• Journal of Ginseng Research
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• v.48 no.5
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• pp.474-480
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• 2024

Background: Recent years have witnessed increasing interest in the high amount of ocotillol-type saponin in Panax vietnamensis, particularly in relation to majonoside R2 (MR2). This unique 3%-5% MR2 content impart Ngoc Linh and Lai Chau ginsengs with unique pharmacological activities. However, in the commercial domain, unauthentic species have infiltrated and significantly hindered access to the authentic, efficacious variety. Thus, suitable analytical techniques for distinguishing authentic Vietnamese ginseng species from others is becoming increasingly crucial. Therefore, MR2 is attracting considerable attention as a target requiring effective management measures. Methods: An enzyme-linked immunosorbent assay (ELISA) was developed by producing monoclonal antibodies against MR2 (mAb 16E11). The method was thoroughly validated, and the potential of the immunoassay was confirmed by high-performance liquid chromatography with ultraviolet spectroscopy. Furthermore, ELISA was applied to the assessment of the MR2 concentrations of various Panax spp., including Korean, American, and Japanese ginsengs. Results and conclusions: An icELISA using mAb 16E11 exhibited linearity between 3.91 and 250 ng/mL of MR2, with detection and quantification limits of 1.53 and 2.50 - 46.6 ng/mL, respectively. Based on this study, the developed icELISA using mAb 16E11 could be a valuable tool for analyzing MR2 level to distinguish authentic Ngoc Linh and Lai Chau ginsengs from unauthentic ones. Furthermore, the analysis of the samples demonstrated that Ngoc Linh and Lai Chau ginsengs exhibit a notably higher MR2 value than all other Panax spp. Thus, MR2 might be their ideal marker compound, and various bioactivities of this species should be explored.

• Journal of Animal Science and Technology
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• v.48 no.2
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• pp.293-306
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• 2006

We characterized physicochemical properties and examined the organoleptic and textural evaluations of Feta cheese made from goat's milk. Nutritional compositions of goat Feta cheese were fat 23.50%, protein 11.03% with moisture content of 59.54%. Cell numbers of lactic starter cultures in Feta cheese maintained from log 8.46 CFU/g and pH 5.76 during storage at 4℃ for 14 day's aging. The color of Feta cheese was whitish (L. 93.19) at after finishing brine salting, but became a little yellowish(b. 3.52) (a. -0.71). For texture profile analysis of goat Feta cheese, hardness, fracturability springness, and cohesiveness seemed to be week, but adhesiveness gumminess, chewiness, and resilience were enhanced as aging times extended to 14days, resulted in the overall textural properties was to be superior to control cheese(commercial Mozzarella cheese). Organoleptic evaluations were examined based on the intensities and the preferences for flavour, tastes, texture and mouth feeling. saltiness, bitterness and acidity were stronger in the intensities than control cheese, but the preferences were enhanced by aging to be better than control cheese at 14 days and later on, however, the texture changed to be weaker in hardness and unpleasant in mouthfeel. The fatty acid compositions of Feta cheese analysed by Gas chromatography were saturated fatty acid 42.06%, monoenoic acids 29.67%, di-enoic acids 24.24%, tri-enoic acids 1.21%.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.97-117
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• 2012

Nowadays, Internet users tend to do a variety of actions at the same time such as web browsing, social networking and multimedia consumption. While watching a video, once a user is interested in any product, the user has to do information searches to get to know more about the product. With a conventional approach, user has to search it separately with search engines like Bing or Google, which might be inconvenient and time-consuming. For this reason, a video annotation platform has been developed in order to provide users more convenient and more interactive ways with video content. In the future of smart TV environment, users can follow annotated information, for example, a link to a vendor to buy the product of interest. It is even better to enable users to search for information by directly discussing with friends. Users can effectively get useful and relevant information about the product from friends who share common interests or might have experienced it before, which is more reliable than the results from search engines. Social networking services provide an appropriate environment for people to share products so that they can show new things to their friends and to share their personal experiences on any specific product. Meanwhile, they can also absorb the most relevant information about the product that they are interested in by either comments or discussion amongst friends. However, within a very huge graph of friends, determining the most appropriate persons to ask for information about a specific product has still a limitation within the existing conventional approach. Once users want to share or discuss a product, they simply share it to all friends as new feeds. This means a newly posted article is blindly spread to all friends without considering their background interests or knowledge. In this way, the number of responses back will be huge. Users cannot easily absorb the relevant and useful responses from friends, since they are from various fields of interest and knowledge. In order to overcome this limitation, we propose a method to filter a user's friends for information search, which leverages semantic video annotation and social networking services. Our method filters and brings out who can give user useful information about a specific product. By examining the existing Facebook information regarding users and their social graph, we construct a user profile of product interest. With user's permission and authentication, user's particular activities are enriched with the domain-specific ontology such as GoodRelations and BestBuy Data sources. Besides, we assume that the object in the video is already annotated using Linked Data. Thus, the detail information of the product that user would like to ask for more information is retrieved via product URI. Our system calculates the similarities among them in order to identify the most suitable friends for seeking information about the mentioned product. The system filters a user's friends according to their score which tells the order of whom can highly likely give the user useful information about a specific product of interest. We have conducted an experiment with a group of respondents in order to verify and evaluate our system. First, the user profile accuracy evaluation is conducted to demonstrate how much our system constructed user profile of product interest represents user's interest correctly. Then, the evaluation on filtering method is made by inspecting the ranked results with human judgment. The results show that our method works effectively and efficiently in filtering. Our system fulfills user needs by supporting user to select appropriate friends for seeking useful information about a specific product that user is curious about. As a result, it helps to influence and convince user in purchase decisions.