• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1510-1510
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• 2001

NIRS uses reflectance signals resulting from bending and stretching vibrations in chemical bonds between carbon, nitrogen, hydrogen, sulfur and oxygen. These reflectance signals are used to measure the concentration of major chemical composition and other descriptors of homogenized and freeze-dried whole broiler carcasses. Six strains of chicken were analyzed and the NIRS model predictions compared to reference data. The results of this comparison indicate that NIRS is a rapid tool for predicting dry matter (DM), fat, crude protein (CP) and ash content in the broiler carcass. Males and females of six commercial strain crosses of broiler chicken (Gallus domesticus) were used in this study (6$\times$2 factorial design). Each strain was grown to 16 weeks of age, and duplicate serial samples were taken for body composition analysis. Each whole carcass was pressure-cooked, homogenized, and a representative sample was freeze-dried. Body composition determined as follows: DM by oven dried method at 105$^{\circ}C$ for 3 hours, fat by Mojonnier diethyl ether extraction, CP by measuring nitrogen content using an auto-analyzer with Kjeldhal digest and ash by combustion in a muffle furnace for 24 hour at 55$0^{\circ}C$. These homogenized and freeze-dried carcass samples were then scanned with a Foss NIR Systems 6500 visible-NIR spectrophotometer (400-2500nm) (Foss NIR Systems, Silver Spring, MD., US) using Infra-Soft-International, ISI, WinISl software (ISI, Port Matilda, US). The NIRS spectra were analyzed using principal component (PC) analysis. This data was corrected for scatter using standard normal “Variate” and “Detrend” technique. The accuracy of the NIRS calibration equations developed using Partial Least Squares (PLS) for predicting major chemical composition and carcass descriptors- such as body mass (BM), bird dry matter and moisture content was tested using cross validation. Discrimination analysis was also used for sex and strain identification. According to Dr John Shenk, the creator of the ISI software, the calibration equations with the correlation coefficient, $R^2$, between reference data and NIRS predicted results of above 0.90 is excellent and between 0.70 to 0.89 is a good quantifying guideline. The excellent calibration equations for DM ($R^2$= 0.99), fat (0.98) and CP (0.92) and a good quantifying guideline equation for ash (0.80) were developed in this study. The results of cross validation statistics for carcass descriptors, body composition using reference methods, inter-correlation between carcass descriptors and NIRS calibration, and the results of discrimination analysis for sex and strain identification will also be presented in the poster. The NIRS predicted daily gain and calculated daily gain from this experiment, and true daily gain (using data from another experiment with closely related broiler chicken from each of the six strains) will also be discussed in the paper.

• The Korean Journal of Pesticide Science
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• 제6권2호
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• pp.72-79
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• 2002

3D-QSAR between fungicidal activitives ($pI_{50}$) against metalaxyl-sensitive (SPC: 95CC7105) or metalaxyl-resisitant (RPC: 95CC7303) isolate of phytophthora blight fungus (Phytophthora capsici), and a set of 3-phenylisoxazole (A) and 3-phenyl-2,5-dihydroisoxazole (B) derivatives as substrates were conducted using comparative molecular field analyses (CoMFA). The antifungal activities of (A) were generally higher than those of (B). And it is assumed that the most stable conformation of the active substrate was approximately planar from conformational search. The CoMFA models proved a good predictive ability and suggested that the electronic field of substrates were higher than hydropohobic field and steric field requirements for recognition forces of the receptor site. And the factors were strongly correlated (cross-validated $q^2>0.570$ & conventional $r^2>0.968$) with the fungicidal activitives. According to the CoMFA analyses, the selectivity factors for RPC suggested that the sterically bulky groups (C14 & C15) and electron withdrawing groups (C15 & C16) have to be introduced to the ortho, meta and para-position on the benzoyl moiety of substrates.

• Cartoon and Animation Studies
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• 통권40호
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• pp.337-365
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• 2015

The objective of this study proposes the new user's addiction model in 'Social Network Games' (SNGs). Research model is derived from the separation of two characteristics. First one is logical characteristics that includes 'Functional' (F), 'Keystroke' (K), and 'Goal' (G). Second one is feeling characteristics that consists a few factors such as 'Emotion' (E), 'Social' (S), and 'Affection' (A). For the pre-test, a total of 30 participants responded to survey in order to inspect the fitness of research questionnaire, roughly validity of the proposed model, and the direction of this reseach. After that for the main test, a total 300 users participated in this research. The final number of effective participants were 261 because 39 were insincere respondents and without playing SNGs who were excluded. Then we examined the measurement model by performing 'Partial Least Squares - Structural Equation Modeling' (PLS-SEM) analysis to test the research hypothesis empirically. The results of the measurement and structural model test lend support to the proposed research model by providing a good fit to the construct data. Interestingly, the model showed the significant effects of the interaction between eleven hypothesis(H1,H2,H3,H4,H5,H6,H7,H8,H9,H10, H12). Only one hypothesis decision t-value not supported that is involved the relationship between SNGs Addiction and Keystroke, H11(1.193). This research expect to contributes to an exploratory SNGs research to clarify the base of addition and will aids understanding of users' behavior associated with SNGs development.

• Knowledge Management Research
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• 제17권4호
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• pp.27-56
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• 2016

Korean traditional markets have been struggling of late as big-sized superstores and SSM(Super Supermarkets) are thriving in the market. They have therefore upgraded their facilities and undertaken management modernization actively to overcome the threat to traditional markets and ensure their competitiveness; however, the effect does not appear to be verifiable. The purpose of this study is to analyze the impact of the organizational characteristics of the traditional market merchant association on social capital and organizational performance. In other words, this paper investigates a merchant association's organizational characteristics in terms of the modernization of business activities of the traditional markets and the influence on their social capital and organizational performance. This study analyzes the traditional market by evaluating the impact of these factors. This study consists of four hypotheses: The first hypothesis relates to the causal relationship between the characteristics of a merchant association and social capital. The second and third hypotheses, respectively, relate to the causal relationships between the social capital of a merchant association and the merchant's satisfaction and that between the social capital of a merchant association and organizational commitment. The last hypothesis relates to the relationship between the organizational commitment of a merchant association and the merchant's satisfaction. This study conducts a reliability and validity analysis of the above factors and analyzes the causal relationships between them by using the PLS(Partial Least Squares) path model as one of the structural equation models. The results of the empirical analysis are summarized as follows: First, the organizational characteristics of the traditional market merchant association have a significant influence on social capital. However, only two sub-hypotheses are not significant; these insignificant hypotheses relate to the relationship between a merchant's entrepreneurship and structural capital and that between a merchant's entrepreneurship and cognitive capital. Second, the social capital of a merchant association influences organizational commitment significantly. Third, the relationship between the social capital of a merchant association and the merchant's satisfaction is mostly significant. However, one of the sub-hypotheses, that is, the relationship between relational capital and a merchant's satisfaction is not exceptionally significant. Lastly, the organizational commitment of a merchant association affect the merchant's satisfaction significantly. Through our extensive study, this paper found that a merchant association's organizational characteristics of the traditional market significantly affect social capital, organizational commitment, and satisfaction through the mediation of social capital. Therefore, in order to activate the key traditional market, an understanding of organizational characteristics and social capital is primarily required. Systematic management and investment pertaining to these two factors will be the first consideration for revitalizing traditional markets.

• Journal of Microbiology and Biotechnology
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• 제27권5호
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• pp.925-932
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• 2017

Changes in the metabolite profiles of Lactobacillus sakei and its growth media, based on different culture times (0, 6, 12, and 24 h), were investigated using gas chromatography-mass spectrometry (MS) and liquid chromatography-MS with partial least squares discriminant analysis, in order to understand the growth characteristics of this organism. Cell and media samples of L. sakei were significantly separated on PLS-DA score plots. Cell and media metabolites, including sugars, amino acids, and organic acids, were identified as major metabolites contributing to the difference among samples. The alteration of cell and media metabolites during cell growth was strongly associated with energy production. Glucose, fructose, carnitine, tryptophan, and malic acid in the growth media were used as primary energy sources during the initial growth stage, but after the exhaustion of these energy sources, L. sakei could utilize other sources such as trehalose, citric acid, and lysine in the cell. The change in the levels of these energy sources was inversely similar to the energy production, especially ATP. Based on these identified metabolites, the metabolomic pathway associated with energy production through lactic acid fermentation was proposed. Although further studies are required, these results suggest that MS-based metabolomic analysis might be a useful tool for understanding the growth characteristics of L. sakei, the most important bacterium associated with meat and vegetable fermentation, during growth.

• Management & Information Systems Review
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• 제37권1호
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• pp.19-40
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• 2018

The purpose of this study is to analyze the effects of a firm's dynamic capabilities measured by sensing, seizing, transforming, coordinating, and learning capabilities on its competitive capabilities, such as product quality, process flexibility, delivery speed, and low cost. The relationship among dynamic capabilities, competitive capabilities, and export firm performance is set up as a research model based on empirical studies related to the existing dynamic capability perspective and competitive capabilities. To test this research model, this study collected 102 samples of data using a questionnaire survey on both manufacturing and exporting firms. The partial least squares method is used and the following results are derived from an empirical analysis. First, dynamic capabilities have a positive effect on competitive capabilities, such as product quality, process flexibility, delivery speed, and low cost. Second, product quality and process flexibility have a positive effect on export firm performance. Third, unlike previous research results, this study finds that the competitive capabilities of a firm in the areas of delivery speed and low cost do not significantly affect its performance. These findings provide meaningful implications for export venture firms that need to acquire and maintain competitive advantage in a rapidly changing environment.

• Journal of The Korean Society of Grassland and Forage Science
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• 제39권4호
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• pp.292-297
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• 2019

In this study, whole crop rice samples were used to develop near-infrared reflectance (NIR) equations to estimate six forage quality parameters: Moisture, crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), Ash and relative feed value (RFV). A population of 564 whole crop rice representing a wide range in chemical parameters was used in this study. Undried finely chopped whole crop rice samples were scanned at 1 nm intervals over the wavelength range 680-2500 nm and the optical data recorded as log 1/Reflectance (log 1/R). NIRS calibrations were developed by means of partial least-squares (PLS) regression. The correlation coefficients of cross-validation (R²_cv) and standard error of cross-validation (SECV) for whole crop rice calibration were 0.98 (SECV 1.81%) for moisture, 0.89 (SECV 0.50%) for CP, 0.86 (SECV 1.79%) for NDF, 0.89 (SECV 0.86%) for ash, and 0.84 (SECV 5.21%) for RFV on a dry matter (%), respectively. The NIRS calibration equations developed in this study will be useful in predicting whole crop rice quality for these six quality parameters.

• Agribusiness and Information Management
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• 제3권2호
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• pp.43-62
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• 2011

The goal of this study is to determine, based on survey results, the underlying factors that affect the intention of the farmers who have not adopted the Hazard Analysis and Critical Control Points (HACCP) system for the rearing phase of pig production to adopt this system in the future. The research model for this study was con structed based on strategic contingency theory, the theory of the diffusion of innovation, and the technology acceptance model (TAM). Using structural equation modeling with partial least squares (PLS), this study analyzes the effects of the intensity of competition, the environmental uncertainty, the innovativeness and self-efficacy of the individual farmers, and the impact of the credibility of the Agricultural Technology Service Center (ATSC), which acts as the principal agent of technology dissemination and as a leader of change, on the perceived usefulness of technology and the farmers' intention to adopt the system. The results of the analysis are as follows. First, with regard to the underlying factors affecting the intention to adopt the new system, the intensity of competition within the industry and the institutional credibility of the ATSC were inferred to underlie the perceived usefulness. Second, institutional credibility has a positive impact on the perceived usefulness of the system, and the perceived usefulness, in turn, has a positive impact on the intention to adopt. The perceived ease of use also has a positive impact on the intention to adopt. Because the factor that has the biggest impact on the intention of a farm to adopt is the credibility of the ATSC, it is crucial for extension organizations, such as the ATSC, to make greater efforts to promote the expansion of the HACCP system. Because farmers feel that the implementation of the HACCP system is an instrumental strategy for coping with the high intensity of competition within the industry, they attempt to gain a competitive edge through the production of safe livestock products.

• Journal of The Korean Society of Grassland and Forage Science
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• 제35권3호
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• pp.257-263
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• 2015

This study was conducted to assess the potential of using NIRS to accurately determine the chemical composition and fermentation parameters in fresh coarse sorghum and sudangrass silage. Near Infrared Spectroscopy (NIRS) has been increasingly used as a rapid and accurate method to analyze the quality of cereals and dried animal forage. However, silage analysis by NIRS has a limitation in analyzing dried and ground samples in farm-scale applications because the fermentative products are lost during the drying process. Fresh coarse silage samples were scanned at 1 nm intervals over the wavelength range of 680~2500 nm, and the optical data were obtained as log 1/Reflectance (log 1/R). The spectral data were regressed, using partial least squares (PLS) multivariate analysis in conjunction with first and second order derivatization, with a scatter correction procedure (standard normal variate and detrend (SNV&D)) to reduce the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation (SECV). The results of this study showed that NIRS predicted the chemical constituents with a high degree of accuracy (i.e. the correlation coefficient of cross validation ($R^2{_{cv}}$) ranged from 0.86~0.96), except for crude ash which had an $R^2{_{cv}}$ of 0.68. Comparison of the mathematical treatments for raw spectra showed that the second-order derivatization procedure produced the best result for all the treatments, except for neutral detergent fiber (NDF). The best mathematical treatment for moisture, acid detergent fiber (ADF), crude protein (CP) and pH was 2,16,16 respectively while the best mathematical treatment for crude ash, lactic acid and total acid was 2,8,8 respectively. The calibrations of fermentation products produced poorer calibrations (RPD < 2.5) with acetic and butyric acid. The pH, lactic acid and total acids were predicted with considerable accuracy at $R^2{_{cv}}$ 0.72~0.77. This study indicated that NIRS calibrations based on fresh coarse sorghum and sudangrass silage spectra have the capability of assessing the forage quality control

• Journal of The Korean Society of Grassland and Forage Science
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• 제37권4호
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• pp.350-357
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• 2017

Near infrared spectroscopy (NIRS) is a rapid and accurate method for analyzing the quality of cereals, and dried animal forage. However, one limitation of this method is its inability to measure fermentation parameters in dried and ground samples because they are volatile, and therefore, respectively lost during the drying process. In order to overcome this limitation, in this study, fresh coarse haylage was used to test the potential of NIRS to accurately determine chemical composition and fermentation parameters. Fresh coarse Italian ryegrass haylage samples were scanned at 1 nm intervals over a wavelength range of 680 to 2500 nm, and optical data were recorded as log 1/reflectance. Spectral data, together with first- and second-order derivatives, were analyzed using partial least squares (PLS) multivariate regressions; scatter correction procedures (standard normal variate and detrend) were used in order to reduce the effect of extraneous noise. Optimum calibrations were selected based on their low standard error of cross validation (SECV) values. Further, ratio of performance deviation, obtained by dividing the standard deviation of reference values by SECV values, was used to evaluate the reliability of predictive models. Our results showed that the NIRS method can predict chemical constituents accurately (correlation coefficient of cross validation, $R_{cv}^2$, ranged from 0.76 to 0.97); the exception to this result was crude ash ($R_{cv}^2=0.49$ and RPD = 2.09). Comparison of mathematical treatments for raw spectra showed that second-order derivatives yielded better predictions than first-order derivatives. The best mathematical treatment for DM, ADF, and NDF, respectively was 2, 16, 16, whereas the best mathematical treatment for CP and crude ash, respectively was 2, 8, 8. The calibration models for fermentation parameters had low predictive accuracy for acetic, propionic, and butyric acids (RPD < 2.5). However, pH, and lactic and total acids were predicted with considerable accuracy ($R_{cv}^2$ 0.73 to 0.78; RPD values exceeded 2.5), and the best mathematical treatment for them was 1, 8, 8. Our findings show that, when fresh haylage is used, NIRS-based calibrations are reliable for the prediction of haylage characteristics, and therefore useful for the assessment of the forage quality.