• Biomolecules & Therapeutics
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• v.25 no.6
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• pp.559-568
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• 2017

Metabolomics has been used as a powerful tool for the analysis and quality assessment of the natural product (NP)-derived medicines. It is increasingly being used in the quality control and standardization of NP-derived medicines because they are composed of hundreds of natural compounds. The most common techniques that are used in metabolomics consist of NMR, GC-MS, and LC-MS in combination with multivariate statistical analyses including principal components analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). Currently, the quality control of the NP-derived medicines is usually conducted using HPLC and is specified by one or two indicators. To create a superior quality control framework and avoid adulterated drugs, it is necessary to be able to determine and establish standards based on multiple ingredients using metabolic profiling and fingerprinting. Therefore, the application of various analytical tools in the quality control of NP-derived medicines forms the major part of this review. $Veregen^{(R)}$ (Medigene AG, Planegg/Martinsried, Germany), which is the first botanical prescription drug approved by US Food and Drug Administration, is reviewed as an example that will hopefully provide future directions and perspectives on metabolomics technologies available for the quality control of NP-derived medicines.

• Journal of Microbiology and Biotechnology
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• v.23 no.7
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• pp.932-941
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• 2013

This work aimed to classify Aspergillus (8 species, 28 strains) by using a secondary metabolite profile-based chemotaxonomic classification technique. Secondary metabolites were analyzed by liquid chromatography ion-trap mass spectrometry (LC-IT-MS) and multivariate statistical analysis. Most strains were generally well separated from each section. A. lentulus was discriminated from the other seven species (A. fumigatus, A. fennelliae, A. niger, A. kawachii, A. flavus, A. oryzae, and A. sojae) with partial least-squares discriminate analysis (PLS-DA) with five discriminate metabolites, including 4,6-dihydroxymellein, fumigatin, 5,8-dihydroxy-9-octadecenoic acid, cyclopiazonic acid, and neosartorin. Among them, neosartorin was identified as an A. lentulus-specific compound that showed anticancer activity, as well as antibacterial effects on Staphylococcus epidermidis. This study showed that metabolite-based chemotaxonomic classification is an effective tool for the classification of Aspergillus spp. with species-specific activity.

• Journal of the Korean Magnetic Resonance Society
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• v.26 no.3
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• pp.24-33
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• 2022

The browning phenomenon of fruits can be easily observed when fruits or vegetables (apples, pears, bananas, potatoes, etc.) are cut with a knife and the part turns brown. When this browning occurs, changes in taste, color, and nutrients usually are introduced. The cause of this browning phenomenon has been well studied for a long time, but these studies have mainly focused on preventing deterioration of processed foods during food processing or storage. Resultantly, there are few studies on how much changes in nutrients (saccharides, amino acids, fats, water-soluble low molecular weight ammonium ions, etc.) are caused by browning. The purpose of this study is to determine the change in nutrients during browning using apple as a model fruit. We conducted a comparative study on how much the nutrient fluctuations differ depending on the presence or absence of pretreatment such as the application of heat. All analysis was conducted using ¹H NMR. The ANOVA analysis showed that the concentrations of 4 amino acids (alanine, asparagine, isoleucine, and valine), 3 types of sugars (fructose, glucose, and xylose), 1 type of organic acid (lactate) and choline were significantly increased in samples showing browning. In addition, the groups before and after browning were clearly separated using multivariate statistical analysis methods (PCA, PLS-DA), which was greatly contributed by two sugar components (fructose and glucose) present in high concentrations in apples.

• Journal of Plant Biotechnology
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• v.42 no.1
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• pp.60-70
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• 2015

The aim of this study was to investigate whether fourier transform infrared (FT-IR) spectroscopy can be applied to simultaneous determination of fatty acids contents in different soybean cultivars. Total 153 lines of soybean (Glycine max Merrill) were examined by FT-IR spectroscopy. Quantification of fatty acids from the soybean lines was confirmed by quantitative gas chromatography (GC) analysis. The quantitative spectral variation among different soybean lines was observed in the amide bond region ($1,700{\sim}1,500cm^{-1}$), phosphodiester groups ($1,500{\sim}1,300cm^{-1}$) and sugar region ($1,200{\sim}1,000cm^{-1}$) of FT-IR spectra. The quantitative prediction modeling of 5 individual fatty acids contents (palmitic acid, stearic acid, oleic acid, linoleic acid, linolenic acid) from soybean lines were established using partial least square regression algorithm from FT-IR spectra. In cross validation, there were high correlations ($R^2{\geq}0.97$) between predicted content of 5 individual fatty acids by PLS regression modeling from FT-IR spectra and measured content by GC. In external validation, palmitic acid ($R^2=0.8002$), oleic acid ($R^2=0.8909$) and linoleic acid ($R^2=0.815$) were predicted with good accuracy, while prediction for stearic acid ($R^2=0.4598$), linolenic acid ($R^2=0.6868$) had relatively lower accuracy. These results clearly show that FT-IR spectra combined with multivariate analysis can be used to accurately predict fatty acids contents in soybean lines. Therefore, we suggest that the PLS prediction system for fatty acid contents using FT-IR analysis could be applied as a rapid and high throughput screening tool for the breeding for modified Fatty acid composition in soybean and contribute to accelerating the conventional breeding.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.3
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• pp.107-117
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• 2017

Entrepreneurship is a means of improving national competitiveness that can expand the industry quantitatively and qualitatively based on new technologies and ideas. As a result, we are implementing a nationwide initiative support policy around the world. It leads to actual results and grows into a global company. It also has the advantage of being able to produce potential creative people through support for startups. In order to cultivate talented people suitable for startup in Korea, Venture For Korea, the internship program is being carried out with the aim of strengthening basic capabilities and establishing an exchange with existing companies. The purpose of this study is to verify the effectiveness of the system by using justice theory among the interns of the startup internship. In order to improve the accuracy of the study, the survey was done by a complete enumeration and the results were analyzed through Smart PLS 2.0. As a result of the analysis, the distributive justice and interactional justice among the fairness variables have a positive effect on the expectancy effect, and the expectancy effect has a positive effect on the satisfaction. However, procedural justice did not appear to have an effect on expectancy effects. This is because it's been only two years after the start of the internship program, and it seems to reflect the lack of consensus about the process among the stakeholders (enterprise, pre-entrepreneur, the government) related to the system. The results of this study are meaningful in that it deduces the insufficient part of the startup internship based on the justice theory. In other words, in order to increase the policy effect of the startup internship, it is necessary not only to emphasize only the purpose, but also to establish a policy direction complementing the procedural aspect.

• Journal of Microbiology and Biotechnology
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• v.21 no.1
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• pp.5-13
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• 2011

In this study, seven Trichoderma species (33 strains) were classified using secondary metabolite profile-based chemotaxonomy. Secondary metabolites were analyzed by liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS-MS) and multivariate statistical methods. T. longibrachiatum and T. virens were independently clustered based on both internal transcribed spacer (ITS) sequence and secondary metabolite analyses. T. harzianum formed three subclusters in the ITS-based phylogenetic tree and two subclusters in the metabolitebased dendrogram. In contrast, T. koningii and T. atroviride strains were mixed in one cluster in the phylogenetic tree, whereas T. koningii was grouped in a different subcluster from T. atroviride and T. hamatum in the chemotaxonomic tree. Partial least-squares discriminant analysis (PLS-DA) was applied to determine which metabolites were responsible for the clustering patterns observed for the different Trichoderma strains. The metabolites were hetelidic acid, sorbicillinol, trichodermanone C, giocladic acid, bisorbicillinol, and three unidentified compounds in the comparison of T. virens and T. longibrachiatum; harzianic acid, demethylharzianic acid, homoharzianic acid, and three unidentified compounds in T. harzianum I and II; and koninginin B, E, and D, and six unidentified compounds in T. koningii and T. atroviride. The results of this study demonstrate that secondary metabolite profiling-based chemotaxonomy has distinct advantages relative to ITS-based classification, since it identified new Trichoderma clusters that were not found using the latter approach.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.104-104
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• 2017

정상적인 부화 여부를 판별하기 위한 1차 검란은 일반적으로 5일~7일 이후에 시행된다. 미부화란을 이보다 더 빠른 시간 안에 검출할 경우 부화에 소요되는 에너지의 감소 효과 및 미부화란을 다른 용도로 활용하는 것을 기대할 수 있다. 시중에서 쉽게 구입할 수 있는 산란계인 하이라인 브라운 품종의 유정란 29개와 인위적인 미부화란을 만들기 위한 동일 품종의 무정란 11개를 사용하였으며 $38^{\circ}C$, 70% 조건의 항온항습기에서 96시간 동안 부화하였다. 스펙트럼 획득 장치의 광원은 녹색영역을 발광하는 LED램프와 일반 할로겐 광원을 별도로 사용하였으며 스펙트로미터는 VIS/NIR 영역인 520~1,180nm영역과 NIR영역인 900~1,700nm영역의 것을 사용하였다. 부화 시작 전과 부화 시작 후 1일 간격으로 각각 1개의 샘플에 대한 1개의 스펙트럼을 측정하였다. 측정 영역은 LED광원을 이용한 경우는 520~1,1800nm, 할로겐광원을 이용한 경우에는 520~1,180nm와 900~1,700nm이었다. 정상 부화여부는 4일차에서 할란하여 확인하였고, 측정 일자별로 PLS-DA분석법을 이용한 판별 모델을 개발하였다. 4일차에서 유정란 29개 중 11개가 정상 부화하였고, 18개는 미부화하였다. 3일차에서 판별 모델의 정확도는 LED광원의 VIS/NIR 영역 스펙트럼을 이용한 경우는 100%, 할로겐 광원의 VIS/NIR 영역 스펙트럼을 이용한 경우는 70%, 할로겐 광원의 NIR영역 스펙트럼을 이용한 경우는 70%였다. 4일차에서 판별 모델의 정확도는 LED광원의 VIS/NIR 영역 스펙트럼을 이용한 경우는 100%, 할로겐 광원의 VIS/NIR 영역 스펙트럼을 이용한 경우는 90%, 할로겐 광원의 NIR영역 스펙트럼을 이용한 경우는 100%였다. 부화 3일차는 정상 부화할 경우 피가 생성되는 시기이다. 피가 형성된 이후의 부화 여부를 판단하는 광원으로는 할로겐램프보다 LED램프를 사용하는 것이 더 적합한 것으로 나타났다.

• Journal of Microbiology and Biotechnology
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• v.22 no.11
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• pp.1523-1531
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• 2012

The metabolite profile of meju during fermentation was analyzed using mass spectrometry techniques, including GC-MS and LC-MS, and the bacterial diversity was characterized. The relative proportions of bacterial strains indicated that lactic acid bacteria, such as Enterococcus faecium and Leuconostoc lactis, were the dominant species. In partial least-squares discriminate analysis (PLS-DA), the componential changes, which depended on fermentation, proceeded gradually in both the GC-MS and LC-MS data sets. During fermentation, lactic acid, amino acids, monosaccharides, sugar alcohols, and isoflavonoid aglycones (daidzein and genistein) increased, whereas citric acid, glucosides, and disaccharides decreased. MS-based metabolite profiling and bacterial diversity characterization of meju demonstrated the changes in metabolites according to the fermentation period and provided a better understanding of the correlation between metabolites and bacterial diversity.

• Preventive Nutrition and Food Science
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• v.19 no.3
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• pp.220-226
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• 2014

In the present report, the effects of blanching, steaming, and high temperature/high pressure processing (HTHP) on the amino acid contents of commonly consumed Korean root vegetables, leaf vegetables, and pulses were evaluated using an Automatic Amino Acid Analyzer. The total amino acid content of the samples tested was between 3.38 g/100 g dry weight (DW) and 21.32 g/100 g DW in raw vegetables and between 29.36 g/100 g DW and 30.55 g/100 g DW in raw pulses. With HTHP, we observed significant decreases in the lysine and arginine contents of vegetables and the lysine, arginine, and cysteine contents of pulses. Moreover, the amino acid contents of blanched vegetables and steamed pulses were more similar than the amino acid contents of the HTHP vegetables and HTHP pulses. Interestingly, lysine, arginine, and cysteine were more sensitive to HTHP than the other amino acids. Partial Least Squares-Discriminate Analyses were also performed to discriminate the clusters and patterns of amino acids.

• Journal of Biosystems Engineering
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• v.42 no.4
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• pp.293-300
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• 2017

Purpose: This study aims to propose a method for fast geographical origin discrimination between domestic and imported rice using a visible/near-infrared (VNIR) hyperspectral imaging technique. Methods: Hyperspectral reflectance images of South Korean and Chinese rice samples were obtained in the range of 400 nm to 1000 nm. Partial least square discriminant analysis (PLS-DA) models were developed and applied to the acquired images to determine the geographical origin of the rice samples. Results: The optimal pixel dimensions and spectral pretreatment conditions for the hyperspectral images were identified to improve the discrimination accuracy. The results revealed that the highest accuracy was achieved when the hyperspectral image's pixel dimension was $3.0mm{\times}3.0mm$. Furthermore, the geographical origin discrimination models achieved a discrimination accuracy of over 99.99% upon application of a first-order derivative, second-order derivative, maximum normalization, or baseline pretreatment. Conclusions: The results demonstrated that the VNIR hyperspectral imaging technique can be used to discriminate geographical origins of rice.