• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.8
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• pp.1236-1247
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• 2014

Gamma irradiated-treatment of natural medicinal plants can be used to improve extraction transference number and for qualitative improvement of color when applied to functional material exploration. This study investigated the biological activities of Aralia elata cortex extracts upon gamma irradiation. In addition, different physical techniques [photostimulated luminescence (PSL) and thermoluminescence (TL)] were used for irradiation identification of Aralia elata cortex. In PSL analysis, non-irradiated (0 kGy) sample showed a negative result of 400 photon counts (PCs), whereas irradiated (5, 10, and 30 kGy) samples showed positive results of 90,100.00, 312,614.33, and 321,661.67 PCs, respectively. In the TL method, growth curve showed very unusual behaviors around $200^{\circ}C$ upon natural-irradiation of the non-irradiated (0 kGy) sample and around $150{\sim}250^{\circ}C$ for the irradiated (5, 10, and 30 kGy) samples. The TL ratio was 0.1 in non-irradiated samples at 0.011, whereas the values of irradiated samples (5, 10, and 30 kGy) were 0.1 at 1.105, 1.009, and 2.206, respectively. For phenolics of gamma-irradiated Aralia elata cortex, water and 50% ethanol extracts had the highest amounts, $17.30{\pm}0.40mg/g$ and $18.87{\pm}0.46mg/g$ at 10 kGy irradiation, respectively. The inhibitory activities of angiotensin-converting enzyme and xanthin oxidase were higher in both irradiated water and 50% ethanol extracts than in non-irradiated ones. For pancreatin ${\alpha}$-amylase and ${\alpha}$-glucosidase inhibitory activities, water and 50% ethanol extracts containing $200{\mu}g/mL$ of phenolics showed high inhibitory activities of 60~100% at all irradiation doses (0~30 kGy). This result confirmed that Aralia elata cortex extracts have greater anti-diabetic effects than acabose as a diabetic remedy. Gamma-irradiated Aralia elata cortex extracts are useful as a functional material with anti-diabetic effects. Thus, Aralia elata cortex extracts can be used as a functional material with various biological activities, and gamma-irradiation can be used to amplify biological activities in plants.

• Development and Reproduction
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• v.10 no.4
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• pp.227-238
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• 2006

Genomic DNAs(gDNAs) were isolated from the venus clam(Gomphina aequilatera) from Samcheok(venus clam from Samcheok; VCS) and Wonsan(venus clam from Wonsan; VCW) located in the East Sea of the Korean Peninsula. The amplified products were generated by agarose gel electrophoresis(AGE) with oligonucleotides primer, detected by staining with ethidium bromide and viewed by ultraviolet ray. The seven arbitrarily selected primers BION-21, BION-23, BION-25, BION-27, BION-29, BION-31 and BION-33 generated the shared loci, polymorphic, and specific loci, with the molecular sizes ranging from 150 bp to 2,400 bp. In this study, 147 polymorphic loci(147/954 loci, 15.41%) in VCS population and 274(274/996 loci, 27.51%) in VCW population were generated with seven primers. These results suggest the genetic variation in VCW population is higher than in VCS population. Especially, the 700 bp bands generated by the primer BION-21 were identified commonly in two Gomphina populations, which identified populations and/or species. This specific primer was found to be useful in the identification of individuals and/or population, resulting from the different DNA polymorphism among individuals/species/population. Two Gomphina populations between the individual SAMCHEOK no. 03 and WONSAN no. 22 showed the longest genetic distance(0.696) in comparison with other individuals used. The complete linkage cluster analysis indicating three genetic groupings and dendrogram revealed close relationships among individual identities within two geographical populations of venus clam(G. aequilatera) from the Samcheok and Wonsan. The intra-species classification and clustering analyses inferred from molecular markers supported the traditional taxonomy of the species based on morphological characters such as shell size, shape and color. Accordingly, as mentioned above, RAPD analysis showed that VCS population was more or less separated from VCW population.

• Korean Journal of Organic Agriculture
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• v.22 no.4
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• pp.743-760
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• 2014

This study aimed to isolate and identify freshwater algae from the organic agricultural ecosystems and investigate its biological characteristics to study the possibility of utilizing a biomass freshwater algae in organic farming. In the survey area, average water temperature was $12.4{\sim}28.2^{\circ}C$ and the pH ranges were from 6.1 to 8.5. The solid culture method is more suitable than liquid culture method for isolation of freshwater algae with lower contamination level and higher isolation frequency. A total of 115 strains were isolated from six freshwater algae habitats in nine regions in Korea. BGMM (BG11 Modified Medium) amended with NaNO3 and $KNO_3$ as a nitrogen, and $Na_2CO_3$ as carbon source was designed to isolate and culture freshwater algae. Absorbance of freshwater algae culture has increased dramatically to four days and decreased after eight days after inoculation. CHK008 of the seven isolates showed the highest absorbance in seven days after culturing in BGMM. The optimal pH of BGMM for culturing freshwater algae was pH 6-7. As light intensity increased, growth of freshwater algae increased. Among the five kinds of carbon sources, glucose and galactose promoted good growth of freshwater algae in BGMM. The colony color of purified 16 green algae isolates showed a separation of green, dark and light green, and of them, eleven algae strains showed a strong fluorescent light under fluorescence microscopy. Cell size of the green algae showed a wide range of variation depending on the species. General morphology of the green algae strains was spherical. Chlamydomonas sp. was elliptical, and Chlorella sorokiniana was ellipsoidal and cylindrical. All strains of the green algae except for Chlamydomonas sp. did not have flagella. One isolate of Chlamydomonas sp. and five isolates of C. sorokiniana secreted mucus. Sixteen isolates of 16 green algae were identified as two family and six species, Chlorella vulgalis, C. sorokiniana, C. pyrenoidosa, C. kessleri, C. emersonii, and Chlamydomonas sp. based on their morphological characteristics.

• Journal of Plant Biotechnology
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• v.46 no.3
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• pp.165-171
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• 2019

Marker-assisted backcrossing (MABC) is useful for selecting an offspring with a highly recovered genetic background for a recurrent parent at early generation to various crops. Moreover, marker-assisted backcrossing (MABC) along with marker-assisted selection (MAS) contributes immensely to overcome the main limitation of the conventional breeding and it accelerates recurrent parent genome (RPG) recovery. In this study, we were employed to incorporate rin gene(s) from the donor parent T13-1084, into the genetic background of HK13-1151, a popular high-yielding tomato elite inbred line that is a pink color fruit, in order to develop a rin HK13-1084 improved line. The recurrent parent genome recovery was analyzed in early generations of backcrossing using SNP markers obtained from genotyping-by-sequencing analysis. From the $BC_1F_1$ and $BC_2F_1$ plants, 3,086 and 4868 polymorphic SNP markers were obtained via GBS analysis, respectively. These markers were present in all twelve chromosomes. The background analysis revealed that the extent of RPG recovery ranged from 56.7% to 84.5% and from 87.8% to 97.8% in $BC_1F_1$ and $BC_2F_1$ generations, respectively. In this study, No 5-1 with 97.8% RPG recovery rate among $BC_2F_1$ plants was similar to HK13-1151 strain in the fruit shape. Therefore, the selected plants were fixed in $BC_2F_2$ generation through selfing. MAS allowed identification of the plants that are more similar to the recurrent parent for the loci evaluated in the backcross generations. MABC can greatly reduce breeding time as compared to the conventional backcross breeding. For instance, MABC approach greatly shortened breeding time in tomato.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.52 no.3
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• pp.239-248
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• 2007

Although high nutritional values and continuous identification of important functional substances of soybean [Glycine max (L.) Merrill.] promote consumption of soybean products worldwide, informations on quality of brand soybean is not enough for consumers. Total of 100 brand soybeans [32 for soypaste and source, 45 black testa (lage), and 17 black testa (small) or medicinal soybean and beansprout soybean] were collected at supermarkets and several external quality factors were analyzed. Brand soybeans were marked with the environmental friendly and intimating words along with soybean (white or yellow), black soybean (black-, frost-, late frost-, green or inner-green-), medicinal soybean and beansprout soybean. Among 100 brand soybeans 30% was 1 kg package and 59% was 500 g package, difference between printed and actual weights of 70% brand soybeans was ${\pm}1%$ and weights of 2/3 of brand soybeans were higher than printed weight. Range of 100 seed weights of soypaste and source, black testa (large) and black testa (small) and beansprout soybeans were $23.7{\sim}47.8g$, $21.9{\sim}44.5g$ and $9.5{\sim}15.0g$, respectively. Although ranges of 100 seed weights of soypaste and source and black testa (large) soybeans were similar, 63% of soypaste and source were less than 29 g, while 78% of black testa (large) soybeans were higher than 30 g. Although average and highest percentages of seeds separated with 6.7 mm sieve were similar with 87.4% and 99.9% for soypaste and source soybean and 86.5% and 99.5% for black testa (large) soybean, respectively, the lowest percentages were 70.7% for soypaste and source soybean and 14.4% for black testa (large) soybean. When 100 seed weight was greater than 35 g, 90% of seeds were remained on 6.7 mm sieve. On the other hand 100 g weight and percentage of seeds remained on 6.7 mm sieve showed significantly positive correlations [r=0.7488** for soypaste and source soybean and r=0.7874** for black testa (large) soybean when 100 seed weight was $20{\sim}30g$. Based on hilum color and/or appearance, 76% of brand soybeans collected (more than 90% in yellow testa soybeans) were found to be mixed more than 10% with other cultivars or landraces. Foreign materials such as sand, piece of clothe, wood piece, dead insects, other soybeans were found in 20% of brand soybeans. Average test weight of brand soybeans was 762g $L^{-1}$ with a range of $645{\sim}820g\;L^{-1}$. Soybeans from local markets were as good as brand soybeans in 100 seed weight, uniformity of seeds, weight of foreign materials and test weight.

• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.59-69
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• 2010

Green or an environmental consciousness has been a major issue for businesses and government offices, as well as consumers, worldwide. In response to this movement, the Korean government announced, in the early 2000s, the era of "Green Growth" as a way to encourage green-related business activities. The Korean fashion industry, in various levels of involvement, presents diverse eco-friendly products as a part of the green movement. These apparel products include organic products and recycled clothing. For these companies to be successful, they need information about who are the consumers who consider green issues (e.g., environmental sustainability) as part of their personal values when making a decision for product purchase, use, and disposal. These consumers can be considered as eco-sumers. Previous studies have examined consumers' purchase intention for or with eco-friendly products. In addition, studies have examined influential factors used to identify the eco-sumers or green consumers. However, limited attention was paid to eco-sumers' disposal or recycling behavior of clothes in comparison with their green product purchases. Clothing disposal behaviors are ways that consumer can get rid of unused clothing and in clue temporarily lending the item or permanently eliminating the item by "handing down" (e.g., giving it to a younger sibling), donating, exchanging, selling, or simply throwing it away. Accordingly, examining purchasing behaviors of eco-friendly fashion items in conjunction with clothing disposal behaviors should improve understanding of a consumer's clothing consumption behavior from the environmental perspective. The purpose of this exploratory study is to provide descriptive information about Korean eco-sumers who have ecologically-favorable lifestyles and behaviors when buying and disposing of clothes. The objectives of this study are to (a) categorize Koreans on the basis of clothing disposal behaviors; (b) investigate the differences in demographics, lifestyles, and clothing consumption values among segments; and (c) compare the purchase intention of eco-friendly fashion items and influential factors among segments. A self-administered questionnaire was developed based on previous studies. The questionnaire included 10 items of clothing disposal behavior, 22 items of LOHAS (Lifestyles of Health and Sustainability) characteristics, and 19 items of consumption values, measured by five-point Likert-type scales. In addition, the purchase intention of two eco-friendly fashion items and 11 attributes of each item were measured by seven-point Likert type scales. Two polyester fleece pullovers, made from fabric created from recycled bottles with the PET identification code, were selected from one Korean brand and one US imported brand among outdoor sportswear brands. A brief description of each product with a color picture was provided in the survey. Demographic variables (i.e., gender, age, marital status, education level, income, occupation) were also included. The data were collected through a professional web survey agency during May 2009. A total of 600 final usable questionnaires were analyzed. The age of respondents ranged from 20 to 49 years old with a mean age of 34 years. Fifty percent of the respondents were males and about 58% were married, and 62% reported having earned university degrees. Principal components factor analysis with varimax rotation was used to identify the underlying dimensions of the clothing disposal behavior scale, and three factors were generated (i.e., reselling behavior, donating behavior, non-recycling behavior). To categorize the respondents on the basis of clothing disposal behaviors, k-mean cluster analysis was used, and three segments were obtained. These consumer segments were labeled as 'Resale Group', 'Donation Group', and 'Non-Recycling Group.' The classification results indicated approximately 98 percent of the original cases were correctly classified. With respect to demographic characteristics among the three segments, significant differences were found in gender, marital status, occupation, and age. LOHAS characteristics were reduced into the following five factors: self-satisfaction, family orientation, health concern, environmental concern, and voluntary service. Significant differences were found in the LOHAS factors among the three clusters. Resale Group and Donation Group showed a similar predisposition to LOHAS issues while the Non-Recycling Group presented the lowest mean scores on the LOHAS factors compared to the other segments. The Resale and Donation Groups described themselves as enjoying or being satisfied with their lives and spending spare-time with family. In addition, these two groups cared about health and organic foods, and tried to conserve energy and resources. Principal components factor analysis generated clothing consumption values into the following three factors: personal values, social value, and practical value. The ANOVA test with the factors showed differences primarily between the Resale Group and the other two groups. The Resale Group was more concerned about personal value and social value than the other segments. In contrast, the Non-Recycling Group presented the higher level of social value than did Donation Group. In a comparison of the intention to purchase eco-friendly products, the Resale Group showed the highest mean score on intent to purchase Product A. On the other hand, the Donation Group presented the highest intention to purchase for Product B among segments. In addition, the mean scores indicated that the Korean product (Product B) was more preferable for purchase than the U.S. product (Product A). Stepwise regression analysis was used to identify the influence of product attributes on the purchase intention of eco product. With respect to Product A, design, price and contribution to environmental preservation were significant to predict purchase intention for the Resale Group, while price and compatibility with my image factors were significant for the Donation Group. For the Non-Recycling Group, design, price compatibility with the factors of my image, participation to eco campaign, and contribution to environmental preservation were significant. Price appropriateness was significant for each of the three clusters. With respect to Product B, design, price and compatibility with my image factors were important, but different attributes were associated significantly with purchase intention for each of the three groups. The influence of LOHAS characteristics and clothing consumption values on intention to purchase Products A and B were also examined. The LOHAS factor of health concern and the personal value factor were significant in the relationships with the purchase intention; however, the explanatory powers were low in the three segments. Findings showed that each group as classified by clothing disposal behaviors showed differences in the attributes of a product, personal values, and the LOHAS characteristics that influenced their purchase intention of eco-friendly products. Findings would enable organizations to understand eco-friendly behavior and to design appropriate strategic decisions to appeal eco-sumers.