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The choice of tea utensils used for brewing significantly impacts the sensory and chemical attributes of tea. In order to assess the influence of various tea sets on the flavor and chemical composition of different tea varieties, a combination of sensory evaluation and high-performance liquid chromatography was employed. The results showed that the content of amino acids in the tea liquid brewed with tin tea utensils was relatively higher, which could exhibit freshness in taste, thus suitable for brewing green tea and white tea. The content of polyphenols, soluble carbohydrates, and water extract in the tea liquid brewed with a porcelain tea set was relatively higher; the sweetness and thickness of the tea liquid were increased, so it was more beneficial to brew black tea. The purple sand tea set was suitable for brewing oolong tea and dark tea, and could endow their respective quality characteristics. Ultimately, these research findings provide a scientific basis for the selection of tea utensils tailored to different types of tea. [ABSTRACT FROM AUTHOR]

With the rapid development of LiDAR technology in recent years, high-resolution LiDAR data possess a great capability to describe fine surface morphology in detail; thus, differencing multi-temporal datasets becomes a powerful tool to explain the surface deformation process. Compared with other differencing methods, ICP algorithms can directly estimate 3D displacements and rotations; thus, surface deformation parameters can be obtained by aligning window point clouds. However, the traditional ICP algorithm usually requires a good initial pose of the point cloud and relies on calculating the spatial distance to match the corresponding points, which can easily lead the algorithm to the local optimum. To address the above problems, we introduced the color information of the point cloud and proposed an improved ICP method that fuses RGB (RGB-ICP) to reduce the probability of matching errors by filtering color-associated point pairs, thus improving the alignment accuracy. Through simulated experiments, the ability of the two algorithms to estimate 3D deformation was compared, and the RGB-ICP algorithm could significantly reduce the deformation deviation (30–95%) in the three-dimensional direction. In addition, the RGB-ICP algorithm was applicable to different terrain structures, especially for smooth terrain, where the improvement was the most effective in the horizontal direction. Finally, it is worth believing that the RGB-ICP algorithm can play a unique role in surface change detection and provide a reliable basis for explaining the surface motion process. [ABSTRACT FROM AUTHOR]

The chemical substances responsible for the kokumi taste of green tea infusion are still unclear. Here, we isolated the kokumi compound-containing fractions from green tea infusion through ultrafiltration, and the major kokumi compounds were characterized as γ-Glu-Gln and γ-Glu-Cys-Gly (GSH) through ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS). The results indicated that peptides and amino acids were essential compounds in the kokumi-enriched fractions for conducting the sense of kokumi. L-theanine had an enhancing effect on the kokumi taste of green tea infusion, which was confirmed in the sensory reconstitution study. Thus, peptides, especially γ-Glu-Gln and GSH, are the major kokumi compounds in green tea infusion, which has the potential of improving the flavor of tea beverages. [ABSTRACT FROM AUTHOR]