Characterization of food surfaces using scale-sensitive fractal analysis

Length-scale and area-scale analyses, two of the scale-sensitive fractal an alyses performed by the software Surfrax www.surfract.com, were used to stu dy food surfaces measured with a scanning laser microscope (SLM). The SLM m easures surfaces, or textures (i.e., acquires topographical data as a colle ction of heights as a function of position), at a spatial and vertical reso lution of 25 mu m. The measured textures are analyzed by using linear and a real tiling (length-scale and area-scale analysis) and by conventional stat istical analyses. Area-scale and length-scale fractal complexities (Lsfc an d Asfc) and the smooth-rough crossover (SRC) are derived from the scale-sen sitive fractal analyses. Both measures proved adequate to quantify and diff erentiate surfaces of foods (e.g., chocolate and a slice of bread), which w ere smooth or porous to the naked eye. Surfaces generated after frying of p otato 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 pa rameters as a function of the size of the measured region was used in selec ting the size of the measured regions for further analysis. The length-scal e method of profile analysis (also called the Richardson or compass method) was useful in determining the directionality or lay of the anisotropic tex ture on food surfaces.