• Korean Journal of Environmental Agriculture
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• v.33 no.3
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• pp.205-212
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• 2014

BACKGROUND: This study focused on the contents of flavonoid compounds in vegetables. Generally vegetables have contributed to a healthy diet, arisen from contains a large amount of fiber and functional ingredients. And flavonoid compounds are one of major functional components in the vegetables. currently research of flavonoid contents does not enough, specially in the part of homegrown vegetable. METHODS AND RESULTS: Vegetable samples were purchased in domestic market. Sample extraction by methanol, distilled water, and formic acid based solvent. Also same solvent used for mobile phase in UPLC. Eleven types of flavonoid compounds were analyzed with same kind of external standard and one kind of internal standard (galangin) for quantification. Standard calibration curve presented linearity with the correlation coefficient $R^2$ > 0.98, analysed from 1 to 50 ppm concentration. The quantitative value and multivariate analysis results were derived from the Excel and SIMCA-P11. Overall, onion has largest amount(916.5 mg/100 g) of flavonoid and also other vegetables have has significant amount[Mugwort: 138.8, Galic stem:123.6 mg/100 g etc.] of flavonoid compounds. Edible portion of vegetables per share for simulating by SIMCA-P11, root vegetables has had difference with other vegetables according to distributions and amounts of flavonoid compounds. CONCLUSION: Optionally, the results from this experiment can use to select the material for flavonoid researches. And based on these results, if this experiment will be continuously complemented, and performed, could used in various fields.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1246-1246
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• 2001

The quality of meat is highly variable in many properties. This variability originates from both animal production and meat processing. At the pre-slaughter stage, animal factors such as breed, sex, age contribute to this variability. Environmental factors include feeding, rearing, transport and conditions just before slaughter (Hildrum et al., 1995). Meat can be presented in a variety of forms, each offering different opportunities for adulteration and contamination. This has imposed great pressure on the food manufacturing industry to guarantee the safety of meat. Tissue and muscle speciation of flesh foods, as well as speciation of animal derived by-products fed to all classes of domestic animals, are now perhaps the most important uncertainty which the food industry must resolve to allay consumer concern. Recently, there is a demand for rapid and low cost methods of direct quality measurements in both food and food ingredients (including high performance liquid chromatography (HPLC), thin layer chromatography (TLC), enzymatic and inmunological tests (e.g. ELISA test) and physical tests) to establish their authenticity and hence guarantee the quality of products manufactured for consumers (Holland et al., 1998). The use of Near Infrared Reflectance Spectroscopy (NIRS) for the rapid, precise and non-destructive analysis of a wide range of organic materials has been comprehensively documented (Osborne et at., 1993). Most of the established methods have involved the development of NIRS calibrations for the quantitative prediction of composition in meat (Ben-Gera and Norris, 1968; Lanza, 1983; Clark and Short, 1994). This was a rational strategy to pursue during the initial stages of its application, given the type of equipment available, the state of development of the emerging discipline of chemometrics and the overwhelming commercial interest in solving such problems (Downey, 1994). One of the advantages of NIRS technology is not only to assess chemical structures through the analysis of the molecular bonds in the near infrared spectrum, but also to build an optical model characteristic of the sample which behaves like the “finger print” of the sample. This opens the possibility of using spectra to determine complex attributes of organic structures, which are related to molecular chromophores, organoleptic scores and sensory characteristics (Hildrum et al., 1994, 1995; Park et al., 1998). In addition, the application of statistical packages like principal component or discriminant analysis provides the possibility to understand the optical properties of the sample and make a classification without the chemical information. The objectives of this present work were: (1) to examine two methods of sample presentation to the instrument (intact and minced) and (2) to explore the use of principal component analysis (PCA) and Soft Independent Modelling of class Analogy (SIMCA) to classify muscles by quality attributes. Seventy-eight (n: 78) beef muscles (m. longissimus dorsi) from Hereford breed of cattle were used. The samples were scanned in a NIRS monochromator instrument (NIR Systems 6500, Silver Spring, MD, USA) in reflectance mode (log 1/R). Both intact and minced presentation to the instrument were explored. Qualitative analysis of optical information through PCA and SIMCA analysis showed differences in muscles resulting from two different feeding systems.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1122-1122
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• 2001

A compact and handhold near infrared (NIR) system using microspectrometer was developed. This system was suitable not only in the laboratory, but also in the field or in the process. This system was first applied for classification of geographical origin of herbal medicine such as ginseng and sesame. To identify the origin of ginseng on site, the portable NIR system is more suitable for real field application. For this study, using the compact NIR system, soft independent modeling of class analogies (SIMCA) with 1100-1750 nm NIR spectra was utilized for classification of geographical origin (Korea and China) of both ginseng and sesame. The accuracy of results is more than 90%. Quantitative analysis for petroleum such as toluene, benzene, tri-methyl benzene, and ethyl benzene was performed with partial least squares (PLS) regression with NIR 1100-1750 nm spectra. This study showed that the NIR method and gas chromatography (GC), which is a standard method, have good correlations. Furthermore, the ash content of Cornu Cervi Parvum was analyzed and the accuracy was confirmed by the developed compact NIR system.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.1
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• pp.51-63
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• 1997

Total suspended particulate matters in the ambient air were analyzed for eight chemical elements (Ca, Co, Cu, Fe, Mn, Pb, Si, and Zn) using an x-ray fluorescence spectrometry (XRF) at the Kyung Hee University - Suwon Campus during 1989 to 1994. To use these data as basis for source identification study, membership of each sample was selected to represent one of the well defined sample groups. The data sets consisting of 83 objects and 8 variables were initially separated into two groups, fine (d$_{p}$<3.3 ${\mu}{\textrm}{m}$) and coarse particle groups (d$_{p}$>3.3 ${\mu}{\textrm}{m}$). A hierarchical clustering method was examined to obtain possible member of homogeneous sample classes for each of the two groups by transforming raw data and by applying various distances. A disjoint principal component analysis was then used to define homogeneous sample classes after deleting outliers. Each of five homogeneous sample classes was determined for the fine and the coarse particle group, respectively. The data were properly classified via an application of logarithmic transformation and Euclidean distance concept. After determining homogeneous classes, correlation coefficients among eight chemical variables within all the homogeneous classes for calculated and meteorological variables (temperature. relative humidity, wind speed, wind direction, and precipitation) were examined as well to intensively interpret environmental factors influencing the characteristics of each class for each group. According to our analysis, we found that each class had its own distinct seasonal pattern that was affected most sensitively by wind direction.ion.

• Toxicological Research
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• v.34 no.3
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• pp.199-210
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• 2018

Skeletal muscle can be ultrastructurally damaged by eccentric exercise, and the damage causes metabolic disruption in muscle. This study aimed to determine changes in the metabolomic patterns in urine and metabolomic markers in muscle damage after eccentric exercise. Five men and 6 women aged 19~23 years performed 30 min of the bench step exercise at 70 steps per min at a determined step height of 110% of the lower leg length, and stepping frequency at 15 cycles per min. $^1H$ NMR spectral analysis was performed in urine collected from all participants before and after eccentric exercise-induced muscle damage conventionally determined using a visual analogue scale (VAS) and maximal voluntary contraction (MVC). Urinary metabolic profiles were built by multivariate analysis of principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA) using SIMCA-P. From the OPLS-DA, men and women were separated 2 hr after the eccentric exercise and the separated patterns were maintained or clarified until 96 hr after the eccentric exercise. Subsequently, urinary metabolic profiles showed distinct trajectory patterns between men and women. Finally, we found increased urinary metabolites (men: alanine, asparagine, citrate, creatine phosphate, ethanol, formate, glucose, glycine, histidine, and lactate; women: adenine) after the eccentric exercise. These results could contribute to understanding metabolic responses following eccentric exercise-induced muscle damage in humans.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.6
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• pp.808-820
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• 2006

In regard to indoor air quality patterns, the government introduced various polices that were about managing and monitoring quality of indoor air as a major assignment, and also executed 'Indoor Air Quality Management Act' which was presented in the May, 2004. However, among the multi-usage facilities controlled by the Act, the school was not included yet. This study goal was to investigate PM 10 pollution patterns of the high school classrooms using a pattern recognition method based on cluster analysis and disjoint principal component analysis, and further to survey levels of inorganic elements in May, June, and September, 2004. A hierarchical clustering method was examined to obtain possible objects in pseudo homogeneous sample classes by transformation raw data and by applying various distance. Following the analysis, the disjoint principal component analysis was used to define homogeneous sample class after deleting outliers. Then three homogeneous Patterns were obtained as follows: the first class had been separated and objects in the class were considered to be sampled under semi-open condition. This class had high concentration of Ca, Fe, Mg, K, Al, and Na which are related with a soil and a chalk compounds. The second class was obtained in which objects were sampled while working air-conditioners and was identified low concentration of PM 10 and elements. Objects in the last class were assigned during rainy day. A chalk, soil element and various types of anthropogenic sources including combustions and industrial influenced the third class. This methodology was thought to be helpful enough to classify indoor air quality patterns and indoor environmental categories when controlling an indoor air quality.

• Korean Journal of Medicinal Crop Science
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• v.24 no.2
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• pp.93-100
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• 2016

Background: A set of logical criteria that can accurately identify and verify the cultivation region of raw materials is a critical tool for the scientific management of traditional herbal medicine. Methods and Results: Volatile compounds were obtained from 19 and 32 samples of Angelica gigas Nakai cultivated in Korea and China, respectively, by using steam distillation extraction. The metabolites were identified using GC/MS by querying against the NIST reference library. Data binning was performed to normalize the number of variables used in statistical analysis. Multivariate statistical analyses, such as Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) were performed using the SIMCA-P software. Significant variables with a Variable Importance in the Projection (VIP) score higher than 1.0 as obtained through OPLS-DA and those that resulted in p-values less than 0.05 through one-way ANOVA were selected to verify the marker compounds. Among the 19 variables extracted, styrene, ${\alpha}$-pinene, and ${\beta}$-terpinene were selected as markers to indicate the origin of A. gigas. Conclusions: The statistical model developed was suitable for determination of the geographical origin of A. gigas. The cultivation regions of six Korean and eight Chinese A. gigas. samples were predicted using the established OPLS-DA model and it was confirmed that 13 of the 14 samples were accurately classified.

• Korean Journal of Soil Science and Fertilizer
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• v.47 no.4
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• pp.275-283
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• 2014

The ${\gamma}$-oryzanol, ferulic acid esters, which are well-known for their function on cholesterol lowering and prevention of inflammation, diabetes and cancer, are found in the seeds of cereal crops such as rice, corn, wheat and rye. Among them, rice has been reported to contain the highest ferulic acid esters. Since rice cultivation with green manure as a N source is an environmental friendly agricultural practice, it is necessary to identify and quantify as well as evaluate the variations in these compounds in rice samples as affected by different green manure conditions. A total of ten components of ${\gamma}$-oryzanol were isolated and cycloartenyl ferulate, 24-methylenecycloartanyl ferulate, campesteryl ferulate and sitosteryl ferulate were identified as the major components in Korean rice cultivars, 'Unkwang' and 'Hopum'. Comparing the ${\gamma}$-oryzanol contents of these varieties, 'Unkwang' showed clearly similar pattern with conventional type. With the PLS-DA (partial least squares of discriminant analysis) using SIMCA 11.0 ver., the specific pattern and cluster of ${\gamma}$-oryzanol scores with green manure conditions were confirmed, and thus distinguishing green manure effects were possible.

• Korean Journal of Environmental Agriculture
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• v.34 no.2
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• pp.98-104
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• 2015

BACKGROUND: ${\gamma}$-Oryzanol, a mixture of ferulic acid esters of triterpene alcohols and sterols, are a nutritionally important group of rice secondary metabolites. The ${\gamma}$-Oryzanol content and composition were found to vary with enviromental factors such as growth temperature, varietal origin, and cultivation method. Therefore, the effect of green manure treatments will be also be an important factor in their content. METHODS AND RESULTS: The ${\gamma}$-Oryzanols extracted using dichloromethane/methanol were analyzed equipped liquid chromatography with a diode array detector. A total of ten components of ${\gamma}$-oryzanol including ${\Delta}7$-stigmastenyl ferulate were isolated of which, cycloartenyl ferulate, 24-methylenecycloartanyl ferulate, campesteryl ferulate and sitosteryl ferulate were identified as the major components in Korean rice variety, Unkwang. The ${\gamma}$-oryzanol content in rice, in the presence of nitrogen fertilization using green manure was similar to conventional nitrogen fertilization, but was higher than the control(no fertilizations). The ${\gamma}$-oryzanol ontent in rice, in the presence of hairy vetch as green manure crop was the highest compared to other crops (opium-poppy, crimson clover, cornflower). As a result of PLS-DA using SIMCA 11.0 ver. as multivariate analysis program on the basis of total data, in all samples, the specific pattern and cluster of ${\gamma}$-oryzanol scores according to green manure crops and conditions were confirmed with possible distinguishing nitrogen effects. CONCLUSION: The nitrogen contained in the green manure crops is considered to play a major role in the formation of ${\gamma}$-oryzanol. Hairy vetch which contains higher nitrogen increased the concentration of ${\gamma}$-oryzanol in rice.

• Analytical Science and Technology
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• v.29 no.1
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• pp.1-9
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• 2016

It is believed that traditional Korean medicines can be managed more scientifically through the development of logical criteria to verify their region of cultivation, and that this could contribute to the advancement of the traditional herbal medicine industry. This study attempted to determine such criteria for Sansuyu. The volatile compounds were obtained from 20 samples of domestic Corni fructus (Sansuyu) and 45 samples of Chinese Sansuyu by steam distillation. The metabolites were identified in the NIST Mass Spectral Library via the obtained gas chromatography/mass spectrometer (GC/MS) data of 53 training samples. Data binning at 0.2 min intervals was performed to normalize the number of variables used in the statistical analysis. Multivariate statistical analyses, such as principle component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) were performed using the SIMCA-P software package. Significant variables with a variable importance in the projection (VIP) score higher than 1.0 were obtained from OPLS-DA, and variables that resulted in a p-value of less than 0.05 through one-way ANOVA were selected to verify the marker compounds. Finally, among the 11 variables extracted, 1-ethylbutyl-hydroperoxide (9.089 min), nonadecane (20.170 min), butylated hydroxytoluene (25.319 min), 5β,7βH,10α-eudesm-11-en-1α-ol (25.921 min), 7,9-bis(2-methyl-2-propanyl)-1-oxaspiro[4.5]deca-6,9-diene-2,8-dione (34.257 min), and 2-decyldodecyl-benzene (54.717 min) were selected as markers to indicate the origin of Sansuyu. The statistical model developed was suitable for the determination of the geographical origin of Sansuyu. The cultivation areas of four Korean and eight Chinese Sansuyu samples were predicted via the established OPLS-DA model, and it was confirmed that 11 of the 12 samples were accurately classified.