• Journal of Applied Biological Chemistry
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• v.65 no.4
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• pp.429-438
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• 2022

The composition of crops reveal natural variation according to genetic characteristics and environmental factors such as the cultivated regions. For comparative investigation of the impact of genetic difference and environmental influence on the levels of bioactive components in rice seeds, 23 cultivars including indica, japonica, and tongil rice were grown in two location in Korea (Jeonju and Cheonan) for two years (2015 and 2016). Sixteen compounds consisting of tocopherols, tocotrienols, phytosterols, and policosanols were identified from 368 rice samples and the compositional data were subjected to data mining processes including principal component analysis and Pearson's correlation analysis. Under 4 different environmental conditions (Jeonju in 2015, Cheonan in 2015, Jeonju in 2016, Cheonan in 2016), the natural variability of rice seeds showed that the genetic background (indica vs japonica vs tongil) had more impact on the compositional changes of bioactive components compared to the environments. Especially, the results of correlation analysis revealed negative correlation between α-, β-tocopherols and γ-, δ-tocopherols as a representative genetic effect that did not changed by the environmental influence.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.10
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• pp.1618-1628
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• 2013

Relationships between fatty acids and tocopherols in conventional and genetically modified peanut cultivars were studied by gas chromatography with flame ion detector and high performance liquid chromatography with fluorescence detection. Eight fatty acids and four tocopherol isomers in the sample set were identified and quantified. Oleic acid and linoleic acid are major fatty acids and the ratio of oleic and linoleic acids ranged from 1.11 to 16.26. Tocopherols contents were 6.76 to 12.24 for ${\alpha}$-tocopherol (T), 0.08 to 0.39 for ${\beta}$-T, 5.28 to 15.02 for ${\gamma}$-T, and 0.17 to 1.17 mg/100 g for ${\delta}$-T. Correlation coefficient (r) for fatty acids and tocopherols indicated a strong inverse relationship between oleic & linoleic acids (r=-0.97, P<0.05) and positive relationships between palmitic & linoleic acids (r=0.95, P<0.05) and ${\gamma}$-T & ${\delta}$-T (r=0.83, P<0.05). Principal component analysis (PCA) of fatty acids and tocopherols gave four significant principal components (PCs, with eigenvalues>1), which together account for 85.49% of the total variance in the data set with PC1 and PC2 contributing 45.27% and 21.33% of the total variability, respectively. Eigen analysis of the correlation matrix loadings of the four significant PCs revealed that PC1 was mainly contributed by palmitic, oleic, linoleic, and gondoic acids, while PC2 was by behenic acid, ${\beta}$-T, and ${\gamma}$-T. The score plot generated by PC1-PC2 identified sample clusters in the two spatial planes based on the oleic and linoleic acids. The score plot PC3-PC4 didn't separate sample groups.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1859-1867
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• 2021

This study investigated seasonal characteristics of the particulate matter (PM) in the atmosphere and rainwater quality in Busan, South Korea, and evaluated the seasonal effect of PM₁₀ concentration in the atmosphere on the rainwater quality using multivariate statistical analysis. The concentration of PM in the atmosphere and meteorological observations(daily precipitation amount and rainfall intensity) are obtained from automatic weather systems (AWS) by the Korea Meteorological Administration (KMA) from March 2020 to August 2020. Rainwater samples (n = 216, 13 rain events) were continuously collected from the beginning of the precipitation using the rainwater collecting device at Pukyong National University. The samples were analyzed for pH, EC (electrical conductivity), water-soluble cations(Na⁺, Mg²⁺, K⁺, Ca²⁺, and NH₄⁺), and anions(Cl^-, NO₃^-, and SO₄^2-). The concentration of PM₁₀ in the atmosphere was steadily measured before and after the precipitation with a custom-built PM sensor node. The measured data were analyzed using principal component analysis (PCA) and Pearson correlation analysis to identify relationships between the concentration of PM₁₀ in the atmosphere and rainwater quality. In spring, the daily average concentration of PM₁₀ (34.11 ㎍/m³) and PM_2.5 (19.23 ㎍/m³) in the atmosphere were relatively high, while the value of daily precipitation amount and rainfall intensity were relatively low. In addition, the concentration of PM₁₀ in the atmosphere showed a significant positive correlation with the concentration of water-soluble ions (r = 0.99) and EC (r = 0.95) and a negative correlation with the pH (r = -0.84) of rainwater samples. In summer, the daily average concentration of PM₁₀ (27.79 ㎍/m³) and PM_2.5 (17.41 ㎍/m³) in the atmosphere were relatively low, and the maximum rainfall intensity was 81.6 mm/h, recording a large amount of rain for a long time. The results indicated that there was no statistically significant correlation between the concentration of PM₁₀ in the atmosphere and rainwater quality in summer.

• Journal of the Korean Orthopaedic Association
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• v.56 no.1
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• pp.61-67
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• 2021

Purpose: To evaluate the prognostic factors affecting poor functional outcomes in patients with retear after rotator cuff repair. Materials and Methods: From January 2013 to December 2018, among 631 patients who underwent arthroscopic repair of a rotator cuff tear, 42 patients, who could be followed-up for more than one year and showed a retear of the repaired cuff on magnetic resonance imaging (MRI), were collected retrospectively. The preoperative demographic data, range of motion, American Shoulder and Elbow Surgeons (ASES) score, fatty degeneration, and tear progression on postoperative MRI, as well as other factors that could affect the clinical outcomes, were analyzed. Patients who scored <80 points on the ASES score were allocated to the poor function group. The risk factors for poor clinical outcomes were compared with the group with ASES scores of 80 or above. Results: The postoperative functional results in the group with retear (n=42) after arthroscopic rotator cuff repair showed significant improvement. Univariate analysis revealed the preoperative visual analogue scale (VAS) score and tear progression to have associations with a poor shoulder function. In addition, subscapularis repair was found to be associated with a good shoulder function. The preoperative VAS score and tear progression except for subscapularis repair were independent factors associated with poor clinical outcomes according to multivariate logistic regression analysis. Conclusion: In patients with retear after rotator cuff repair, the preoperative VAS and tear progression in postoperative MRI are factors predicting a poor functional outcome.

• Geophysics and Geophysical Exploration
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• v.7 no.3
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• pp.164-173
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• 2004

To delineate geothermal water movement at the Pohang geothermal development site, Self-Potential (SP) survey and monitoring were carried out during pumping tests. Before drilling, background SP data have been gathered to figure out overall potential distribution of the site. The pumping test was performed in two separate periods: 24 hours in December 2003 and 72 hours in March 2004. SP monitoring started several days before the pumping tests with a 128-channel automatic recording system. The background SP survey showed a clear positive anomaly at the northern part of the boreholes, which may be interpreted as an up-flow Bone of the deep geothermal water due to electrokinetic potential generated by hydrothermal circulation. The first and second SP monitoring during the pumping tests performed to figure out the fluid flow in the geothermal reservoir but it was not easy to see clear variations of SP due to pumping and pumping stop. Since the area is covered by some 360 m-thick tertiary sediments with very low electrical resistivity (less than 10 ohm-m), the electrokinetic potential due to deep groundwater flow resulted in being seriously attenuated on the surface. However, when we compared the variation of SP with that of groundwater level and temperature of pumping water, we could identify some areas responsible to the pumping. Dominant SP changes are observed in the south-west part of the boreholes during both the preliminary and long-term pumping periods, where 3-D magnetotelluric survey showed low-resistivity anomaly at the depth of $600m\~1,000m$. Overall analysis suggests that there exist hydraulic connection through the southwestern part to the pumping well.

• Journal of Plant Biotechnology
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• v.43 no.2
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• pp.213-222
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• 2016

This study aims to establish a system for the rapid discrimination of Zoysia species using metabolite fingerprinting of FT-IR spectroscopy combined with multivariate analysis. Whole cell extracts from leaves of 19 identified Zoysia japonica, 6 identified Zoysia sinica, and 38 different unidentified Zoysia species were subjected to Fourier transform infrared spectroscopy (FT-IR). PCA (principle component analysis) and PLS-DA (partial least square discriminant analysis) from FT-IR spectral data successfully divided the 25 identified turf grasses into two groups, representing good agreement with species identification using molecular markers. PC (principal component) loading values show that the $1,100{\sim}950cm^{-1}$ region of the FT-IR spectra are important for the discrimination of Zoysia species. A dendrogram based on hierarchical clustering analysis (HCA) from the PCA and PLS-DA data of turf grasses showed that turf grass samples were divided into Zoysia japonica and Zoysia sinica in a species-dependent manner. PCA and PLS-DA from FT-IR spectral data of Zoysia species identified and unidentified by molecular markers successfully divided the 49 turf grasses into Z. japonica and Z. sinica. In particular, PLS-DA and the HCA dendrogram could mostly discriminate the 47 Z. japonica grasses into two groups depending on their origins (mountainous areas and island area). Considering these results, we suggest that FT-IR fingerprinting combined with multivariate analysis could be applied to discriminate between Zoysia species as well as their geographical origins of various Zoysia species.

• Journal of The Korean Society of Grassland and Forage Science
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• v.26 no.1
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• pp.53-62
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• 2006

Near infrared reflectance spectroscopy (NIRS) has been increasingly used as a rapid, accurate method of evaluating some chemical compositions in forages. Analysis of forage quality by NIRS usually involves dry ground samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations and spectral math treatments on prediction ability of chemical composition for corn silage by NIRS. A population of 112 corn silage representing a wide range in chemical parameters were used in this investigation. Samples of com silage were scanned at 2nm intervals over the wavelength range 400-2500nm and the optical data recorded as log l/Reflectance(log l/R) and scanned in overt-dried grinding(ODG), liquid nitrogen grinding(LNG) or intact fresh(IF) condition. Samples were analysed for neutral detergent fiber(NDF), acid detergent fiber(ADF), acid detergent lignin(ADL), crude protein(CP) and crude ash content were expressed on a dry-matter(DM) basis. The spectral data were regressed against a range of chemical parameters using modified partial least squares(MPLS) multivariate analysis in conjunction with four spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation(SECV). The results of this study show that NIRS predicted the chemical parameters with very high degree of accuracy(the correlation coefficient of cross validation$(R^2cv)$ range from $0.70{\sim}0.95$) in ODG. The optimum equations were selected on the basis of minimizing the standard error of prediction(SEP). The Optimum sample preparation methods and spectral math treatment were for ADF, the ODG method using 2,10,5 math treatment(SEP = 0.99, $R^2v=0.93$), and for CP, the ODG method using 1,4,4 math treatment(SEP = 0.29. $R^2v=0.91$).

• Journal of The Korean Association For Science Education
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• v.38 no.1
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• pp.57-68
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• 2018

The purpose of this study is to categorize learning style groups and to analyze students' learning interest and self-regulated learning abilities, according to their learning style and giftedness. One hundred and twenty-three (123) science-gifted student and 296 regular students participated in this study, responding to learning style, self-regulated learning, and learning interest questionnaires. Data were analyzed, using 2-stage cluster analysis, $x^2$ test, two way-MANOVA test, and $Scheff{\acute{e}}$ test. The results are as follows: First, by 2-stage cluster analysis, four groups were categorized: 'high-score thinking style,' 'external-liberal,' 'executive-conservative,' and 'low-score thinking style.' In the gifted group, high-score thinking style (51.2%) was the most popular, then executive-conservative (30.2%), external-liberal (17.1%), and low-score thinking style (1.6%); in the regular student group, the executive-conservative group was the biggest, then high-score thinking style (20.6%), external-liberal (11.6%), and then the low-score thinking style (8.7%). Second, in terms of learning interest, the analysis by thinking style showed that the high-score thinking style group had higher learning interest compared to the executive-conservative and the low-thinking style group. The high-thinking style group's thoughtful interest also scored the highest compared with the others. The gifted students' thoughtful interest and investigative interest also were higher than regular students '. Third, in terms of the self-regulated learning, the analysis by thinking style showed that the high-score thinking style group showed higher scores on all sub-variances than other groups, especially having highest control-belief scores. Also, gifted students had higher scores on control-belief and searching information. Based on these results, the ways for effective education and support were discussed.

• Journal of Plant Biotechnology
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• v.42 no.3
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• pp.257-264
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• 2015

To determine whether metabolite fingerprinting for whole cell extracts based on Fourier transform infrared (FT-IR) spectroscopy can be used to discriminate and compare metabolic equivalence, standard medicinal parts from four medicinal plants (Cynanchum wilfordii Hemsley, Atractylodes japonica Koidz, Polygonum multiflorum Thunberg and Astragalus membranaceus Bunge) and their in vitro-produced adventitious roots were analyzed by FT-IR spectroscopy. The principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) from the FT-IR spectral data showed that the whole metabolic pattern from Cynanchum wilfordii was highly similar to Astragalus membranaceus. However, Atractylodes japonica and Polygonum multiflorum showed significantly different metabolic patterns. Furthermore, adventitious roots from Cynanchum wilfordii and Astragalus membranaceus also showed similar metabolic patterns compared to their standard medicinal parts. These results clearly show that mass proliferation of adventitious roots may be applied to aquire novel supply of standard medicinal parts from medicinal plants. However, the whole metabolic pattern from adventitious roots of Atractylodes japonica and Polygonum multiflorum were not similar to their standard medicinal parts. Furthermore, FT-IR spectroscopy combined with multivariate analyses established in this study may be applied as an alternative tool to discriminate the whole metabolic equivalence from several standard medicinal parts. Thus, we suggest that these metabolic discrimination systems may be applied for metabolic standardization of herbal medicinal resources.

• Journal of Plant Biotechnology
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• v.45 no.3
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• pp.250-256
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• 2018

To determine whether metabolite fingerprinting for whole cell extracts based on Fourier transform infrared spectroscopy (FT-IR) can be used to discriminate and compare metabolic equivalence, standard medicinal parts of Cynanchum wilfordii (Maxim.) Hemsl. and their adventitious roots were subjected to FT-IR. The principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) from FT-IR spectral data showed that whole metabolic pattern from the adventitious root of Cynanchum wilfordii was highly similar to its standard medicinal parts. These results clearly showed that mass proliferation of adventitious roots could be applied for the novel supply of standard medicinal parts of medicinal plants. Furthermore, FT-IR spectroscopy combined with multivariate analysis established in this study could be applied as an alternative tool for discriminating of whole metabolic equivalence from standard medicinal parts. Thus, it is proposed that these metabolic discrimination systems from the adventitious root of Cynanchum wilfordii could be applied for metabolic standardization of in vitro grown Cynanchum wilfordii.