The effect of additives combination on rheological properties of dough and quality of bread with Agaricus bisporus powder

The bread with Agaricus bisporus powder has the defects of poor texture and taste, so it is necessary to optimize the appropriate additives in order to improve its quality. The purpose of this study was to evaluate improvement of the combination of vital wheat gluten, sucrose fatty acid esters and cellulase on the improved Agaricus bisporus powder bread (IABPB), with wheat bread (WB) and bread with Agaricus bisporus powder (ABPB) as control. The results of rheological properties indicated the dough samples improved with three improvers had higher solid-like behaviour than the control sample. The results of nutritional quality analysis showed that the protein and dietary fiber content of IABPB was higher than those of WB and ABPB, but the fat content was relatively low. In addition, the additives combination could effectively improve the baking quality of ABPB. Compared with ABPB without additives, the specific volume increased by 21.22%, the brightness of bread crumb increased by 8.75%, but the crumb hardness decreased by 32.57%. Furthermore, the study on texture property and water migration during the storage showed that the addition of three improvers could delay the aging of bread. Therefore, it was feasible to use additives combination as a special quality improver for ABPB, which could effectively improve its quality.

Texture–Property Relationships in Aluminum Alloys: Simulations and Experiments

Aluminum alloys provide a huge and increasing application spectrum for formed and cast products. This article texture and anisotropy of aluminum alloys. Topics covered include: experimental determination of surface strains, nanotextures and microtextures, constitutive laws for crystal plasticity finite element simulations and cellular automata for recrystallization, microscopic aspects of texture evolution during plastic deformation and recrystallization, relationship between texture, microstructure and surface properties, integration anisotropy into metal-forming simulations, and crystallographic approximation elastic-plastic anisotropy.

Clustering-Based Color Image Segmentation Using Local Maxima

Color image segmentation has contributed significantly to image analysis and retrieval of relevant images. Color image segmentation helps the end user subdivide user input images into unique homogenous regions of similar pixels, based on pixel property. The success of image analysis is largely owing to the reliability of segmentation. The automatic segmentation of a color image into accurate regions without over-segmentation is a tedious task. Our paper focuses on segmenting color images automatically into multiple regions accurately, based on the local maxima of the GLCM texture property, with pixels spatially clustered into identical regions. A novel Clustering-based Image Segmentation using Local Maxima (CBIS-LM) method is presented. Our proposed approach generates reliable, accurate and non-overlapping multiple regions for the given user input image. The segmented regions can be automatically annotated with distinct labels which, in turn, help retrieve relevant images based on image semantics.