• Journal of the Korean Society of Tobacco Science
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• v.27 no.1 s.53
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• pp.134-140
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• 2005

The purpose of this study was the discrimination of different tobacco types by the E-Nose/tongue and the analysis of what human sensory attributes are correlated with e-instrument's sensors. Samples were made from five groups of Korean domestic tobacco leaves, aged burley and not aged, aged flue-cured and not aged and blending types of the four. Instrumental tests were conducted to discriminate characteristics among different tobacco samples by the E-Nose and the E-Tongue. Sensory attributes of tobacco tastes were impact, irritation, bitterness, hay-like, tobacco taste, smoke volume, smoke pungent and mouth cleanness. STATISTICA software was used to analyze correlation between the human sensory data and the raw data of e-instruments. Discrimination analysis can be achieved using principal components analysis (PCA) and discriminant factorial analysis(DFA). As a result, impact, bitterness, irritation, smoke volume and smoke pungent of human sensory attributes were correlated with data from the several clustered E-Nose sensors(p < 0.10). And bitterness, irritation, and smoke pungent of human sensory attributes were correlated with data from the E-Tongue sensors(p < 0.10). PCA plot by the E-Nose shows that aged tobacco and not aged were discriminated and DFA plot shows that three groups(aged burley, not aged burley and flue-cured) were discriminated. PCA plot by the E- Tongue shows that flue-cured tobacco was separated from burley. Our results indicated that the e-instruments are sensitive enough to distinguish among tobacco types and their several sensors are reacted to the human sensory attributes.

• Analytical Science and Technology
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• v.10 no.5
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• pp.362-369
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• 1997

Chemometric technique was applied to the sugar composition in five honeys of known botanical or geographical origin following HPLC. Fructose and glucose were predominant carbohydrates in honeys, and small amount of sucrose was also detected in one sample. Sugar contents in honeys samples were compared by the geographical or botanical origin. Fructose/glucose ratio ranged from 0.99 to 1.55 was obtained and these results are in good agreement with the ratio of literature. The plot of principal components analysis(PCA) showed that different honey samples grouped into distinct cluster by the geographical or botanical origin. Increasing the first or second principal component score, higher amount of sugar or less fructose/glucose ratio was observed in PCA plot. Chemometric approach was very useful to provide pattern recognition of sugar profile or quality indices of honey sample and to detect adulteration.

• Weed & Turfgrass Science
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• v.3 no.4
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• pp.269-275
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• 2014

A survey was conducted to identify the occurrence of problematic weed species on the Dioscorea oppostifolia fields in South Korea. Total 43 sites of the 8 different regions in S. Korea were investigated from May to October, 2014. In yam fields, the identified weeds were distributed in 11 families and 44 species. The exotic plants were identified as 3 families, 10 genera, 10 species. The vegetation of Dioscorea oppostifolia fields was classified into communities of 7 groups by methods of the Zurich-Montpellier school of phytosociology (Xanthium canadense Community, Bidens frondosa Community, Echinochloa oryzoides Community, Eclipta prostrata Community, Portulaca oleracea Community, Centipeda minima Community, Rorippa islandica Community). The weeds occurred in Dioscorea oppostifolia fields were divided into three groups in principal component plot analysis (PCA). Without weed control, yields loss in yam production was reached up to 82% as compared to weed controlled fields.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1281-1281
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• 2001

Near-infrared (NIR) spectra have bean measured for high-density (HDPE), linear low-density (LLDPE), and low-density (LDPE) polyethylene in pellet or thin films. The obtained spectra have been analyzed by conventional spectroscopic analysis methods and chemometrics. By using the second derivative, principal component analysis (PCA), and two-dimensional (2D) correlation analysis, we could separate many overlapped bands in the NIR. It was found that the intensities of some bands are sensitive to density and crystallinity of PE. This may be the first time that such bands in the NIR region have ever been discussed. Correlations of such marker bands among the NIR spectra have also been investigated. This sort of investigation is very important not only for further understanding of vibration spectra of various of PE but also for quality control of PE by vibrational spectroscopy. Figure 1 (a) and (b) shows a NIR reflectance spectrum of one of the LLDPE samples and that of PE, respectively. Figure 2 shows a PC weight loadings plot of factor 1 for a score plot of PCA for the 16 kinds of LLDPE and PE based upon their 51 NIR spectra in the 1100-1900 nm region. The PC loadings plot separates the bands due to the $CH_3$ groups and those arising form the $CH_2$ groups, allowing one to make band assignments. The 2D correlation analysis is also powerful in band enhancement, and the band assignments based upon PCA are in good agreement with those by the 2D correlation analysis.(Figure omitted). We have made a calibration model, which predicts the density of LLDPE by use of partial least square (PLS) regression. From the loadings plot of regression coefficients for the model , we suggest that the band at 1542, 1728, and 1764 nm very sensitive to the changes in density and crystalinity.

• Journal of the Korean Wood Science and Technology
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• v.46 no.3
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• pp.285-296
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• 2018

As a study for the verification of heat treated wood according to ISPM No. 15, the spectroscopic characteristics of the heat treated wood surface were analyzed. Various functional groups were observed on the IR spectrum, but it was difficult to find any particular difference between wood species, heat treatment time and storage period. HBI (hydrogen-bonding intensity) shows the change of the heat treated wood according to the storage time, but the change of wood with the heat treatment time was hard to be observed. On the PCA score plot, however, it was possible to sort the wood according to the heat treatment time of 60 minutes or 90 minutes in the species. The standards for classification of heat-treated wood in PCA were aromatic rings in lignin and C-H bending in cellulose, and these components were able to classify heat-treated wood by ISPM No. 15.

• Weed & Turfgrass Science
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• v.4 no.4
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• pp.279-287
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• 2015

The present research was carried out in order to investigate the occurrence of problematic weed species in Cnidium officinale Makino. Field in South Korea. Total 53 sites of the 3 different regions in S. Korea were investigated from May to October, 2014. In Cnidium officinale fields, the identified weeds were distributed in 35 families and 99 species. Total 5 communities that consist of Commelina communis, Eleocharis kuroguwai, Persicaria vulgaris, Chenopodium album-Acalypha australis, and Galinsoga ciliata dominated the appearance. The weeds occurred in Cnidium officinale fields were divided into three groups in principal component plot analysis (PCA). It was observed that in control weeds plots; 20 plants of Cnidium officinale fresh weight is 739.9 g while the uncontrolled plots have no Cnidium officinale plants. The current investigation could be useful for estimation of future weeds occurrence, weed flora dynamics and establishment of weed control methods in Cnidium officinale fields in Korea.

• Journal of Distribution Science
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• v.13 no.9
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• pp.103-112
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• 2015

Purpose - This paper aims to provide a step-by-step approach to factor analytic procedures, such as principal component analysis (PCA) and exploratory factor analysis (EFA), and to offer a guideline for factor analysis. Authors have argued that the results of PCA and EFA are substantially similar. Additionally, they assert that PCA is a more appropriate technique for factor analysis because PCA produces easily interpreted results that are likely to be the basis of better decisions. For these reasons, many researchers have used PCA as a technique instead of EFA. However, these techniques are clearly different. PCA should be used for data reduction. On the other hand, EFA has been tailored to identify any underlying factor structure, a set of measured variables that cause the manifest variables to covary. Thus, it is needed for a guideline and for procedures to use in factor analysis. To date, however, these two techniques have been indiscriminately misused. Research design, data, and methodology - This research conducted a literature review. For this, we summarized the meaningful and consistent arguments and drew up guidelines and suggested procedures for rigorous EFA. Results - PCA can be used instead of common factor analysis when all measured variables have high communality. However, common factor analysis is recommended for EFA. First, researchers should evaluate the sample size and check for sampling adequacy before conducting factor analysis. If these conditions are not satisfied, then the next steps cannot be followed. Sample size must be at least 100 with communality above 0.5 and a minimum subject to item ratio of at least 5:1, with a minimum of five items in EFA. Next, Bartlett's sphericity test and the Kaiser-Mayer-Olkin (KMO) measure should be assessed for sampling adequacy. The chi-square value for Bartlett's test should be significant. In addition, a KMO of more than 0.8 is recommended. The next step is to conduct a factor analysis. The analysis is composed of three stages. The first stage determines a rotation technique. Generally, ML or PAF will suggest to researchers the best results. Selection of one of the two techniques heavily hinges on data normality. ML requires normally distributed data; on the other hand, PAF does not. The second step is associated with determining the number of factors to retain in the EFA. The best way to determine the number of factors to retain is to apply three methods including eigenvalues greater than 1.0, the scree plot test, and the variance extracted. The last step is to select one of two rotation methods: orthogonal or oblique. If the research suggests some variables that are correlated to each other, then the oblique method should be selected for factor rotation because the method assumes all factors are correlated in the research. If not, the orthogonal method is possible for factor rotation. Conclusions - Recommendations are offered for the best factor analytic practice for empirical research.

• Food Science of Animal Resources
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• v.24 no.3
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• pp.260-265
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• 2004

This study was carried out to investigate aroma patterns of Hanwoo (Korean cattle) beef using electronic nose during refrigerated storage, and to compare these results with chemical quality (pH, TBARS). The M. longissimus muscle from Hanwoo carcasses after 24 hrs postmortem was obtained and stored at 5${\pm}$1$^{\circ}C$ for 7 days. Sensitivity (dR/RO) values among electronic nose data were changed differently during refrigerated storage, and showed significant difference on the 7th day of storage (p<0.01). The dR/RO from SY/G, SY/AA, SY/Gh, SY/gCTl, SY/gCT decreased but those from SY/LG, T30/1, P10/1, P10/2, P40/1, T70/2, PA2 increased during storage for 7 days. Mapping these data using PCA (principal component analysis) showed that the 1st day data were present in the middle of the right side, the 3rd day data were present in bottom part of this area and the 7th day data spread out more widely on the left side. In case of DFA (discriminant factor analysis), the flock clustered round and located in different side clearly comparing with PCA plot. In analysis of correlation coefficients among electronic nose data and chemical quality data, there was significant correlation among sensor data (p<0.001). But pH and TBARS were not significantly correlated with electronic nose data. Consequently, PCA and DFA plot by electronic nose data showed difference during refrigerated storage and there were significant correlations among sensors. Therefore it will be possible to detect separate aroma patterns of Hanwoo beef using electronic nose.

• Biomolecules & Therapeutics
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• v.17 no.2
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• pp.133-137
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• 2009

The root of Astragalus membranaceus is a traditional folk medicine that has been used for many therapeutic purposes in Asia. It reportedly acts as an immunostimulant, tonic, hepatoprotective, diuretic, antidiabetic, analgesic, expectorant, sedative, and anticancer drug. In this study, metabolomic profiling was applied to the roots of A. membranaceus of different ages using NMR coupled with two multivariate statistical analysis methods: such as principal components analysis (PCA) and canonical discriminant analysis (CDA). This allowed various metabolites to be assigned in NMR spectra, including $\gamma$-aminobutyric acid (GABA), aspartic acid, succinic acid, glutamic acid, glutamine, N-acetyl aspartic acid, acetic acid, arginine, alanine, threonine, lactic acid, and valine. The score plot from PCA and also CDA allowed a clear separation between samples according to age.

• Horticulture, Environment, and Biotechnology : HEB
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• v.59 no.6
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• pp.919-927
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• 2018

To compare the antioxidant properties and flavonols in various parts; dry skin (DS) and edible portion (EP), of 8 red onions (Allium cepa L, ROs), total content of phenolics (TPC), flavonoids (TFC), and anthocyanins (TAC) and DPPH radical scavenging properties were estimated and the content of six flavonols were quantified by HPLC-PDA analysis. The major component of DS and EP of RO was quercetin and quercetin-4'-glucoside, respectively. Score plots of the PCA and PLS-DA were segregated by flavonols content and antioxidant properties according to the EP and DS of ROs. Loading plot of the PCA showed that the quercetin and sum of flavonol content were highly correlated with antioxidant activity of ROs. Therefore, flavonol content and antioxidant activity can be used as markers for distinct parts of ROs.