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Measuring the food microstructure by two-point cluster function

机译:通过两点聚类函数测量食品的微观结构

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The clustering of pores of three types of bread was studied by measuring the two point cluster function, C-2(r). The ability of this function in describing the connectivity among the structure elements of bread was proved by comparing the C-2(r) of a "reference" and a "reconstructed" bread image having the same porosity fraction and lineal path distribution function, L(r). The two point cluster function of the void phase of two commercial, "Pan Briosce" and "Pancarre", and a non commercial, "White", bread enabled to highlight significant differences of their topological properties. "White" bread was characterized from more homogeneous pores with a lower degree of connectivity while the "Pancarre" samples exhibited voids highly connected producing pores bigger in size and with a shape extremely complex. Furthermore, for the first time it was proved as the microstructure information of the two point cluster function allows discriminating the 90% of the total variace of bread samples. (C) 2015 Elsevier Ltd. All rights reserved.
机译:通过测量两点聚类函数C-2(r),研究了三种类型的面包的孔的聚集。通过比较具有相同孔隙率和线性路径分布函数L的“参考”和“重构”面包图像的C-2(r),证明了该函数描述面包结构元素之间的连通性的能力。 (r)。两个商用“ Pan Briosce”和“ Pancarre”以及一个非商用“ White”面包的空隙相的两点聚类功能可以突出显示其拓扑特性的显着差异。 “白”面包的特征是孔隙更均匀,连通性较低,而“ Pancarre”样品则表现出高度连通的空隙,从而形成较大的孔且形状极其复杂。此外,首次证明两点聚类函数的微观结构信息可区分面包样品总变异性的90%。 (C)2015 Elsevier Ltd.保留所有权利。

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