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Apios is a legume known to be nutrient dense. However, it is difficult for older adults to consume due to chewing difficulties. In this study, we analyzed its nutritional contents and antioxidant capacity and improved its texture through enzymatic treatment (polygalacturonase, cellulase, and α-amylase) to make it more palatable for older adults. Apios has been shown to have higher antioxidant capacity than other tubers, which is beneficial for geriatric health. Enzyme treatment (ETG1 7.12 h, ETG2 9.64 h, ETG3 over 6.48 h) made the texture suitable for consumption by the elderly. SEM analysis showed that the pore size increased and the cell wall was disrupted, resulting in irregular cell tissues. These changes can facilitate mastication and improve nutrient intake. Therefore, the enzyme-treated Apios is easy to chew, so it will be able to improve the intake of nutrients that the elderly need. In addition, it is expected to contribute to the expansion of the elder-friendly food industry by applying enzyme treatment to personalized food development considering different chewing abilities of the elderly. [ABSTRACT FROM AUTHOR]

This paper presents a physical space design method for mixed reality-based immersive environments by improving the color rendering of optically visible head-mounted displays. In OST-HMD, the phenomenon that the light of the external environment is combined with the enhanced image occurs, which reduces the visibility of the content. Moreover, previous studies to solve this problem required additional optical components or performed only simple verification. Proposed physical space was designed using black curtains, blinds, low-reflection structures, and adjustable lighting. The physical space can be adapted to the intended use of the physical space through physical transitions for multiple users without additional optics. To verify the usefulness of this environment, we measured the color gamut and intensity spectrum in three experimental environments. Also, we analyzed the factors that change the color gamut according to the components and the surrounding environment. As a result, the color gamut improved by up to 4.7 times from 19.92% to 93.53% based on the environment and improved by up to 4.1 times from 21% to 86.29% depending on the location. The experimental results revealed that the presented method could reduce the factors that degrade the color gamut within all measurement locations and significantly improve the color gamut. [ABSTRACT FROM AUTHOR]