Browsing by Author "Brown, CA"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Characterization of food surfaces using scale-sensitive fractal analysis
    (FOOD NUTRITION PRESS INC, 2000) Pedreschi, F; Aguilera, JM; Brown, CA
    Length-scale and area-scale analyses, two of the scale-sensitive fractal analyses performed by the software Surfrax 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 mu m. 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.
  • Thumbnail Image
    Item
    Characterization of the surface properties of chocolate using scale-sensitive fractal analysis
    (TAYLOR & FRANCIS INC, 2002) Pedreschi, F; Aguilera, JM; Brown, CA
    A scanning laser microscope was used at its highest resolution (25 mum) to study the surface of three kinds of commercial chocolate. Data of measured surfaces were analyzed by scale-sensitive fractal analysis (SSFA) using linear and area tiling (length-scale and area-scale analysis) and by conventional statistical analyses for roughness. Area-scale and length-scale fractal complexities (Lsfc and Asfc) and the smooth-rough crossover (SRC) derived from SSFA proved adequate to characterize the surface roughness of chocolate and changes in topography as a result of bloom. The three chocolate surfaces analyzed had similar values of Asfc, Lsfc and ARa. Nestle milk chocolate presented significant higher values of SRC than those corresponding to the other two kinds of chocolate analyzed (e.g., 0.051 mm(2) vs. 0.038 and 0.037 mm(2) in the case of area-scale sensitive analysis) implying a rougher surface.