• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1121-1121
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• 2001

A previous study (Berzaghi et al., 2001) evaluated the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural networks (ANN) on the prediction of the chemical composition of forages, using a large NIR database. The study used forage samples (n=25,977) from Australia, Europe (Belgium, Germany, Italy and Sweden) and North America (Canada and U.S.A) with reference values for moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected using 10 different Foss NIR Systems instruments, only some of which had been standardized to one master instrument. The aim of the present study was to evaluate the behaviour of these different calibration methods when predicting the same samples measured on different instruments. Twenty-two sealed samples of different kind of forages were measured in duplicate on seven instruments (one master and six slaves). Three sets of near infrared spectra (1100 to 2500nm) were created. The first set consisted of the spectra in their original form (unstandardized); the second set was created using a single sample standardization (Clone1); the third was created using a multiple sample procedure (Clone6). WinISI software (Infrasoft International Inc., Port Mathilda, PA, USA) was used to perform both types of standardization, Clone1 is just a photometric offset between a “master” instrument and the “slave” instrument. Clone6 modifies both the X-axis through a wavelength adjustment and the Y-axis through a simple regression wavelength by wavelength. The Clone1 procedure used one sample spectrally close to the centre of the population. The six samples used in Clone 6 were selected to cover the range of spectral variation in the sample set. The remaining fifteen samples were used to evaluate the performances of the different models. The predicted values for dry matter, protein and neutral detergent fibre from the master Instrument were considered as “reference Y values” when computing the statistics RMSEP, SEPC, R, Bias, Slope, mean GH (global Mahalanobis distance) and mean NH (neighbourhood Mahalanobis distance) for the 6 slave instruments. From the results we conclude that i) all the calibration techniques gave satisfactory results after standardization. Without standardization the predicted data from the slaves would have required slope and bias correction to produce acceptable statistics. ii) Standardization reduced the errors for all calibration methods and parameters tested, reducing not only systematic biases but also random errors. iii) Standardization removed slope effects that were significantly different from 1.0 in most of the cases. iv) Clone1 and Clone6 gave similar results except for NDF where Clone6 gave better RMSEP values than Clone1. v) GH and NH were reduced by half even with very large data sets including unstandardized spectra.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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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.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.138-147
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• 2018

Purpose: A narrowband hyperspectral imaging sensor of high-dimensional spectral bands is advantageous for identifying the reflectance by selecting the significant spectral bands for predicting crop yield over the broadband multispectral imaging sensor for each wavelength range of the crop canopy. The images acquired by each imaging sensor were used to develop the models for predicting the Chinese cabbage yield. Methods: The models for predicting the Chinese cabbage (Brassica campestris L.) yield, with multispectral images based on unmanned aerial vehicle (UAV), were developed by simple linear regression (SLR) using vegetation indices, and forward stepwise multiple linear regression (MLR) using four spectral bands. The model with hyperspectral images based on the ground were developed using forward stepwise MLR from the significant spectral bands selected by dimension reduction methods based on a partial least squares regression (PLSR) model of high precision and accuracy. Results: The SLR model by the multispectral image cannot predict the yield well because of its low sensitivity in high fresh weight. Despite improved sensitivity in high fresh weight of the MLR model, its precision and accuracy was unsuitable for predicting the yield as its $R^2$ is 0.697, root-mean-square error (RMSE) is 1170 g/plant, relative error (RE) is 67.1%. When selecting the significant spectral bands for predicting the yield using hyperspectral images, the MLR model using four spectral bands show high precision and accuracy, with 0.891 for $R^2$, 616 g/plant for the RMSE, and 35.3% for the RE. Conclusions: Little difference was observed in the precision and accuracy of the PLSR model of 0.896 for $R^2$, 576.7 g/plant for the RMSE, and 33.1% for the RE, compared with the MLR model. If the multispectral imaging sensor composed of the significant spectral bands is produced, the crop yield of a wide area can be predicted using a UAV.

• Journal of Food Hygiene and Safety
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• v.22 no.4
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• pp.257-267
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• 2007

The possibility of rapid non-destructive qualitative and quantitative analysis of vegetable oils such as perilla, com, soybean and rapaseed oils in sesame oils was evaluated. A calibration equation calculated by MPLS(Modified Partial Least Squares) regression technique was developed and coefficients of determination for perilla oil, com oil, soybean oil and rapaseed oil contents were 0.9992, 0.9694, 0.9795 and 0.9790 respectively. According to the data obtained from validation study, $R^2$ of contents of perilla, com, soybean, rapaseed oils were 0.997, 0.848, 0.957 and 0.968, and SEP of content of them 0.747, 5.069, 3.063 and 3.000 by MPLS respectively. The results indicate that the NIRS procedure can potentially be used as a non-destructive analysis method for the rapid and simple measurement of sesame oil mixed with other vegetable oils. The detection limits of the NIRS for perilla oil, com oil, soybean oil and rapaseed oil were presumed as 2%, $15{\sim}20%,\;15{\sim}20%$ and 10%, respectively.

• The Journal of the Korea Contents Association
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• v.17 no.2
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• pp.360-374
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• 2017

This study investigates the effects of trust and distrust on intention to purchase in open markets, based on the ideas derived from previous studies such as coexistence of trust and distrust, and two distinct trustees in open markets-intermediary and sellers. Specifically, this study i) proposes a trust-distrust model of intermediary and sellers, ii) explores the transfer of trust and distrust from intermediary to sellers, and iii) discovers the antecedents of trust and distrust. The empirical validation using Partial Least Squares shows three results as follows. First, trust in intermediary positively affects intention to purchase through the mediated impact of trust in sellers. That is, trust in intermediary transfers to trust in sellers. Second, distrust in intermediary negatively affects intention to purchase through the mediated impact of customers' perceived risk. Third, structural assurance and perceived website quality positively affect trust in intermediary. The results of this research have implications for intermediary firms not only to build trust but also to manage distrust level. However, this study could not identify any antecedent of distrust, so further research for these antecedents will be needed in the future.

• Journal of Microbiology and Biotechnology
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• v.28 no.2
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• pp.199-209
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• 2018

Volatile organic compounds (VOCs) are increasingly been recognized as the chemical mediators of mold interactions, shaping their community dynamics, growth, and metabolism. Herein, we selectively examined the time-correlated (0 D-11 D, where D = incubation days) effects of intraspecies VOC-mediated interactions (VMI) on Aspergillus oryzae KCCM 60345 (S1), following co-cultivation with partner strain A. oryzae KACC 44967 (S2), in a specially designed twin plate assembly. The comparative evaluation of $S1_{VMI}$ (S1 subjected to VMI with S2) and its control ($S1_{Con}$) showed a notable disparity in their radial growth ($S1_{VMI}$ < $S1_{Con}$) at 5 D, protease activity ($S1_{VMI}$ > $S1_{Con}$) at 3-5 D, amylase activity ($S1_{VMI}$ < $S1_{Con}$) at 3-5 D, and antioxidant levels ($S1_{VMI}$ > $S1_{Con}$) at 3 D. Furthermore, we observed a distinct clustering pattern for gas chromatography-time of flight-mass spectrometry datasets from 5 D extracts of $S1_{VMI}$ and $S1_{Con}$ in principle component analysis (PC1: 30.85%; PC2: 10.31%) and partial least squares discriminant analysis (PLS-DA) (PLS1: 30.77; PLS2: 10.15%). Overall, 43 significantly discriminant metabolites were determined for engendering the metabolic variance based on the PLS-DA model (VIP > 0.7, p < 0.05). In general, a marked disparity in the relative abundance of amino acids ($S1_{VMI}$ > $S1_{Con}$) at 5 D, organic acids ($S1_{VMI}$ > $S1_{Con}$) at 5 D, and kojic acid ($S1_{VMI}$ < $S1_{Con}$) at 5-7 D were observed. Examining the headspace VOCs shared between S1 and S2 in the twin plate for 5 D incubated samples, we observed the relatively higher abundance of C-8 VOCs (1-octen-3-ol, (5Z)-octa-1,5-dien-3-ol, 3-octanone, 1-octen-3-ol acetate) having known semiochemical functions. The present study potentially illuminates the effects of VMI on commercially important A. oryzae's growth and biochemical phenotypes with subtle details of altered metabolomes.

• The Korean Journal of Pesticide Science
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• v.6 no.2
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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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.229-238
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• 2017

The study suggested plans to solve the problems of unsold apartments that lead to social and economic issues in our society, analyzed the characteristic factors related to the unsold apartment residents, investigated the preference factors, and finally determined the influence structure between the characteristic factors of residents and the mitigation factor of unsold apartment, for the repurchase intention. From previous studies, this study determined the characteristic factors based on the physical, environmental, social and economic characteristics to make up the characteristic factors for the unsold apartment residents. Then, through a Focus Group Interview (FGI) among the members of a real estate specialist group, it summarized the suitable factors for analysis and analyzed the influence structure between all factors through Partial Least Squares Structural Equation Modeling (PLS-SEM). The study results show that the mitigation factors are the most profound cause of the decision-making for unsold apartment residents, followed by economic factors and residential factors. In addition, the residential satisfaction for the unsold apartment residents has a positive relation with the repurchase intention.

• Cartoon and Animation Studies
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• s.40
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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.

• Journal of Distribution Science
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• v.13 no.11
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• pp.111-121
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• 2015

Purpose - This study's purpose is to investigate the impact of supply chain management (SCM) factors among targeted Korean distribution firms. Antecedents are established for supply chain orientation (SCO) for the management and organization of cultural assets. The research sets up SCO corresponding to management cultural assets and to organizational factors in the results. The research model is created to examine the SCO based on a strategic perspective and the operational performance of the SC and SCM. In addition, an integrated model is constructed to analyze the moderating effect by setting partner cooperation as a relational capital factor. The main aim of this study is to analyze the characteristics of the supply chain structure as a source of competitive advantage for distribution service firms participating in the supply chain. In the moderating effects analysis, the role of partner cooperation as relational capital is examined in detail. Research design, data, and methodology - The study examined the existing research related to supply chains, discussing the antecedents of the performance of SCM and SCO. SCM was established with the partner's cooperation as relational capital. Including the moderating effects of the partner cooperation, the research proposed a seven hypotheses path analysis model. The samples were collected from the Korean export enterprises in the distribution service sector, with 185 samples selected for the final analysis. To try and measure the four latent variables presented in the analysis model based on existing studies, 22 measurement items were used. The empirical analysis used the appropriate PLS (partial least squares) method on the path analysis reliability and validity and for common method bias. After testing the seven hypotheses, the research tested the moderating effects to the path analysis. Using PLS as structural equation modeling, the seven hypotheses were tested including the moderating effects of the partner relational capital on the 185 samples. Results - In the results, the SCO had a positive impact on both SCM and the relational capital of partner cooperation. The SCM had a significant impact on the operational performance of the SC. Further, partner cooperation also had a significant impact on SCM and the operational performance of the SC. The moderating effect analysis of the SCM and partner cooperation found a significant impact on the operational performance of the SC. On the other hand, the moderating effect of the SCO and partner cooperation did not affect the SCM. Conclusion - The results of this research show that the existing supply chain-related research can be applied to the operational performance of the SC for a Korean distribution service firm. In view of the fact that SCO is a source of competitive advantage, it should be taken into account when a firm wants to improve the performance of the SCM of the distribution service. This is because it can be assumed that SCO plays a role in supply chain management for the distribution firm.