CHARACTERIZATION OF FOOD SURFACES USING SCALE‐SENSITIVE FRACTAL ANALYSIS

Length-scale and area-scale analyses, two of the scale-sensitive fractal analyses performed by the software Surfraxhttp://www.surfract.com, were used to study food surfaces measured with a scanning laser microscope (SLM). The SLM measures surfaces, or textures (i.e., acquires topographical data as a collection of heights as a function of position), at a spatial and vertical resolution of 25 μm. The measured textures are analyzed by using linear and areal tiling (length-scale and area-scale analysis) and by conventional statistical analyses. Area-scale and length-scale fractal complexities (Lsfc and Asfc) and the smooth-rough crossover (SRC) are derived from the scale-sensitive fractal analyses. Both measures proved adequate to quantify and differentiate surfaces of foods (e.g., chocolate and a slice of bread), which were smooth or porous to the naked eye. Surfaces generated after frying of potato products (e.g., potato chips and French fries) had similar values of Asfc and SRC, and larger (implying more complex and rougher surfaces) than those of the raw potato. Variability of surface texture characterization parameters as a function of the size of the measured region was used in selecting the size of the measured regions for further analysis. The length-scale method of profile analysis (also called the Richardson or compass method) was useful in determining the directionality or lay of the anisotropic texture on food surfaces.