• Journal of the East Asian Society of Dietary Life
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• v.12 no.1
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• pp.38-46
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• 2002

This study was carried out in order to investigate dextran formation and internal structure during fermentation of the oligosaccharide Jeung-Pyun. The dextran and sugar reducing contents of Jeung-Pyun batter and the specific volume and the internal structure of Jeung-Pyun were analyzed as a function of fermentation time. The specific volume of Jeung-Pyun peaked at the 7th hour of fermentation. The dextran content of Jeung-Pyun batters peaked at the 7~13th hour of fermentation, and Fructooligosaccharide Jeung-Pyun had the least peak value. Reducing sugar content of Jeung-Pyun batters slowly decreased as fermentation progressed. From the air pore size and distribution of Jeung-Pyun observed by SEM, the sucrose Jeung-Pyun fermented for 3~7 hours and oligosaccharide one fermented for 7 hours were judged as the best. It was concluded that dextran may be formed by fermentation of oligosaccharides as well as sucrose and dextran has a significant role on the volume expansion of Jeung-Pyun.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.763-776
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• 2020

Onions show severe volatility in production and price because crop conditions highly depend on the weather. The government has designated onions as a sensitive agricultural product, and prepared various measures to stabilize the supply and demand. First of all, preemptive and reliable information on predicting onion production is essential to implement appropriate and effective measures. This study aims to contribute to improving the accuracy of production forecasting by developing a model to estimate the final weight of onions bulb. For the analysis, multi-level model is used to reflect the hierarchical data characteristics consisting of above-ground growth data in individual units and meteorological data in parcel units. The result shows that as the number of leaf, stem diameter, and plant height in early May increase, the bulb weight increases. The amount of precipitation as well as the number of days beyond a certain temperature inhibiting carbon assimilation have negative effects on bulb weight, However, the daily range of temperature and more precipitation near the harvest season are statistically significant as positive effects. Also, it is confirmed that the fitness and explanatory power of the model is improved by considering the interaction terms between level-1 and level-2 variables.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.312-326
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• 2020

Generation of weather forecasts at 100 m resolution through a statistical downscaling process was implemented by Korea Meteorological Administration Post- Processing (KMAPP) system. The KMAPP data started to be used in various industries such as hydrologic, agricultural, and renewable energy, sports, etc. Cheorwon area and Jeonbuk area have horizontal planes in a relatively wide range in Korea, where there are many complex mountainous areas. Cheorwon, which has a large number of in-situ and remotely sensed phenological data over large-scale rice paddy cultivation areas, is considered as an appropriate area for verifying KMAPP prediction performance in agricultural areas. In this study, the performance of predicting KMAPP temperature changes according to ecological changes in agricultural areas in Cheorwon was compared and verified using KMA and National Center for AgroMeteorology (NCAM) observations. Also, during the heat wave in Jeonbuk Province, solar radiation forecast was verified using Automated Synoptic Observing System (ASOS) data to review the usefulness of KMAPP forecast data as input data for application models such as livestock heat stress models. Although there is a limit to the need for more cases to be collected and selected, the improvement in post-harvest temperature forecasting performance in agricultural areas over ordinary residential areas has led to indirect guesses of the biophysical and phenological effects on forecasting accuracy. In the case of solar radiation prediction, it is expected that KMAPP data will be used in the application model as detailed regional forecast data, as it tends to be consistent with observed values, although errors are inevitable due to human activity in agricultural land and data unit conversion.