• Asian-Australasian Journal of Animal Sciences
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• v.18 no.5
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• pp.643-648
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• 2005

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid, accurate method of evaluating some chemical constituents in cereal grains and forages. If samples could be analyzed without drying and grinding, then sample preparation time and costs may be reduced. This study was conducted to develop robust NIRS equations to predict fermentation quality of corn (Zea mays) silage and to select acceptable sample preparation methods for prediction of fermentation products in corn silage by NIRS. Prior to analysis, samples (n = 112) were either oven-dried and ground (OD), frozen in liquid nitrogen and ground (LN) and intact fresh (IF). Samples were scanned from 400 to 2,500 nm with an NIRS 6,500 monochromator. The samples were divided into calibration and validation sets. The spectral data were regressed on a range of dry matter (DM), pH and short chain organic acids using modified multivariate partial least squares (MPLS) analysis that used first and second order derivatives. All chemical analyses were conducted with fresh samples. From these treatments, calibration equations were developed successfully for concentrations of all constituents except butyric acid. Prediction accuracy, represented by standard error of prediction (SEP) and $R^2_{v}$ (variance accounted for in validation set), was slightly better with the LN treatment ($R^2$ 0.75-0.90) than for OD ($R^2$ 0.43-0.81) or IF ($R^2$ 0.62-0.79) treatments. Fermentation characteristics could be successfully predicted by NIRS analysis either with dry or fresh silage. Although statistical results for the OD and IF treatments were the lower than those of LN treatment, intact fresh (IF) treatment may be acceptable when processing is costly or when possible component alterations are expected.

• Information Systems Review
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• v.16 no.3
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• pp.89-112
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• 2014

This tutorial presents an approach to perform the PLS structural equation modeling using the R. For this purpose, the practical guide defines the criteria for the PLS structural equation modeling by reviewing previous studies, and shows how to analyze the research model with an example using the "plspm" which is the R package for the performing PLS path analysis against the criteria. This practical guide will be useful for the study of the PLS model analysis for new researchers and will provide the knowledge base for in-depth analysis through the new PLS structural equation modeling technique using R which is the integrated statistical software operating environment for the researchers familiar with the PLS structural equation modeling.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.12
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• pp.1948-1956
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• 2020

Objective: The purpose of this study was to reveal the metabolic shift in the fungus cocultured with the methanogen (Methanobrevibacter thaueri). Methods: Gas chromatography-mass spectrometry was used to investigate the metabolites in anaerobic fungal (Pecoramyces sp. F1) cells and the supernatant. Results: A total of 104 and 102 metabolites were detected in the fungal cells and the supernatant, respectively. The partial least squares-discriminant analysis showed that the metabolite profiles in both the fungal cell and the supernatant were distinctly shifted when co-cultured with methanogen. Statistically, 16 and 30 metabolites were significantly (p<0.05) affected in the fungal cell and the supernatant, respectively by the co-cultured methanogen. Metabolic pathway analysis showed that co-culturing with methanogen reduced the production of lactate from pyruvate in the cytosol and increased metabolism in the hydrogenosomes of the anaerobic fungus. Citrate was accumulated in the cytosol of the fungus co-cultured with the methanogen. Conclusion: The co-culture of the anaerobic fungus and the methanogen is a good model for studying the microbial interaction between H₂-producing and H₂-utilizing microorganisms. However, metabolism in hydrogenosome needs to be further studied to gain better insight in the hydrogen transfer among microorganisms.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.1
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• pp.79-90
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• 2020

Objective: In the present study, an liquid chromatography/mass spectrometry (LC/MS) metabolomics approach was performed to investigate potential biomarkers of milk production in high- and low-milk-yield dairy cows and to establish correlations among rumen fluid metabolites. Methods: Sixteen lactating dairy cows with similar parity and days in milk were divided into high-yield (HY) and low-yield (LY) groups based on milk yield. On day 21, rumen fluid metabolites were quantified applying LC/MS. Results: The principal component analysis and orthogonal correction partial least squares discriminant analysis showed significantly separated clusters of the ruminal metabolite profiles of HY and LY groups. Compared with HY group, a total of 24 ruminal metabolites were significantly greater in LY group, such as 3-hydroxyanthranilic acid, carboxylic acids, carboxylic acid derivatives (L-isoleucine, L-valine, L-tyrosine, etc.), diazines (uracil, thymine, cytosine), and palmitic acid, while the concentrations of 30 metabolites were dramatically decreased in LY group compared to HY group, included gentisic acid, caprylic acid, and myristic acid. The metabolite enrichment analysis indicated that protein digestion and absorption, ABC transporters and unsaturated fatty acid biosynthesis were significantly different between the two groups. Correlation analysis between the ruminal microbiome and metabolites revealed that certain typical metabolites were exceedingly associated with definite ruminal bacteria; Firmicutes, Actinobacteria, and Synergistetes phyla were highly correlated with most metabolites. Conclusion: These findings revealed that the ruminal metabolite profiles were significantly different between HY and LY groups, and these results may provide novel insights to evaluate biomarkers for a better feed digestion and may reveal the potential mechanism underlying the difference in milk yield in dairy cows.

• The Journal of Information Systems
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• v.26 no.3
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• pp.91-118
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• 2017

Purpose The purpose of this research is to investigate the effect of social capitals on organizational knowledge sharing characteristics and individual innovation activities in community of practice (CoP) of manufacturing company. Design/methodology/approach For this purpose, we divide social capitals as three dimensions, i.e. structural, relational, and cognitive dimension. Structural dimension also consists of closure and Brokerage. Relational social capital is defined as trust about colleagues, superior authorities, and organization. Then, cognitive social capital is defined as a shared understanding among individuals, such as a shared language and codes within CoP. Knowledge Sharing is defined as quantity and quality of shared knowledge. We also defines the cause and effect relationships among social capitals, organizational knowledge sharing characteristics, and individual innovation activities in CoP of manufacturing company as follows. The social capitals will have positive effects on quality of shared knowledge. Then the quality of shared knowledge will have positive effects on the individual innovation activities. This paper tested the validity of these hypothesized casual effects and the sub-hypothesized causal relationships. For the purpose, we used the Partial Least Squares (PLS) for analyzing the causal relationships. Findings Our empirical results show that social capitals of CoP mostly have effects on organizational knowledge sharing characteristics (quantity and quality of shared knowledge) and knowledge sharing activities also have effects on individual innovative activities in the workplace. In this study, these result have a significant implication that a private company will be able to gain organizational innovative performance much better by strengthening CoP supporting activities.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.6
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• pp.107-119
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• 2015

Recently, middle and low social class entered in the upper class for the specific reasons and joined reference group in order to present demonstration effect. This phenomenon was assumed the consumer's desire for housing estate not from the leisure class. The superiority which feels belong to reference group, that was able to purchase high price product and the competence which can afford a high price goods are effective in housing estate. The study had been researched for Veblen effect according to residence estate. The partial least squares path modeling was used for Veblen effect affected by various psychological attributes, housing patterns and demographics for analysis. As a result, the conspicuous consumption from tenants was higher than residents, the social face sensitivity affected positively for self esteem and housing pattern, therefore, it caused conspicuous consumption. Moreover, we found conspicuous consumption had been increased followed by more spacious housing and higher income.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.5
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• pp.401-406
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• 2001

The applicability of non-destructive near infrared reflectance spectroscopic (NIRS) method was tested to determine the protein and oil contents of intact soybean [Glycine max (L.) Merr.] seeds. A total of 198 soybean calibration samples and 101 validation samples were used for NIRS equation development and validation, respectively. In the developed non-destructive NIRS equation for analysis of protein and oil contents, the most accurate equation was obtained at 2, 8, 6, 1(2nd derivative, 8 nm gap, 6 points smoothing, and 1 point second smoothing) and 2, 1, 20, 10 math treatment conditions with Standard Normal Variate and Detrend (SNVD) scatter correction method and entire spectrum (400-2500 nm) by using Modified Partial Least Squares (MPLS) regression, respectively. Validation of these non-destructive NIRS equations showed very low bias (protein: 0.060%, oil: -0.017%) and standard error of prediction (SEP, protein: 0.568 %, oil : 0.451 %) as well as high coefficient of determination ($R^2$, protein: 0.927, oil: 0.906). Therefore, these non-destructive NIRS equations can be applicable and reliable for determination of protein and oil content of intact soybean seeds, and non-destructive NIRS method could be used as a mass screening technique for selection of high protein and oil soybean in breeding programs.

• The Journal of the Korea Contents Association
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• v.15 no.12
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• pp.387-406
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• 2015

Recently emotional labor is an essential situation for hospital employees in relation to surface and deep acting as the core of emotional labor strategies. This study empirically examines the relation between hospital employees' emotional intelligence and emotional labor strategies in the context of emotional labor. For empirical experiments, we conducted a questionnaire survey targeting hospital employees, and we employed the method of Partial Least Squares (PLS) for data analysis. Major findings are as follows. Hospital employees' emotional intelligence including self emotion appraisal, others' emotion appraisal, regulation of emotion, and use of emotion, have a significantly positive effect on hospital employees' deep acting. And hospital employees' deep acting has a significantly positive effect on hospital employees' organizational attachment, knowledge sharing intentions, and innovative activities.

• Journal of Microbiology and Biotechnology
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• v.22 no.1
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• pp.100-106
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• 2012

In this study, the metabolite profiles of three Aspergillus strains during rice koji fermentation were compared. In the partial least squares discriminant analysis-based gas chromatography-mass spectrometry data sets, the metabolite patterns of A. oryzae (KCCM 60345) were clearly distinguished from A. kawachii (KCCM 60552) and only marginal differences were observed for A. oryzae (KCCM 60551) fermentation. In the 2 days fermentation samples, the overall metabolite levels of A. oryzae (KCCM 60345) were similar to the A. oryzae (KCCM 60551) levels and lower than the A. kawachii (KCCM 60552) levels. In addition, we identified discriminators that were mainly contributing tyrosinase inhibition (kojic acid) and antioxidant activities (pyranonigrin A) in A. oryzae (KCCM 60345) and A. kawachii (KCCM 60552) inoculated rice koji, respectively. In this study, we demonstrated that the optimal inoculant Aspergillus strains and fermentation time for functional rice koji could be determined through a metabolomics approach with bioactivity correlations.

• Environmental Analysis Health and Toxicology
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• v.25 no.4
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• pp.295-306
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• 2010

Objectives : This study was undertaken to examine the metabolomic changes due to gender and diurnal variation at sampling time and to identify an appropriate time point for urine sampling in epidemiologic studies using metabolomic profiles. Methods : Urine samples were collected twice a day (morning and afternoon) from 20 healthy Korean adults after fasting for 8 hours. The metabolomic assay was investigated using $^1H$ NMR spectroscopy coupled with the principal components analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The metabolites responsible for differentiation between groups were identified through the loading plot of PLS-DA and quantified using Chenomx NMR Suite with a 600 MHz library. Results : Metabolites responsible for differentiation in gender and sampling time were creatinine, trimethyl anine oxide (TMAO), hippurate, mannitol, citrate and acetoacetate. Dimethylamine showed difference only as a factor of diurnal time. The level of creatinine was higher in men compared to women, and the levels of citrate, TMAO, hippurate, mannitol, and acetoacetate were higher in women compared to men. The levels of creatinine, TMAO, hippurate, dimethylamine and mannitol were higher in the morning rather than the afternoon while those of citrate and acetoacetate were higher in the afternoon rather than the morning. Conclusions : Since urinary metabolomic profiles varied by gender and diurnal cycle, urine sampling should be performed at the same time point for all participants in epidemiologic studies using metabolomic profiles.