This study examined the antioxidant activity and quality of Jeung-pyun prepared with different concentrations of hardy kiwi powder at 0%, 2.5%, 5%, 7.5%, and 10%. When the moisture content of Jeung-pyun was between 49.94-53.33%, the pH measurement showed a significant decrease with the increase of the hardy kiwi powder from 3.95 to 4.82. The L (lightness) values and the (redness) values decreased, whereas the b (yellowness) values increased with increasing amounts of hardy kiwi powder. The study showed a significant decrease in hardness, chewiness, and gumminess as the proportion of hardy kiwi powder in the Jeung-pyun increased. The total polyphenol content and DPPH radical scavenging activity increased noticeably as more hardy kiwi powder was added to the Jeung-pyun. As a result, the study groups with added hardy kiwi powder showed higher antioxidant activity than the control groups. Based on the results, this study recommends hardy kiwi as a good ingredient for enhancing the functionality of Jeung-pyun.

In this study, we tried to find out the most appropriate pre-processing method and to verify the feasibility of developing a low-price sensing system for predicting the hardy kiwis sugar content based on VNIRS and subsequent spectral analysis. A total of 495 hardy kiwi samples were collected from three farms in Muju, Jeollabukdo, South Korea. The samples were scanned with a spectrophotometer in the range of 730-2300 nm with 1 nm spectral sampling interval. The measured data were arbitrarily separated into calibration and validation data for sugar content prediction. Partial least squares (PLS) regression was performed using various combinations of pre-processing methods. When the latent variable (LV) was 8 with the pre-processing combination of standard normal variate (SNV) and orthogonal signal correction (OSC), the highest R2 values of calibration and validation were 0.78 and 0.84, respectively. The possibility of predicting the sugar content of hardy kiwi was also examined at spectral sampling intervals of 6 and 10 nm in the narrower spectral range from 730 nm to 1200 nm for a low-price optical sensing system. The prediction performance had promising results with R2 values of 0.84 and 0.80 for 6 and 10 nm, respectively. Future studies will aim to develop a low-price optical sensing system with a combination of optical components such as photodiodes, light-emitting diodes (LEDs) and/or lamps, and to locate a more reliable prediction model by including meteorological data, soil data, and different varieties of hardy kiwi plants.