Literature DB >> 21183015

X-ray microtomography to study the microstructure of cream cheese-type products.

J Laverse1, M Mastromatteo, P Frisullo, M A Del Nobile.   

Abstract

In this work, the imaging x-ray microtomography technique, new to the field of food science, was used for the analysis of fat microstructure and quantification of the fat present in cream cheese-type products. Five different types of commercially produced cheeses, chosen for their variability of texture, were used for this experiment: sample A, sample B, sample C, sample D, and sample E. Appropriate quantitative 3-dimensional parameters describing the fat structure were calculated (e.g., the geometric parameter percentage of fat volume was calculated for each image as a representation of the percentage of total fat content within the sample). The dynamic-mechanical properties of these samples were also studied using a controlled-strain rotational rheometer. Storage modulus and loss modulus were determined in a frequency range of 0.01 to 10 Hz. The strain value was obtained by preliminary strain sweep oscillatory trials to determine the linear viscoelastic region of the cream cheese-type products. Statistical correlation analysis was performed on the results to help identify any microstructural-mechanical structure relationships. The results from this study show that microtomography is a suitable technique for the microstructural analysis of fat in cream cheese-type products, as it does not only provide an accurate percentage of the volume of the fat present but can also determine its spatial distribution.
Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21183015     DOI: 10.3168/jds.2010-3524

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  1 in total

1.  Structural parameters for X-ray micro-computed tomography (μCT) and their relationship with the breakage rate of maize varieties.

Authors:  Junfeng Hou; Ying Zhang; Xiuliang Jin; Pengfei Dong; Yanan Guo; Keru Wang; Yinghu Fan; Shaokun Li
Journal:  Plant Methods       Date:  2019-12-27       Impact factor: 4.993

  1 in total

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