Evaluating the ability of different characterization parameters to describe the surface of fried foods.

Abstract

The objective of this work is to identify surface topography characterization parameters that are capable of discriminating the surfaces of different fried foods. Three fried food model systems with clearly different surfaces were formulated from vital wheat gluten, native wheat starch, and potato flakes. The surfaces were measured with a scanning laser microscope (SLM), and the ability of several parameters to discriminate between them was tested. Two conventional parameters, the root mean square roughness (Sq) and the surface Kurtosis (Sku), were calculated, along with parameters derived from area-scale fractal analysis: smooth-rough crossover (SRC), fractal dimension, and relative area as a function of scale. The coefficient of variation (COV) of Sq, Sku, and SRC and fractal dimension of different sizes of measurement regions were calculated for the surface of the roughest product in order to specify a measurement region that would be sufficiently large to be representative. The size of the representative region was found to be 25 mm2. Among the parameters evaluated in this study, the most reliable parameter for discriminating the surfaces of fried foods is the relative area calculated from area-scale fractal analysis.