• Korean Journal of Breeding Science
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• v.40 no.4
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• pp.361-370
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• 2008

In order to better understand the morphological differentiation of the two cultivated types of Perilla crop and their weedy types in Korea and Japan, we studied the variation of 62 accessions by examining 15 morphological characteristics. By using ANOVA (one-way analysis of variance), we determined that var. frutescens and var. crispa showed significant morphological differences in terms of plant height and seed weight. Furthermore, cultivated var. frutescens and var. crispa could also be clearly discriminated from one another using PCA (principal component analysis). Specifically, quantitative and qualitative characteristics such as plant height, seed weight, degree of pubescence, shape of leaf, color of leaf, fragrance of plant, color of flower, color of stem and seed size greatly contributed to differences seen in the positive and negative direction on the first axis. In our study, most accessions of cultivated var. frutescens and those of its weedy type could be clearly discriminated from one another, however, most accessions of cultivated and weedy types of var. crispa were not clearly discriminated by the ANOVA and PCA analyses. These results indicated that cultivated var. frutescens can be considered to be a domesticated form, while the cultivated var. crispa can not be considered to be a domesticated form in Korea and Japan. It is our belief that our results concerning the morphological variations among cultivated types of Perilla crop and their weedy types in Korea and Japan will help ensure the long-term success of breeding programs and maximize the use of the germplasm resources in Korea.

• Journal of Korean Medicine for Obesity Research
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• v.21 no.2
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• pp.80-94
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• 2021

Objectives: The purpose of this study is to re-evaluate the importance of questions of obesity syndrome differentiation (OSD) questionnaire based on real-world survey and to explore the possibility of simplifying OSD types. Methods: The OSD frequency was identified, and variance threshold feature selection was performed to filter the questions. Filtered questions were clustered by K-means clustering and hierarchical clustering. After principal component analysis (PCA), the distribution patterns of the subjects were identified and the differences in the syndrome distribution were compared. Results: The frequency of OSD in spleen deficiency, phlegm (PH), and blood stasis (BS) was lower than in food retention (FR), liver qi stagnation (LS), and yang deficiency. We excluded 13 questions with low variance, 7 of which were related to BS. Filtered questions were clustered into 3 groups by K-means clustering; Cluster 1 (17 questions) mainly related to PH, BS syndromes; Cluster 2 (11 questions) related to swelling, and indigestion; Cluster 3 (11 questions) related to overeating or emotional symptoms. After PCA, significant different patterns of subjects were observed in the FR, LS, and other obesity syndromes. The questions that mainly affect the FR distribution were digestive symptoms. And emotional symptoms mainly affect the distribution of LS subjects. And other obesity syndrome was partially affected by both digestive and emotional symptoms, and also affected by symptoms related to poor circulation. Conclusions: In-depth data mining analysis identified relatively low importance questions and the potential to simplify OSD types.

• Food Science and Preservation
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• v.30 no.4
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• pp.573-588
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• 2023

The purpose of this study was to monitor changes in the quality of ginseng and predict its shelf-life. As the storage period of ginseng increased, some quality indicators, such as water-soluble pectin (WSP), CDTA-soluble pectin (CSP), cellulose, weight loss, and microbial growth increased, while others (Na₂CO₃-soluble pectin/NSP, hemicellulose, starch, and firmness) decreased. Principal component analysis (PCA) was performed using the quality attribute data and the principal component 1 (PC1) scores extracted from the PCA results were applied to the multivariate analysis. The reaction rate at different temperatures and the temperature dependence of the reaction rate were determined using kinetic and Arrhenius models, respectively. Among the kinetic models, zeroth-order models with cellulose and a PC1 score provided an adequate fit for reaction rate estimation. Hence, the prediction model was constructed by applying the cellulose and PC1 scores to the zeroth-order kinetic and Arrhenius models. The prediction model with PC1 score showed higher R² values (0.877-0.919) than those of cellulose (0.797-0.863), indicating that multivariate analysis using PC1 score is more accurate for the shelf-life prediction of ginseng. The predicted shelf-life using the multivariate accelerated shelf-life test at 5, 20, and 35℃ was 40, 16, and 7 days, respectively.

• Journal of Korean Society on Water Environment
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• v.35 no.1
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• pp.19-27
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• 2019

The purpose of this study is to evaluate the water quality and phytoplankton community in Bukhan River which account for 44.4 % of the total inflow into Lake Paldang, using multivariate statistical techniques (i.e., correlation analysis, principal component analysis (PCA)/factor analysis (FA)). Water samples were collected from March to November 2015 and the following parameters measured; water temperature, pH, DO, EC, SS, BOD, Chl-a, COD, TN, $NO_3-N$, $NH_3-N$, TP, DTP, $PO_4-P$, and phytoplankton community. The water quality of the main stream and the tributaries were not significantly different apart from the relatively high concentration of BOD, COD and nutrients recorded in MH. The highest cell density of Stephanodiscus hantzschii and Merismopedia glauca dominated phytoplankton was observed in PD. Based on the correlation analysis, total phytoplankton and cyanophyceae were highly correlated with BOD, COD and nutrients. PCA/FA resulted in four main factors accounting for 82.240 % of the total variance in the water quality dataset. The group of component 1 (TN, DTN, DO, $NO_3-N$, water temperature) and component 2 ($PO_4-P$, T-P, DTP, SS) were classified as nutrient element factor whereas component 3 (Chl-a, COD, BOD, $NH_3-N$, pH) was related to organic substances. Hence, the identification of the main potential environmental pollution factors in Bukhan River will help policy makers make better and more informed decisions on how to improve the water quality.

• Journal of the Korean Society of Food Culture
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• v.37 no.3
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• pp.239-247
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• 2022

This study evaluated the sensory characteristics of sauerkraut prepared by adding 0.5, 1.0, 1.5, 2.0, and 2.5% (w/w) sea salt to cabbage. The quantitative descriptive analysis (QDA) and acceptance test of sauerkraut were determined for each salt concentration, and the principal component analysis (PCA) and partial least square regression (PLSR) analysis were performed to confirm the correlation between each factor. Results of the QDA determined 14 descriptive terms; furthermore, brightness and yellowness of appearance and the sour, salty, and bitter flavors differed significantly according to the salt concentration. Results from the PCA explained 22.56% PC1 and 65.34% PC2 of the total variation obtained. Sauerkraut prepared using 0.5, 1.0, and 1.5% sea salt had high brightness, moistness, sour odor, green odor, sour flavor, carbonation, hardness, chewiness, and crispness, whereas sauerkraut prepared with 2.0 and 2.5% sea salt had high yellowness, glossiness, salty flavor, sweet flavor, and bitter flavor. Hierarchical cluster analysis classified the products into two clusters: sauerkraut of 0.5, 1.0, and 1.5%, and sauerkraut of 2.0 and 2.5%. Results of PLSR determined that sauerkraut of 1.0 and 1.5% were the closest to texture, taste, and overall acceptance. We, therefore, conclude that sauerkrauts prepared using 1.0 and 1.5% sea salt have excellent characteristics in appearance, taste, and texture.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.33-40
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• 2005

The aim of remotely sensed data classification is to produce the best accuracy map of the earth surface assigning each pixel to its appropriate category of the real-world. The classification of satellite multi-spectral image data has become tool for generating ground cover map. Many classification methods exist. In this study, MLC(Maximum Likelihood Classification), ANN(Artificial neural network), SVM(Support Vector Machine), Naive Bayes classifier algorithms are compared using IKONOS image of the part of Dalsung Gun, Daegu area. Two preprocessing methods are performed-PCA(Principal component analysis), ICA(Independent Component Analysis). Boosting algorithms also performed. By the combination of appropriate feature selection pre-processing and classifier, the best results were obtained.

• 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.

• The Journal of Asian Finance, Economics and Business
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• v.2 no.3
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• pp.5-15
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• 2015

This research paper has been attempted to inventory the atmospheric factors, contributing to better sales. Exploratory study was undertaken to identify various signs of store atmospherics variables that influence the buying behaviour of buyers. Thirty-four variables identified from this study were used to create a structured questionnaire. This questionnaire was then administered among shoppers in NCR Delhi using non-probability convenience sampling. To determine the atmospheric factors, Principal Component Analysis (PCA) along with Varimax Rotation was attempted. Using principal component factor analysis on the data collected, nine factors were identified to have impact on the store atmospheric. These were Querulous, Music, Sensitive, Budget Seeker, Sensuous, Light, Idler, Space seeker and Comfort Seeker. Contrary to the various earlier studies where music, space seeker and comfort seeker were considered to be most significant factors, light and querulous have emerged out to be the major factor that influences the store atmospheric. This study shows that customers are sensitive, space seekers and sensuous. Constituents of these factors reveal distinct patterns. This research may be used as guidelines for development and management of shopping malls in emerging countries. Retail marketers in India can take this cue in designing their strategies to attract consumers.

• Journal of Korea Multimedia Society
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• v.17 no.1
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• pp.34-42
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• 2014

In this paper an embedding algorithm based on commute time is implemented by organizing patches according to the graph-based metric, and its performance is analyzed by comparing with the results of principal component analysis embedding. It is usual that the dimensionality reduction be done within some acceptable approximation error. However this paper shows the proposed manifold embedding method generates the intrinsic geometry corresponding to the signal despite severe approximation error, so that it can be applied to the areas such as pattern classification or machine learning.

• Korean Journal of Pharmacognosy
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• v.44 no.3
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• pp.235-241
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• 2013

Aucklandia lappa Decne (Compositae) has been used for treatment of abdominal pain, vomiting, diarrhea, chronic inflammation, and antibacterial effect. The quality of these herbs has been affected by many factors such as collection time, place, temperature, cultivation environment and manufacturing process. We used costunolide and dehydrocostuslactone as marker compounds for quality evaluation of rhizome of Aucklandia lappa. 66 samples of Aucklandia lappa were collected from those habitats in Korea and China. The developed HPLC-DAD method was applied to investigate for quality control of Aucklandia lappa samples. The average contents of the costunolide and dehydrocostuslactone were 2.3895% and 0.9258%, respectively. The principal component analysis (PCA) exhibited that classification of Aucklandia lappa according to origin not separated. Results of this study may be satisfactory applied to determination of content criteria of Aucklandia lappa.