Coffee processing requires continuous optimization to preserve sensory quality while improving process efficiency. Although hyperspectral imaging has been widely applied for food quality evaluation, its use for predicting coffee cup score during controlled drying remains limited. This study aimed to evaluate the effect of drying temperature on the drying kinetics of Caturra coffee and to develop a predictive model for cup score using hyperspectral imaging combined with Partial Least Squares Regression (PLSR). Coffee samples were dried at four constant temperatures (30, 40, 50, and 60 °C) in forced-convection ovens, and hyperspectral reflectance images (400–1000 nm) were acquired using a Specim FX10 camera. Sensory evaluation was conducted by six certified Q Arabica Graders. Drying times were 52, 34, 30, and 20 h at 30, 40, 50, and 60 °C, respectively, with corresponding cup scores of 83.21, 83.50, 83.60, and 83.26 points. Effective moisture diffusivity ranged from ${10}^{-13}$ to ${10}^{-12}$ m²/s, while mass transfer coefficients were on the order of ${10}^{-9}$ m/s, with activation energies of 28.016 and 19.272 kJ/mol. No significant differences in cup score were observed among drying temperatures ($p>0.05$). A PLSR-based model was developed to estimate cup score from hyperspectral data, achieving $R^2$ values of 0.770 and 0.855 and RMSE values of 0.515 and 0.518 for calibration and validation, respectively. Key wavelengths at 480, 600, 720, and 940 nm were identified as the most influential spectral regions associated with chemical compounds affecting sensory quality. These findings demonstrate the potential of integrating drying kinetics and hyperspectral imaging as a rapid and non-destructive approach for objective prediction of coffee sensory quality during processing.

In their article “Coupling at a distance HDG and BEM”, Cockburn, Sayas and Solano proposed an iterative coupling of the hybridizable discontinuous Galerkin method (HDG) and the boundary element method (BEM) to solve an exterior Dirichlet problem. The novelty of the numerical scheme consisted of using a computational domain for the HDG discretization whose boundary did not coincide with the coupling interface. In their article, the authors provided extensive numerical evidence for convergence, but the proof of convergence and the error analysis remained elusive at that time. In this article we fill the gap by proving the convergence of a relaxation of the algorithm and providing a priori error estimates for the numerical solution.

In their article "Coupling at a distance HDG and BEM", Cockburn, Sayas and Solano proposed an iterative coupling of the hybridizable discontinuous Galerkin method (HDG) and the boundary element method (BEM) to solve an exterior Dirichlet problem. The novelty of the numerical scheme consisted of using a computational domain for the HDG discretization whose boundary did not coincide with the coupling interface. In their article, the authors provided extensive numerical evidence for convergence, but the proof of convergence and the error analysis remained elusive at that time. In this article we fill the gap by proving the convergence of a relaxation of the algorithm and providing a priori error estimates for the numerical solution.

Temperature abuse during storage represents a critical factor influencing microbial behavior in meat products, particularly in non-conventional matrices such as guinea pig meat. This study aimed to characterize and compare the primary growth kinetics of Aerobic mesophilic bacteria and Staphylococcus aureus (S. aureus) in guinea pig meat burgers under controlled temperature abuse conditions (30, 35, and 40 °C). Microbial growth was monitored over 96 h and described using the modified Gompertz model to estimate key kinetic parameters, including maximum specific growth rate (µ_max) and lag phase duration (λ). Aerobic mesophilic bacteria exhibited increasing µ_max values with temperature, indicating enhanced metabolic activity under elevated thermal conditions. In contrast, S. aureus showed reduced µ_max and prolonged λ at 40 °C, suggesting stress-induced modulation of growth dynamics. These findings demonstrate that temperature increases do not uniformly accelerate microbial proliferation across different populations within the same food matrix. The contrasting kinetic responses indicate that Aerobic mesophilic bacteria and S. aureus respond differently to temperature abuse conditions, highlighting that total aerobic counts alone may not reliably predict pathogen behavior in guinea pig meat burgers.