Search Results (170)

Climate change has increased the vulnerability of coffee farming by affecting the environmental conditions that sustain production. The objective of this study was to analyze how climate change vulnerability has been assessed in coffee farming systems through a systematic review of the scientific literature. The methodology consisted of a systematic search in the Dimensions database using the terms vulnerability, climate change, and coffee. A total of 49 articles were analyzed according to four analytical axes: (1) chronology and institutional origin, (2) study subjects and spatial location, (3) theoretical and methodological approaches, and (4) temporal scale. The results show an increase in research beginning in 2020, led mainly by institutions from the United States and Brazil, which together accounted for 28.8% of the total studies. A high diversity of study subjects was identified, grouped into seven categories and 18 thematic areas, with coffee farmers, households, and production systems being the most prominent, mainly located in Brazil and Nicaragua. Assessments based on the Intergovernmental Panel on Climate Change (IPCC) framework predominated, particularly those using composite indices, climate suitability models, and hybrid approaches combining biophysical and socio-economic variables. The current vulnerability was the dominant temporal scale. The review highlights substantial methodological diversity, spatial concentration of studies, and limited incorporation of prospective scenarios. Full article

The sustainability of Coffea arabica L. production in Oaxaca, Mexico, is increasingly threatened by climate change, biodiversity loss, and pest pressure, along with other factors that undermine the responsiveness of small-scale producers in the state, such as trade restrictions and coffee-related regulatory frameworks. These challenges are particularly acute in mountainous regions like Oaxaca, where coffee cultivation plays a central role in rural livelihoods, cultural identity, and territorial development. Studies demonstrate that localized models are vital for rural improvement, reducing the carbon footprint, and maintaining economic viability. Despite extensive research on agronomic, environmental, and market factors, sustainability strategies for coffee production often remain fragmented and insufficiently integrated. This systematic review used the Scopus Review database, searching by title, abstract, and keywords such as “sustainable coffee production” from 2015 to 2026. A total of 1085 documents were retrieved and processed using VOSviewer software to generate a bibliographic map in which frequently used words are grouped by color to show their relationships. Using Oaxaca as a regional case study, the article synthesizes the key factors influencing coffee productivity and quality, examines the main socio-environmental challenges, and proposes a conceptual framework that integrates agroecosystem management with socioeconomic processes under external climate and market pressures. The proposed framework highlights the central role of agroforestry systems and ecosystem services in improving climate resilience, conserving biodiversity, and supporting quality-oriented value chains. These processes generate feedback loops that influence farmers’ livelihoods, food security, and territorial sustainability. While grounded in the context of Oaxaca, the socio-ecological review and conceptual framework presented here are applicable to other Arabica-producing regions facing similar challenges, providing a structured basis for future research, policy design, and integrated sustainability strategies. Full article

Saudi Arabia’s Arabica coffee is produced almost entirely by smallholder farmers. Although the local production meets only a small share of national consumption, the sector has expanded substantially in recent years under national development initiatives and strategic investment. This study diagnoses the smallholder value chain in Jazan, Asir and Al Baha through a cross-sectional survey of 347 farms in 14 governorates (May–November 2023). Mean green-bean yield was 0.37 kg per tree (median 0.25), which is within the global smallholder Arabica range, and the top 6.5% of the farms exceeded 1 kg per tree. Water scarcity was the leading production constraint (84.9% of respondents). This prompted a separate, exploratory irrigation survey of 57 Jazan farms (January 2024), which found true drip irrigation to be about 50% more water-productive than basin or stripped-emitter systems, a finding that would need confirmation through controlled trials. Although membership is self-selected and unmeasured confounding cannot be excluded, farmers who belonged to a producer organisation consistently performed better across the value chain. Their yields were higher (0.40 versus 0.23 kg per tree, p = 0.003), and this advantage held after adjustment for farm and farmer characteristics (+78%, 95% CI + 33 to +137). In addition, 24% of members undertook on-farm roasting against 3.9% of non-members. These findings point to wider producer-organisation coverage, more efficient irrigation and improved post-harvest handling as priority areas for intervention and future evaluation. Full article

Coffee cultivation offers benefits such as biodiversity conservation, economic sustenance for farmers, and health advantages. This quantitative, microsociological, and applied study, with a non-experimental, cross-sectional design and explanatory level, aimed to evaluate the impact of agronomic practices and socioeconomic factors on coffee yields among farmers in the Monzón Valley (Huánuco, Peru). Using the hypothetico-deductive method, logit and probit regression models were employed, employing an ordered probabilistic model with multiple responses. Data were collected through simple random sampling, surveying 152 producers. The probit model proved most suitable for explaining yield levels, classified as low (<0.60 Tn/ha/year), medium (0.61–1.00), and high (1.01–2.20). The most influential indicators were biological and cultural control, crop age, organic farming practices, altitude, cultivation of more than one variety, seed selection, monetary income, and farmer experience. The study concludes that the probit model adequately explains the relationship between the agronomic and socioeconomic variables that determine yield. The findings provide valuable evidence for the design of local agricultural policies and producer support programs. Furthermore, the study explicitly contributes to the advancement of the Sustainable Development Goals (SDGs), particularly SDG 1 (No Poverty), SDG 8 (Decent Work and Economic Growth), and SDG 12 (Responsible Consumption and Production), by identifying factors that link sustainable coffee productivity with the socioeconomic well-being of farming communities. Full article

Coffee is a major export earner for Uganda, raking in over USD 2 billion in 2025. The global price of coffee is tagged to the perceived quality in the cup which in turn is affected by the chemical composition of the green bean. Breeding for market-preferred Arabica coffee varieties is a major objective of coffee breeding programs. Determination of coffee bean chemical constituents is routinely done through expensive, slow and tedious laboratory procedures, making it unsustainable of resource-limited public sector coffee breeding programs. Here, we demonstrate the use of near-infrared spectroscopy (NIRS) and the machine learning algorithms partial least squares (PLS), random forest (RF) and support vector machine (SVM) for the prediction of caffeine, protein and trigonelline in Arabica coffee. NIRS provides a fast, accurate and reliable method of simultaneously predicting multiple sample constituents. Ripe coffee cherries were picked from 172 farmers’ fields, air dried in the laboratory at room temperature and processed to green beans. NIRS spectra were taken on the milled green bean at 400–2500 nm, with a 0.5 nanometer (nm) step. Reference data for caffeine, protein and trigonelline were collected on the same sample scanned with NIRS. A set of 12 spectral pretreatments were applied prior to making calibrations with the PLS, RF and SVM algorithms and 70% of the data as a training set and 30% as a test set. Caffeine content of reference samples ranged from 1.94–3.0 g/100 g, protein content ranged from 11.16–15.94% while trigonelline ranged from 0.94–1.23 g/100 g. The best calibrations for all algorithms and analytes were obtained using raw (untreated) spectra, which gave the same results as the Savitzky–Golay (SG) pretreatment. For caffeine, the best model (R²p = 0.89, RMSEP = 0.007, RPD = 3.34) was obtained with the SVM algorithm, while for protein, the best model (R²p = 0.98, RMSEP = 0.14, RPD = 6.92) was obtained using the PLS algorithm. Finally, for trigonelline, all three models had very high prediction accuracies (R²p = 0.98–0.99, RMSEP = 0.007–0.009, RPD = 8.53–10.52). Collectively, these results demonstrate the potential of using NIRS for rapid and simultaneous prediction of coffee green bean constituents to aid selection decisions. Full article

Shaded Arabica coffee production in agroforestry systems, as opposed to full-sun production, is a nature-based solution improving soil water balance, reducing heat exposure of coffee plants, and supporting sustainable forest management as opposed to deforestation. For this coffee production system in Mexico, which is dominated by smallholders as the largest group of coffee producers, we herein analyze current and estimate future yields. For the first time, to our best knowledge, this is done with a process-based coffee agroforestry model CAF2014 that we adapted for geo-spatial applications and named CAF2014-Rhaobi. Modeling of smallholders’ representative management is based on tree thinning, pruning frequency, and nitrogen supply through fertilizer and litter from nitrogen-fixing shade trees. Modeled historical yields generally agree with the reported numbers; however, there are discrepancies explained by modeling assumptions and simplifications. While shade trees help sustain coffee production, the projected drop in yields under present management is about 30% at the end of the century compared to the present as estimated using an ensemble of CMIP6 SSP5-8.5 climate projections. Economic analysis for three typologies of Mexican small coffee producers (conventional low, high-efficiency, and organic) reveals the major role of farmer associations and organic coffee price premiums in making production economically sustainable. This emphasizes the need for innovative marketing approaches and policies supporting farmers opting for certified production. Full article

This research examines stakeholders’ perspectives in Colombia and Switzerland on blockchain traceability systems in the coffee industry. Adopting the Unified Theory of Acceptance and Use of Technology (UTAUT) as an interpretive framework, the study analyzes these perceptions through the constructs of performance expectancy, effort expectancy, social influence, and facilitating conditions. Using a quantitative cross-sectional design with an exploratory scope, we survey 360 participants, comprising 60 coffee supply chain companies and 300 consumers. Results reveal that 78.3% of stakeholders consider traceability essential, yet only 46.7% are familiar with blockchain. Stakeholders identify three primary benefits: improved transparency (91.7%), fraud prevention (88.3%), and enhanced security (86.7%). However, significant barriers persist: high implementation costs (95%), limited expertise (91.7%), and lack of awareness (93.3%). Geographic differences emerge: Colombian stakeholders prioritize cost reduction and fraud prevention, while Swiss participants focus on data management and privacy protection. Among consumers, 62.7% express interest in provenance information, 56.7% are willing to pay for blockchain systems, and 59% are interested in tipping farmers. The study classifies benefits and drawbacks across nine dimensions, providing a comprehensive framework for understanding the multidimensional impacts of blockchain on the coffee supply chain. Full article

Conventional sterilization methods limit smallholder mushroom cultivation in PNG. This study evaluated alternative disinfection approaches for Pleurotus ostreatus (P. ostreatus) using coffee parchment and Cenchrus fungiraminus (C. fungigraminus) as substrates. After screening 20 strains, the superior strain PXF9 was selected. Three methods were compared: (1) Complete Sterilization with Aseptic Inoculation (CSAI) applied to T1 (experimental) and T2 (sawdust control); (2) Short Sterilization with Open Inoculation (SSOI) applied to T3 (experimental) and T5 (control); and (3) Non sterilization with Open Inoculation (NSOI) applied to T4 (experimental). CSAI (T1) achieved the highest yield (3985.26 ± 2.00 ^d g/24 bags), biological efficiency (83.03%), protein (28.44 g/100 g), and profit (14.76 USD), with the fastest colonization (21 days). SSOI (T3) produced the largest fruiting bodies; NSOI (T4) had the lowest heavy metal levels. SSOI and NSOI were economically beneficial (9.88 and 5.96 UDS per 24 bags). Bioactive compounds (e.g., naringenin, ergosterol peroxide), were detected across treatments. While CSAI maximizes productivity, SSOI and NSOI offer low-cost alternatives for resource-limited farmers. Full article

Coffee tourism has emerged as a significant niche within community-based tourism development across the Global South, promising economic diversification and cultural preservation. Yet the human resource foundations of this sector remain under-theorized relative to those of marketing and the supply chain. This study examines the human resource challenges confronting coffee tourism development in Bajawa, Flores, Indonesia—an emerging destination strategically positioned within national tourism priorities. Drawing on qualitative research including in-depth interviews with 42 informants (coffee farmers, tourism workers, village officials, private sector facilitators, and NGO representatives), document analysis, and field observations, the study suggests that workforce sustainability in coffee tourism is undermined by three intersecting dynamics: precarious labor regimes characterized by casualization and income instability; significant skill gaps across the coffee–tourism nexus; and institutional fragmentation wherein state programs, private sector initiatives, and customary labor systems operate without coherent coordination. The findings highlight that human resource challenges are not merely technical capacity deficits but are produced through informal labor arrangements, unequal power relations, and governance fragmentation. The study contributes theoretically by extending precarity scholarship to emerging destination contexts and proposing an integrative framework linking labor regimes, competency development, and workforce sustainability. Full article

This study seeks to explain how structural factors, farmers’ capacity, technology adoption, and market orientation jointly shape productivity in smallholder Arabica coffee farming. Primary data were collected from 152 Arabica coffee farmers in Kerinci Regency, Jambi Province, Indonesia, between June and August 2025 and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that infrastructure and government policy have positive and significant effects on technology adoption. However, infrastructure does not directly affect productivity, whereas government policy shows a negative, significant effect on productivity, suggesting a possible misalignment between policy support and farmers’ practical production needs. In contrast, digital literacy and market orientation are found to be the main determinants that significantly enhance productivity. Technology adoption does not have a significant effect, either directly or as a mediating variable, suggesting a gap between adoption and utilization at the farm level. The moderation analysis reveals that market orientation strengthens the relationship between digital literacy and productivity. Overall, these findings emphasize that productivity improvement is not solely determined by technology, but is more strongly influenced by farmers’ capacity and market orientation. Full article

Coffee production, particularly in shade-grown farms, plays a crucial role in the livelihoods of Mexican farmers. Shade-grown coffee systems are also recognised for supporting biodiversity and enhancing carbon capture. Nevertheless, the geographical heterogeneity of Mexico makes the selection of tree species in these agroforestry systems challenging. This study develops region-specific priority lists to conserve biodiversity, improve carbon capture, and support the livelihoods of producers across nine coffee-growing regions within the state of Chiapas. We identified the tree species distributed in each region using an extensive dataset from the Global Biodiversity Information Facility and a novel approach that enhanced spatial resolution of the prioritisation process, despite biases in collection efforts. A set of 23 criteria, including conservation status, carbon content, and documented uses by local communities, was compiled from databases and literature reviews and used to calculate a priority score for each species. Based on these scores, a list of 20 recommended species was generated for each region. However, additional participatory validation is needed to translate these lists into practice. A similarity analysis revealed that geographically proximate regions shared similar species composition. Overall, this study provides a transparent framework for regionally tailored shade-tree selection to inform conservation and restoration planning in coffee agroforestry landscapes. Full article

Coffea, a plant species of significant agricultural value used in coffee production, is a key commodity that supports the livelihoods of millions of people worldwide. However, coffee cultivation faces substantial threats from various pathogens, including Pseudomonas coronafaciens pv. garcae (Pcg), the causative agent of bacterial blight. This pathogen compromises coffee plant health, leading to reduced yields and plant death and impacting farmers and large-scale producers. Understanding the mechanisms underlying resistance to Pcg in the leaves of the resistant IAC 2211-6 Coffea arabica accession is crucial for developing effective control strategies. This study aimed to identify candidate biomarkers of resistance by comparing the leaf metabolome of (i) the resistant IAC 2211-6 and the susceptible IAC 125 RN Coffea arabica accessions and (ii) Pcg-infected and uninfected leaves. Untargeted metabolomics revealed distinct metabolic profiles between accessions. Flavonoids were more abundant in susceptible leaves. In contrast, resistant leaves showed increased levels of pipecolic acid ethyl ester, a structural derivative of a key systemic acquired resistance signal, and spiropreussione B, a compound associated with fungal endophytes. These findings highlight candidates potentially linked to resistance and suggest that systemic signaling and beneficial microbial interactions may contribute to resilience. Full article

Tanniferous forages, leaves and pods from legume trees can be used as feed additives to reduce enteric CH₄ in tropical regions of the world where smallholder farmers cannot afford to purchase commercial anti-methanogenic feed additives. The present work aimed to evaluate the impact of small doses of Gliricidia sepium (G. sepium) alone or in combination with coffee pulp (COP) on enteric CH₄ production in cattle. A 4 × 4 Latin square experimental design was used, where four Holstein x Charolais heifers of 390 ± 50 kg body weight were used. Four treatments were evaluated, with G. sepium (GSep) and COP used as additives. The control treatment (CON) had no additives and was offered ad libitum, the COP treatment contained 1.0 kg DM d⁻¹ of COP, the treatment with G. sepium contained 0.342 kg DM d⁻¹ of this plant, and the treatment with both plants (COP + GSep) had 0.505 and 0.171 kg DM d⁻¹, respectively. The lowest CH₄ production was observed for the COP + GSep treatment, followed by GSep, with 17% and 14.2% less CH₄, respectively, compared to the CON treatment (p < 0.05). We concluded that supplementation with G. sepium, alone or in combination with COP, can be used as part of a strategy to mitigate enteric CH₄ production in tropical cattle production systems. To the best of our knowledge, this is the first time two natural additives have been used together to reduce enteric methane in cattle fed a low-quality forage. Full article

Climate change is increasingly threatening the sustainability of coffee farming in northern Peru, particularly in the Amazonas region, where coffee cooperatives serve as vital socioeconomic hubs for thousands of families. This study analyzed historical climate data from 1979 to 2024 to project trends up to 2030, integrating local perceptions from coffee producers to identify trends, anomalies, and future scenarios within four coffee cooperatives in northern Peru. We examined variables such as precipitation, temperature, evapotranspiration, and wind speed using nonparametric statistical analyses and SARIMA time-series models. The findings indicate a steady increase in maximum and average temperatures, alongside greater irregularity in precipitation. Specifically, the Bagua Grande and COOPARM cooperatives are experiencing precipitation deficits, while the Alta Montaña and Ocumal cooperatives are facing excess rainfall. Additionally, we project an increase in evapotranspiration by 2030. Surveys conducted with coffee growers reveal a consensus regarding irregular rainfall patterns; however, there is less recognition of the rising temperature trends. This discrepancy emphasizes the importance of combining scientific data with local knowledge to develop more effective adaptation strategies at the cooperative level. We conclude that enhancing climate training and cooperative management is essential for improving the resilience of regional coffee farming. Full article

To promote a sustainable coffee industry, Davao Oriental has branded its coffee in association with Mt. Hamiguitan. This study profiles the production capacities and agricultural practices of smallholder coffee farmers along the Mt. Hamiguitan buffer zone, focusing on women’s roles and farmers’ climate change awareness and adaptation strategies. Fifty-seven purposively selected farmers (28 females, 29 males) were interviewed using a validated semi-structured questionnaire. Data were analyzed using thematic analysis and descriptive statistics. Most farmers (70%) were old (≥51) with over 40 years of experience (51%). Non-participation in farmers’ associations (73.7%) surpassed active membership (26.3%), with only 14% attending training. Most farmers (65%) intercropped 500–600 Robusta coffee trees/ha, with many farms established in the 1980s (36%). The farmers performed clearing (82%) and pruning (94%) of their coffee. Women played a vital role, especially during drying and harvesting. All respondents acknowledged climate change and employed practices such as intercropping, pruning, using ipil-ipil for shade, and utilizing nets, which, though originally aimed at improving crop resilience, can also serve as adaptations to mitigate the impacts of climate change. Recommendations for fostering sustainable practices while improving livelihoods include joining cooperatives, providing training for enhanced climate change adaptation strategies, and increasing women’s participation in coffee production. Full article