• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.2
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• pp.125-130
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• 2008

This study analyzed the growth, seed quality, and yield of major early-maturing soybean cultivars by comparing them in order to utilize the research results in the selection of early-maturing soybean cultivars in multi-cropping farms in the Southern area. This field trial was conducted at Naju region (latitude $35^{\circ}04'N$, longitude $126^{\circ}54'E$), Jeonnam, with planting on June 15. The maturing date for Keunol-kong and Hwaseong-put-kong was found to be around September 12, which was earlier than other cultivars. Thus, there were advantages to introducing a cropping system as well as having good seed quality and high yield. On the other hand, the maturing date for Saeol-kong and Sinrok-kong was found to be around September 20, which was a little bit late; however, the seed quality of the cultivars was good and they had a high yield. Therefore, if we want to sow the following crops of soybeans around mid-September, Keunol-kong and Hwaseong-put-kong are advantageous, while for the seeding around late September, Saeol-kong and Sinrok-kong would be good. This study was also performed to identify the limitation time for early harvesting by reviewing seed quality and yield of major early-maturing soybean cultivars according to early harvesting. When harvesting Keunol-kong on September 6, which was six days earlier than the optimal harvesting time (September 12), there was no difference in seed weight, yield, or seed quality than those of the harvested at the optimum maturing time. As for Saeol-kong, when harvesting on September 18, which was six days earlier than the optimal harvesting time (September 24), there was no difference in seed weight, yield, or seed quality than those of the harvested at the optimum maturing time. Therefore, the stable limitation time for early harvesting of Keunol-kong and Saeol-kong was concluded to be six days earlier than the optimal harvesting time.

• Korean journal of applied entomology
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• v.27 no.2
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• pp.117-124
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• 1988

An Investigation of insect pests in rice stored was carried out in Jeonnam region of Korea. The total of 2 class, 7 orders 16 families and 25 species were recorded in Lepidoptera; 8, Coleoptera; 11, Orthoptera; 1, Thysanura 1, blattaria; 2, Hymenoptera; 1 and mites; 2 spe-cies. The important species among them were Sitotroga cerealella, Ephestia cautella, Paral-ipsa gularis, Poldia, in Lepidoptera, and Sitophilus orzae, Oryzaephilus surianmensis, Cryptolestes ferrugineus, Tribolium castaneum, Tenebroides mauritanicus, Attagenus japonicus, in Coleoptera and Blatella germanica, in Blattaria and Acarus siro Petrobia latens, in mites. The duration of maximum occurrence were the late June to mid July for Sitotroga cerealella, the mod July to early August for Oryzaephilus surianmensis the mid July to August for Tribolium castaneum, the early July to late July for Sitophilus orzae, the mid June to early July for Attagenus japonicus the mid June to late Spetember for Blatella germanica and the late April to late May for Acarus siro and Petrobia latens, respectively in investigation, Blatella germanica(Blattaria) which was no problem in stored rice insect till now was mainly distributed a coastal plain and period of occurrence was long amount of occurrence was great. Rice weevil has 4 generations under natural conditions and the peak of 1st perood time was ranged from middle of jun. to last decade of Jun., 2nd period was from the lats decade of Jul. to first decade of Aug., 3rd period was from middle of Sep. to late Sep., 4th period was middle of Oct. to early Nov.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.58 no.1
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• pp.57-66
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• 2013

The purpose of this study was to investigate the effects of shifts in sowing time on the ecological responses, growth and yields of major soybean cultivars in a southern region of South Korea. Experiments were carried out in Naju, Jeonnam Province (latitude $35^{\circ}$ 04'N, longitude $126^{\circ}$ 54'E) for three years from 2008 to 2010. The test cultivars included Saeol-kong and Tawon-kong of the summer type, Taekwang-kong and Pungsannamul-kong, and Cheongja3 of the autumn type. Sowing took place on May 15 and 30, June 15 and 30, and July 15 of each year. Of the summer type soybean cultivars, Saeol-kong showed a smaller curtailment in days from sowing to flowering, days from flowering to maturity, and days from sowing to maturity according to sowing time postponement than Tawon-kong. Of the autumn type soybean cultivars, Taekwang-kong exhibited a lower photoperiodic response in reproductive growth period than Pungsannamul-kong and Cheongja3, both of which recorded higher level photoperiodic responses in vegetative growth stages and reproductive growth periods than other test cultivars, with the former exhibiting higher levels than the latter. Most of the test cultivars tended to decrease in stem length, node numbers of the main stem, and stem diameter according to postponed sowing time, but there were no significant differences in stem length and node numbers of the main stem of the Saeol-kong cultivar. Differences in sowing times did not affect the first setting pod node order of Saeol-kong and Tawon-kong summer type cultivars of internode lengths of all of the test cultivars. All of the test cultivars tended to show decreases in pod number per plant due to postponement of sowing time except for the Saeol-kong cultivar. The variation was more prominent in small grain cultivars such as Tawon-kong and Pungsannamul-kong with the latter autumn type cultivar showing especially large variation. Yields were the greatest for the Tawon-kong, Taekwang-kong, and Pungsannamul-kong cultivars sown on May 30 and Cheongja3 sown on May 30 and June 15. There were no significant differences in the yields of Saeol-kong for different sowing times from May 30 to July 15, with the yields lowest for the batch sown on May 15.

• Journal of Animal Science and Technology
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• v.54 no.4
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• pp.247-253
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• 2012

Ultrasound measures of back fat thickness (UBF), eye muscle area (UEMA) and marbling score (UMS) and carcass measures of carcass weight (CW), backfat thickness (BF), eye muscle area (EMA) and marbling score (MS) were available on 26,129 Hanwoo steers. Statistically significant differences by regions of the farms location and birth years-seasons for the steers taken ultrasound measures and their carcass measures (p<0.01) were found. Steers in Gyeonggi province showed the highest values in ultrasound measures and carcass traits except in BF compared to steers in the other provinces. Comparing between ultrasound and carcass measures, UBF was thicker in general than BF in all regions except in Daejeon city. UEMA was higher than EMA in all regions except in Gyeonggior in Jeju provinces. Especially, the difference in Jeonnam province between UEMA and EMA was $7cm^2$ while the differences between UMS and MS ranged from 0.9 to 2.26 depending on the regions of steers located. Steers born in spring showed greater ultrasound or carcass values than those born in autumn. However, carcass measures of steers born in autumn were greater than those born in spring, 2009 except MS. The pearson and residual correlations were 0.63 and 0.65 between UBF and BF, 0.31 and 0.32 between UEMA and EMA and 0.56 and 0.56 between UMS and MS, respectively.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.2
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• pp.95-110
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• 2022

This study was conducted to determine the extent to which climate change is expanding areas in which barley can be successfully cultivated. In 2019 and 2020, we collected data on areas that had requested certified seeds from the Korea Seed and Variety Service to determine potential cultivation areas. In addition, we surveyed the growth and yield of different types of barley in fields. Certified seeds of hulled and dehulled barley were requested by farmers across Korea from the Korea Seed and Variety Service in both years. Areas that were provided with certified seeds were considered potential barley cultivation areas. The varieties and use rates of certified seeds varied based on the barley type and region. For example, certified seeds of dehulled barley in 2019 and 2020 were not used in some areas, whereas in others, these seeds constituted 100% of the seeds sown for barley crops. In 2019 and 2020, the average sowing days in Korea were from October 17 to November 9 for dehulled barley, October 26 to November 13 for hulled barley, October 19 to November 5 for malting barley, and October 3 to November 1 for naked oats. Thus, the sowing days of the barley types varied depending on the area and year they were used. For example, in the case of hulled barley in Jeonnam, some farmers sowed until December 12. The yield per 10 a of barley cultivation was typically higher in the main production areas than in the cultivation limit areas. In extreme cases, harvest was impossible in some cultivation limited areas, such as Gangwon-do. Based on the current 20-year January minimum average temperature (JMAT) in Korea (2002-2021), climate change scenarios suggest that barley cultivation is feasible, provided that the minimum temperature in January is no lower than -10℃, -8℃, and -4℃ for hulled barley, dehulled barley, and for malting barley and naked oats, respectively. Additionally, cultivation of barley across South Korea seems feasible based on data on certified barley seeds by area. Although both JMAT and certified seed data suggest that barley cultivation across Korea is feasible, our survey results of barley growth and yield showed that harvest was impossible in certain cultivation areas, such as Gangwon-do. Therefore, climate change scenarios related to the cultivation limits of different barley types need to be re-estimated by factoring in survey data on the growth and yield of crops within those cultivation areas.

• Journal of Ginseng Culture
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• v.5
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• pp.52-76
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• 2023

This article focuses on changes in the ginseng industry in the 1930s in areas other than the Government Contract Cultivation (GCC) zones. A major characteristic of the ginseng industry in the 1930s was the rapid increase in the area covered by ginseng gardens: the area was about 212 ha in 1929 and 252 ha in 1930 and 1931 but soared to around 441 ha in 1938. This occurred because the non-GCC areas increased significantly during this period. Until the early 1930s, the ratio of GCC to non-GCC areas was 70:30. By the late 1930s, however, the ratio had changed to 53:47. The reason for this change was that the area of the newly established ginseng gardens in the GCC zones had decreased, while that of the non-GCC ginseng gardens had steadily increased. Due to the Japanese invasion of China, China boycotted red ginseng, and exports were sluggish, so the GCC areas were reduced. On the other hand, the non-GCC ginseng gardens were not affected, and the area they covered steadily increased. As a result, in the 1930s, the ginseng industry outside of the GCC areas grew rapidly. The region that led the growth of the ginseng industry outside of the GCC zone was Jeonbuk. By the late 1930s, Jeonbuk dominated the other provinces and accounted for more than 50% of the non-GCC farming zone. Gyeongbuk and Gangwon-do followed Jeonbuk in terms of ginseng cultivation areas. While Gyeonggi-do, Gyeongnam, and Chungbuk were also active in ginseng cultivation, Jeonnam and Chungnam were not active. In the 1930s, the growth of the ginseng industry outside of the GCC zones was driven by the efforts of ginseng farmers and the support of local governments. An examination of Yecheon-gun in Gyeongbuk, Ganghwa-gun in Gyeonggi, and Jecheon-gun in Chungcheongbuk-do showed that ginseng farmers organized cooperatives as the ginseng industry steadily developed in these regions, and these cooperatives worked systematically to cultivate and sell ginseng. In the case of Ganghwa-gun, activities were carried out to incorporate the GCC zone. The Deoksan Ginseng Association in Jecheon-gun determined that financing for cultivation was key and requested subsidies from the provincial government. Administrative authorities also supported the activities of the ginseng farmers. The activities of the farmers and the support of the administrative authorities together led to the growth of the ginseng industry during this period.

• Journal of Korean Society of Forest Science
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• v.113 no.1
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• pp.40-50
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• 2024

Pine forests are continuously declining due to competition with broadleaf trees, such as oaks, as a consequence of changes in the natural dynamics of forest ecosystem. This natural decline creates a risk of losing the various benefits pine trees have provided to people in the past. Therefore, it is necessary to prepare future forest management directions by considering the state of pine tree decline in each region. The goal of this study is to understand the characteristics of pine forest changes according to forest dynamics and to predict future regional changes. For this purpose, we evaluated the trend of change in pine forests and extracted various variables(topography, forest stand type, disturbance, and climate) that affect the change, using time-series National Forest Inventory (NFI) data. Also, using selected key variables, a model was developed to predict future changes in pine forests. As a results, it showed that the importance of pine trees in forests across the country has decreased overall over the past 10 years. Also, 75% of the sample points representing pine trees remained unchanged, while the remaining 25% had changed to mixed forests. It was found that these changes mainly occurred in areas with good moisture conditions or disturbance factors inside and outside the forest. In the next 10 years, approximately 14.2% of current pine forests was predicted to convert to mixed forests due to changes in natural forest dynamics. Regionally, the rate of pine forest change was highest in Jeju(42.8%) and Gyeonggi(26.9%) and lowest in Gyeongbuk(8.8%) and Gangwon(13.8%). It was predicted that pine forests would be at a high risk of decline in western areas of the Korean Peninsula, including Gyeonggi, Chungcheong, and Jeonnam. This results can be used to make a management plan for pine forests throughout the country.

• Korean small business review
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• v.31 no.2
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• pp.103-120
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• 2009

As business incubation centers (BICs) have been operating for more than 10 years in Korea, many early stage startups tend to use the services provided by the incubating centers. BICs in Korea have accumulated the knowledge and experience in the past ten years and their services have been considerably improved. The business incubating service has three facets : (1) business infrastructure service, (2) direct service, and (3) indirect service. The mission of BICs is to provide the early stage entrepreneurs with the incubating service in a limited period time to help them grow strong enough to survive the fierce competition after graduating from the incubation. However, the incubating services sometimes fail to foster the independence of new startup companies, and raise the dependence of many companies on BICs. Thus, the dependence on BICs is a very important factor to understand the survival of the incubated startup companies after graduation from BICs. The purpose of this study is to identify the main factors that influence the firm's dependence on BICs and to characterize the relationships among the identified factors. The business incubating service is a core construct of this study. It includes various activities and resources, such as offering the physical facilities, legal service, and connecting them with outside organizations. These services are extensive and take various forms. They are provided by BICs directly or indirectly. Past studies have identified various incubating services and classify them in different ways. Based on the past studies, we classify the business incubating service into three categories as mentioned above : (1) business infrastructure support, (2) direct support, and (3) networking support. The business infrastructure support is to provide the essential resources to start the business, such as physical facilities. The direct support is to offer the business resources available in the BICs, such as human, technical, and administrational resources. Finally, the indirect service was to support the resource in the outside of business incubation center. Dependence is generally defined as the degree to which a client firm needs the resources provided by the service provider in order to achieve its goals. Dependence is generated when a firm recognizes the benefits of interacting with its counterpart. Hence, the more positive outcomes a firm derives from its relationship with the partner, the more dependent on the partner the firm must inevitably become. In business incubating, as a resident firm is incubated in longer period, we can predict that her dependence on BICs would be stronger. In order to foster the independence of the incubated firms, BICs have to be able to manipulate the provision of their services to control the firms' dependence on BICs. Based on the above discussion, the research model for relationships between dependence and its affecting factors was developed. We surveyed the companies residing in BICs to test our research model. The instrument of our study was modified, in part, on the basis of previous relevant studies. For the purposes of testing reliability and validity, preliminary testing was conducted with firms that were residing in BICs and incubated by the BICs in the region of Gwangju and Jeonnam. The questionnaire was modified in accordance with the pre-test feedback. We mailed to all of the firms that had been incubated by the BICs with the help of business incubating managers of each BIC. The survey was conducted over a three week period. Gifts (of approximately ₩10,000 value) were offered to all actively participating respondents. The incubating period was reported by the business incubating managers, and it was transformed using natural logarithms. A total of 180 firms participated in the survey. However, we excluded 4 cases due to a lack of consistency using reversed items in the answers of the companies, and 176 cases were used for the analysis. We acknowledge that 176 samples may not be sufficient to conduct regression analyses with 5 research variables in our study. Each variable was measured through multiple items. We conducted an exploratory factor analysis to assess their unidimensionality. In an effort to test the construct validity of the instruments, a principal component factor analysis was conducted with Varimax rotation. The items correspond well to each singular factor, demonstrating a high degree of convergent validity. As the factor loadings for a variable (or factor) are higher than the factor loadings for the other variables, the instrument's discriminant validity is shown to be clear. Each factor was extracted as expected, which explained 70.97, 66.321, and 52.97 percent, respectively, of the total variance each with eigen values greater than 1.000. The internal consistency reliability of the variables was evaluated by computing Cronbach's alphas. The Cronbach's alpha values of the variables, which ranged from 0.717 to 0.950, were all securely over 0.700, which is satisfactory. The reliability and validity of the research variables are all, therefore, considered acceptable. The effects of dependence were assessed using a regression analysis. The Pearson correlations were calculated for the variables, measured by interval or ratio scales. Potential multicollinearity among the antecedents was evaluated prior to the multiple regression analysis, as some of the variables were significantly correlated with others (e.g., direct service and indirect service). Although several variables show the evidence of significant correlations, their tolerance values range between 0.334 and 0.613, thereby demonstrating that multicollinearity is not a likely threat to the parameter estimates. Checking some basic assumptions for the regression analyses, we decided to conduct multiple regression analyses and moderated regression analyses to test the given hypotheses. The results of the regression analyses indicate that the regression model is significant at p < 0.001 (F = 44.260), and that the predictors of the research model explain 42.6 percent of the total variance. Hypotheses 1, 2, and 3 address the relationships between the dependence of the incubated firms and the business incubating services. Business infrastructure service, direct service, and indirect service are all significantly related with dependence (β = 0.300, p < 0.001; β = 0.230, p < 0.001; β = 0.226, p < 0.001), thus supporting Hypotheses 1, 2, and 3. When the incubating period is the moderator and dependence is the dependent variable, the addition of the interaction terms with the antecedents to the regression equation yielded a significant increase in R2 (F change = 2.789, p < 0.05). In particular, direct service and indirect service exert different effects on dependence. Hence, the results support Hypotheses 5 and 6. This study provides several strategies and specific calls to action for BICs, based on our empirical findings. Business infrastructure service has more effect on the firm's dependence than the other two services. The introduction of an additional high charge rate for a graduated but allowed to stay in the BIC is a basic and legitimate condition for the BIC to control the firm's dependence. We detected the differential effects of direct and indirect services on the firm's dependence. The firms with long incubating period are more sensitive to indirect service positively, and more sensitive to direct service negatively, when assessing their levels of dependence. This implies that BICs must develop a strategy on the basis of a firm's incubating period. Last but not least, it would be valuable to discover other important variables that influence the firm's dependence in the future studies. Moreover, future studies to explain the independence of startup companies in BICs would also be valuable.