Mathematical modelling and validation of oil migration on a model chocolate system using magnetic resonance imaging (MRI)
Oil migration is a common problem in chocolate confectionery products leading to quality defects, particularly fat bloom. Magnetic resonance imaging (MRI) is among the most novel techniques as being a non-destructive method to monitor and quantify migration. The main objective of this study was to model oil migration of peanut butter over dark chocolate layer system stored at 30°C with the predictions of a Fickian-based mathematical model. For this purpose, signal intensity (SI) values of chocolate layers containing migrated oil through peanut butter were obtained by using MRI over a time frame of 18 days. Although there are similar studies, different chocolate formulations and peanut butter were used in this study. Experimental data were fitted to a Fickian-based mathematical model. Parameters (C0, b) belonging to time varying boundary conditions and diffusion coefficients (D) were estimated using MATLAB program. Dimensionless equilibrium interface concentrations (C0) were found between 0.70 and 3.53 over time. Time constant (b) was obtained as 0.14 day-1. During storage, D values varied from 8.09×10-11 to 5.42×10-10 m2 s-1. Higher D values were obtained at day 1 indicating faster migration rate.
Cikrikci, S. and Oztop, M.H. 2017. Mathematical modelling and validation of oil migration on a model chocolate system using magnetic resonance imaging (MRI). Acta Hort. (ISHS) 1152:273-280
fat bloom, peanut butter, Fickian, diffusion coefficient, storage