• Korean Journal of Environmental Agriculture
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• v.38 no.4
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• pp.321-331
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• 2019

BACKGROUND: Pinoxaden is the phenylpyrazoline herbicide developed by Syngenta Crop Protection, Inc. and marketed on 2006. The maximum residue levels for wheat and barley were set by import tolerance. Thus, Ministry of Food and Drug Safety (MFDS) official analytical method determining Pinoxaden residue was necessary in various food matrixes. Satisfaction of international guideline of CODEX (Codex Alimentarius Commission CAC/GL 40) and National Institute of Food and Drug Safety Evaluation-MFDS (2017) are additional pre-requirements for analytical method. In this study, liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was investigated to analyze residue of Pinoxaden (M4), which is defined as pesticide residue in Korea, in foods. METHODS AND RESULTS: Pinoxaden (M4) was extracted followed by acid digestion (2hr reflux with 1N HCl) and pH adjusting (pH 4-5 with 3% ammonium solution). To remove oil, additional clean-up step with hexane saturated with acetonitrile was required to high oil contained sample before purification. HLB cartridge and nylon syringe filter were used for purification. Then, samples were analyzed by LC-MS/MS using reserve phase column C₁₈. Five agricultural group representative commodities (mandarin, potato, soybean, hulled rice, and red pepper) were used to verify the method in this study. The liner matrix-matched calibration curves were confirmed with coefficient of determination (r²) > 0.99 at calibration range 0.002-0.2 mg/kg. The limits of detection and quantitation were 0.004 and 0.01 mg/kg, respectively, which were suitable to apply Positive List System (PLS). Mean average accuracies of pinoxaden (M4) were shown to be 74.0-105.7%. The precision of pinoxaden and its metabolites were also shown less than 14.5% for all five samples. CONCLUSION: The method investigated in this study was suitable to CODEX (CAC/GL 40) and National Institute of Food and Drug Safety Evaluation-MFDS (2017) guideline for residue analysis. Thus, this method can be useful for determining the residue in various food matrixes in routine analysis.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.3
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• pp.233-242
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• 2016

Startup must be agile and be able to handle extreme changes, survive unpredicted threats, and capitalize on emerging business opportunities. Agile teams continually sense changes for competitive action and marshal the necessary knowledge. While team members share their knowledge, there must be emerging various type of conflicts in teams. This study examines the relationship among the conflict, knowledge sharing and agility in startup context. At the same time, we tested the roles of shard vision both moderating variable between conflict and knowledge sharing, and antecedent for knowledge sharing. Different two types of conflict, task conflict and relationship conflict, knowledge sharing, agility, and different impact of shared vision are identified from literatures and tested. 182 data points were collected from under 5-year old startup's representatives to test these hypotheses. PLS data analysis indicated that the task conflict and shard vision positively effect on knowledge sharing, and then knowledge sharing has statistically significant effect on agility. And the impact of conlict has been weakened by shared vision's moderating effect. Based on the results, we proposed practically several team management skills for startup managers, leaders and stakeholder, and explained theoretical contributions.

• Journal of Distribution Science
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• v.14 no.2
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• pp.135-144
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• 2016

Purpose - The purpose of this paper is to empirically investigate the moderating effects of social capital on antecedents factors path of export performance in the materials and components SMEs(Small and Medium-sized Enterprises) of Busan and Kyungnam region. In case of materials and components SMEs, they are always trying to achieve business performance including export sales and market share, but it is difficult for them to increase performance due to the limitation of inner & tangible resources. Therefore intangible asset such as technology capability and its antecedents factors which are technology innovation and learning orientation are getting more important to SMEs. In addition, it is supposed that social capital such as local network including distribution channel in overseas market plays an essential role to enhance export performance. Accordingly, the main goal of this study is to find out the relationship between export performance and antecedents factors and the validity of social capital as a moderating valuable. Research design, data, and methodology - Technology innovation, learning orientation and technology capability have been used as antecedents factors for export performance and social capital such as network diversity and intensity has been used for moderating effects analysis. In order to select these valuables mentioned above, this study examined the existing researches on a basis of Resources Based View, Organizational Learning Theory and Social Capital theory. To achieve the objective of this paper, 7 hypotheses including the moderating effects have been proposed with 6 potential variables measured by 24 questions. The survey was carried out from December 2014 to March 2015 and 137 samples out of total 175 were selected for the analysis. PLS(Partial Least Squares) has been used for the methodology of empirical analysis for both antecedents factors path and moderating effects. Results - Research findings are as follows. First, technology innovation has a significant impact on learning orientation, learning orientation has a positive effect on the technology capability and technology capability also has a significant impact on export performance. Therefore 3 valuables are proved as antecedents factors of export performance. Second, the social capital(both network diversity and intensity) plays a moderating role with learning orientation to technology capability. However, there is no moderating effects between both of social capital and technology capability regarding export performance. Conclusions - According to path analysis results, it is suggested that the materials and components SMEs should raise technology innovation and learning orientation in order to improve technology capability and export performance. Meantime, the moderating effect analysis shows that SMEs should consider local network diversity and intensity along with learning orientation to add up technology capability. But local network diversity and intensity does not work systematically with technology capability for export performance and it means that SMEs should find the appropriate local partners for the purpose of establishing concrete distribution channels based on marketing perspective, not for improving technology capability.

• Journal of the Society of Disaster Information
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• v.16 no.3
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• pp.542-549
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• 2020

Purpose: As nitrate nitrogen produced during fermentation of liquid fertilizer is a pollution indicator of water, in this study, four research areas where liquid fertilizer was sprayed were selected, and a model was designed to estimate the concentration of nitrate nitrogen pollution. Method: Prior to shooting on site, a spectrum library was constructed by dividing the ratio of liquid fertilizer into 5 groups: 0%, 25%, 50%, 75%, and 100%. PLSR (Partial least squares regression) method was applied to hyperspectral images acquired in the study area based on the aspect of spectrum. Result: The behavior of nitrate nitrogen was confirmed by 1st and 2nd differentiation of the spectrum of the constructed liquid fertilizer. PLSR concentration estimation modeling was implemented using images from field experiments and compared with actual concentration of nitrate nitrogen. Conclusion: When comparing the PLSR concentration estimation model with the actual concentration of nitrate nitrogen, it was measured that the detection is possible in high concentration areas where the concentration of nitrate nitrogen is 70mg/kg or more.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.4
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• pp.361-368
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• 2002

The aim of this study was to investigate the effect of preprocessing the transmitted energy spectrum data on development of a robust model to predict the sugar content in intact apples. The spectrum data were measured from 120 Fuji apple samples conveying at the speed of 2 apples per second. Computer algorithms of preprocessing methods such as MSC, SNV, first derivative, OSC and their combinations were developed and applied to the raw spectrum data set. The results indicated that correlation coefficients between the transmitted energy values at each wavelength and sugar contents of apples were significantly improved by the preprocessing of MSC and SNV in particular as compared with those of no-preprocessing. SEPs of the prediction models showed great difference depending on the preprocessing method of the raw spectrum data, the largest of 1.265%brix and the smallest of 0.507% brix. Such a result means that an appropriate preprocessing method corresponding to the characteristics of the spectrum data set should be found or developed for minimizing the prediction errors. It was observed that MSC and SNV are closely related to prediction accuracy, OSC is to number of PLS factors and the first derivative resulted in decrease of the prediction accuracy. A robust calibration model could be d3eveloped by the combined preprocessing of MSC and OSC, which showed that SEP=0.507%brix, bias=0.0327 and R2=0.8823.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1262-1262
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• 2001

The rice plant is one of the important staple crops in Korea. The high yield with low cost in rice is required the soil fertility and the development of new precise method of fertilizer application by nutritional diagnosis. Now, in Korea, the nitrogen application system for the rice plant is composed of the basal fertilization, fertilization at tillering stage and fertilization at panicle stage, which the nitrogen fertilization at panicle stage amount to about 30 percent in the total amount. Thus, this experiment carried out to the development of the system that can measure the nitrogen content in the rice plant at panicle stage rapidly with the near infrared spectroscopy, and to predict the appropriate quantity of the nitrogen fertilization at panicle stage based on calibration model for test of nitrogen content in rice plant. The samples were collected from 48 varieties in 4 regions which are mainly cultivated in the southern part of Korea. And then, it collected by classifying into the leaf, the whole plant and the stem since 7 days before the nitrogen fertilization at panicle stage. The ranges of the nitrogen contents were 1.6∼4.0%, 1.7∼3.0% and 1.4∼2.7% in the leaf, the whole plant and the stem, respectively. In the calibration models created by each part of the plant under the Multiple Linear Regression(MLR) method, the calibration model for the leaf recorded the relatively high accuracy. The mutual crossing test on unknown samples were carried out using Partial Least Square(PLS) calibration model. That is, the nitrogen content in the stem was tested by calibration model made by the leaf model and that of stem was tested by calibration model made by whole plant sample. When unknown leaf sample was tested by calibration model made by all sample that collected from each part in rice plant such as leaf, stem and whole plant, it recorded the highest accuracy. As a result, to test the nitrogen content in the rice plant at panicle stage, the nitrogen content in the leaf shall be tested by the calibration model composed of the leaf, the stem and the whole plant. In future, to estimated the amount of nitrogen fertilization at panicle stage for rice plant , it will be calculated based on regression model between rice yield and nitrogen content of leaf measured by calibration model made by mixed sample including leaf, stem and whole plant.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1281-1281
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• 2001

Near-infrared (NIR) spectra have bean measured for high-density (HDPE), linear low-density (LLDPE), and low-density (LDPE) polyethylene in pellet or thin films. The obtained spectra have been analyzed by conventional spectroscopic analysis methods and chemometrics. By using the second derivative, principal component analysis (PCA), and two-dimensional (2D) correlation analysis, we could separate many overlapped bands in the NIR. It was found that the intensities of some bands are sensitive to density and crystallinity of PE. This may be the first time that such bands in the NIR region have ever been discussed. Correlations of such marker bands among the NIR spectra have also been investigated. This sort of investigation is very important not only for further understanding of vibration spectra of various of PE but also for quality control of PE by vibrational spectroscopy. Figure 1 (a) and (b) shows a NIR reflectance spectrum of one of the LLDPE samples and that of PE, respectively. Figure 2 shows a PC weight loadings plot of factor 1 for a score plot of PCA for the 16 kinds of LLDPE and PE based upon their 51 NIR spectra in the 1100-1900 nm region. The PC loadings plot separates the bands due to the $CH_3$ groups and those arising form the $CH_2$ groups, allowing one to make band assignments. The 2D correlation analysis is also powerful in band enhancement, and the band assignments based upon PCA are in good agreement with those by the 2D correlation analysis.(Figure omitted). We have made a calibration model, which predicts the density of LLDPE by use of partial least square (PLS) regression. From the loadings plot of regression coefficients for the model , we suggest that the band at 1542, 1728, and 1764 nm very sensitive to the changes in density and crystalinity.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1273-1273
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• 2001

The efficiency of the luminal fermentation process influences overall efficiency of luminal production, animal health and reproduction. Ruminant production systems have a significant impact on the global environment, as well. Animal wastes contribute to pollution of the environment as ammonia volatilized to the air and nitrate leached to ground water. Microbial protein synthesis in the rumen satisfies a large proportion of the protein requirements of animals. Quantifying the microbial synthesis is possible by using markers for lumen bacteria and protozoa such as nucleic acids, purine bases, some specific amino acids, or by isotopic $^{15}N,^{32}P,\;and\;^{35}S$ labelled feeds. All those methods require cannulated animals, they are time-consuming and some methods are very expensive as well. Many attempts have been made to find an alternative method for indirect measurement of microbial synthesis in intact animals. The present investigations aimed to assess possibilities of NIRS for prediction of purine nitrogen excretion and ruminal microbial nitrogen synthesis by NIR spectra of urine. Urine samples were collected from 12 growing sheep,6 of them male, and 6- female. The sheep were included in feeding experiment. The ration consisted of sorghum silage and protein supplements -70:30 on dry matter basis. The protein supplements were chosen to differ in protein degradability. The urine samples were collected daily in a vessel containing $60m{\ell}$ 10% sulphuric acid to reduce pH below 3 and diluted with tap water to 4 liters. Samples were stored in plastic bottles and frozen at $-20^{\circ}C$ until chemical and NIRS analysis. The urine samples were analyzed for purine derivates - allantoin, uric acid, xantine and hypoxantine content. Microbial nitrogen synthesis in the lumen was calculated according to Chen and Gomes, 1995. Transmittance urine spectra with sample thickness 1mm were obtained by NIR System 6500 spectrophotometer in the spectral range 1100-2500nm. The calibration was performed using ISI software and PLS regression, respectively. The following statistical results of NIRS calibration for prediction of purine derivatives and microbial protein synthesis were obtained.(Table Omitted). The result of estimation of purine nitrogen excretion and microbial protein synthesis by NIR spectra of urine showed accuracy, adequate for rapid evaluation of microbial protein synthesis for a large number of animals and different diets. The results indicate that the advantages of the NIRS technology can be extended into animal physiological studies. The fast and low cost NIRS analyses could be used with no significant loss of accuracy when microbial protein synthesis in the lumen and the microbial protein flow in the duodenum are to be assessed by NIRS.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1520-1520
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• 2001

Food adulteration is a serious consumer fraud and a potentially dangerous practice. Regulatory authorities and food processors require a rapid, non-destructive test to accurately confirm authenticity in a range of food products and raw materials. Olive oil is prime target for adulteration either on the basis of the processing treatments used for its extraction (extra virgin vs virgin vs ordinary oil) or its geographical origin (e.g. Greek vs Italian vs Spanish). As part of an investigation into this problem, some preliminary work focused on the ability of near infrared spectroscopy to discriminate between virgin olive oils from separate regions of the Mediterranean i. e. Crete and the Peloponese. A total of 46 oils were collected: 18 originated in Crete and 28 in the Peloponese. Oils were stored in a temperature-controlled room at 2$0^{\circ}C$ prior to spectral collection at room temperature (15-18$^{\circ}C$). Samples (approximately 0.5$m\ell$) were placed in the centre of the quartz window in a camlock reflectance cell; the gold-plated baking plate was then gently placed into the cell against the glass so as to minimize the formation of air bubbles. The rear of the camlock cell was then screwed into place producing a sample thickness of 0.5mm. Spectra were recorded between 400 and 2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. Spectral collection took place over 2-3 days. Data were analysed using both WINISI and The Unscrambler software to investigate the possibility of discriminating between the oils from Crete and the Peloponese. A number of data pre-treatments were used and discriminant models were developed using discriminant PLS (WINISI & Unscrambler) and SIMCA (Unscrambler). Despite the small number of samples involved, a satisfactory discrimination between these two oil types was achieved. Graphical examination of principal component scores for each oil type also holds out the possibility of separating oils from either Crete and the Peloponese on the basis of districts within each region. These preliminary data suggest the potential of near infrared spectroscopy to act as a screening technique for the confirmation of geographic origin of extra virgin olive oils. The sample presentation strategy adopted uses only small volumes of material and produces high quality spectra.

• 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.