee in Brazil under current and future climates considering new CMIP6 models

The susceptibility to climate change concerns the coffee market worldwide due to possible severe productivity losses. Brazil is the world's largest Arabica coffee producer and has crops in regions considered persistent climate change hotspots. Our study analyzed risks, vulnerabilities, and susceptibilities to pests and diseases in these regions under current and future climates and outlined adaptive measures to reduce future vulnerabilities. Ten risk indicators based on Arabica coffee requirements were proposed: water supply (Iw), base (TIB) and maximum temperature stresses (TImax), which delimit the temperature range where Arabica coffee grows and productivity is penalized outside both ranges, frost stress (TIfrost), diseases such as rust (DIrust), brown eye spot (DIbrown), and Phoma leaf spot (DIphoma), pests such as coffee berry borer (PIberry), coffee leaf miner (PIminer), and yield loss due to water stress (Iyg). Daily near-surface air temperature (minimum, mean, and maximum), relative humidity, precipitation, and global solar radiation were used from 16 General Circulation Models (GCMs) from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), which are derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in three Shared Socioeconomic Pathways scenarios (SSP245, SSP370 and SSP585). All risk indicators were calculated for the current climate (1995-2014) and projected for the near (2041-2060), intermediate (2061-2080), and far future (2081-2100) in three SSPs and then classified into five risk classes (very low, low, moderate, high and very high). Our results indicated that due to increases in TImax and Iyg indicators, with high to very high risk in area and magnitude, Arabica coffee plantations will be negatively affected and economically unfeasible for about 35 % to 75 % of the studied area throughout the 21st century. Furthermore, the rust and the leaf miner will remain a concern in future climates due to increased temperatures and reduced relative humidity. The future of Arabica coffee crops in Brazil will depend on adopting effective adaptive measures and prudent agricultural strategies to address anticipated risks, including shifting crops to higher altitude areas, introducing more climate-resilient coffee cultivars/varieties, using agroforestry or intercropping systems, planting in closer spacing or higher density planting, and employing dripper or partial root-zone irrigation techniques.

Small RNAs: Promising Molecules to Tackle Climate Change Impacts in Coffee Production

Over the centuries, human society has evolved based on the ability to select and use more adapted species for food supply, which means making plant species tastier and more productive in particular environmental conditions. However, nowadays, this scenario is highly threatened by climate change, especially by the changes in temperature and greenhouse gasses that directly affect photosynthesis, which highlights the need for strategic studies aiming at crop breeding and guaranteeing food security. This is especially worrying for crops with complex phenology, genomes with low variability, and the ones that support a large production chain, such as Coffea sp. L. In this context, recent advances shed some light on the genome function and transcriptional control, revealing small RNAs (sRNAs) that are responsible for environmental cues and could provide variability through gene expression regulation. Basically, sRNAs are responsive to environmental changes and act on the transcriptional and post-transcriptional gene silencing pathways that regulate gene expression and, consequently, biological processes. Here, we first discuss the predicted impact of climate changes on coffee plants and coffee chain production and then the role of sRNAs in response to environmental changes, especially temperature, in different species, together with their potential as tools for genetic improvement. Very few studies in coffee explored the relationship between sRNAs and environmental cues; thus, this review contributes to understanding coffee development in the face of climate change and towards new strategies of crop breeding.

Genetic-environment interactions and climatic variables effect on bean physical characteristics and chemical composition of Coffea arabica

BACKGROUND

The effects of the environment and genotype in the coffee bean chemical composition were studied using nine trials covering an altitudinal gradient [600-1100 m above sea level (a.s.l.)] with three genotypes of Coffea arabica in the northwest mountainous region of Vietnam. The impacts of the climatic conditions on bean physical characteristics and chemical composition were assessed.

RESULTS

We showed that the environment had a significant effect on the bean density and on all bean chemical compounds. The environment effect was stronger than the genotype and genotype-environment interaction effects for cafestol, kahweol, arachidic (C20:0), behenic acid (C22:0), 2,3-butanediol, 2-methyl-2-buten-1-ol, benzaldehyde, benzene ethanol, butyrolactone, decane, dodecane, ethanol, pentanoic acid, and phenylacetaldehyde bean content. A 2 °C increase in temperature had more influence on bean chemical compounds than a 100 mm increase in soil water content. Temperature was positively correlated with lipids and volatile compounds. With an innovative method using iterative moving averages, we showed that correlation of temperature, vapour pressure deficit (VPD) and rainfall with lipids and volatiles was higher between the 10th and 20th weeks after flowering highlighting this period as crucial for the synthesis of these chemicals. Genotype specific responses were evidenced and could be considered in future breeding programmes to maintain coffee beverage quality in the midst of climate change.

CONCLUSION

This first study of the effect of the genotype-environment interactions on chemical compounds enhances our understanding of the sensitivity of coffee quality to genotype environment interactions during bean development. This work addresses the growing concern of the effect of climate change on speciality crops and more specifically coffee. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Estimating the impact on water scarcity due to coffee production, trade, and consumption worldwide and a focus on EU

Coffee consumption is concentrated in the "Global North", while production is mainly located in the "Global South". This trade-driven dependency leads to the exploitation of natural resources. As an export-oriented cash crop, such dependency jeopardizes the existence of a fair distribution of the risks and revenues among all the actors taking part in its globalized supply chain. Coffee trees are mainly rain-fed and only partly irrigated. However, the increasing global coffee demand led to higher consumption of freshwater, which can exacerbate the stressed condition of already stressed water basins. This study quantifies the impact of global coffee consumption on water scarcity, considering the larger system made of producer and consumer countries. The global displacement of such impact is driven by consumer preferences. We found that the US, EU and Asian countries' coffee consumption create impact on water scarcity mostly in African and South American countries, which is also representative of the economic disparities existing behind the global trade flows. Climate change will likely affect the varieties currently preferred by global consumers. Therefore, immediate environmental sustainability actions including water resource preservation are necessary to face current and future challenges.

Integrating temperature-dependent development and reproduction models for predicting population growth of the coffee berry borer, Hypothenemus hampei Ferrari

The coffee berry borer, Hypothenemus hampei Ferrari (Coleoptera: Curculionidae, Scolytinae), is the most devastating insect pest of coffee worldwide. It feeds on the beans inside the berries leading to significant crop losses and unmarketable products. This study aims to model the impact of temperature on H. hampei fecundity and population growth parameters, as a contribution to the prediction of infestation risk. The fecundity was assessed on fresh coffee beans at six constant temperatures in the range 15-30°C, with RH 80 ± 5% and photoperiod 12:12 L:D. Nonlinear models were fitted to the relationship between fecundity and temperature using the ILCYM software. The best fecundity model was combined to development models obtained for immature stages in a previous study in order to simulate life table parameters at different constant temperatures. Females of H. hampei successfully oviposited in the temperature range 15-30°C, with the highest fecundity observed at 23°C (106.1 offspring per female). Polynomial function 8 model was the best fitted to the relationship between fecundity and temperature. With this model, the highest fecundity was estimated at 23°C, with 110 eggs per female. The simulated net reproductive rate (R₀) was maximal at 24°C, with 50.08 daughters per female, while the intrinsic rate of increase (r_m) was the highest at 26°C, with a value of 0.069. Our results will help understand H. hampei population dynamics and develop an ecologically sound management strategy based on a better assessment of infestation risk.

A Systematic Review on the Impacts of Climate Change on Coffee Agrosystems

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.

Coffee Yield Stability as a Factor of Food Security

Yield fluctuation is a major risk in all agricultural sectors, and it influences Goal 2 (food security) of the UN SDGs. Yield fluctuations are expected due to climate change, risking stable coffee supplies, and compromising coffee-exporting countries' ability to earn revenue to pay for food imports. Technology minimizing yield fluctuations is crucial for food security and for coffee farmers to earn a stable income. Fluctuations are small if yields remain close to the mean yield trends. In this study, the coffee yields of major producers are analyzed, together with zonal temperature data, to see where coffee is grown with stable technology under rising temperatures; thus, we demonstrate the advantages of the Yield Stability Index (YSI) over traditional stability measurements in guiding policy formulation and managerial decisions. The Yield Stability Index (YSI) is applied for 1961-1994 and 1995-2020, for the world's 12 major coffee-producing countries. The YSI indicates that of the 12 countries, only Indonesia, Honduras, and Mexico maintain stable yield levels, while Brazil and Vietnam considerably improve their yield stability, which traditional stability measures cannot grasp. Country-wise differences exist in environmental vulnerability and adaptability, with implications for food security. The novelty is the application of the YSI, and the connection between yield stability, climate change, and food security.

Climate Smart Agriculture Implementation on Coffee Smallholders in Indonesia and Strategy to Accelerate

Sustainable coffee production is significantly threatened by climate change. While implementing CSA practices offers numerous benefits, adoption rates remain low. Coffee plantations are dominated by smallholders and located in rural areas, making them more complex and requiring a comprehensive analysis and intervention. This study used an exploratory approach to assess farmers’ preferences for CSA practices, identify barriers to implement, and design a support system model. The investigation focused on Arabica and Robusta farmers, with case studies from two Indonesian production centres. Preferences assessment used conjoint analysis, barriers evaluation used Mann–Whitney analysis, model development used synthetic approaches, and priority analysis used the Analytical Hierarchy Process. The study revealed that diversification is more desirable than cultivation, soil management, and water management. Arabica farmers preferred intercropping with annual crops, whereas Robusta farmers preferred perennials crops. Robusta farmers assessed that agricultural inputs, such as labor, capital, climatic data, and farm equipment and machinery, existed as barriers. However, these represent a lesser issue for Arabica farmers. We proposed agricultural innovation support system, consisting of innovation support facilities and services, as a comprehensive support system model to accelerate CSA implementation. Further analysis showed that the priority strategy for Arabica farmers is support services that focus on network development, while for Robusta farmers is support facilities that focus on climate information system development.

Ecological and genomic vulnerability to climate change across native populations of Robusta coffee (Coffea canephora)

The assessment of population vulnerability under climate change is crucial for planning conservation as well as for ensuring food security. Coffea canephora is, in its native habitat, an understorey tree that is mainly distributed in the lowland rainforests of tropical Africa. Also known as Robusta, its commercial value constitutes a significant revenue for many human populations in tropical countries. Comparing ecological and genomic vulnerabilities within the species' native range can provide valuable insights about habitat loss and the species' adaptive potential, allowing to identify genotypes that may act as a resource for varietal improvement. By applying species distribution models, we assessed ecological vulnerability as the decrease in climatic suitability under future climatic conditions from 492 occurrences. We then quantified genomic vulnerability (or risk of maladaptation) as the allelic composition change required to keep pace with predicted climate change. Genomic vulnerability was estimated from genomic environmental correlations throughout the native range. Suitable habitat was predicted to diminish to half its size by 2050, with populations near coastlines and around the Congo River being the most vulnerable. Whole-genome sequencing revealed 165 candidate SNPs associated with climatic adaptation in C. canephora, which were located in genes involved in plant response to biotic and abiotic stressors. Genomic vulnerability was higher for populations in West Africa and in the region at the border between DRC and Uganda. Despite an overall low correlation between genomic and ecological vulnerability at broad scale, these two components of vulnerability overlap spatially in ways that may become damaging. Genomic vulnerability was estimated to be 23% higher in populations where habitat will be lost in 2050 compared to regions where habitat will remain suitable. These results highlight how ecological and genomic vulnerabilities are relevant when planning on how to cope with climate change regarding an economically important species.

Interactions between Geomorphology and Production Chain of High-Quality Coffee in Costa Rica

High-altitude coffee has an international reputation due to its high quality, especially in countries with a long production history, such as Costa Rica. Specific geographical characteristics determine the regions where high-altitude coffee can be cultivated. Over the last two decades, new production conditions have promoted the growth of smallholder coffee farms in the Upper Buenavista Catchment (UBC) in the South of Costa Rica. To understand this phenomenon’s process, we initially performed a detailed geomorphological mapping of the high-elevation production sites in the UBC. Then, we used remote sensing to determine the coffee land cover (2005, 2012, and 2018) to compare their landforms. Furthermore, we analyzed the production–processing–market chain that has promoted coffee plantations since 2005. Our results show that coffee farmers chose more unstable and erosive areas with short-term production prospects to cultivate premium-priced coffee. Moreover, farmers have changed their role in the coffee sector, evolving from small producers to entrepreneurs with specialized knowledge. These actions may reduce economic risks and improve the household incomes of smallholder coffee producers. However, limited research has been conducted along the tropics about the relationships between landforms, socioeconomic drivers, and high-altitude coffee yield. Therefore, our results are essential to present geomorphology and applied geography as baselines in land-use planning for agricultural landscapes.

Heterogeneous effects of climatic conditions on Andean bean landraces and cowpeas highlight alternatives for crop management and conservation

The use and conservation of agrobiodiversity have become critical to face the actual and future challenges imposed by climate change. Collecting phytogenetic resources is a first step for their conservation; however, the genetic material must be analysed to understand their potential to improve agricultural resilience and adaptation to the new climatic conditions. We have selected nine Phaseolus vulgaris, one P. lunatus and two Vigna unguiculata landraces from two different climatic backgrounds of the Andean region of South Ecuador and one P. vulgaris commercial cultivar, and we grew them under two different conditions of temperature and humidity (open field and greenhouse). Then, we recorded data for 32 characters of plant architecture, flower and fruit characteristics and yield, and 17 events in the phenology of the plants. We analysed the impact of treatment on species, climatic background, and each of the landraces, and identified both characters and landraces that are mostly affected by changes in their environmental conditions. Overall, higher temperatures were benign for all materials except for two P. vulgaris landraces from cold background, which performed better or developed faster under cold conditions. Finally, we calculated a climate resilience landrace index, which allowed us to classify the landraces by their plasticity to new environmental conditions, and found heterogeneous landrace susceptibility to warmer conditions. Two P. vulgaris landraces were highlighted as critical targets for conservation.

Modeling coffee (Coffea arabica L.) climate suitability under current and future scenario in Jimma zone, Ethiopia

Climate suitability is important for coffee (Coffea arabica L.) production in climate variability-prone regions like Ethiopia. The aim of this study was to assess the current and future climate suitability for the species in the Jimma zone under moderate (RCP4.5) and worst (RCP8.5) climate change scenarios. Field surveys and Worldclim and Paleoclim databases were used to capture 224 C. arabica species' location points and 9 bioclimatic data, respectively. The MaxEnt model with integration of ArcGis was used to simulate and characterize these data. The diagnostic outcome of the model showed that the anticipated climate change will increase the areas of suitability in the first and third coffee sub-zones, while there will be a decrease in the second sub-zone. Net suitability under the RCP4.5 would be decreased by 4.75 and 6.09% in the 2050s and 2070s, respectively. Indeed, under the RCP8.5, total suitability will be expected to be increased by 2.52% and 2.25% in the 2050s and 2070s, respectively. For the 2050s and 2070s, the suitability gap between RCP4.5 and RCP8.5 was estimated to be 401 km² and 1567 km², respectively. To summarize, with the exemption of RCP 8.5 within the 2070s, the suitability would be improved and come up short in all circumstances. To keep Arabica coffee in its original habitat, we suggest that the entire climate change adjustment procedures that are prearranged under the RCP4.5 ought to be executed to sustain the crop trees in its origin. Otherwise, moving the crop plant from impeded areas to suitable ones is crucial.

The Coffee Compromise: Is Agricultural Expansion into Tree Plantations a Sustainable Option?

In tropical regions, land-use pressures between natural forest, commercial tree plantations, and agricultural land for rural communities are widespread. One option is to increase the functionality of commercial plantations by allowing agroforestry within them by rural communities. Such land-sharing options could address wider societal and environmental issues and reduce pressure on natural forest. To investigate the trade-offs involved, we used InVEST to model the ecosystem services provided by growing coffee under commercial pine plantations in Indonesia against other land-use options. Pine–coffee agroforestry provided worse supporting and regulating services (carbon, sediment and nitrogen retention, catchment runoff) than natural forest; however, it provided greater provisioning services (product yield) directly to smallholders. Converting pine monoculture into pine-coffee agroforestry led to increases in all ecosystem services, although there was an increased risk to water quality. Compared with coffee and root crop monocultures, pine–coffee agroforestry provided higher levels of supporting and regulating services; however, product yields were lower. Thus, opening up pine plantations for agroforestry realises additional income-generating opportunities for rural communities, provides wider ecosystem service benefits, and reduces pressure for land-use change. Lower smallholder yields could be addressed through the management of shade levels or through Payments for Ecosystem Services schemes.

Climate Change Impact on Peruvian Biomes

The biodiversity present in Peru will be affected by climatic and anthropogenic changes; therefore, understanding these changes will help generate biodiversity conservation policies. This study analyzes the potential distributions of biomes (B) in Peru under the effects of climate change. The evaluation was carried out using the random forest (RF) method, six bioclimatic variables, and digital topography for the classification of current B in Peru. Subsequently, the calibrated RF model was assimilated to three downscaled regional climate models to project future B distributions for the 2035–2065 horizon. We evaluated possible changes in extension and elevation as well as most susceptible B. Our projections show that future scenarios agreed that 82% of current B coverage will remain stable. Approximately 6% of the study area will change its current conditions to conditions of higher humidity; 4.5% will maintain a stable physiognomy, but with an increase in humidity; and finally, 6% will experience a decrease in humidity but maintain its appearance. Additionally, glaciers and swamps are indicated as the most vulnerable B, with probable losses greater than 50% of their current area. These results demonstrate the need to generate public policies for the adaptation and mitigation of climate effects on B at a national scale.

Expected global suitability of coffee, cashew and avocado due to climate change

Coffee, cashew and avocado are of high socio-economic importance in many tropical smallholder farming systems around the globe. As plantation crops with a long lifespan, their cultivation requires long-term planning. The evaluation of climate change impacts on their biophysical suitability is therefore essential for developing adaptation measures and selecting appropriate varieties or crops. In this study, we modelled the current and future suitability of coffee arabica, cashew and avocado on a global scale based on climatic and soil requirements of the three crops. We used climate outputs of 14 global circulation models based on three emission scenarios to model the future (2050) climate change impacts on the crops both globally and in the main producing countries. For all three crops, climatic factors, mainly long dry seasons, mean temperatures (high and low), low minimum temperatures and annual precipitation (high and low), were more restrictive for the global extent of suitable growing regions than land and soil parameters, which were primarily low soil pH, unfavourable soil texture and steep slopes. We found shifts in suitable growing regions due to climate change with both regions of future expansion and contraction for all crops investigated. Coffee proved to be most vulnerable, with negative climate impacts dominating in all main producing regions. For both cashew and avocado, areas suitable for cultivation are expected to expand globally while in most main producing countries, the areas of highest suitability may decrease. The study reveals that climate change adaptation will be necessary in most major producing regions of all three crops. At high latitudes and high altitudes, however, they may all profit from increasing minimum temperatures. The study presents the first global assessment of climate change impacts on cashew and avocado suitability.

Multiple pathways towards achieving a living income for different types of smallholder tree-crop commodity farmers

Many sources indicate that smallholder tree-crop commodity farmers are poor, but there is a paucity of data on how many of them are poor and the depth of poverty. The living income concept establishes the net annual income required for a household in a place to afford a decent standard of living. Based on datasets on smallholder cocoa and tea farmers in Ghana, Ivory Coast and Kenya and literature, we conclude that a large proportion of such farmers do not have the potential to earn a living income based on their current situation. Because these farmers typically cultivate small farm sizes and have low capacity to invest and to diversify, there are no silver bullets to move them out of poverty. We present an assessment approach that results in insights into which interventions can be effective in improving the livelihoods of different types of farmers. While it is morally imperative that all households living in poverty are supported to earn a living income, the assessment approach and literature indicate that focussing on short- to medium-term interventions for households with a low likelihood of generating a living income could be: improving food security and health, finding off-farm and alternative employment, and social assistance programmes. In the long term, land governance policies could address land fragmentation and secure rights. Achieving living incomes based on smallholder commodity production requires more discussion and engagement with farmers and their household members and within their communities, coordination between all involved stakeholders, sharing lessons learnt and data.

Climate Change and Coffee Quality: Systematic Review on the Effects of Environmental and Management Variation on Secondary Metabolites and Sensory Attributes of Coffea arabica and Coffea canephora

Climate change is impacting crop performance and agricultural systems around the world with implications for farmers and consumers. We carried out a systematic review to synthesize evidence regarding the effects of environmental factors associated with climate change and management conditions associated with climate adaptation on the crop quality of a culturally-relevant perennial crop, coffee (Coffea arabica and Coffea canephora). Seventy-three articles were identified that addressed the study's research question including 42 articles on environmental factors, 20 articles on management conditions, and 11 articles on both. While variation was found between studies, findings highlight that coffee quality is vulnerable to changes in light exposure, altitude, water stress, temperature, carbon dioxide, and nutrient management. Both increases as well as decreases were found in secondary metabolites and sensory attributes that determine coffee quality in response to shifts in environmental and management conditions. The most consistent evidence identified through this systematic review includes the following two trends: (1) increased altitude is associated with improved sensory attributes of coffee and; (2) increased light exposure is associated with decreased sensory attributes of coffee. Research gaps were found regarding the effects of shifts in carbon dioxide, water stress, and temperature on the directionality (increase, decrease, or non-linear) of coffee quality and how this varies with location, elevation, and management conditions. This systematic review further identified the following research needs: (1) long-term studies that examine the interactive effects of multiple environmental factors and management conditions on coffee quality; (2) studies that examine the interaction between sensory attributes and secondary metabolites that determine coffee quality and; (3) studies on the feasibility of various climate-adaptation strategies for mitigating the effects of climate change on coffee quality. Evidence-based innovations are needed to mitigate climate impacts on coffee quality toward enhanced sustainability and resilience of the coffee sector from farm to cup.

Breeding for the Main Agricultural Farming of Arabica Coffee

So far, the main Arabica coffee breeding programmes in Latin America have focused on the selection of varieties adapted to intensive full-sun farming systems. Meanwhile, little attention has been paid to breeding varieties specifically adapted to shade, which is the main characteristic of agroforestry systems (AFS). Yet the specialty coffee sector is currently expanding and seeking specific sensory qualities related to exotic varieties and no breeding programme exists to create new varieties for this type of market. Two trials were set up: one in full sun and the other under shade. F1 hybrids and their parents (pure lines and Ethiopian accessions) were studied in a factorial-crossing design to measure tree volume, yield (3 years), bean size, the bean NIRS signature and the final cupping score. Bean size and the final cupping score seemed to be relatively unaffected by shading. Strong maternal heritability was observed for bean size. In the trials, F1 hybrids produced “75–80%” more than the maternal lines and “40–50%” more than the male parents in the shade trial and in the full-sun trial, respectively. By choosing the F1 hybrid, it is possible to increase productivity under both shade and full sun while simultaneously achieving good sensory qualities. Selecting a F1 hybrid for “specialty coffee” seems exceptional. This raises a fundamental issue concerning the maternal heritability of seed biochemical composition. We conclude that selection under shade is essential for the selection of varieties adapted to AFS.

Regional Climate Models Validation for Agroclimatology in Romania

Regional climate projections are widely used in impact studies such as adaptations in agronomy. The big challenge of the climate modeling community is to serve valuable instructions regarding the reliability of these simulations to encourage agronomists to use this kind of information properly. The study validates 15 high-resolution ensembles from the Coordinated Regional Climate Downscaling Experiment-European Domain (EURO-CORDEX) for maximum temperature, minimum temperature, and precipitation to fulfill this task. Three evaluation metrics are calculated (mean absolute error, root mean square error, and correlation) for the means and the 5th and 95th percentiles. The analyses are elaborated for annual and monthly means and the vegetation periods of maize and winter wheat. Only arable lands are considered to exclude the effects of the topography. Furthermore, an ensemble selection is applied based on the evaluation metrics to reduce the data use. The five models with the best performance in the case of winter wheat are CNRM-CM5-CLMcom-CCLM4-8-17_v1, MOHC-HadGEM2-ES-IPSL-WRF381P_v1, MOHC-HadGEM2-ES-KNMI-RACMO22E_v2, MOHC-HadGEM2-ES-CLMcom-CCLM4-8-17_v1, and MPI-M-MPI-ESM-LR-KNMI-RACMO22E_v1. In the case of the vegetation period of maize, the models with the best skills are MPI-M-MPI-ESM-LR-KNMI-RACMO22E_v1, CNRM-CM5-IPSL-WRF381P_v2, MPI-M-MPI-ESM-LR-SMHI-RCA4_v1a, MOHC-HadGEM2-ES-IPSL-WRF381P_v1, and MOHC-HadGEM2-ES-KNMI-RACMO22E_v2. Quantifying the errors in climate simulations against observations and elaborating a selection procedure, we developed a consistent ensemble of high time and space resolution climate projections for agricultural use in Romania.

Quantifying the Annual Cycle of Water Use Efficiency, Energy and CO2 Fluxes Using Micrometeorological and Physiological Techniques for a Coffee Field in Costa Rica

Coffee is one of the most commonly traded agricultural commodities globally. It is important for the livelihoods of over 25 million families worldwide, but it is also a crop sensitive to climate change, which has forced producers to implement management practices with effects on carbon balance and water use efficiency (WUE) that are not well understood due to data scarcity. From this perspective, we propose crop canopy coupling to the atmosphere (Ώ) as an index of resilience and stability. We undertook an integrated observational approach for the scaling-up of measurements along the soil–plant–atmosphere continuum at different stages of the coffee crop phenological cycle. Additionally, we develop this perspective under pronounced climatic seasonality and variability, in order to assess carbon balance, WUE, and agroecosystem resilience in a sun-grown coffee field. Further, we devised a field layout that facilitates the measurement of intrinsic, instantaneous, and actual water use efficiency and the assessment of whether coffee fields differ in canopy structure, complexity, and agronomic management and whether they are carbon sources or sinks. Partitioning soil and canopy energy balances and fluxes in a sun-grown coffee field using eco-physiological techniques at the leaf and whole plant levels (i.e., sap flow and gas exchange), as proposed here, will allow the scaling-up to whole fields in the future. Eddy covariance was used to assess real-time surface fluxes of carbon, gross primary productivity (GPP), and evapotranspiration, as well as components of the energy balance and WUE. The preliminary results support the approach used here and suggested that coffee fields are CO2 sinks throughout the year, especially during fruit development, and that the influence of seasonality drives the surface–atmosphere coupling, which is dominant prior to and during the first half of the rainy season. The estimated WUE showed consistency with independent studies in coffee crops and a marked seasonality driven by the features of the rainy season. A plan for the arborization of the coffee agroecosystem is suggested and the implications for WUE are described. Future comparison of sun- and shade-grown coffee fields and incorporation of other variables (i.e., crop coefficient-KC for different leaf area index (LAI) values) will allow us to better understand the factors controlling WUE in coffee agroecosystems.

Primary Metabolite Profile Changes in Coffea spp. Promoted by Single and Combined Exposure to Drought and Elevated CO2 Concentration

Climate change scenarios pose major threats to many crops worldwide, including coffee. We explored the primary metabolite responses in two Coffea genotypes, C. canephora cv. Conilon Clone 153 and C. arabica cv. Icatu, grown at normal (aCO₂) or elevated (eCO₂) CO₂ concentrations of 380 or 700 ppm, respectively, under well-watered (WW), moderate (MWD), or severe (SWD) water deficit conditions, in order to assess coffee responses to drought and how eCO₂ can influence such responses. Primary metabolites were analyzed with a gas chromatography time-of-flight mass spectrometry metabolomics platform (GC-TOF-MS). A total of 48 primary metabolites were identified in both genotypes (23 amino acids and derivatives, 10 organic acids, 11 sugars, and 4 other metabolites), with differences recorded in both genotypes. Increased metabolite levels were observed in CL153 plants under single and combined conditions of aCO₂ and drought (MWD and SWD), as opposed to the observed decreased levels under eCO₂ in both drought conditions. In contrast, Icatu showed minor differences under MWD, and increased levels (especially amino acids) only under SWD at both CO₂ concentration conditions, although with a tendency towards greater increases under eCO₂. Altogether, CL153 demonstrated large impact under MWD, and seemed not to benefit from eCO₂ in either MWD and SWD, in contrast with Icatu.

Calcium and Potassium Nutrition Increases the Water Use Efficiency in Coffee: A Promising Strategy to Adapt to Climate Change

Coffee (Coffea spp.) represents one of the most important sources of income and goods for the agricultural sector in Central America, Colombia, and the Caribbean region. The sustainability of coffee production at the global and regional scale is under threat by climate change, with a major risk of losing near to 50% of today’s suitable area for coffee by 2050. Rain-fed coffee production dominates in the region, and under increasing climate variability and climate change impacts, these production areas are under threat due to air temperature increase and changes in rainfall patterns and volumes. Identification, evaluation, and implementation of adaptation strategies for growers to cope with climate variability and change impacts are relevant and high priority. Incremental adaptation strategies, including proper soil and water management, contribute to improved water use efficiency (WUE) and should be the first line of action to adapt the coffee crop to the changing growing conditions. This research’s objective was to evaluate at field level over five years the influence of fertilization with calcium (Ca+2) and potassium (K+) on WUE in two coffee arabica varieties: cv. Castillo and cv. Caturra. Castillo has resistance against coffee leaf rust (CLR) (Hemileia vastatrix Verkeley and Brome), while Caturra is not CLR-resistant. WUE was influenced by yield changes during the years by climate variability due to El Niño–ENSO conditions and CLR incidence. Application of Ca+2 and K+ improved the WUE under such variable conditions. The highest WUE values were obtained with an application of 100 kg CaO ha−1 year−1 and between 180 to 230 kg K2O ha−1 year−1. The results indicate that adequate nutrition with Ca+2 and K+ can improve WUE in the long-term, even underwater deficit conditions and after the substantial incidence. Hence, an optimum application of Ca+2 and K+ in rain-fed coffee plantations can be regarded as an effective strategy to adapt to climate variability and climate change.

Organic Farming Practices and Shade Trees Reduce Pest Infestations in Robusta Coffee Systems in Amazonia

Coffee agroforestry systems could reconcile agricultural and environmental objectives. While pests and diseases can reduce yield, their interactions with shade and nutrition have been rarely researched, and are particularly lacking in perennial systems. We hypothesized that intermediate shade levels could reduce coffee pests while excess shade could favor fungal diseases. We hypothesized that organic rather than mineral fertilization would better synchronize with nutrient uptake and higher nutrient inputs would be associated with reduced pest and disease damage due to higher plant vigor, yet effects would be less obvious in shaded plots as coffee growth would be light-limited. Using three-year-old trees of Coffea canephora var. Robusta (robusta coffee) in the Ecuadorian Amazon, we compared a full-sun system with four shading methods creating different shade levels: (1) Myroxylon balsamum; (2) Inga edulis; (3) Erythrina spp.; or, (4) Erythrina spp. plus Myroxylon balsamum. Conventional farming at either (1) moderate or (2) intensified input and organic farming at (3) low or (4) intensified input were compared in a split-plot design with shade as the main plot factor and farming practice as the sub-plot factor. The infestation of the following pests and disease incidences were evaluated monthly during the dry season: brown twig beetle (Xylosandrus morigerus), coffee leaf miner (Leucoptera coffeella), coffee berry borer (Hypothenemus hampei), anthracnose disease (Colletotrichum spp.), thread blight (Pellicularia koleroga), and cercospora leaf spot (Cercospora coffeicola). Coffee berry borer and brown twig beetle infestation were both reduced by 7% in intensified organic treatments compared to intensified conventional treatments. Colonization of coffee berry borer holes in coffee berries by the entomopathogenic fungus Beauveria bassiana was also assessed. Brown twig beetle infestation was significantly higher under full sun than under Inga edulis, yet no other shade effects were detected. We demonstrate for the first time how intensified input use might promote pest populations and thus ultimately lead to robusta coffee yield losses.

Projections of Local Knowledge-Based Adaptation Strategies of Mexican Coffee Farmers

Local knowledge can be a strategy for coping with extreme events and adapting to climate change. In Mexico, extreme events and climate change projections suggest the urgency of promoting local adaptation policies and strategies. This paper provides an assessment of adaptation actions based on the local knowledge of coffee farmers in southern Mexico. The strategies include collective and individual adaptation actions that farmers have established. To determine their viability and impacts, carbon stocks and fluxes in the system’s aboveground biomass were projected, along with water balance variables. Stored carbon contents are projected to increase by more than 90%, while maintaining agroforestry systems will also help serve to protect against extreme hydrological events. Finally, the integration of local knowledge into national climate change adaptation plans is discussed and suggested with a local focus. We conclude that local knowledge can be successful in conserving agroecological coffee production systems.

Hybrid coffee cultivars may enhance agroecosystem resilience to climate change

Anthropogenic climate change is predicted to cause shifts in temperature and precipitation patterns that will be detrimental for global agriculture. Developing comprehensive strategies for building climate resilient agroecosystems is critical for maintaining future crop production. Arabica coffee (Coffea arabica) is highly sensitive to the quantity and timing of precipitation, so alterations in precipitation patterns that are predicted under climate change are likely to be a major challenge for maintaining coffee agroecosystems. We assessed cultivar selection as a potential component of more resilient coffee agroecosystems by evaluating water stress responses among five Arabica coffee cultivars (clonal hybrids H10 and H1 and seedling lines Catuai 44, Catuai, and Villa Sarchi) using a precipitation reduction experiment in the highlands of Tarrazú, Costa Rica. During the first harvest (eighteen months after planting), plants under the rainout treatment had 211 % greater total fruit weight and over 50 % greater biomass than under the control treatment, potentially due to protection from unusually high rainfall during this period of our experiment. At the second harvest (30 months after planting), after a year of more typical rainfall, plants under rainout still produced 66 % more fruit by weight than under control. The magnitude of the responses varied among cultivars where, at the first harvest, H10 and H1 had approximately 92 % and 81 % greater fruit production and 18 % and 22 % greater biomass, respectively, and at the second harvest H10 had 60 % more fruit production than the overall average. Thus, our findings suggest that the hybrid lines H10 and H1 are more resilient than the other cultivars to the stress of high soil moisture. Overall, our results indicate that stress due to higher than average rainfall could impair coffee plant growth and production, and that cultivar selection is likely to be an important tool for maintaining the viability of coffee production, and the resilience of global agroecosystems more generally, under climate change.

Assessment of Potential Climate Change Impacts on Montane Forests in the Peruvian Andes: Implications for Conservation Prioritization

Future climate change will result in profound shifts in the distribution and abundance of biodiversity in the Tropical Andes, and poses a challenge to contemporary conservation planning in the region. However, currently it is not well understood where the impacts of climate disruption will be most severe and how conservation policy should respond. This study examines climate change impacts in the Peruvian Andes, with a specific focus on tropical montane forest ecosystems, which are particularly susceptible to climate change. Using an ensemble of classification models coupled with different climate change scenarios, we estimate high and low potential impacts on montane forest, by projecting which areas will become climatically unsuitable to support montane forest ecosystems by 2070. These projections are subsequently used to examine potential impacts on protected areas containing montane forest. The modeling output indicates that climate change will have a high potential impact on 58% of all montane forests, particularly in the elevation range between 800 and 1200 m.a.s.l. Furthermore, about 64% of montane forests located in protected areas will be exposed to high potential impact. These results highlight the need for Peru’s conservation institutions to incorporate climate change considerations into prevailing conservation plans and adaptation strategies. To adjust to climate change, the adaptive capacity of forest ecosystems in the Peruvian Andes should be enhanced through restorative and preventive conservation measures such as improving forest functions and mitigating deforestation and forest degradation pressures.

Genetic diversity of native and cultivated Ugandan Robusta coffee (Coffea canephora Pierre ex A. Froehner): Climate influences, breeding potential and diversity conservation

Wild genetic resources and their ability to adapt to environmental change are critically important in light of the projected climate change, while constituting the foundation of agricultural sustainability. To address the expected negative effects of climate change on Robusta coffee trees (Coffea canephora), collecting missions were conducted to explore its current native distribution in Uganda over a broad climatic range. Wild material from seven forests could thus be collected. We used 19 microsatellite (SSR) markers to assess genetic diversity and structure of this material as well as material from two ex-situ collections and a feral population. The Ugandan C. canephora diversity was then positioned relative to the species’ global diversity structure. Twenty-two climatic variables were used to explore variations in climatic zones across the sampled forests. Overall, Uganda’s native C. canephora diversity differs from other known genetic groups of this species. In northwestern (NW) Uganda, four distinct genetic clusters were distinguished being from Zoka, Budongo, Itwara and Kibale forests A large southern-central (SC) cluster included Malabigambo, Mabira, and Kalangala forest accessions, as well as feral and cultivated accessions, suggesting similarity in genetic origin and strong gene flow between wild and cultivated compartments. We also confirmed the introduction of Congolese varieties into the SC region where most Robusta coffee production takes place. Identified populations occurred in divergent environmental conditions and 12 environmental variables significantly explained 16.3% of the total allelic variation across populations. The substantial genetic variation within and between Ugandan populations with different climatic envelopes might contain adaptive diversity to cope with climate change. The accessions that we collected have substantially enriched the diversity hosted in the Ugandan collections and thus contribute to ex situ conservation of this vital genetic resource. However, there is an urgent need to develop strategies to enhance complementary in-situ conservation of Coffea canephora in native forests in northwestern Uganda.

Warm nights drive Coffea arabica ripening in Tanzania

Studies have demonstrated that plant phenophases (e.g. budburst, flowering, ripening) are occurring increasingly earlier in the season across diverse ecologies globally. Despite much interest that climate change impacts have on coffee (Coffea arabica), relatively little is known about the driving factors determining its phenophases. Using high-resolution microclimatic data, this study provides initial insights on how climate change is impacting C. arabica phenophases in Tanzania. In particular, we use generalized additive models to show how warming nocturnal temperatures (T_night), as opposed to day-time or maximum temperatures, have a superseding effect on the ripening of coffee and subsequent timing of harvest. A warm night index (WNI), generated from mean nocturnal temperature, permits accurate prediction of the start of the harvest season, which is superior to existing methods using growing degree days (GDD). The non-linear function indicates that a WNI of 15 °C is associated with the latest ripening coffee cherries (adjusted R² = 0.95). As the WNI increases past the inflection point of ~ 16 °C, ripening occurs earlier and progresses more or less linearly at a rate of ~ 17 ± 1.95 days for every 1 °C increase in WNI. Using the WNI will thus not only allow farmers to more accurately predict their harvest start date, but also assist with identifying the most suitable adaptation strategies which may reduce harvest-related costs and buffer potential losses in quality and production.

Evaluation of Land Suitability Methods with Reference to Neglected and Underutilised Crop Species: A Scoping Review

In agriculture, land use and land classification address questions such as "where", "why" and "when" a particular crop is grown within a particular agroecology. To date, there are several land suitability analysis (LSA) methods, but there is no consensus on the best method for crop suitability analysis. We conducted a scoping review to evaluate methodological strategies for LSA. Secondary to this, we assessed which of these would be suitable for neglected and underutilised crop species (NUS). The review classified LSA methods reported in articles as traditional (26.6%) and modern (63.4%). Modern approaches, including multi-criteria decision-making (MCDM) methods such as analytical hierarchy process (AHP) (14.9%) and fuzzy methods (12.9%); crop simulation models (9.9%) and machine learning related methods (25.7%) are gaining popularity over traditional methods. The MCDM methods, namely AHP and fuzzy, are commonly applied to LSA while crop models and machine learning related methods are gaining popularity. A total of 67 parameters from climatic, hydrology, soil, socio-economic and landscape properties are essential in LSA. Unavailability and the inclusion of categorical datasets from social sources is a challenge. Using big data and Internet of Things (IoT) improves the accuracy and reliability of LSA methods. The review expects to provide researchers and decision-makers with the most robust methods and standard parameters required in developing LSA for NUS. Qualitative and quantitative approaches must be integrated into unique hybrid land evaluation systems to improve LSA.

Elevated [CO2] benefits coffee growth and photosynthetic performance regardless of light availability

Despite being evolved in shaded environments, most coffee (Coffea arabica L.) is cultivated worldwide under sparse shade or at full sunlight. Coffee is ranked as greatly responsive to climate change (CC), and shading has been considered an important management strategy for mitigating the harmful CC outcomes on the crop. However, there is no information on the effects of enhanced [CO₂] (eC_a) on coffee performance in response to light availability. Here, we examined how carbon assimilation and use are affected by eC_a in combination with contrasting light levels. For that, greenhouse-grown plants were submitted to varying light levels (16 or 7.5 mol photons m^-2 day^-1) and [CO₂] (ca. 380 or 740 μmol mol^-1 air) over six months. We demonstrated that both high light and eC_a improved growth and photosynthetic performance, independently. Despite marginal alterations in biomass partitioning, some allometric changes, such as higher root biomass-to-total leaf area and lower leaf area ratio under the combination of eC_a and high light were found. Stimulation of photosynthetic rates by eC_a occurred with no direct effect on stomatal and mesophyll conductances, and no signs of photosynthetic down-regulation were found irrespective of treatments. Particularly at high light, eC_a led to decreases in both photorespiration rates and oxidative pressure. Overall, our novel findings suggest that eC_a could tandemly act with shading to mitigate the harmful CC effects on coffee sustainability.

Enhancing Vietnam’s Nationally Determined Contribution with Mitigation Targets for Agroforestry: A Technical and Economic Estimate

The Nationally Determined Contributions (NDCs) of several non-Annex I countries mention agroforestry but mostly without associated mitigation target. The absence of reliable data, including on existing agroforestry practices and their carbon storage, partially constrains the target setting. In this paper, we estimate the mitigation potential of agroforestry carbon sequestration in Vietnam using a nationwide agroforestry database and carbon data from the literature. Sequestered carbon was estimated for existing agroforestry systems and for areas into which these systems can be expanded. Existing agroforestry systems in Vietnam cover over 0.83 million hectares storing a 1346 ± 92 million ton CO2 equivalent including above-, belowground, and soil carbon. These systems could be expanded to an area of 0.93–2.4 million hectares. Of this expansion area, about 10% is considered highly suitable for production, with a carbon sequestration potential of 2.3–44 million ton CO2 equivalent over the period 2021–2030. If neglecting agroforestry’s potential for modifying micro-climates, climate change can reduce the highly suitable area of agroforestry and associated carbon by 34–48% in 2050. Agroforestry can greatly contribute to Vietnam’s 2021–2030 NDC, for example, to offset the greenhouse gas emissions of the agriculture sector.

Coffee Microbiota and Its Potential Use in Sustainable Crop Management. A Review

Intensive coffee production is accompanied by several environmental issues, including soil degradation, biodiversity loss, and pollution due to the wide use of agrochemical inputs and wastes generated by processing. In addition, climate change is expected to decrease the suitability of cultivated areas while potentially increasing the distribution and impact of pests and diseases. In this context, the coffee microbiota has been increasingly studied over the past decades in order to improve the sustainability of the coffee production. Therefore, coffee associated microorganisms have been isolated and characterized in order to highlight their useful characteristics and study their potential use as sustainable alternatives to agrochemical inputs. Indeed, several microorganisms (including bacteria and fungi) are able to display plant growth-promoting capacities and/or biocontrol abilities toward coffee pests and diseases. Despite that numerous studies emphasized the potential of coffee-associated microorganisms under controlled environments, the present review highlights the lack of confirmation of such beneficial effects under field conditions. Nowadays, next-generation sequencing technologies allow to study coffee associated microorganisms with a metabarcoding/metagenomic approach. This strategy, which does not require cultivating microorganisms, now provides a deeper insight in the coffee-associated microbial communities and their implication not only in the coffee plant fitness but also in the quality of the final product. The present review aims at (i) providing an extensive description of coffee microbiota diversity both at the farming and processing levels, (ii) identifying the “coffee core microbiota,” (iii) making an overview of microbiota ability to promote coffee plant growth and to control its pests and diseases, and (iv) highlighting the microbiota potential to improve coffee quality and waste management sustainability.

Shade trees preserve avian insectivore biodiversity on coffee farms in a warming climate

AIM

Coffee is an important export for many developing countries, with a global annual trade value of $100 billion, but it is threatened by a warming climate. Shade trees may mitigate the effects of climate change through temperature regulation that can aid in coffee growth, slow pest reproduction, and sustain avian insectivore diversity. The impact of shade on bird diversity and microclimate on coffee farms has been studied extensively in the Neotropics, but there is a dearth of research in the Paleotropics.

LOCATION

East Africa.

METHODS

We created current and future regional Maxent models for avian insectivores in East Africa using Worldclim temperature data and observations from the Global Biodiversity Information Database. We then adjusted current and future bioclimatic layers based on mean differences in temperature between shade and sun coffee farms and projected the models using these adjusted layers to predict the impact of shade tree removal on climatic suitability for avian insectivores.

RESULTS

Existing Worldclim temperature layers more closely matched temperatures under shade trees than temperatures in the open. Removal of shade trees, through warmer temperatures alone, would result in reduction of avian insectivore species by over 25%, a loss equivalent to 50 years of climate change under the most optimistic emissions scenario. Under the most extreme climate scenario and removal of shade trees, insectivore richness is projected to decline from a mean of 38 to fewer than 8 avian insectivore species.

MAIN CONCLUSIONS

We found that shade trees on coffee farms already provide important cooler microclimates for avian insectivores. Future temperatures will become a regionally limiting factor for bird distribution in East Africa, which could negatively impact control of coffee pests, but the effect of climate change can be potentially mediated through planting and maintaining shade trees on coffee farms.