Degradation of nutraceuticals in low- and intermediate-moisture foods heated at high temperature (>100 degrees C) is difficult to model because of the nonisothermal condition. Isothermal experiments above 100 degrees C are difficult to design because they require high pressure and small sample size in sealed containers. Therefore, a nonisothermal method was developed to estimate the thermal degradation kinetic parameter of nutraceuticals and determine the confidence intervals for the parameters and the predicted Y (concentration). Grape pomace at 42% moisture content (wb) was heated in sealed 202 x 214 steel cans in a steam retort at 126.7 degrees C for > 30 min. Can center temperature was measured by thermocouple and predicted using Comsol software. Thermal conductivity (k) and specific heat (C(p)) were estimated as quadratic functions of temperature using Comsol and nonlinear regression. The k and C(p) functions were then used to predict temperature inside the grape pomace during retorting. Similar heating experiments were run at different time-temperature treatments from 8 to 25 min for kinetic parameter estimation. Anthocyanin concentration in the grape pomace was measured using HPLC. Degradation rate constant (k(110 degrees C)) and activation energy (E(a)) were estimated using nonlinear regression. The thermophysical properties estimates at 100 degrees C were k = 0.501 W/m degrees C, Cp= 3600 J/kg and the kinetic parameters were k(110 degrees C)= 0.0607/min and E(a)= 65.32 kJ/mol. The 95% confidence intervals for the parameters and the confidence bands and prediction bands for anthocyanin retention were plotted. These methods are useful for thermal processing design for nutraceutical products.