Evaluation of Yogurt Microstructure Using Confocal Laser Scanning Microscopy and Image Analysis

Abstract

The microstructure of protein networks in yogurts defines important physical properties of the yogurt and hereby partly its quality. Imaging this protein network using confocal scanning laser microscopy (CSLM) has shown good results, and CSLM has become a standard measuring technique for fermented dairy products. When studying such networks, hundreds of images can be obtained, and here image analysis methods are essential for using the images in statistical analysis. Previously, methods including gray level co-occurrence matrix analysis and fractal analysis have been used with success. However, a range of other image texture characterization methods exists. These methods describe an image by a frequency distribution of predefined image features (denoted textons). Our contribution is an investigation of the choice of image analysis methods by performing a comparative study of 7 major approaches to image texture description. Here, CSLM images from a yogurt fermentation study are investigated, where production factors including fat content, protein content, heat treatment, and incubation temperature are varied. The descriptors are evaluated through nearest neighbor classification, variance analysis, and cluster analysis. Our investigation suggests that the texton-based descriptors provide a fuller description of the images compared to gray-level co-occurrence matrix descriptors and fractal analysis, while still being as applicable and in some cases as easy to tune.

Effects of cold storage time on the quality and active probiotics of yogurt fermented by Bifidobacterium lactis and commercial bacteria Danisco

“…The above results indicated that the internal network structure of yogurt was stable and could withstand high frequency disruption, and yogurt systems showed a solid state, which was consistent with the results of Skytte et al. (2015). With the increase of frequency, tan δ decreased first and then increased, indicating that the elastic components were lost and the viscous components were gradually increased in the solid‐like yogurt system, and the elastic behavior of yogurt was gradually weakened, whereas the viscous behavior was enhanced (Zhao et al., 2013).…”

Dextran modulates physical properties of rennet‐induced milk gels

“…Pictures were acquired at a resolution of 1024 × 1024 using the Leica LAS AF 2.7.3 software (Leica Microsystems GmbH, Wetzlar, Germany). For image texture analysis, grey level co‐occurrence (GLC) matrices (Fagan et al , ; Skytte et al , ) were generated from grey scale 8‐bit images using version 0.4 plugin in Fiji (ImageJ Version 1.49b, http://www.fiji.sc).…”

Fermented coconut jelly as a probiotic vehicle, physicochemical and microbiology characterisation during an in vitro digestion

“…Then, they were washed with distilled water three times. All micrographs were captured using the modified method of Skytte et al (2015). A Leica DM IRE2 confocal scanning laser microscope (Leica Microsystems, Heidelberg, Germany) and a 40 × oil immersion objective (40 × HCX PL Apo 1.25 Oil) were used.…”