Search Results (212)

Liberica coffee (Coffea liberica), including its varieties C. liberica var. liberica and C. liberica var. dewevrei (Excelsa), is the third most commercially important coffee species; however, scientific knowledge on its physicochemical, bioactive, and sensory characteristics remains limited compared with Arabica and Robusta. This study evaluates the development of Liberica coffee research and synthesizes current evidence on its key quality attributes. A bibliometric analysis of publications indexed in Scopus, PubMed, and Semantic Scholar was conducted to identify trends, themes, and knowledge gaps, followed by a targeted review of physical properties, bioactive compounds, antioxidant and antibacterial activities, and sensory characteristics. Results show a gradual increase in Liberica research over the past decade, with a shift toward quality attributes and functional properties. Liberica coffee exhibits distinctive physical traits, moderate caffeine levels, and a bioactive profile characterized by chlorogenic acids that vary with processing and roasting, alongside relatively stable alkaloids such as trigonelline and theobromine. The diterpene composition, particularly the kahweol-to-cafestol ratio, distinguishes Liberica varieties. Sensory studies report fruity, jackfruit-like aromas, moderate acidity, and a relatively full body. Despite its potential, standardized data remain limited, highlighting the need for integrated research to support quality differentiation and value addition. Full article

Background/Objectives: Coffea canephora (robusta) and Coffea liberica var. dewevrei (excelsa) cultivated in the Comoros islands represent understudied coffee varieties grown in a unique volcanic terroir. Despite their agricultural significance and potential bioactive value, no comprehensive biochemical or nutritional characterization of these Comorian coffees had previously been conducted. This study therefore aimed to provide the first integrated biochemical and nutritional characterization of both varieties and to evaluate the influence of the islands’ specific edaphoclimatic conditions on their chemical composition. Methods: An integrated analytical approach was employed, combining UV-Vis spectrophotometry, HPLC, ionomics, and FTIR-ATR spectroscopy to quantify polyphenols, flavonoids, caffeine, soluble sugars, antioxidant activity, mineral profiles, and macromolecular composition of green coffee beans from both species. Results: Robusta exhibited significantly higher levels of total polyphenols (121.79 ± 2.73 mg GAE/g), total flavonoids (29.43 ± 2.20 mg QE/g), caffeine (1.52% w/w), total soluble sugars (60.47 ± 3.37 mg GE/g), and antioxidant activity (64.97 ± 6.25 mM Trolox eq/g). Conversely, excelsa demonstrated a distinct mineral profile, with significantly higher concentrations of magnesium, calcium, sodium, zinc, and copper. FTIR spectroscopy confirmed distinct vibrational fingerprints between the two species, particularly in lipid and carbohydrate signatures. Conclusions: These findings position Comorian robusta as a potent source of antioxidants and stimulants, while excelsa offers a nutritionally balanced profile with nutraceutical potential, providing a scientific basis for valorizing both varieties as high-value niche products and contributing to the preservation of coffee agro-biodiversity. Full article

Coffee (Coffea arabica) is a very important world commodity because of the countries involved in its production, along with the total cultivated area, production volume, consumption and economic impact. In Mexico, the coffee producing areas are located mainly in the hilly terrain of southern Mexico under agroforestry systems predominantly owned by smallholders. Low productivity is faced especially in the state of Oaxaca as a result of inadequate management practices such as aged plantations and deficient practices of pruning and plant nutrition. In order to evaluate the effect of inorganic fertilization on coffee yield, an experiment was carried out at three plantations located in the coastal coffee producing region of the state of Oaxaca, Mexico. Six treatments considering varied amounts of inorganic nitrogen (N), phosphorus (P) and potassium (K) and lime application were applied in coffee plantations with the varieties Typica and Oro azteca. A randomized complete block design with four replications was used. The experiments were conducted in areas with three- or four-year-old plants, with the objective of having at least one harvest for yield evaluation. The variables’ plant height and coffee yield per plant were registered. The soil was classified based on soil profile description and lab analyses. The results showed that the soil in the study area is a Lithic Ustorthent with low pedogenic evolution and the application of inorganic nitrogen, phosphorus and potassium along with dolomitic lime, increased coffee yield on both varieties of arabica coffee: Typica and Oro azteca. Full article

Coffee pulp, a by-product of coffee processing and a rich source of bioactive compounds, is a promising raw material for functional beverages. However, the influence of genetic variability among coffee varieties on the functional and sensory properties of pulp infusions remains poorly understood. This study evaluated physicochemical, antioxidant, and sensory properties of infusions from nine Coffea arabica L. varieties. Significant differences among varieties were observed (p < 0.05). The pH ranged from 5.36 to 6.42, and titratable acidity from 0.06 to 0.08 g/100 mL, indicating a mild acidic profile. Antioxidant activity (DPPH) ranged from 460.52 to 1006.03 µmol TE/L, and total phenolic content from 29.47 to 59.27 mg GAE/L. Geisha showed the highest antioxidant activity and phenolic content, while Casiopea exhibited the highest reducing capacity. In contrast, Oro Azteca, Excelencia, and H1 achieved the highest sensory acceptance. Multivariate analysis confirmed clear differentiation among varieties and a separation between bioactive and sensory-related attributes. These findings highlight the role of varietal selection in balancing functional potential and consumer acceptance, supporting the development of functional beverages within a circular economy framework. Full article

We propose a partially linear regression linear model to explain coffee prices before and after the COVID-19 pandemic. This new regression model incorporates the fundamental assumption of linearity and nonlinearity between these variables. We consider the penalized quasi-likelihood method for parameter estimation and present residual analysis for the new regression model. A simulation study examines penalized quasi-likelihood estimators and the empirical distribution of the quantile residuals. Furthermore, the article aims to identify variables that influence changes in coffee prices, such as the price of Arabica and Robusta varieties, supply (expressed in millions of bags of production), global consumption, exchange rates, inflation, and the pandemic. Full article

The main commercial species of coffee is Coffea arabica; however, it is highly susceptible to biotic and abiotic factors. For this reason, scions of Coffea arabica species are used on robusta (Coffea canephora) rootstocks since grafting can modify the organoleptic, nutraceutical, and nutritional characteristics of crops. The objective of this study was to evaluate the effects of five roasting degrees (light, medium light, medium, medium dark, and dark) in two varieties of Coffea arabica species (Colombia Rojo and Costa Rica 95) and their respective grafts on C. canephora variety Romex. The concentrations of acrylamide, caffeine, and chlorogenic acids were analyzed using HPLC, and the nutrient content was analyzed using plasma induction atomic emission spectrophotometry. The graft of the Colombia Rojo variety with the medium dark roast had the highest concentration of caffeine (1.523%). The same variety with the light roast had the highest concentration of chlorogenic acid (3.088 mg g⁻¹), while the highest acrylamide content (336.70 ng g⁻¹) was found in the same variety with the medium light roast. The roasting degree, variety, and grafting of coffee influence the organoleptic, nutraceutical, and nutritional contents of coffee infusions. Full article

With evolving consumption trends, the coffee market is experiencing increasing demand for high-quality, traceable coffees, which, in turn, has led to price growth. Therefore, due to its increased economic value, coffee has become a constant target of fraudulent actions. As result, many analytical techniques have been explored as tools for coffee classification and authentication, of which the use of digital, hyperspectral and/or multispectral imaging is noteworthy. This type of analysis provides rapid, non-destructive, environmentally friendly, and increasingly accessible alternatives to conventional analytical methods. By consulting three different databases, this work systematically revised articles published in the last 10 years, which utilize digital image analysis and hyper/multispectral imaging for the botanical and geographical classification and authentication of coffees. The reviewed studies (n = 17) demonstrate that, when paired with classification algorithms, discrimination across species, origins, and quality categories can be achieved. A critical point to highlight is the importance of using whole beans and standardizes roast degree to avoid biasing the models. Concerning digital images, relying solely on color features limits the robustness of the classification models. Incorporating complementary textural and shape features is thus necessary to capture the coffee botanical or geographic information, as shown in a minor number of the selected studies. In a similar fashion, for hyper/multispectral imaging, there is still potential to further exploit the spatial information, thus achieving the technique’s full potential. The evidence indicates that image-based methods are steadily progressing into reliable tools for coffee authentication. Full article

The management of specialty coffee production represents a complex dynamical process characterized by highly nonlinear interconnections between environmental variables, agronomic practices, and chemical compositions. Traditionally, the classification of specialty coffee relies on sensory evaluations conducted by highly certified coffee experts named Q-Graders, using a strict, standardized Specialty Coffee Association (SCA) protocol. However, scientific methods that generate spectral fingerprints provide a more reliable guarantee of quality while also ensuring traceability to the farm of origin. Panamanian Geisha coffee is one of the world’s most expensive award-winning microlots, frequently exceeding 1000 American dollars per pound, with a record-breaking price of over 30,000 American dollars per kilogram in 2025. This research presents an integrated framework that combines Precision Agriculture Management Systems (PAMSs) and a traceability architecture that facilitates the collection of georeferenced coffee bean samples using a mobile application (apps), while preserving the coffee varieties and geographical origin necessary for the subsequent identification of the spectral fingerprint by chemical specialists in their laboratory. A mathematical model is introduced to formally characterize the mobile application’s behavior, distributed structure, and inherent constraints. Serving as a mathematical blueprint, this model identifies critical influencing factors and establishes strategic assumptions to distill complex real-world variables into a rigorous, manageable framework. Large-scale experiments conducted across more than 820 coffee farms in Chiriquí, Panama, demonstrate that the proposed decentralized architecture effectively coordinates the acquisition and synchronization of georeferenced chemical data. The decentralized architecture of the mobile application utilizes private blockchain technology to facilitate autonomous operations, effectively decoupling the system from central authorities to ensure functional continuity in environments characterized by intermittent connectivity. Full article

This study investigated the differences in rhizosphere soil properties and their associations with microbial communities across eight Coffea arabica cultivars cultivated under uniform conditions at the Kangping Education and Research Base in Pu’er, Yunnan. We assessed arbuscular mycorrhizal fungi (AMF) colonization and spore density, analyzed soil chemical properties—including pH, organic matter (OM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), alkali-hydrolyzable nitrogen (AN), available phosphorus (AP), available potassium (AK), and slowly available potassium (SK)—and characterized microbial communities via high-throughput sequencing. The findings of this study demonstrate that coffee variety significantly influences the contents of available nutrients (AN, AP, AK) and OM in the rhizosphere soil. Sequencing indicated that Ascomycota dominated the fungal community, Chloroflexi and Proteobacteria were the primary bacterial phyla, and Glomus and Sclerocystis were the predominant AMF genera. Analysis of alpha diversity showed that in the bacterial community, S8 exhibited the highest diversity and richness, while S6 showed the lowest. For the fungal community, S6 had the highest diversity, S2 displayed the highest richness, and S5 showed the lowest values for both diversity and richness. Within the AMF community, S8 demonstrated the highest diversity, S7 exhibited the highest richness, and S6 had the lowest diversity and richness values. Overall, bacterial diversity surpassed fungal diversity. Redundancy analysis identified AK as a common key factor influencing both bacterial and fungal communities. Besides AK, OM and TN were also significant drivers for the fungal and bacterial communities, respectively, while the AMF community was most strongly associated with SK Full article

Caffeine is one of the most well-known biologically active compounds in coffee beans, and its content largely determines the taste and stimulating properties of the drink. However, the amount of caffeine in beans can vary significantly depending on growing conditions, even within the same coffee variety. The growing global demand for coffee and the current market dynamics emphasize the necessity to investigate how the origin of coffee beans influences beverage quality. Arabica beans, particularly the Red Bourbon variety, are known to exhibit variations in chemical composition, sensory characteristics, and technological behavior depending on their cultivation environment. The study aimed to evaluate the physicochemical and sensory properties of Arabica Red Bourbon beans sourced from distinct geographic regions, considering factors such as altitude and local environmental conditions. The sensory characteristics of the resulting beverages were evaluated using the capping method, and water activity, density, moisture content, color, pH, extractivity and caffeine content were determined. Roasted bean color ranged from 61.4 to 62.5, while ground coffee color was 72.5–75.4. Moisture content was highest in Col and R (3.4%) and lowest in Con (3.1%). The greatest moisture loss during roasting occurred in S and R (13.4%). Water activity decreased from 0.50–0.56 in green beans to 0.18–0.30 post-roasting. Extraction yield ranged from 20.03 to 21.21%, and total dissolved solids (TDS) varied at 1.23–1.30%. The least acidic sample was S (pH 5.04). Colombian beans contained unusually high caffeine. The conducted research confirmed that the geographical origin of Arabica Red Bourbon beans significantly impacts their physicochemical and sensory attributes. Variations in moisture, acidity, and caffeine content were observed among the samples, despite a consistent roasting profile. Full article

The quality of different coffee varieties varies, and the corresponding bioactive value of coffee processing byproducts is often overlooked. For that, we employed HPLC, GC-MS, and electronic sensory analyses to evaluate the key bioactive components, antioxidant potential, and flavor traits of green coffee bean and coffee processing byproducts of seven coffee varieties. The results showed that green coffee beans (Oe+Ie) and exocarp (Ep) possessed strong antioxidant activity and high total phenolic content (TPC), caffeine and trigonelline content. Among the varieties, DR390 contained higher levels of total phenols, caffeine, and trigonelline, whereas DR402 was rich in caffeine and chlorogenic acid. In addition, RY3 exhibited higher TPC, total flavonoid content (TFC), caffeine, and chlorogenic acid. The parchment (Pc) layer was rich in soluble sugars (1.83–5.43%), while the silverskin (Sk) contained relatively high levels of chlorogenic acid (3.58–4.69 mg/g). Flavor analysis identified eleven classes of volatile compounds in green coffee bean (Oe+Ie) and byproducts (Ep, Pc, Sk), with esters, ketones, alcohols, and aldehydes being the most prevalent. Seven key aroma compounds, including methyl salicylate, phenethyl alcohol, nonanal, and benzaldehyde, were identified across the various structural tissues of coffee fruit. Distinct flavor profiles were observed among the coffee fruit parts: green coffee bean (Oe+Ie) was nutty; the Ep showed fruity and cocoa-like aromas; the Pc and Sk exhibited papery and nutty aromas, respectively. Varieties DR397, DR402, and RY3 exhibited pronounced aroma profiles. Comprehensive analysis showed that DR402 and RY3 had higher overall scores for bioactive and flavor components than other varieties in their groups. In summary, green coffee bean (Oe+Ie) exhibited strong antioxidant activity and high levels of bioactive compounds. Coffee byproducts, such as the Ep, hold potential for extracting natural antioxidants and bioactive compounds to develop specialty products or for other high-value utilization. Full article

Early and non-destructive detection of plant-parasitic nematodes is critical for implementing site-specific management in coffee production systems. This study evaluated the potential of unmanned aerial vehicle (UAV) multispectral and thermal imaging, combined with textural analysis, to detect Meloidogyne exigua infestation in Coffea arabica (Topázio variety). Field surveys were conducted in two contrasting seasons (dry and rainy), and nematode incidence was identified and quantified by counting root galls. Vegetation indices (NDVI, GNDVI, NGRDI, NDRE, OSAVI), individual spectral bands, canopy temperature, and Haralick texture features were extracted from UAV-derived imagery and correlated with gall counts. Under the conditions of this experiment, strong correlations were observed between gall number and the red spectral band in both seasons (R > 0.60), while GNDVI (dry season) and NGRDI (rainy season) showed strong negative correlations with gall density. Thermal imaging revealed moderate positive correlations with infestation levels during the dry season, indicating potential for early stress detection when foliar symptoms were absent. Texture metrics from the red and green bands further improved detection capacity, particularly with a 3 × 3 pixel window at 135°. These results demonstrate that UAV-based multispectral and thermal imaging, enhanced by texture analysis, can provide reliable early indicators of nematode infestation in coffee. Full article

Propolis is a complex mixture of natural compounds, including resinous terpenoids, flavonoids, aromatic acids, and essential oils, and has strong antimicrobial, antifungal, and antioxidant properties. The chemical composition of propolis determines its properties and strongly depends on a wide variety of different plant sources, as well as other climate and environmental parameters. In order to determine the main compounds, in this study, we applied an integrated analysis of propolis by thin-layer chromatography (TLC) to characterize and compare the phytochemical profiles of selected bioactive materials in raw propolis. TLC served as a rapid, cost-effective, and highly visual technique to separate and identify key constituents, including terpenoids, flavonoids, and phenolic compounds in propolis, without a need for further precleaning steps after performing ultrasonic extraction. Complementary methods, such as FTIR spectroscopy, were employed to validate and quantify the active components detected through TLC screening. In addition, the UV-VIS method revealed the solubility of raw propolis in different solvents, after testing for coffee ring effects. The results confirmed that the complex structure of the raw sample can be more thoroughly revealed by two-dimensional TLC, which enables not only rapid and verifiable qualitative results but also detection of overlapping spots. Moreover, by comparing the results with data from the literature, not only can particular chemical compounds be efficiently determined by TLC but also the regional origin of samples. Full article

This study examined how visual attention to specialty coffee label elements relates to consumers’ stated purchase intention. A total of 105 regular specialty coffee consumers viewed the front and back panels, simultaneously, of six commercially available labels while their eye movements were recorded with an eye tracker. Areas of Interest (AOIs) were defined for the label’s content, and a Normalized Fixation Ratio (NFR; proportional fixation time scaled by AOI area) was calculated. Purchase intention was measured on a seven-point structured scale, and the association between NFR and purchase intention was modeled using Landscape Segmentation Analysis (LSA). Heatmaps showed that central regions of the front and back panels were attentional “hot zones”, particularly when they contained sensory claims, cupping score, origin and traceability, roast level, coffee variety, and the “specialty coffee” designation. In contrast, weight, best-before date, grain or ground, and contact information consistently received little attention. Higher NFR values for sensory and origin-related cues were positively associated with purchase intention; labels that gave these attributes visual prominence achieved the highest intention scores. These findings indicate that consumers prioritize sensory and traceability-related information over technical or administrative cues and that both the content and graphic salience of label elements are critical for driving perceived value and choice. Results provide evidence-based guidance for structuring specialty coffee labels to optimize communication. Full article

Climate change is expected to reduce coffee yields and intensify infestations by Hypothenemus hampei, the most destructive coffee pest worldwide. Strengthening host plant resistance offers a sustainable approach to mitigate these impacts. This study aimed to characterize F₃ progenies derived from crosses between Castillo^®—a variety with high agronomic performance and resistance to Hemileia vastatrix—and Ethiopian Coffea arabica introductions exhibiting antibiosis to H. hampei for agronomic traits and, for the first time, modeled reductions in H. hampei infestation under projected climate change scenarios. Thirteen F₃ progenies with medium plant stature, rust resistance, and high productivity were selected using a 6 × 7 lattice design. Antibiosis was quantified under controlled conditions by infesting individual coffee beans with a single female borer and validated under field conditions by artificially infesting productive branches with 100 females. Relative to the susceptible control, oviposition decreased by 18.0–25.8% under controlled conditions and by 24.1–69.8% in the field. To anticipate progeny performance under warmer conditions, simulation modeling integrating laboratory and field data under Neutral and El Niño scenarios for the Naranjal and Paraguaicito experimental stations, indicated that progenies exhibiting 34–55% reductions in oviposition would maintain infestation below the economic damage threshold (5%) throughout the eight-month fruit development period. Progenies with the highest antibiosis (55%) would reach the action threshold (2%) only in the seventh month. These findings demonstrate the potential of antibiosis-based resistance to reduce insecticide use and strengthen integrated pest management under projected climate change scenarios. Full article