• Korean Journal of Agricultural Science
• /
• v.46 no.2
• /
• pp.239-256
• /
• 2019

The quality of tomatoes drastically changes according to storage conditions, such as temperature, humidity, and air composition. High storage temperatures result in the degradation of the firmness and color of tomatoes and in decay by bacteria, whereas chilling injury and softening can be caused by storage at low temperatures. The gas composition in the storage and packaging are other parameters that influence the quality and shelf life of tomatoes by preventing excessive transpiration and respiration. In addition, tomato quality is dependent on the degree of maturity and harvest season. Because there are many quality parameters, it is necessary to systemically establish an optimal standard, and this approach requires collecting and reviewing various data on storage conditions. The aim of this review was to provide basic information by comparing and analyzing studies on the changes in tomato quality (firmness, color, lycopene content, and acidity of tomatoes) during storage and to describe a few models that can assess the quality parameters. Many studies have provided results from experiments on the effects of postharvest control (e.g., storage temperature, packaging film, and gas treatment, as reviewed above) on tomato quality including firmness, soluble solids content, and lycopene content. However, it is still necessary to conduct an overall analysis of the published conditions and to determine the best method for preserving the quality of tomatoes as well as other fruits.

• Asia-Pacific Journal of Business
• /
• v.11 no.3
• /
• pp.63-77
• /
• 2020

Purpose - The purpose of this study is to examine the effects of personal characteristics, loan characteristics, and interest rate characteristics of 2,653 borrowers on the delinquency possibility. In doing so, this study applies both multiple regression and logistic regression models to the data of credit unions in the city of Daegu. Design/Methodology/Approach - The major results of multiple regression analysis using SPSS are as follows. Findings - As for the results of testing the significance of the regression coefficients, it has been found that among the personal characteristics variables membership, credit rating, credit rating changes, and LTV have significant positive (+) effects on the delinquency possibility. Also it has been shown that among the loan characteristics variables loan amount, loan balance, total debt amount, collateral type, collateral amount, and repayment method have significant positive (+) effects on the delinquency possibility. Furthermore it has been found that among the interest rate characteristics variables both overdue interest rate and interest rate spread have positive (+) effects on the delinquency possibility. However, it has been shown that among the personal characteristics variables equity and membership do not have significant effects on the delinquency possibility, and that normal interest rate among the interest rate characteristics variables also do not have a significant effect on the delinquency possibility. Research Implications - By systematically analyzing the variables affecting delinquency possibility based on the results of this study, credit unions might get positive help in improving the system of managing receivables. Furthermore, the results of this study could be extended and applied to other types of financial institutions, so that financial institutions in general will also get some help to systematically manage the delinquency possibility.

• Korean small business review
• /
• v.42 no.2
• /
• pp.117-137
• /
• 2020

We examine the current status of smart factory deployment and diffusion programs in Korea, and seek to promote manufacturing innovation from the perspective of SMEs. The main conclusions of this paper are as follows. First, without additional market creation and supply chain improvement, smart factories are unlikely to raise profitability leading to overinvestment. Second, new business models need to connect "manufacturing process efficiency" with "R&D" and "marketing" in value chain in smart factories. Third, when introducing smart factories, we need to focus on the areas where process-embedded technology is directly linked to corporate competitiveness. Based on the modularity-maturity matrix (Pisano and Shih, 2012) and the examples of U.S. Manufacturing Innovation Institute (MII), we establish the new smart factory deployment policy measures as follows. First, we shift our smart factory strategy from quantitative expansion to qualitative upgrading. Second, we promote by each sector the formation of industrial commons that help SMEs to jointly develop R&D, exchange standardized data and practices, and facilitate supplier-led procurement system. Third, to implement new technology and business models, we encourage partnerships, collaborations, and M&As between conventional SMEs and start-ups and business ventures. Fourth, the whole deployment process of smart factories is indexed in detail to identify the problems and provide appropriate solutions.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.55 no.4
• /
• pp.312-318
• /
• 2010

This study was carried out to develop and test a prototype program that recommends the nitrogen topdressing rate using the color digital camera image taken from rice field at panicle initiation stage (PIS). This program comprises four models to estimate shoot N content (PNup) by color digital image analysis, shoot N accumulation from PIS to maturity (PHNup), yield, and protein content of rice. The models were formulated using data set from N rate experiments in 2008. PNup was found to be estimated by non-linear regression model using canopy cover and normalized green values calculated from color digital image analysis as predictor variables. PHNup could be predicted by quadratic regression model from PNup and N fertilization rate at panicle initiation stage with $R^2$ of 0.923. Yield and protein content of rice could also be predicted by quadratic regression models using PNup and PHNup as predictor variables with $R^2$ of 0.859 and 0.804, respectively. The performance of the program integrating the above models to recommend N topdressing rate at PIS was field-tested in 2009. N topdressing rate prescribed for the target protein content of 6.0% by the program were lower by about 30% compared to the fixed rate of 30% that is recommended conventionally as the split application rate of N fertilizer at PIS, while rice yield in the plots top-dressed with the prescribed N rate were not different from those of the plots top-dressed with the fixed N rates of 30% and showed a little lower or similar protein content of rice as well. And coefficients of variation in rice yield and quality parameters were reduced substantially by the prescribed N topdressing. These results indicate that the N rate recommendation using the analysis of color digital camera image is promising to be applied for precise management of N fertilization. However, for the universal and practical application the component models of the program are needed to be improved so as to be applicable to the diverse edaphic and climatic condition.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.24 no.3
• /
• pp.164-178
• /
• 2022

Uncertainties in weather forecasts would affect the reliability of yield prediction using crop models. The objective of this study was to compare uncertainty in crop yield prediction caused by the use of the weather forecast data. Daily weather data were produced at 10 km spatial resolution using W eather Research and Forecasting (W RF) model. The nearest neighbor method was used to downscale these data at the resolution of 5 km (W RF5K). Parameter-elevation Regressions on Independent Slopes Model (PRISM) was also applied to the WRF data to produce the weather data at the same resolution. W RF5K and PRISM data were used as inputs to the CROPGRO-SOYBEAN model to predict crop yield. The uncertainties of the gridded data were analyzed using cumulative growing degree days (CGDD) and cumulative solar radiation (CSRAD) during the soybean growing seasons for the crop of interest. The degree of agreement (DOA) statistics including structural similarity index were determined for the crop model outputs. Our results indicated that the DOA statistics for CGDD were correlated with that for the maturity dates predicted using WRF5K and PRISM data. Yield forecasts had small values of the DOA statistics when large spatial disagreement occured between maturity dates predicted using WRF5K and PRISM. These results suggest that the spatial uncertainties in temperature data would affect the reliability of the phenology and, as a result, yield predictions at a greater degree than those in solar radiation data. This merits further studies to assess the uncertainties of crop yield forecasts using a wide range of crop calendars.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.41 no.spc1
• /
• pp.25-45
• /
• 1996

Soyfoods have potential roles in the prevention and treatment of chronic diseases, most notably cancer, osteoporosis, and heart disease. There is evidence that carcinogenesis are supressed by isolated soybean derived products in vivo such as a protease inhibitor, phytic acid, saponins and isoflavones. It is believed that supplementation of human diets with soybean products markedly reduces human cancer mortality rates. Especially, recent papers recognize the potential benefit of soybean isoflavone components for reducing the risk of various cancers. Isoflavones exhibit a multitude of medicinal effects that influence cell growth and regulation, which may have potential value in the prevention and treatment of cancer. In addition to potential biological effects, soybean isoflavones have the important physiological functions such as the induction of Bradyrizobium japonicum nod genes and the responses of soybean tissues to infection by Phytophthora megasperma as well as biochemical activities such as antifungal and antibacterial actions. Genistin, daidzin, glycitin and their aglycone (genistein, daidzein, glycitein) are the principal isoflavones found in soybean. Malonyl and acetyl forms have also been detected but they are thermally unstable and are usually transformed during the processing in glucoside form. Most soy products, with the exception of soy sauce, alcohol-extracted soy protein concentrate, and soy protein isolate, have total isoflavone concentrations similar to those in the whole soybean. Soybean-containing diets inhibit mammary tumorigenesis in animal models of breast cancer, therefore, it is possible that dietary isoflavones are an important factor accounting for the lower incidence and mortality from breast cancer. Of the total soybean seed isoflavones, $80\~90\%$ were located in cotyledons, with the remainder in the hypocotyls. The hypocotyls had a higher concentrations of isoflavones on a weight basis compared with cotyledons. Isoflavone contents were influenced by genetics, crop years, and growth locations. The effect of crop year had a greater impact on the isoflavone contents than that of location. The climate condition might be the attribution factor to variation in isoflavone contents. Also, while the isoflavone content of cotyledons exhibited large variations in response to high temperature during seed development, hypocotyls showed high concentration in isoflavone content. So, it is concluded that one of the factors affecting isoflavone content in soybean seeds is temperature during seed development. High temperature, especially in maturity stage, causes lower isoflavone content in soybean seed. It is also suggested that there may exist a different mechanism to maintain isoflavone contents between cotyledon and seed hypocotyls. In a conclusion, soy foods may be able to have a significant beneficial impact on public health.

• Journal of Korea Spatial Information System Society
• /
• v.1 no.2 s.2
• /
• pp.63-80
• /
• 1999

This study presents NGDM(National Geospatial Information Distribution Model) in order to effectively utilize and differently apply geospatial information which is important in the dispersion of GIS. In order to establish the NGDM, this study draws the guideline of NGDM in Korea by analyzing its present condition of domestic and foreign geospatial information distribution. It also investigates some major factors forming the infrastructure of NGDM in regulative, technical, physical, and social aspects. Based on these factors, this study presents a three-staged NGDM that is applicable in Korea. The NGDM consists of four components that are the consumer, supplier, gateway for the clearinghouse and the clearinghouse of the geospatial information. According to the management form of geospatial information, the types of NGDM are classified as the concentration type, the distribution type, and compound type. Also, this study explains the mutual relationship between the NGDM's components and suggests a three-staged NGDM of planting, growth, and maturity period considering comparison results of classified models and development direction of regulation, protocol, communication network, electronic commerce, and etc.

• Journal of Korean Society for Quality Management
• /
• v.41 no.4
• /
• pp.725-735
• /
• 2013

Purpose: The purpose of this study is to propose an Integrated Safety Evaluation Process (ISEP) that can enhances the safety aspect of the safety-critical system. This process utilizes the advantages of the iterative Systems Engineering process combined with the safety assessment process that is commonly and well defined in many standards and/or guidelines for railway, aerospace, and other safety-critical systems. Methods: The proposed process model is based on the predefined system lifecycle, in each phase of which the appropriate safety assessment activities and the safety data are identified. The interfaces between Systems Engineering process and the safety assessment process are identified before the two processes are integrated. For the integration, the elements at lower level of Systems Engineering process are combined with the relevant elements of safety assessment process. This combined process model is represented as Enhanced Functional Flow Block Diagram (EFFBD) by using CORE(R) that is commercial modelling tool. Results: The proposed model is applied to the lifecycle and management process of the United States aircraft system. The US aircraft systems engineering process are composed of twelve key elements, among which the requirements management, functional analysis, and Synthesis processes are considered for examplenary application of the proposed process. To synchronize the Systems Engineering process and the safety assessment process, the Systems Engineering milestones are utilized, where the US aircraft system has thirteen milestones. Taking into account of the nine steps in the maturity level, the integrated process models are proposed in some phases of lifecycle. The flows of processes are simulated using CORE(R), confirming the flows are timelined without any conflict between the Systems Engineering process and the safety assessment process. Conclusion: ISEP allows the timeline analysis for identifying activity and data flows. Also, the use of CORE(R) is shown to be effective in the management and change of process data, which helps for the ISEP to apply for the development of safety critical system. In this study, only the first few phases of lifecyle are considered, however, the implementation through operation phases can be revised by combining the elements of safety activities regarding those phases.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.15 no.1
• /
• pp.26-39
• /
• 2013

Yield reduction in major cereal grains seems unavoidable with the existing cropping systems under the projected climate change in Korea. Crop models were used to predict the effects of planting date shift on grain yields of rice, winter barley and soybeans at 64 agroclimatic zones in Korea. The shift of planting date by 7, 14, and 21 days before and after the recommended planting dates were incorporated in DSSAT experiment files to simulate growth, development and grain yields of major cereal crops. These included 3 rice cultivars representing early-, medium- and late-maturity groups, 1 winter barley and 1 soybean cultivars. Partial mitigation in yield reduction was found with earlier planting in the early maturing rice cultivar and with delayed planting in the late maturing rice cultivar under the RCP8.5 projected climate change in Korea. Additional yield increase in winter barley was expected by earlier planting treatments. Soybean showed a positive effect on grain yield with earlier planting. However, the rate was much lower than the case with winter barley and delayed planting caused yield reduction.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.20 no.3
• /
• pp.243-251
• /
• 2018

The gridded simulation of crop growth, which would be useful for shareholders and policy makers, often requires specialized computation tasks for preparation of weather input data and operation of a given crop model. Here we developed an automated system to allow for crop growth simulation over a region using the DSSAT (Decision Support System for Agrotechnology Transfer) model. The system consists of modules implemented using R and shell script languages. One of the modules has a functionality to create weather input files in a plain text format for each cell. Another module written in R script was developed for GIS data processing and parallel computing. The other module that launches the crop model automatically was implemented using the shell script language. As a case study, the automated system was used to determine the maximum soybean yield for a given set of management options in Illinois state in the US. The AgMERRA dataset, which is reanalysis data for agricultural models, was used to prepare weather input files during 1981 - 2005. It took 7.38 hours to create 1,859 weather input files for one year of soybean growth simulation in Illinois using a single CPU core. In contrast, the processing time decreased considerably, e.g., 35 minutes, when 16 CPU cores were used. The automated system created a map of the maturity group and the planting date that resulted in the maximum yield in a raster data format. Our results indicated that the automated system for the DSSAT model would help spatial assessments of crop yield at a regional scale.