• Food Science of Animal Resources
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• v.38 no.2
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• pp.362-375
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• 2018

This study proposed a rapid microscopic examination method for pork freshness evaluation by using the self-assembled hyperspectral microscopic imaging (HMI) system with the help of feature extraction algorithm and pattern recognition methods. Pork samples were stored for different days ranging from 0 to 5 days and the freshness of samples was divided into three levels which were determined by total volatile basic nitrogen (TVB-N) content. Meanwhile, hyperspectral microscopic images of samples were acquired by HMI system and processed by the following steps for the further analysis. Firstly, characteristic hyperspectral microscopic images were extracted by using principal component analysis (PCA) and then texture features were selected based on the gray level co-occurrence matrix (GLCM). Next, features data were reduced dimensionality by fisher discriminant analysis (FDA) for further building classification model. Finally, compared with linear discriminant analysis (LDA) model and support vector machine (SVM) model, good back propagation artificial neural network (BP-ANN) model obtained the best freshness classification with a 100 % accuracy rating based on the extracted data. The results confirm that the fabricated HMI system combined with multivariate algorithms has ability to evaluate the fresh degree of pork accurately in the microscopic level, which plays an important role in animal food quality control.

• Korean Journal of Food Science and Technology
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• v.47 no.1
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• pp.20-26
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• 2015

This study aimed to establish a rapid system for discriminating the cultivation origins and cultivars of dry persimmons, using metabolite fingerprinting by Fourier transform infrared (FT-IR) spectroscopy combined with multivariate analysis. Whole-cell extracts from the sepals of four Korean cultivars and two different Chinese dry persimmons were subjected to FT-IR spectroscopy. Principle component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) of the FT-IR spectral data successfully discriminated six dry persimmons into two groups depending on their cultivation origins. Principal component loading values showed that the 1750-1420 and $1190-950cm^{-1}$ regions of the FT-IR spectra were significantly important for the discrimination of cultivation origins. The accuracy of prediction of the cultivation origins and cultivars by PLS regression was 100% (p<0.01) and 85.9% (p<0.05), respectively. These results clearly show that metabolic fingerprinting of FT-IR spectra can be applied for rapid discrimination of the cultivation origins and cultivars of commercial dry persimmons.

• Korean Journal of Plant Resources
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• v.31 no.6
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• pp.641-651
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• 2018

Floral scents and metabolites from cut flowers of 14 peony cultivars (Paeonia lactiflora Pall.) were analyzed to discriminate different cultivars and to compare the Korean cultivar with the other cut peonies imported to Korea using electronic nose (E-nose) and Fourier transform infrared (FT-IR) spectroscopy combined with multivariate analysis, respectively. Principal component analysis (PCA) and discriminant function analysis (DFA) dendrogram of peony floral scents were not precisely same but there were 3 groups including same cultivars. PCA and partial least squares-discriminant analysis (PLS-DA) dendrograms of peony metabolites showed that different cut peony cultivars were clustered into two major groups including same cultivars. Fragrance pattern of Korean 'Taebaek' was classified to same group with 'Jubilee' on the PCA and DFA results and its metabolite pattern was clearly discriminated by the PCA and PLS-DA compared to the other cultivars. These results show that the 14 peony cut flowers could be discriminated corresponding to their chemical relationship and the metabolic profile of Korean 'Taebaek' has distinctive characteristics. Furthermore, we suggest that these results could be used as the preliminary data for breeding new cut peony cultivars and for improving the availability of Korean cut peony in cosmetic industry.

• Korean Journal of Food Science and Technology
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• v.26 no.6
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• pp.750-758
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• 1994

Flavour components of seven Korean folk sojues, five Chinese kaoliangchiews and Japanese shochu were determined by GC and GC-MS after solid phase extraction with polydivinyl benzene. Less volatile ethyl succinate and ethyl pelargonate were present in Korean folk sojues while volatile ethyl acetate and ethyl butyrate in Chinese kaoliangchiews. In the case of alcohols, the amount of isopentyl alcohol was relatively higher than that of isobutyl alcohol or n-propyl alcohol in Korean folk sojues. On the contrary, less volatile n-propyl alcohol was present more than isopentyl alcohol in Chinese kaoliangchiews. Multivariate statistical analyses involving principal components analysis (PCA) and discriminant analysis (DA) were applied to the GC data. The results of PCA clearly demonstrate that the first principal scores of Korean folk sojues were similar but the second principal scores were different from each other. Classification of Korean sojues and Chinese kaoliangchiews into two groups could be conducted by DA. These results suggested that the common charateristics and identities as a distilled liquors was found in Korean folk sojues.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.3
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• pp.173-177
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• 2001

This study was conducted to investigate a potential utilitization of multivariate statistical analysis(Factor analysis, Discrimination analysis) on interpretation of rice plant lodging reason. Rice plants were sampled in paddy around Taegu city at from 25 to 29 of September in 2000. Mineral nutrient content(phosphate, potassium) of rice plant were significantly higher at 99% level, Silicate content were lower at 95% level in lodged samples than in normal. Plant characteristics associate with lodging(Culm length, second and third internode length, bight of center gravity) were significantly longer in lodged rice plant than in non lodged. Result of Factor analysis were that first principle component were culm length, second(N2) and third internode length(N3), second principle component were Ca content, first internode length(N1) and N3/culm length, third principle component were center gravity length(G) and G/culm length, fourth were nitrogen, phosphate, and potassium content, fifth were N2/culm length, N2+N3/culm length, Sixth was silicate content of rice plant. Linear discriminant equation distinguished lodged rice plants with non lodged rice plants very well. Prediction value was 100%, most explainable variable were phosphate content, culm length and third length.

• Animal Systematics, Evolution and Diversity
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• v.11 no.2
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• pp.183-197
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• 1995

Description and identifications of 6 species belonging to genus Phintella from Korea are in insufficient and inaccurate situation. In the present paper, redescriptions illustrations and identification key are provided for 7 species of genus Phintella including P. popovi newly recorded in Korean spider fauna, and Ocius munitus described by Wesolowska (1981s) was synonymized to P.cavaleriei. For the author's identiication and pairing to be valid multivariate analysis was performed with 13 RVCs below STD 0.05 to 134 individuals. The result of discriminant analysis carried out with 13 RVCs of 134 individuals was not satisfactory, but cluster analysis performed with mean ratio values of 14 OTUs to 13 RVCs showed the same result with author's pairing except P.abnormis , which has larger dissimilarity than the pairs of the others. So pairing of 7 species was possible as a whole because one species only failed in pairing , even though this is imperful result. This method to be helpful to pairing test and identification if it were to improve.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.23-23
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• 2017

Recent favor on high quality food and concern on food safety have demonstrated the superiority of Hanwoo (Korean native cattle). In general, the price of cow is higher than those of steer and bull, causing cheating issues in the market. Hence, this study is to discriminate genders of Hanwoo with identification of factors which highly influence gender discrimination based on the big-size deboning data. Totally, there were 31 variables in the deboning data, and we divided into them two categories: data obtained before and after deboning. Discriminant function analysis was then applied into the data to determined the accuracy of gender discrimination in Hanwoo. The result showed that Hanwoo could be classified by gender with 99.2% of accuracy when using all 31 variables. In detail, it was possible to identify 93 of 94 bulls (98.9%), 96 of 96 cows (100%) and 74 of 75 steers (98.7%). The most significant variables was chuck, sirloin, armbone shin, plates, retail and cuts percentage, sequentially. With variables obtainable before deboning, accuracies of classification were 91.5% for bulls, 92.7% for cows, and 89.3% for steers. The most significant variables was water, cold carcass weight and back-fat thickness. The discrimination accuracy was higher with data obtainable after deboning: bulls (98.9%), cows (99.0%) and steers (98.7%). In this case, chuck, sirloin and armbone shin were the factors determined the classification ability. This study showed that Hanwoo can be classified based on deboning data with appropriate statistics, further suggesting weight of cut of beef might be the standard for gender classification.

• Journal of the Korean Wood Science and Technology
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• v.48 no.5
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• pp.591-607
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• 2020

This study was aimed to investigate the changes of chemical composition of the volatile organic compounds (VOCs) emitted from red pine needles in the process of needle abscission or senescence. The VOCs in intact, senescent, and litter red pine needle samples were analyzed by headspace-solid phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC/MS). And then, multivariate statistical interpretation of the processed data sets was conducted to investigate similarities and dissimilarities of the needle samples. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to investigate the dataset structure and discrimination between samples, respectively. From the data preview, the levels of major components of VOCs from needles were not significantly different between needle samples. By PCA investigation, the data reduction according to classification based on the chlorophyll a / chlorophyll b (Ca/Cb) ratio were found to be ideal for differentiating intact, senescent, and litter needles. The following OPLS-DA taking Ca/Cb ratio as y-variables showed that needle samples were well grouped on score plot and had the significant discriminant compounds, respectively. Several compounds had significantly correlated with Ca/Cb ratio in a bivariate correlation analysis. Notably, the litter needles had a higher content of oxidized compounds than the intact needles. In summary, we found that chemical compositions of VOCs between intact, senescent, and litter needles are different each other and several compounds reflect characteristic of needle.

• Journal of Korean Society of Forest Science
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• v.105 no.2
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• pp.157-166
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• 2016

This study was carried out to classify the current forest cover types and to propose the successional trends in the natural forest of Mt. Deogyu. The vegetation data were collected by the point-centered quarter method. The forest cover types were classified by various multivariate statistical analysis methods such as cluster analysis, indicator species analysis and multiple discriminant analysis. This forests were classified into five forest types by the species composition of upper layer and topographic positions: Quercus mongolica forest in the ridge, Fraxinus mandushurica-F. rhynchophylla-Cornus controversa forest and F. mandushurica forest in the valley, the Q. serrata - Pinus densiflora - Q. mongolica forest and P. densiflora forest in the low-slope. As a result of the forest successional trends depending on ecological and environmental characteristics in each forest type, the current forest types were expected that the forest succession would be proceeded toward Q. mongolica forest, F. mandshurica forest, mixed mesophytic forest, and oak-Carpinus laxiflora forest.

• Food Science of Animal Resources
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• v.41 no.2
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• pp.312-323
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• 2021

The purpose of this study was to use 1H nuclear magnetic resonance (1H NMR) to quantify taste-active and bioactive compounds in chicken breasts and thighs from Korean native chicken (KNC) [newly developed KNCs (KNC-A, -C, and -D) and commercial KNC-H] and white-semi broiler (WSB) used in Samgye. Further, each breed was differentiated using multivariate analyses, including a machine learning algorithm designed to use metabolic information from each type of chicken obtained using 1H-13C heteronuclear single quantum coherence (2D NMR). Breast meat from KNC-D chickens were superior to those of conventional KNC-H and WSB chickens in terms of both taste-active and bioactive compounds. In the multivariate analysis, meat portions (breast and thigh) and chicken breeds (KNCs and WSB) could be clearly distinguished based on the outcomes of the principal component analysis and partial least square-discriminant analysis (R2=0.945; Q2=0.901). Based on this, we determined the receiver operating characteristic (ROC) curve for each of these components. AUC analysis identified 10 features which could be consistently applied to distinguish between all KNCs and WSB chickens in both breast (0.988) and thigh (1.000) meat without error. Here, both 1H NMR and 2D NMR could successfully quantify various target metabolites which could be used to distinguish between different chicken breeds based on their metabolic profile.