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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,Kwak, Chul-won The Royal Society of Chemistry 2012 The Analyst Vol.137 No.16
<P>The potential of transmission Raman spectroscopy for direct analysis of packed granular samples, one of the most frequently encountered sample types in the field of non-destructive spectroscopic analysis, has been evaluated. For this purpose, transmission Raman spectra were collected by laser illumination through packed corn kernels to determine their protein concentration. Back-scattering Raman spectra of the same samples were also collected for comparison. Raman spectral features of the major kernel constituents were initially characterized, and Raman mapping over the whole kernel face was performed to investigate the inhomogeneous distribution of constituents in a kernel. Possible variations of transmission spectral features depending on the laser illumination on different locations of a kernel were investigated, since the orientation of kernels in the packing was essentially random. Rotation of kernel packing during spectral collection was helpful in improving the compositional representation of packed kernels. With partial least squares (PLS) regression, the protein concentrations were determined using both spectral collection methods and the resulting accuracies were compared. As a result, the transmission measurement provided a more accurate determination of protein concentration since it enabled deeper sampling across the packed kernels, leading to a better compositional representation of them. By contrast, in the back-scattering measurement, kernels on the top of the packing were mainly sampled for the spectral acquisition. Moreover, the back-scattering spectral feature, more weighted to constituents localized at the outer portion of a kernel, was short of representing the overall composition of a kernel.</P> <P>Graphic Abstract</P><P>The potential of transmission Raman spectroscopy for direct analysis of packed granular samples, one of the most frequently encountered sample types in the field of non-destructive spectroscopic analysis, has been evaluated. <IMG SRC='http://pubs.rsc.org/services/images/RSCpubs.ePlatform.Service.FreeContent.ImageService.svc/ImageService/image/GA?id=c2an35443h'> </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>
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>