Two algorithms able to compute lineal-path distribution function L(z) and two-point correlation function, S2 (r1, r2) from 2D digital images of foods were developed and validated. Particularly, "Altamura" and "White" breads as well as "Napoli" sausages were studied. Lineal-path function was modeled by considering the foods as two-phase random systems composed from polydisperse overlapping disks. Instead, two-point correlation function was modeled by using a Debye's equation. In all cases a good agreement between experimental and theoretical trend was obtained stating the high accuracy of the algorithms in the extraction of correlation functions as well as the possibility to model breads and sausages as two-phase random systems. Also, important morphological properties such as pores distribution, pore size homogeneity and their spatial distribution, were obtained. For instance, although the estimated radius of the pores was lower for "Altamura" bread rather that for "White", its slowest decay of L(z) highlighted that the pores showed a high dimensional inhomogeneity. © 2013 Springer Science+Business Media New York.
|Titolo:||Statistical Description of Food Microstructure. Extraction of Some Correlation Functions From 2D Images|
|Data di pubblicazione:||2013|
|Appare nelle tipologie:||1.1 Articolo in rivista|