• 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 IKEEE
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• v.22 no.4
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• pp.999-1005
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• 2018

This paper proposed a search-based high resolution frequency estimation method in power systme. The proposed frequency estimation method adopts a slope-based adaptive search as a base of adaptive estimation structure. The architectural and operational parameters in this adaptive algorithm are changed using the information from context layer analysis of the signals including a localized full-search of spectral peak. The convergence rate of the proposed algorithm becomes much faster than those of other conventional slope-based adaptive algorithms by effectively reducing search range with the application of the localized full-search of spectrum peak. The improvements in accuracy and convergence rate of the proposed algorithm are confirmed through the performance comparison with other representative frequency estimation methods, such as, DFT(discrete Fourier transform) method, ECKF(extended complex Kalman filter), and MV(minimum variable) method.

• 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.

• Journal of Biosystems Engineering
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• v.38 no.4
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• pp.312-317
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• 2013

Purpose: Conventional methods used to evaluate seeds viability are destructive, time consuming, and require the use of chemicals, which are not feasible to implement to process plant in seed industry. In this study, the effectiveness of Fourier transform near infrared (FT-NIR) spectroscopy to differentiate between viable and nonviable watermelon seeds was investigated. Methods: FT-NIR reflectance spectra of both viable and non-viable (aging) seeds were collected in the range of 4,000 - 10,000 $cm^{-1}$ (1,000 - 2,500 nm). To differentiate between viable and non-viable seeds, a multivariate classification model was developed with partial least square discrimination analysis (PLS-DA). Results: The calibration and validation set derived from the PLS-DA model classified viable and non-viable seeds with 100% accuracy. The beta coefficient of PLS-DA, which represented spectral difference between viable and non-viable seeds, showed that change in the chemical component of the seed membrane (such as lipids and proteins) might be responsible for the germination ability of the seeds. Conclusions: The results demonstrate the possibility of using FT-NIR spectroscopy to separate seeds based on viability, which could be used in the development of an online sorting technique.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.30.1-30.1
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• 2020

The ASKAP-EMU survey is a deep wide-field radio continuum survey designed to cover the entire southern sky and a significant fraction of the northern sky up to +30°. Here, we report a discovery of a radio relic in the merging cluster SPT-CL J2023-5535 at z=0.23 from the ASKAP-EMU pilot 300 square degree survey (800-1088 MHz). The deep high-resolution data reveal a ~2 Mpc-scale radio halo elongated in the east-west direction, coincident with the intracluster gas. The radio relic is located at the western edge of this radio halo stretched ~0.5 Mpc in the north-south orientation. The integrated spectral index of the radio relic within the narrow bandwidth is α1088MHz800MHz = -0.76 ± 0.06. Our weak-lensing analysis shows that the system is massive (M200 = 1.04 ± 0.36 × 1015M⊙) and composed of at least three subclusters. We suggest a scenario, wherein the radio features arise from the collision between the eastern and middle subclusters. Furthermore, the direct link between the local AGN and the relic along with the discontinuities in X-ray observation hint us that we are looking at the site of re-acceleration.

• Food Science and Preservation
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• v.24 no.1
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• pp.145-152
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• 2017

In this study, near infrared (NIR) spectroscopy known as a non-destructive analysis technique was applied to investigate peptide cleavage and consequent release of amino acids in soybean lumps as affected by its moisture content and incubation time during fermentation at 25 for 3 weeks. The NIR spectra of the soybean lump semi-dried and soaked in saline water showed that absorption intensity around 1,400 nm originating from hydrogen bonds of water decreased and absorption band shifted to 1,430 nm as moisture content decreased during incubation at 25 for 3 weeks. In addition, absorption around 2,050 nm which was assigned to amino groups increased as incubation time increased. NIR spectra data from 1,000 to 2,250 nm showed higher accuracy in the discriminant analysis between outside and inside parts of fermented soybean lumps than visible spectra result. NIR spectroscopy for the amino acid and moisture contents in traditional fermented soybean lumps showed relatively good accuracy with the multiple correlation coefficient ($R^2$) of 0.91 and 0.81, respectively, and root mean square error of cross validation (RMSECv) of 0.23 and 0.83%, respectively, in partial least square regression (PLSR). These results indicate that NIR spectral observations could be applicable to control the fermentation process for preparation of soybean products.

• Korean Journal of Soil Science and Fertilizer
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• v.37 no.4
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• pp.259-265
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• 2004

A quicker method was developed for foliar analysis in diagnosis of nitrogen in apple trees based on multivariate calibration procedure using partial least squares regression (PLSR) and principal component regression (PCR) to establish the relationship between reflectance spectra in the near infrared region and nitrogen content of fresh- and dry-leaf. Several spectral pre-processing methods such as smoothing, mean normalization, multiplicative scatter correction (MSC) and derivatives were used to improve the robustness and performance of the calibration models. Norris first derivative with a seven point segment and a gap of six points on MSC gave the best result of partial least squares-1 PLS-1) model for dry-leaf samples with root mean square error of prediction (RMSEP) equal to $0.699g\;kg^{-1}$, and that the Savitzky-Golay first derivate with a seven point convolution and a quadratic polynomial on MSC gave the best results of PLS-1 model for fresh-samples with RMSEP of $1.202g\;kg^{-1}$. The best PCR model was obtained with Savitzky-Golay first derivative using a seven point convolution and a quadratic polynomial on mean normalization for dry leaf samples with RMSEP of $0.553g\;kg^{-1}$, and obtained with the Savitzky-Golay first derivate using a seven point convolution and a quadratic polynomial for fresh samples with RMSEP of $1.047g\;kg^{-1}$. The results indicate that nitrogen can be determined by the near infrared reflectance (NIR) technology for fresh- and dry-leaf of apple.

• 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.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1522-1522
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• 2001

Beverages based on fruit juices are among the most popular commercially available drinks. There is an ever-increasing demand for these juices in the market. Orange juice is one of the most common as well as most favorite flavor. The fruit processing industries have a tremendous responsibility of quality control. For quality evaluation estimation of various components of the juice is necessary. Sucrose, glucose, fructose, citric acid and malic acid are the prime components of orange juice. Little information is available on analysis of orange juice. However, conventional and general wet chemistry procedures are currently being used which are no longer desired by the industry owing to the time involved, labor input and harmful chemicals required for each analysis. Need to replace these techniques with new, highly specific and automated sophisticated techniques viz. HPLC and spectroscopy has been realized since long time. Potential of Near Infrared Spectroscopy in quantitative analysis of different components of food samples has also been well established. A rapid, non-destructive and accurate technique based on Near Infrared Spectroscopy for determination of sugars and organic acids in orange juice will be highly useful. The current study is an investigation into the potential of Near Infrared Diffuse Reflectance Spectroscopy for rapid quantitative analysis of sucrose, glucose, fructose citric acid and malic acid in orange juice. All the Near Infrared measurements were peformed on a dispersive NIR spectrophotometer (ELICO 153) in diffuse reflectance mode. The spectral region from 1100 to 2500nm has been explored. The calibration has been performed on synthetic samples that are mixtures of sucrose, glucose, fructose, citric acid and malic acid in different concentration ranges typically encountered real orange juice. These synthetic samples are therefore considered to be representatives of natural juices. All the Near Infrared spectra of synthetic samples were subjected to mathematical analysis using Partial Least Square (PLS) algorithm. After the validation, calibration was applied to commercially available real samples and freshly squeezed natural juice samples. The actual concentrations were compared with those predicted from calibration curve. A good correlation is obtained between actual and predicted values as indicated by correlation coefficient ($R^2$) value, which is close to unity, showing the feasibility of the technique.

• 한국해양학회지
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• v.28 no.1
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• pp.1-16
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• 1993

The monthly mean sea levels at 48 stations located at the East and Yellow Seas coasts of Korea, Russia and Japan are processed to investigate seasonal sea level variations. The strong seasonal variations are found to be at the west coast of Korea (42.1 cm in Kunsan), in the region of the Korea strait and near the southern part of Primorye (30-33 cm); the weak ones near the southwestern coast of the Sakhalin Island (10-12 cm). Practically for the whole study area except the southwest Sakhalin, the general picture of the seasonal sea level changes is alike: the mean sea level rises in summer-autumn and falls in winter-spring. The spectral analysis of the records also shows that the seasonal oscillations strongly dominate in the sea level variations, more than 80% or total energy in the southern part of the investigated region and 50-70% in the northern part relate to these oscillations. The annal peak significantly prevails in spectra of the monthly sea levels for the majority of stations, the semiannual peak is also well manifested, but the seasonal peaks of higher order (corresponding to the periods of four and three months) reveal only at some records. The maximal amplitudes of annual component by a least square method are found at the Yellow Sea coast of Korea (20-21 cm) and also near the Japanese coast of the korea Strait (19-19 cm). The semiannual component has the maximal amplitudes (3-4 cm) near the south and southwestern coasts of the Sakhalin Island. The annual range of the sea levels is much weaker here than in the other regions, the relative investment of the seasonal oscillations in total energetic budget is only 35-40%, annual ($A_1$) and semiannual ($A_2$) components have nearly the same amplitude (seasonal factor $F=A_1/A_2=0.9-1.2$). On the basis of the present examination on sea level changes together with the results of Tomizawa et. al.(1984) the whole investigated area may be divided into 10 subregions, 2 of them are related to the Yellow Sea and Western part of the Korea Strait (Y1, Y2), the other ones (E1-E8) to the East Sea.