The thermophysical properties of coffee have a special partaking during the drying process since a material‐depending heat and mass transfer occurs between the bean and the drying air. Conditional to the thermophysical properties of the parchment coffee, the drying can be more or less efficient, affecting the final quality and seed safety. Several coffee varieties have been studied; however, the National Coffee Research Center of Colombia has developed new highly productive coffee varieties resistant to different diseases: Cenicafé 1 and Castillo®. Nevertheless, the thermophysical properties of these specific varieties were not yet investigated; moreover, the availability of information related to these properties of different coffee varieties in the literature is relatively scarce. Thus, this study targeted to determine the parchment coffee thermophysical properties of these new varieties at five different moisture contents % (wb): 53%, 42%, 32%, 22% and 11%, using optimized techniques and methods to ensure high accuracy and exactness. It was found that the new varieties have larger, heavier, and denser beans; it was also seen that the bulk thermal conductivity and the bulk‐specific heat are higher in these varieties than in the older ones. It was also revealed that the length, width, thickness, and surface area did not change as the moisture was removed, whereas the bulk density, kernel density, mass, bulk‐specific heat, and bulk thermal conductivity decreased as the moisture was reduced. Displaying better thermophysical properties will improve the drying and roasting processes; hence, a better final product can be expected from these varieties.Practical applications: Knowing the thermal and physical properties of these new varieties will allow the growers and coffee processing facilities to predict, simulate and control different post‐harvesting processes such as pulping, fermentation, drying, storing, and roasting. Also, the already developed mathematical models to estimate coffee drying times can be updated, improving the accuracy of the predictions, bed porosities, mass, and heat transfer in order to safeguard the innocuousness of the product.

Highlights The forced and natural convection drying processes of a single coffee grain can be predicted. The moisture distribution profiles depict the drying phenomena and water concentration zones. With accurate predictive drying curves, coffee growers can ensure high-quality coffee beans. Abstract. Different coffee drying technologies face complex tasks in ensuring an acceptable final seed moisture content. This research performed a Finite Element Analysis (FEA) study, simulating a single coffee bean's drying process as a transient mass diffusion model under mechanical and natural convection conditions, so the drying behavior and data of both case scenarios can be foreseen and controlled by a predictive Finite Element Model (FEM). A wet bean was 3D-scanned and digitized as the FEA simulation geometry; the water diffusion between the grain and the atmosphere was defined by a diffusion coefficient subject to the drying air temperature and the grain's moisture content. Three cases were studied: mechanical grain drying at three different temperatures (50, 45, and 40°C) in a forced convection environment; variable natural convection drying under environmental conditions (wet and dry season); and constant natural convection (wet and dry season), including the variation in day/night temperature and relative humidity. The results agree well with the data found in the literature, obtaining the graphical moisture distribution of the phenomena, predictive drying curves, diffusion coefficients, and isotherms. Both simulated drying scenarios provide essential information for coffee growers to improve and control their drying processes, thus obtaining high-quality grains, reducing contamination by microorganisms, and ensuring the integrity of their products. Keywords: Coffea arabica, Coffee Drying, Coffee Seed, Finite Element Model, Moisture Diffusion.

Coffee pulp, the primary residue generated during the wet processing of Coffea arabica L., is frequently applied directly to fields as a crude soil amendment. However, this practice often lacks proper microbial stabilization, limiting its agronomic potential and posing risks due to the presence of phytotoxic compounds. In Colombia, disease-resistant varieties such as Coffea arabica L. var. Castillo and var. Cenicafé 1, developed by the National Coffee Research Center (Cenicafé), are the amongst the most widely cultivated varieties in the country; however, despite their widespread adoption, the microbial ecology of postharvest residues from these varieties remains poorly characterized. This study aimed to isolate and functionally characterize native microbial communities from the pulp of Coffea arabica var. Castillo and var. Cenicafé 1, and to evaluate their role in postharvest processing and organic waste management. Fresh pulp samples were collected from a wet-processing facility located in tropical mid-elevation zones. A total of 53 microbial isolates were recovered using culture-dependent techniques on selective media targeting yeasts, lactic acid bacteria (LAB), and filamentous fungi. Amplicon sequencing of the 16S rRNA gene (V3–V4 region) and ITS1 region was conducted to profile bacterial and fungal communities, revealing diverse microbial consortia dominated by Aspergillus, Lactobacillus, Leuconostoc, Pichia, and Saccharomyces species. Enzymatic screening indicated high pectinolytic and cellulolytic activity. Composting trials using inoculated pulp showed a ~40% reduction in composting time and improved nutrient content. These findings support the use of native microbiota to enhance composting efficiency and postharvest valorization, contributing to more sustainable and circular coffee systems.

Yeasts are the usual contaminants in fruit juices and other beverages, responsible for the decrease in the quality and shelf-life of such products. Preservatives are principally added to these beverages to enhance their shelf-life. With the increasing consumer concern towards chemical food additives, plant-derived antimicrobials have attracted the attention of researchers as efficient and safer anti-yeast agents. However, the methods currently used for determining their anti-yeast activity are time- and material-consuming. In this study, the anti-yeast effect of plant phenolic compounds in apple and orange juice food models using microtiter plates has been evaluated in order to validate the modified broth microdilution method for screening the antimicrobial activity of juice preservative agents. Among the twelve compounds tested, four showed a significant in vitro growth-inhibitory effect against all tested yeasts (Saccharomyces cerevisiae, Zygosaccharomyces bailii, and Zygosaccharomyces rouxii) in both orange and apple juices. The best results were obtained for pterostilbene in both juices with minimum inhibitory concentrations (MICs) ranging from 32 to 128 μg/mL. Other compounds, namely oxyresveratrol, piceatannol, and ferulic acid, exhibited moderate inhibitory effects with MICs of 256–512 μg/mL. Furthermore, the results indicated that differences in the chemical structures of the compounds tested significantly affected the level of yeast inhibition, whereas stilbenes with methoxy and hydroxy groups produced the strongest effect. Furthermore, the innovative assay developed in this study can be used for screening the anti-yeast activity of juice preservative agents because it saves preparatory and analysis time, laboratory supplies, and manpower in comparison to the methods commonly used.