• Journal of Mushroom
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• v.19 no.3
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• pp.166-175
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• 2021

In this study, monokaryons of "Heukari" (Pleurotus ostreatus) and "Hosan" (Pleurotus pulmonarius) were separated to remove the cell wall, and a cross-species protoplast fusion was developed through chemical treatment with polyethylene glycol. The protoplast-fused PF160306 and PF160313 strains have a culture period of 10 and 2 days shorter than that of the "Heuktari" and "Hosan" cultivars, respectively. Furthermore, the growth of the strains was faster than that of the existing cultivars. The yield was 135.9 g per bottle, which was approximately 8% higher than that of the commercially available "Hosan" cultivar; however, it was not statistically significant. A growth survey was conducted after treatment at five temperatures (15, 18, 21, 23, and 25℃). The growth of the strains accelerated with the increase in temperature. However, at 21℃, the yellow color of pileus was the brightest. Band pattern, assessed using URP Primer 7, was similar to that of the "Hosan" cultivar. The DPPH radical scavenging capacity and polyphenol content were 62.5% and 43.5 mg/mL, respectively, for "Sunjung" and 65.7% and 49.9 mg/mL, respectively, for PF160313. Furthermore, the antihypertensive activities of the "Sunjung" cultivar and PF160313 were similarly high at 74% and 75%, respectively. In conclusion, cross-species hybridization via the protoplast fusion technique can be used for obtaining primary data for mushroom breeding to develop new varieties. In addition, the protoplast fusion technique might aid in expanding the market for yellow mushrooms.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.151-176
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• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• Journal of the Korean Society of Food Culture
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• v.32 no.5
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• pp.383-393
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• 2017

This study was conducted to analyze the dietary lifestyle of local Chinese consumers and to classify dietary characteristics according to their dietary lifestyle factors and dietary behaviors. This investigation was conducted for 1 month from 1 January 2017 targeting 300 adult males and females living in China using the online survey company surveymonkey. Four factors relating to dietary lifestyle were identified, gourmet factor, healthy factor, convenience factor and economic factor, and these were grouped into 4 clusters according to their dietary lifestyle factor scores. Group 1, the gourmet economy group, showed a high percentage of living alone and a high frequency of eating out, but a relatively low percentage of three regular meals per day. Their dietary lifestyle was sensitive to gourmet factors and economic factors, but less sensitive to health and convenience factors. Group 2, the wide interest group, contained a high percentage of individuals in their 30s, as well as more highly educated individuals and a higher income than other groups. Because their dietary lifestyle scores tended to be higher than those of other groups, they sought a variety of new foods and gourmet meals for enjoyment of dining and life, as well as well-being food materials and foods related to health. Group 3, the health economic group, constituted a family-type consumer group with lower income level than the other groups. Members of this group were seeking health food and natural food in their dietary lifestyle and tended to pursue a high economic profit ratio when purchasing food. Finally, group 4 showed a relatively higher percentage of women over 30 and individuals with a college level or higher education than the other groups. This group was more interested in health and taste than price and convenience, and showed the highest LOHAS orientation among middle aged Chinese women. Moreover, members of this group directly utilized their knowledge regarding nutrition in real life.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.11
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• pp.1649-1657
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• 2016

The purpose of this study was to investigate the body mass index (BMI), dietary intake attitudes, and nutrient intake status according to sugar-containing food intake frequency of 409 college students in Gyeonggi-do. Subjects were categorized into three groups according to sugar-containing food intake frequency: rare intake group (n=113), average intake group (n=195), and frequent intake group (n=101). The average height and weight (P<0.001) of each group were $163.8{\pm}0.11cm$ and $52.9{\pm}8.6kg$, $164.4{\pm}0.1cm$ and $56.2{\pm}6.4kg$, and $167.9{\pm}0.1cm$ and $68.0{\pm}15.7kg$, respectively. The average BMIs of the groups were $19.6{\pm}2.3$, $20.7{\pm}0.8$, and $24.0{\pm}2.7$, respectively (P<0.001). Dietary intake attitude scores of the groups were $30.73{\pm}5.68$, $30.11{\pm}5.51$, and $28.00{\pm}5.31$, respectively (P<0.001). As a result of nutrient intake status, daily averages of energy and carbohydrate intake of the frequent intake group were significantly higher than those of the rare intake group (P<0.05). On the other hand, vitamin A, vitamin $B_1$, and vitamin C intakes of the rare intake group were significantly higher than those of the frequent intake group (P<0.05). Using multiple regression analysis, we found that BMI was the most significant variable affecting sugar-containing food intake. Therefore, nutrition education is necessary to improve nutrient intake while considering sugar intake for maintenance of healthy weight.