Search Results (559)

Identifying Coffea arabica genotypes that combine high cup quality with consistent sensory performance across harvests is relevant for specialty coffee breeding. This study evaluated 37 C. arabica accessions from the EPAMIG Active Germplasm Bank in Patrocínio, Minas Gerais, Brazil, during the 2020 and 2021 harvests. Naturally processed coffees were assessed by trained cuppers using the Specialty Coffee Association protocol and a complementary descriptive ballot for intensity attributes and aroma/flavor nuances. Final cup score, sensory descriptors, across-harvest agreement, principal component analysis, Spearman correlations, and variance components were evaluated. All two-harvest genotype means exceeded 80 points (81.21–85.58), although two genotype-by-harvest means fell below this threshold. The genotype × harvest interaction was significant and exceeded the genotypic variance, resulting in low across-harvest repeatability (H² = 0.30; 95% CI 0–0.64). Scores were, on average, 1.64 points lower in 2021, with low agreement between harvests (ICC = 0.077). MG 1196, MG 1175, and MG 1197 combined comparatively high means with small between-harvest differences and were identified as priority candidates for further validation. Higher cup scores were associated with body, sweetness, aftertaste, and fruity, floral, and sweet nuances. Additional harvests and environments are required before definitive selection. Full article

Coffee husks (Coffea arabica) are abundant agro-industrial by-products with potential for value-added applications, making the optimization of drying conditions essential for preserving their quality. This study evaluated the effects of drying temperature on the drying kinetics, thermodynamic properties, and volatile profile of coffee husks from organic and conventional production systems. Samples were dried in a convective fixed-bed dryer at 30, 40, and 50 °C. Drying kinetics were described using fifteen mathematical models, while thermodynamic parameters (ΔH, ΔS, and ΔG), volatile compounds (HS-SPME/GC–MS), water activity (Aw), and texture were evaluated. The Modified Henderson and Pabis model provided the best fit to the drying data (R² > 0.99). A total of 505 volatile compounds were identified, and samples dried at 40 °C retained the highest number of sensory-relevant compounds. Organic coffee husks exhibited a distinct volatile profile compared with conventional husks, possibly due to differences in postharvest processing. Drying reduced water activity to values below 0.60, which are generally considered unfavorable for the growth of most microorganisms during storage. Overall, the results suggest that drying at 40 °C provides a suitable balance between drying performance and volatile compound preservation in coffee husks. 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

The phenological responses of different progenies to the effect of ambient temperature on the duration of the fruit ripening cycle in Coffea arabica L. remain poorly understood. In this study, the ripening cycle in the coffee progenies of the Cenicafé 1 variety was recorded using the number of growing degree days during the main and secondary harvests. Concurrently, variables such as the number of fruits per node, firmness, diameter, volume, fresh mass, dry mass of the pericarp and bean, and the fruit respiration rate were measured. A semiparametric repeated-measures analysis of variance was used to assess inferential components, and Spearman’s multiple correlations were used to examine the associations between variables. No significant differences were observed between the progenies for any variable. However, we detected differences between harvests in terms of the number of growing degree days, number of fruits per node, fruit firmness, fruit diameter, fruit fresh mass, and pericarp and grain dry mass. Furthermore, the correlation analysis revealed that the physical characteristics of the fruit exhibited the strongest associations among themselves. The absence of significant differences in the ripening cycle and fruit characteristics among the progenies may be attributed to their shared genetic origin. Finally, the observed change in the number of fruits per node between harvests directly influenced the physical characteristics of the fruits (diameter, volume, fresh mass, and pericarp dry mass), as the reduced physical space available for individual fruit growth when the node fruit load was higher limited their development. Full article

Microbial inoculants such as Trichoderma have been proposed as sustainable tools to improve seedling quality in coffee nurseries; however, their effectiveness may vary according to formulation and genotype. This study evaluated three treatments: a solid Trichoderma formulation (1 kg m⁻³ of substrate) based on a multispecies consortium (T. harzianum, T. asperellum, and T. viride; 5 × 10⁹ conidia g⁻¹), a liquid formulation of T. harzianum (1 × 10⁸ CFU mL⁻¹; 1 L m⁻³ of substrate), and a non-inoculated control, using three Coffea arabica varieties (Catimor, Marsellesa, and Gran Colombia) under controlled nursery conditions. A linear mixed model was applied, considering variety and inoculant type as fixed effects and replicates as random effects. The results show that the biostimulant response is strongly modulated by the variety × inoculant interaction. The solid formulation was superior in promoting the expansion of the photosynthetic apparatus, increasing leaf area by 24.6%. In turn, the liquid formulation optimized structural vigor, increasing stem diameter by 17.3% and reducing slenderness by 13.1%. Inoculation reduced the lignification index by 10.4%, favoring dynamic vegetative growth. These improvements were integrated into the Dickson Quality Index, which reached values of 0.41–0.70, greatly exceeding the critical threshold of 0.20 for medium- to high-quality seedlings. It is concluded that Trichoderma acts as a physiological compensator that harmonizes plant architecture, although its efficacy depends on specific compatibility with the genotype, which is essential for ensuring the successful establishment of coffee plants under field conditions. Full article

Robusta coffee (Coffea canephora) possesses great industrial potential, whereas its intrinsic flavor defects compromise market competitiveness. Honey processing utilizing residual pulp and mucilage is capable of improving green coffee quality; nevertheless, the absence of quantitative research regarding graded pulp retention limits its industrial application. In this study, fermentation experiments with gradient retention of coffee cherry pulp were conducted to clarify the differential regulatory effects of varying coffee cherry pulp-retention amounts on physicochemical properties, functional components and volatile flavor precursor compounds of Hainan Robusta coffee. Quantitative scoring of coffee quality using international standard cup measuring instruments and the grey relational analysis was further employed to comprehensive quality assessment. Compared with the 0% coffee cherry pulp-retention treatment, all other treatments showed higher levels of selected functional components and volatile flavor precursor compounds. The 66% coffee cherry pulp-retention treatment enriched key roasting flavor substrates: sucrose, organic acids, pyrazines, and esters were increased by 8.74%, 26.58%, 80.66% and 30.18%, respectively. Meanwhile this treatment exhibited significantly lower protein and alkaloid contents than the 100% and 33% coffee cherry pulp-retention treatments, and significantly lower flavonoid content than the 0% and 33% coffee cherry pulp-retention treatments. This treatment exhibited remarkably excellent cup scores by 80.35 and superior comprehensive quality, outperforming the other treatments by 6.05–18.51%. This study identifies the optimal coffee cherry pulp-retention ratio for Robusta coffee post-harvest honey processing, providing theoretical basis and feasible technical references for the quality improvement, standardized processing and industrial promotion of local Robusta coffee. Full article

Coffee cultivation in the Western Amazon is based on Coffea canephora Pierre ex A. Froehner clones with limited nutritional characterization. This study aimed to quantify the genetic variability in leaf mineral concentrations among 64 widely cultivated genotypes. The experiment was conducted at the Embrapa experimental field station in Ouro Preto do Oeste, Rondônia, using a randomized complete block design with three replications. Leaf concentrations of N, P, K, Ca, Mg, S, B, Cu, Fe, Mn, Zn, Na, and Al were evaluated. Significant genotype effects were observed for all evaluated elements (p ≤ 0.01), with high heritability estimates for K, Cu, Mn, N, and S. The decreasing order of leaf macronutrient concentrations was N > K > Ca > Mg > S > P. Among the evaluated elements, Fe, Mn, Zn, Na, and Al showed the greatest variation, with clones LB33, N8G8, BRS1216, and GJ30 standing out for their higher concentrations of Zn/Na, Al, N, and K, respectively. Multivariate analyses indicated that variation in foliar mineral concentrations was predominantly continuous, although the clones were partitioned into two groups with contrasting profiles. Group 1 was associated with higher concentrations of P, Cu, Fe, Mn, and Al, whereas Group 2 showed higher relative concentrations of N, K, Ca, Mg, S, Na, and Zn. These findings reveal distinct foliar mineral profiles among the evaluated clones and provide a basis for selecting contrasting genotypes for future studies on clone-specific nutritional responses. Full article

Tropical riparian ecosystems are among the most threatened biomes on Earth, yet decade-scale, spatially explicit documentation of vegetation loss and landscape fragmentation in community-based ecotourism corridors remains scarce. This study investigates whether agricultural intensification associated with ecotourism development has driven measurable vegetation decline and landscape fragmentation in the Ledok Amprong riparian corridor (Poncokusumo District, Malang Regency, East Java; 8.21 ha, 800–900 m a.s.l.), a mixed-canopy riparian system dominated by Ficus benjamina, Albizia chinensis, and bamboo (Phyllostachys spp.) interspersed with smallholder coffee (Coffea canephora) agroforestry, over the period 2015–2024. We applied multi-temporal Sentinel-2 (10 m) imagery, NDVI analysis, supervised Maximum-Likelihood classification (Overall Accuracy: 89.75%, Kappa: 0.86), and FRAGSTATS-derived landscape metrics to quantify vegetation dynamics and land cover transition. Results show that agricultural land expanded by 157.51% (1.14 to 2.93 ha), while vegetation cover declined by 28.45% (6.27 to 4.49 ha). A strong negative correlation between agricultural expansion and vegetation loss (r = −0.96, p < 0.001) confirmed agriculture as the primary driver of ecosystem degradation. Landscape fragmentation intensified markedly: patch density increased by 49.6%, the connectivity index declined by 23.5%, and the fragmentation index increased by 54.3%. These findings establish the first quantitative, decade-scale spatiotemporal baseline for this ecotourism corridor and demonstrate that community-based ecotourism development, without adequate spatial governance, accelerates rather than mitigates riparian degradation—a paradox with broad implications for tropical riparian conservation governance worldwide. Evidence-based management recommendations include 10–30 m dynamic buffer zones, a 2.5 ha targeted restoration programme, and a Payment for Ecosystem Services (PES) mechanism, offering a transferable framework for sustainable riparian ecotourism management across rapidly urbanizing tropical watersheds. Full article

The genetic diversity of Coffea arabica L. plays a strategic role in the development of cultivars with differentiated agronomic and sensory attributes. However, the chemical discrimination of genealogical groups still represents a challenge due to the strong environmental influence on bean metabolism. In this study, ¹H NMR-based metabolomics associated with supervised chemometric models was applied to discriminate three genealogical groups of C. arabica (Bourbon, Mundo Novo, and Timor Hybrid) using 38 green coffee samples harvested during the 2020 and 2021 crop seasons. Spectra were processed by bucketing and analyzed using PCA, PLS-DA, Elastic Net, Random Forest, and SVM-RBF. PCA explained 52.91% of the total variability in the first two components but did not promote clear separation among groups. Among the supervised classifiers, PLS-DA showed the best balance between predictive performance, statistical stability, and chemical interpretability, achieving a balanced accuracy of 89.4% under repeated cross-validation. The five-component model presented an overall error rate of 12.1% after repeated 5-fold cross-validation with 100 simulations. VIP scores and loadings identified discriminant metabolites for each group: lipids, amino acids, and organic acids for Bourbon; amino acids and organic acids for Mundo Novo; and chlorogenic acids for Timor Hybrid. These results highlight the potential of ¹H NMR metabolomics as a complementary tool for varietal discrimination and support for breeding programs. Full article

The prediction of specialty coffee quality remains a central challenge for value addition in the agricultural sector. This study presents a computational approach to model the complex sensory quality of Arabica coffee (Coffea arabica L.) using synthetic data grounded in real-world statistics. A synthetic dataset (identical to the real dataset with a number of samples = 207) was generated using Cholesky decomposition based on the descriptive statistics and Pearson correlation matrix extracted from the Coffee Quality Institute (CQI) Arabica 2023 database, comprising 17 numerical variables including sensory attributes, defect counts, and Total Cup Points. The synthetic dataset achieved a Kolmogorov–Smirnov similarity of 89.55% with the real data, with the target variable Total Cup Points preserved with high fidelity (real mean: 83.71; synthetic mean: 83.65). An ordinal classification model (Random Forest) trained exclusively on the synthetic data and validated against real-world samples achieved an overall accuracy of 87.92% and a Quadratic Weighted Kappa (QWK) of 0.9502, indicating excellent agreement and confirming the model’s ability to capture the ordinal hierarchy of coffee quality. SHAP (SHapley Additive exPlanations) analysis revealed consistent feature importance rankings between real and synthetic domains, with Aftertaste, Overall, and Flavor emerging as the top three most influential predictors. This study validates the use of statistically grounded synthetic data for training robust machine learning models in agricultural research, demonstrating that synthetic environments can effectively replicate empirical patterns and enable cross-domain generalizability. The complete code and datasets are publicly available for reproducibility. Full article

The Growth-Regulating Factor (GRF) family and their co-activators, GRF-Interacting Factors (GIFs), are key players in the trade-off between plant development and stress adaptation, functioning as canonical targets of the highly conserved miR396 family, which mediates responses to environmental stressors including high temperatures and water deficits. The “starlet” phenomenon in the allotetraploid Coffea arabica L. is a developmental disorder that results in malformed flowers, frequently associated with environmental stress and floral sterility. Since their underlying molecular mechanisms remain uncharacterized, we performed a genome-wide identification of the CaGRF and CaGIF families and quantified their transcriptional profiles in shoot apical meristems (SAMs) and across multiple stages of floral bud development. Our findings reveal significant differential expression of the GRF-GIF module between typical and starlet tissues throughout development, including the SAM. Intriguingly, these results do not correlate with the levels of a representative member of the miR396 family, indicating that the GRF-GIF expression shifts in starlet-flowers may be uncoupled from miR396 levels. This work provides the first molecular insights into the enigmatic starlet phenomenon in Coffea arabica L., addressing an understudied aspect of coffee reproductive development and its implications for the reproductive stability (and productivity) of this important tropical crop species. Full article

Agricultural research helps us to reduce the risks associated with climate variability, pests and diseases, market fluctuations, and biennial bearing. However, genotype characterization is often conducted independently of economic performance and yield stability, limiting the identification of genotypes that combine high yield, stability, and economic return potential. This study characterized the genotype × harvest season interaction and gross revenue of Coffea canephora clones evaluated in Rondônia, Brazil, over five harvest seasons (2021–2025). Twenty-eight genotypes were evaluated in a randomized complete block design with four replications and five plants per plot, and yield stability was assessed using the centroid method. Cumulative yield over five harvest seasons totaled 306.22 bags ha⁻¹, with a mean of 61.24 bags ha⁻¹ per harvest season. The genotype × harvest season interaction revealed distinct temporal yield patterns. Genotypes closest to the ideotype of maximum yield and stability included BAG19, BRS1216, GJ8, GJ25, AS2, and BAG24. Gross revenue simulations based on contrasting historical coffee price scenarios indicated the economic superiority of these clones. Differences in yield potential contributed more to gross revenue variation than biennial bearing. Relative to the overall mean of the 28 genotypes, these clones achieved an 85% increase in mean yield and a 61.2% increase in mean gross revenue. Full article

Adventitious rooting remains a major constraint for the clonal propagation of Coffea arabica, limiting the large-scale multiplication of elite genotypes. This study evaluated the effects of genotype, auxin treatment, and their interaction on adventitious rooting and basal callus formation in coffee cuttings under controlled nursery conditions, while morphophysiological traits were assessed as complementary indicators of cutting performance. A completely randomized 3 × 3 factorial design was used, including three hybrids (H3, Excelencia, and Milenio) and three plant growth regulator (PGR) treatments: control, indole-3-butyric acid (IBA), and a commercial auxin formulation (RH; NAA + IBA). Rooting probability and root number were significantly affected by PGR treatment, whereas the longest root length was influenced by hybrid, PGR treatment, and their interaction. Model-estimated rooting probability increased from 4.76% in the control to 17.05% under IBA and 35.73% under RH. Similarly, the estimated number of roots per cutting increased from 0.14 in the control to 0.99 under IBA and 1.85 under RH. Although the hybrid × PGR interaction was not significant for rooting probability, the highest observed rooting percentage was recorded in H3 under RH (52.38%), followed by Milenio under RH (33.33%). For the longest root length, the strongest responses were observed under RH, particularly in Milenio (71.15 mm) and H3 (70.08 mm). Callus formation varied among treatments, but its association with rooting performance was weak and inconsistent. Morphophysiological traits provided complementary information on cutting status but were not interpreted as direct mechanistic drivers of rooting. These findings indicate that adventitious rooting in C. arabica was more closely associated with genotype-dependent responsiveness to exogenous auxin than with the extent of callus formation. However, anatomical studies are needed to determine the developmental origin of root primordia and their possible relationship with callus tissue. Full article