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김석원,조수화,Hoeil Chung,유장렬 한국식물생명공학회 2007 JOURNAL OF PLANT BIOTECHNOLOGY Vol.34 No.3
To determine whether pattern recognition based on metabolite fingerprinting for whole cell extracts of higher plants is applied to discriminate plants genetically, leaf samples of eight cultivars of Catharanthus roseus were subjected to Fourier transform infrared spectroscopy (FT-IR). FT-IR fingerprint region data were analyzed by principal component analysis (PCA). Major peaks as biomarkers were identified as the most significant contributors to distinguish samples by using genetic programming. A hierarchical dendrogram based on the results from PCA separated the eight cultivars into two major groups in the same manner as the dendrograms based on genetic fingerprinting methods such as RAPD and AFLP. A slight difference between the dendrograms was found only in branching pattern within each subgroup. Therefore, we conclude that the hierarchical dendrogram based on PCA of the FT-IR data represents the most probable chemotaxonomical relationship between cultivars, which is in general agreement with the genetic relationship determined by conventional DNA fingerprinting methods.
Shin, Kayeong,Chung, Hoeil The Royal Society of Chemistry 2015 The Analyst Vol.140 No.15
<P>We report a sponge-based transmission surface-enhanced Raman scattering (TSERS) substrate that combines the bulk sampling capabilities of a transmission measurement to improve the quantitative representation of sample concentration with several sponge properties useful for analysis such as fast sample uptake, easy sample enrichment, and a stable polymeric structure. Among nine commercially available sponges made of different materials, a melamine sponge was ultimately selected for this study because it provided the fastest sample uptake and a low background Raman signal. Simultaneously, the amino groups and three-nitrogen hybrid rings in its structure could easily hold Au nanoparticles (AuNPs) inside the sponge. AuNP-incorporated sponges (AuNP sponges) were prepared by simply soaking a melamine sponge in a AuNP solution; these sponges were initially used to measure 4-nitrobenzenethiol (4-NBT) samples with different concentrations in order to evaluate their ability as TSERS substrates. The intensities of the 4-NBT peaks clearly varied according to changes in the concentration, and the relative standard deviation (RSD) of the peak intensity estimated by the measurements of five independently prepared AuNP sponges was 10.0%. Sample enrichment was easily completed by repeated suctioning of the sample into the AuNP sponges followed by depletion of the solvent, so three-time enrichment doubled the intensity. Furthermore, paraquat samples were prepared in diverse matrices (de-ionized water, tap water, river water, and orange juice) and measured using the AuNP sponges. The paraquat peaks were clearly observed from these samples and their peak intensities became smaller with the increased compositional complexity of the matrices. Our overall results demonstrate that the TSERS sponge substrates are easy to prepare and practically versatile for SERS analysis of diverse samples.</P> <P>Graphic Abstract</P><P>We report a sponge-based transmission surface-enhanced Raman scattering (TSERS) substrate that combines the bulk sampling capabilities of a transmission measurement to improve the quantitative representation of sample concentration with several sponge properties useful for analysis such as fast sample uptake, easy sample enrichment, and a stable polymeric structure. <IMG SRC='http://pubs.rsc.org/services/images/RSCpubs.ePlatform.Service.FreeContent.ImageService.svc/ImageService/image/GA?id=c4an02216e'> </P>
Hwang, Jinyoung,Chung, Hoeil The Royal Society of Chemistry 2013 The Analyst Vol.138 No.5
<P>A simple strategy for enhancing the Raman spectral selectivity of complex mixture samples by measuring them in a frozen state at low temperatures has been demonstrated and proven to improve the accuracy for compositional analysis. For evaluation, the Raman spectra of synthetic hydrocarbon mixtures that were composed of eleven hydrocarbons (<I>n</I>-hexane, <I>n</I>-heptane, <I>n</I>-octane, <I>n</I>-nonane, isooctane, cyclohexane, methylcyclohexane, benzene, toluene, xylene, and indan) were continuously collected during the elevation of their temperature from cryogenic to near room temperature. The accuracy of determination of <I>n</I>-paraffin concentrations improved significantly when the samples were measured at the temperature range between approximately −175 and −155 °C in comparison to the measurements at room temperature. However, the improvement of accuracy was relatively marginal for the concentration determination of naphthenic and aromatic components. Since <I>n</I>-paraffins are easily compressible and deformable in frozen conditions, the subsequent spectral variations could be diverse depending on their molecular structures. Due to this fact, the spectral discrimination among the paraffin components, as well as in comparison to other components, was enhanced and the improved spectral selectivity eventually led to more accurate determination of concentrations. Overall, the proposed strategy is simple and effective, so it is applicable for analysis of real complex mixture samples.</P> <P>Graphic Abstract</P><P>Raman spectra collected at a frozen state provide improved spectral selectivity for compositional analysis. <IMG SRC='http://pubs.rsc.org/services/images/RSCpubs.ePlatform.Service.FreeContent.ImageService.svc/ImageService/image/GA?id=c2an36575h'> </P>
Score–moment combined linear discrimination analysis (SMC-LDA) as an improved discrimination method
Han, Jintae,Chung, Hoeil,Han, Sung-Hwan,Yoon, Moon-Young Royal Society of Chemistry 2007 The Analyst Vol.132 No.1
<P>A new discrimination method called the score–moment combined linear discrimination analysis (SMC-LDA) has been developed and its performance has been evaluated using three practical spectroscopic datasets. The key concept of SMC-LDA was to use not only the score from principal component analysis (PCA), but also the moment of the spectrum, as inputs for LDA to improve discrimination. Along with conventional score, moment is used in spectroscopic fields as an effective alternative for spectral feature representation. Three different approaches were considered. Initially, the score generated from PCA was projected onto a two-dimensional feature space by maximizing Fisher's criterion function (conventional PCA-LDA). Next, the same procedure was performed using only moment. Finally, both score and moment were utilized simultaneously for LDA. To evaluate discrimination performances, three different spectroscopic datasets were employed: (1) infrared (IR) spectra of normal and malignant stomach tissue, (2) near-infrared (NIR) spectra of diesel and light gas oil (LGO) and (3) Raman spectra of Chinese and Korean ginseng. For each case, the best discrimination results were achieved when both score and moment were used for LDA (SMC-LDA). Since the spectral representation character of moment was different from that of score, inclusion of both score and moment for LDA provided more diversified and descriptive information.</P> <P>Graphic Abstract</P><P>Moment is an effective alternative for spectral feature representation. <IMG SRC='http://pubs.rsc.org/services/images/RSCpubs.ePlatform.Service.FreeContent.ImageService.svc/ImageService/image/GA?id=b611252h'> </P>
Lee, Youngbok,Chung, Hoeil,Kim, Nakjoong Society for Applied Spectroscopy 2006 Applied spectroscopy Vol.60 No.8
<P>The proper selection of the spectral range in partial least squares (PLS) calibration is critical when highly overlapping spectra from compositionally complex samples are used, such as naphtha and gasoline. In particular, the relevant spectral information related to a given property is frequently localized in a narrow range, and the most selective region may be difficult to locate. We have presented the importance of range optimization in near-infrared (NIR) spectroscopy for the analyses of petrochemical and petroleum products that are generally highly complex in composition. For this purpose, the determination of a detailed compositional analysis (so called PIONA) and the distillation temperature of naphtha were evaluated. In the same fashion, the research octane number (RON) and Reid vapor pressure (RVP) were selected for gasoline. By optimizing the range using moving window (MW) PLS, the overall calibration performance was improved by finding the optimal spectral range for each property. In particular, for a detailed compositional analysis of naphtha, it was effective to search for localized spectral information in a relatively narrow range with fewer factors.</P>