• Korean Journal of Food Science and Technology
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• v.38 no.6
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• pp.835-837
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• 2006

The geographical origin of Tricholoma matsutake mushrooms was studied using near-infrared spectroscopy. Modified partial least-square regression analyses were used to discriminate geographical origin. Two-hundred fifty-six of 259 actual domestic Tricholoma matsutake were classified as domestic produce, Sixty of 81 actual imported mushrooms were correctly classified as imported, while the other 21 imported from North Korea were not clearly classified. The accuracy of geographical origin discrimination was 92.94% The correlation coefficient, standard error of calibration, and standard error of prediction from modified partial least-square regression analysis were 0.84, 15.10% and 18.30% respectively.

• Journal of Biosystems Engineering
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• v.35 no.6
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• pp.450-457
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• 2010

Although cherry tomato is one of major vegetables consumed in fresh vegetable market, the quality grading method is mostly dependant on size measurement using drum shape sorting machines. Using Visible/Near-infrared spectroscopy, apparatus to be able to acquire transmittance spectrum data was made and used to estimate firmness, sugar content, and acidity of cherry tomatoes grown at hydroponic and soil culture. Partial least square (PLS) models were performed to predict firmness, sugar content, and acidity for the acquired transmittance spectra. To enhance accuracy of the PLS models, several preprocessing methods were carried out, such as normalization, multiplicative scatter correction (MSC), standard normal variate (SNV), and derivatives, etc. The coefficient of determination ($R^2_p$) and standard error of prediction (SEP) for the prediction of firmness, sugar, and acidity of cherry tomatoes from green to red ripening stages were 0.859 and 1.899 kgf, with a preprocessing of normalization, 0.790 and $0.434^{\circ}Brix$ with a preprocessing of the 1st derivative of Savitzky Golay, and 0.518 and 0.229% with a preprocessing normalization, respectively.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1117-1128
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• 2016

In genetic association studies with high-dimensional genomic data, regularization procedures based on penalized likelihood are often applied to identify genes or genetic regions associated with diseases or traits. A network-based regularization procedure can utilize biological network information (such as genetic pathways and signaling pathways in genetic association studies) with an outstanding selection performance over other regularization procedures such as lasso and elastic-net. However, network-based regularization has a limitation because cannot be applied to high-dimension genomic data with a group structure. In this article, we propose to combine data dimension reduction techniques such as principal component analysis and a partial least square into network-based regularization for the analysis of high-dimensional genomic data with a group structure. The selection performance of the proposed method was evaluated by extensive simulation studies. The proposed method was also applied to real DNA methylation data generated from Illumina Innium HumanMethylation27K BeadChip, where methylation beta values of around 20,000 CpG sites over 12,770 genes were compared between 123 ovarian cancer patients and 152 healthy controls. This analysis was also able to indicate a few cancer-related genes.

• Food Science and Biotechnology
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• v.14 no.2
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• pp.280-285
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• 2005

Applicability of near infrared reflectance spectroscopy (NIRS) was examined for quality control of red pepper powder in milling factories. Prediction of chemical composition was performed using modified partial least square (MPLS) techniques. Analysis of total 51 and 21 red pepper powder samples by conventional methods for calibration and validation, respectively, revealed standard error of prediction (SEP) and correlation coefficient ($R^2$) of moisture content, ASTA color value, capsaicinoid content, and total sugar content were 0.55 and 0.90, 8.58 and 0.96, 31.60 and 0.65, and 1.82 and 0.86, respectively; SEP and $R^2$ were low and high, respectively, except for capsaicinoid content. The results indicate, with slight improvement, on-line quality measurement of red pepper powder with NIRS could be applied in red pepper milling factories.

• 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 Convergence Society for SMB
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• v.4 no.3
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• pp.7-13
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• 2014

In recent years, according to the increasing of information security compliance, information security management system's requirements is not a matter of choice but an essential problem. In this respect, this research have an invention to survey what it will affect employees in compliance with the privacy policy antecedents and how to apply this information for the future, and to suggest ways to improve the employees' information security policy compliance intentions. In this paper, To investigate the factors affecting the degree of information security policy compliance using the structural equation of least squares (PLS Partial Least Square) in the confumatory level (confirmatory), the factor analysis of the primary factor analysis and secondary last. The results is that almost of influencing factors affect to the compliance with information security policies directly, but not affect self-efficacy.

• Journal of the East Asian Society of Dietary Life
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• v.22 no.6
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• pp.836-850
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• 2012

This study was conducted to identify the sensory characteristics of the Korean traditional confectionery, dasik, prepared under different conditions and to compare their consumer acceptance in Korea. To accomplish this, descriptive analysis of eight samples prepared using two types of rice cake powder, dasik (Rflour, Rflour_Omija), brown rice powder red ginseng dasik (Brice_Ginseng_P), pinepollen dasik (PineP), black sesame dasik (BSesame), bean dasik (Rbean), and two types of mungbean starch dasik (Starch_Omija, Starch_Greentea), was conducted by ten trained panelists. In addition, 81 consumers evaluated the overall acceptance (OL), acceptance of appearance (APPL), odor (ODL), flavor (FLL), and texture (TXTL) of the samples using a 9-point hedonic scale, as well as the perceived intensities of sesame flavor, sweetness, and hardness using a 9-point just-about-right (JAR) scale. Partial least square- regression (PLSR) indicated that the BSesame and Rbean samples, which had significantly (p<0.05) high roasted sesame, burnt, greasy, glossy, and cooked chestnut flavor scores, had the highest acceptability and consumer desire scores. Additionally, the PineP and Rflour_Omija samples, which had relatively high particle size, transparency, roughness, spoiled tofu, fermentation and raw rice flavor scores, were the least preferred samples. Therefore, roasted sesame, burnt, greasy, glossy, and cooked chestnut flavor attributes were considered drivers of "liking" whereas particle size, transparent, roughness, spoiled tofu, fermentation, and raw rice flavor attributes acted as drivers of "disliking" among consumers.

• Journal of Plant Biotechnology
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• v.38 no.1
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• pp.9-14
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• 2011

To determine whether pattern recognition based on metabolite fingerprinting for whole cell extracts can be used to discriminate cultivars metabolically, leaves of nine commercial Orostachys plants were subjected to Fourier transform infrared spectroscopy (FT-IR). FT-IR spectral data from leaves were analyzed by principal component analysis (PCA) and Partial least square discriminant analysis (PLS-DA). The dendrogram based on hierarchical clustering analysis of these PLS-DA data separated the nine Orostachys species into five major groups. The first group consisted of O. iwarenge 'Yimge', 'Jeju', 'Jeongsun' and O. margaritifolius 'Jinju' whereas in the second group, 'Sacheon' was clustered with 'Busan,' both of which belong to O. malacophylla species. However, 'Samchuk', belong to O. malacophylla was not clustered with the other O. malacophylla species. In addition, O. minuta and O. japonica were separated to the other Orostachys plants. Thus we suggested that the hierarchical dendrogram based on PLS-DA of FT-IR spectral data from leaves represented the most probable chemotaxonomical relationship between commercial Orostachys plants. Furthermore these metabolic discrimination systems could be applied for reestablishment of precise taxonomic classification of commercial Orostachys plants.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.1
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• pp.35-44
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• 2016

Seed viability is one of the most important parameters that is directly related with seed germination performance and seedling emergence. In this study, a hyperspectral imaging (HSI) system having a range of 1000-2500 nm was used to classify viable watermelon seeds from nonviable seeds. In order to obtain nonviable watermelon seeds, a total of 96 seeds were artificially aged by immersing the seeds in hot water ($25^{\circ}C$) for 15 days. Further, hyperspectral images for 192 seeds (96 normal and 96 aged) were acquired using the developed HSI system. A germination test was performed for all the 192 seeds in order to confirm their viability. Spectral data from the hyperspectral images of the seeds were extracted by selecting pixels from the region of interest. Each seed spectrum was averaged and preprocessed to develop a classification model of partial least square discriminant analysis (PLS-DA). The developed PLS-DA model showed a classification accuracy of 94.7% for the calibration set, and 84.2% for the validation set. The results demonstrate that the proposed technique can classify viable and nonviable watermelon seeds with a reasonable accuracy, and can be further converted into an online sorting system for rapid and nondestructive classification of watermelon seeds with regard to viability.

• Journal of the Society of Disaster Information
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• v.16 no.3
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• pp.513-525
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• 2020

Purpose: The purpose of this study is to analyze the characteristics of local factors affecting number of tuberculosis death by urban and rural areas. Method: The Partial Least Square(PLS) Regression analysis was used to solve the problem of multicollinearity and number of samples. Result: As a result of analysis, The number of tuberculosis deaths in urban and rural areas is about three times as large. As a result of analysis about Regional Characteristics Factor, In general, children, elderly people, and economically vulnerable populations are more likely to be exposed to tuberculosis. In differential results, it shows that environmental factors such as ultrafine dust and sulfur dioxide have a significant impact on the number of tuberculosis deaths in urban areas and social factors such as depression experience rate in rural areas. Conclusion: The Tuberculosis prevention and management policies that reflect the characteristics of urban and rural areas are needed in the future.