Characterization of Food Structures and Functionalities

Some functional properties such as texture and nutrition are the most important attributes used by consumers to assess food qualities, which have been used for in nearly all kinds of food products, from beverage, yoghurt, and ice cream to bread and noodles. Nowadays, there is a desire tomake foods healthier and at the same time not diminish sensory quality. This requires an understanding of key elements of food structure associated with texture and nutritional perception. In terms of taste perception, texture is perceived during oral processing of food

Seeking Salient Facial Regions for Cross-Database Micro-Expression Recognition

Cross-Database Micro-Expression Recognition (CDMER) aims to develop the Micro-Expression Recognition (MER) methods with strong domain adaptability, i.e., the ability to recognize the Micro-Expressions (MEs) of different subjects captured by different imaging devices in different scenes. The development of CDMER is faced with two key problems: 1) the severe feature distribution gap between the source and target databases; 2) the feature representation bottleneck of ME such local and subtle facial expressions. To solve these problems, this paper proposes a novel Transfer Group Sparse Regression method, namely TGSR, which aims to 1) optimize the measurement and better alleviate the difference between the source and target databases, and 2) highlight the valid facial regions to enhance extracted features, by the operation of selecting the group features from the raw face feature, where each region is associated with a group of raw face feature, i.e., the salient facial region selection. Compared with previous transfer group sparse methods, our proposed TGSR has the ability to select the salient facial regions, which is effective in alleviating the aforementioned problems for better performance and reducing the computational cost at the same time. We use two public ME databases, i.e., CASME II and SMIC, to evaluate our proposed TGSR method. Experimental results show that our proposed TGSR learns the discriminative and explicable regions, and outperforms most state-of-the-art subspace-learning-based domain-adaptive methods for CDMER

Shear degradation of corn starches with different amylose contents

This work investigated the effect of shear on the starch degradation, with a particular focus on the changes in molecular and lamellar structures. Corn starches with different amylose/amylopectin ratios (waxy corn starch, or WCS: 1:99; normal corn starch, or NCS: 25:75; and Gelose 80 starch, or G80: 80:20) were used as model materials to be processed using a Haake twin-rotor mixer for different times. Molecular and lamellar structural analysis was performed using size-exclusion chromatography (SEC) and small-angle X-ray scattering (SAXS). The degree of damage of starch at the granule level was evaluated by an assay kit. The results showed that amylose molecules in starch granules did not change significantly, while amylopectin molecules degraded to a stable size caused by the shear treatment. The average thickness of semi-crystalline lamellae disappeared rapidly during processing. A typical positive deviation from Porod's law at a high q region was observed, attributed to the presence of thermal density fluctuations or mixing within phases. Nonetheless, the degree of mixing within phases for the processed samples was lower than the native starch. The study of the mass fractal structure indicated that the scattering objects of the processed starches were more compact than those of the native counterparts. Furthermore, waxy corn starch (containing mostly amylopectin) experienced the greatest granule damage than the other starches. All the results showed that the rigid crystal structure in amylopectin is more sensitive to the shear treatment than the flexible amorphous structure in amylose. This mechanistic understanding at the microstructure level is helpful in designing the processing of starch-based foods or plastics with desired functional properties

Different genetic strategies to generate high amylose starch mutants by engineering the starch biosynthetic pathways

This review systematically documents the major different strategies of generating high-amylose (HAS) starch mutants aiming at providing high resistant starch, by engineering the starch biosynthesis metabolic pathways. We identify three main strategies based on a new representation of the starch structure: 'the building block backbone model': i) suppression of starch synthases for reduction of amylopectin (AP) side-chains; ii) suppression of starch branching enzymes (SBEs) for production of AM-like materials; and iii) suppression of debranching enzymes to restrain the transformation from over-branched pre-AP to more ordered AP. From a biosynthetic perspective, AM generated through the second strategy can be classified into two types: i) normal AM synthesized mainly by regular expression of granule-bound starch synthases, and ii) modified linear AP chains (AM-like material) synthesized by starch synthases due to the suppression of starch branching enzymes. The application of new breeding technologies, especially CRISPR, in the breeding of HAS crops is also reviewed

Lamellar structure change of waxy corn starch during gelatinization by time-resolved synchrotron SAXS

In situ experiment of synchrotron small- and wide-angle X-ray scattering (SAXS/WAXS) was used to study the lamellar structure change of starch during gelatinization. Waxy corn starch was used as a model material to exclude the effect of amylose. The thicknesses of crystalline (d), amorphous (d) regions of the lamella and the long period distance (d) were obtained based on a 1D linear correlation function. The SAXS and WAXS results reveal the multi-stage of gelatinization. Firstly, a preferable increase in the thickness of crystalline lamellae occurs because of the water penetration into the crystalline region. Then, the thickness of amorphous lamellae has a significant increase while that of crystalline lamellae decreases. Next, the thickness of amorphous lamellae starts to decrease probably due to the out-phasing of starch molecules from the lamellae. Finally, the thickness of amorphous lamellae decreases rapidly, with the formation of fractal gel on a larger scale (than that of the lamellae), which gradually decreases as the temperature further increases and is related to the concentration of starch molecular chains. This work system reveals the gelatinization mechanism of waxy corn starch and would be useful in starch amorphous materials processing

Characterization of Food Structures and Functionalities

Some functional properties such as texture and nutrition are the most important attributes used by consumers to assess food qualities, which have been used for in nearly all kinds of food products, from beverage, yoghurt, and ice cream to bread and noodles. Nowadays, there is a desire tomake foods healthier and at the same time not diminish sensory quality. This requires an understanding of key elements of food structure associated with texture and nutritional perception. In terms of taste perception, texture is perceived during oral processing of food

Food polymers functionality and applications

Food polymers are polymers from edible plants, animals, and microorganisms that can be used in food systems, including proteins, polysaccharides, and peptides. Generally, food polymers can be classified into three groups based on their sources: (1) plant-based food polymers, such as starch, dietary fiber, and cereal protein; (2) animal-based food polymers, such as meal protein; (3) microorganism-based food polymers, such as fungus polysaccharides. The oils and/or lipid from plant and animals could also be considered as food polymers although their molecular weights are relatively small