• Journal of The Korean Society of Grassland and Forage Science
• /
• v.31 no.4
• /
• pp.415-422
• /
• 2011

This study evaluated the feasibility of using a portable near infrared reflectance spectrometer working in the 900~1,600 nm range for the measurement of quality-related parameters (moisture, pH, Acid detergent fiber (ADF), Neutral detergent fiber (NDF), Crude protein (CP), lactic acid) in intact silage. The calibration result for the Phazir (handheld, Polychromix) was compared with the result for the Spectrastar (Lab. based, Unity). A total of 67 Italian ryegrass silages were used to build calibration models using different spectral signal pre-treatments and the partial least squares regression (PLS) method. The good calibration statistics in two instruments was obtained for moisture content of Italian ryegrass silages with over $R^2$ = 0.95. The Phazir spectrometer was less accurate in measuring of ADF, NDF and CP contents. The Spectrastar instrument yielded greater precision for pH and lactic acid content; statistic values were over $R^2$ = 0.82 and the standard error of calibration (SEC) = 0.21% and 0.24%. Thus, the NIR measurement of forage quality in the field by portable NIR analyzers was shown not to be feasible, but additional investigations are required to discern the key instrumental and operational parameters that may influence the portable NIR measurement.

• The Korean Journal of Pesticide Science
• /
• v.6 no.3
• /
• pp.209-217
• /
• 2002

Two different QSAR methods, the comparative molecular similarity indices analyses (CoMSIA) and hologram quantitative structure activity relationship (HQSAR) are studied for the fungicidal activities ($pI_{50}$) of 2-N-benzyl-5-phenoxy-3-isothiazolone derivatives against sensitive (SPC: 95CC7105) and resisitive (RPC: 95CC7303) phytophthora blight fungus (Phytaphthora capsici). According to the findings from these QSAR investigation, the cross-validation value, $q^2$ and Pearson correlation coefficient, $r^2$ in the two methods were CoMSIA: RPC; $q^2=0.675,\;r^2=0.942$, SPC; $q^2=0.350,\;r^2=0.876$ and HQSAR: RPC; $q^2=0.519,\;r^2=0.869$, SPC; $q^2=0.483,\;r^2=0.990$, respectively. Therefore, the two models of comparative statistical significance were obtained. From the CoMSIA contour maps, the important factors for selective fungicidal activity against RPC are to be expected that the lower hydrophobic and not bulkiness substituent as hydrogen bonding acceptor have to introduce to meta and para-position (C1-C6) on the phenoxy moiety. And the results of prediction suggest that HQSAR method showed higher fungicidal activity than CoMSIA method.

• Journal of Food Hygiene and Safety
• /
• v.21 no.4
• /
• pp.204-212
• /
• 2006

This study was conducted to investigate the possibility of rapid and non-des tructive evalution of AV (Acid Value), IV (Iodine Value) and fatty acids in sesame oils. The samples were scanned over the range $400\sim2500nm$ using transmittance spectrum of NIRS(Near-infrared spectroscopy). A calibration equation calculated by MPLS regression technique was developed and correlation coefficient of determination for AV, IV, palmitic acid, stearic acid, linoleic acid and linolenic acid content were 0.9907, 0.9677, 0.9527, 0.9210, 0.9829, 0.9736 and 0.9709 respectively. The validation model for measuring the AV content had R of 0.989, SEP of 0.058 and IV content had R of 0.944, SEP of 0.562 and palmitic acid content had R of 0.924, SEP of 0.194 and stearic acid content had R of 0.717, SEP of 0.168 and oleic acid content had R of 0.989, SEP of 0.221 and linoleic acid content had R of 0.967, SEP of 0.297 and linolenic acid content had R of 0.853, SEP of 0.480 by MPLS. The obtained results indicate that the NIRS procedure can potentially be used as a non-destructive analysis method for the purpose of rapid and simple measurement of AV, IV and fatty acids in sesame oils.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.44 no.6
• /
• pp.847-853
• /
• 2015

The purpose of this study was to compare color, protease, and antioxidant activities of Korean traditional soy sauce fermented for 120 days in Onggis obtained from five regions-Gangjin, Jeju, Ulsan, Yeoju, and Yesan in Korea. The brown color of soy sauce was increased during the fermentation period and was the highest in soy sauce fermented in Yesan. The values of total phenol contents, protease activity, and ferric reducing antioxidant power (FRAP) and 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activity activities were also increased during the fermentation period of soy sauce. Soy sauce fermented in Gangjin Onggi showed the highest protease activity, total phenol contents, DPPH radical scavenging activity, and FRAP ability. The partial least squares regression analysis indicated that the regional Onggis affect the quality of soy sauce with in terms of color, protease activity, and antioxidant activity.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.1
• /
• pp.208-213
• /
• 2021

There is a lack of studies comparing the internal quality of fruit with its external quality. However, issues of internal quality of fruit such as internal browning are important. We propose a method of classifying normal apples and internally browned apples using a near-infrared (NIR) non-destructive system. Specifically, we found the optimal wavelength and characteristics of the spectra for determining the internal browning of Fuji apples. The NIR spectra of apples were obtained in the wavelength range of 470-1150 nm. A group of normal apples and a group of internally browned apples were identified using principal component analysis (PCA), and a partial least squares regression (PLSR) analysis was performed to develop and evaluate the discriminant model. The PCA analysis revealed a clear difference between the normal and internally browned apples. From the PLSR, the correlation coefficient of the predictive model without pretreatment was determined to be 0.902 with an RMSE value of 0.157. The correlation coefficient of the predictive model with pretreatment was 0.906 with an RMSE value of 0.154. The results show that this model is suitable for classifying normal and internally browned apples and that it can be applied for the sorting and evaluation of agricultural products for internal and external defects.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.41 no.1
• /
• pp.29-34
• /
• 2021

Near infrared reflectance spectroscopy (NIRS) is routinely used for the determination of nutrient components of forages. However, little is known about the impact of sample preparation and wavelength on the accuracy of the calibration to predict minerals. This study was conducted to assess the effect of sample preparation and wavelength of near infrared spectrum for the improvement of calibration and prediction accuracy of Calcium (Ca) and Phosphorus (P) in imported hay using NIRS. The samples were scanned in reflectance in a monochromator instrument (680-2,500 nm). Calibration models (n = 126) were developed using partial least squares regression (PLS) based on cross-validation. The optimum calibrations were selected based on the highest coefficients of determination in cross validation (R2) and the lowest standard error of cross-validation (SECV). The highest R2 and the lowest SECV were obtained using oven-dry grinded sample preparation and 1,100-2,500 nm wavelength. The calibration (R2) and SECV were 0.99 (SECV: 468.6) for Ca and 0.91 (SECV: 224.7) for P in mg/kg DM on a dry weight, respectively. Results of this experiment showed the possibility of NIRS method to predict mineral (Ca and P) concentration of imported hay in Korea for routine analysis method to evaluate the feed value.

• Asia pacific journal of information systems
• /
• v.17 no.4
• /
• pp.207-228
• /
• 2007

Measuring Information Technology(IT) organizations' activities have been limited to mainly measure financial indicators for a long time. However, according to the multifarious functions of Information System, a number of researches have been done for the new trends on measurement methodologies that come with financial measurement as well as new measurement methods. Especially, the researches on IT Balanced Scorecard(BSC), concept from BSC measuring IT activities have been done as well in recent years. BSC provides more advantages than only integration of non-financial measures in a performance measurement system. The core of BSC rests on the cause-and-effect relationships between measures to allow prediction of value chain performance measures to allow prediction of value chain performance measures, communication, and realization of the corporate strategy and incentive controlled actions. More recently, BSC proponents have focused on the need to tie measures together into a causal chain of performance, and to test the validity of these hypothesized effects to guide the development of strategy. Kaplan and Norton[2001] argue that one of the primary benefits of the balanced scorecard is its use in gauging the success of strategy. Norreklit[2000] insist that the cause-and-effect chain is central to the balanced scorecard. The cause-and-effect chain is also central to the IT BSC. However, prior researches on relationship between information system and enterprise strategies as well as connection between various IT performance measurement indicators are not so much studied. Ittner et al.[2003] report that 77% of all surveyed companies with an implemented BSC place no or only little interest on soundly modeled cause-and-effect relationships despite of the importance of cause-and-effect chains as an integral part of BSC. This shortcoming can be explained with one theoretical and one practical reason[Blumenberg and Hinz, 2006]. From a theoretical point of view, causalities within the BSC method and their application are only vaguely described by Kaplan and Norton. From a practical consideration, modeling corporate causalities is a complex task due to tedious data acquisition and following reliability maintenance. However, cause-and effect relationships are an essential part of BSCs because they differentiate performance measurement systems like BSCs from simple key performance indicator(KPI) lists. KPI lists present an ad-hoc collection of measures to managers but do not allow for a comprehensive view on corporate performance. Instead, performance measurement system like BSCs tries to model the relationships of the underlying value chain in cause-and-effect relationships. Therefore, to overcome the deficiencies of causal modeling in IT BSC, sound and robust causal modeling approaches are required in theory as well as in practice for offering a solution. The propose of this study is to suggest critical success factors(CSFs) and KPIs for measuring performance for IT organizations and empirically validate the casual relationships between those CSFs. For this purpose, we define four perspectives of BSC for IT organizations according to Van Grembergen's study[2000] as follows. The Future Orientation perspective represents the human and technology resources needed by IT to deliver its services. The Operational Excellence perspective represents the IT processes employed to develop and deliver the applications. The User Orientation perspective represents the user evaluation of IT. The Business Contribution perspective captures the business value of the IT investments. Each of these perspectives has to be translated into corresponding metrics and measures that assess the current situations. This study suggests 12 CSFs for IT BSC based on the previous IT BSC's studies and COBIT 4.1. These CSFs consist of 51 KPIs. We defines the cause-and-effect relationships among BSC CSFs for IT Organizations as follows. The Future Orientation perspective will have positive effects on the Operational Excellence perspective. Then the Operational Excellence perspective will have positive effects on the User Orientation perspective. Finally, the User Orientation perspective will have positive effects on the Business Contribution perspective. This research tests the validity of these hypothesized casual effects and the sub-hypothesized causal relationships. For the purpose, we used the Partial Least Squares approach to Structural Equation Modeling(or PLS Path Modeling) for analyzing multiple IT BSC CSFs. The PLS path modeling has special abilities that make it more appropriate than other techniques, such as multiple regression and LISREL, when analyzing small sample sizes. Recently the use of PLS path modeling has been gaining interests and use among IS researchers in recent years because of its ability to model latent constructs under conditions of nonormality and with small to medium sample sizes(Chin et al., 2003). The empirical results of our study using PLS path modeling show that the casual effects in IT BSC significantly exist partially in our hypotheses.

• Food Engineering Progress
• /
• v.15 no.1
• /
• pp.48-55
• /
• 2011

In this research, the near-infrared absorption from 1,100-2,300 nm was used to measure the content of capsaicinoids in the red-pepper powder by using the Acousto-optic tunable filters (AOTF) spectrometer with sample plate and sample rotating unit. Non-spicy red-pepper samples from one location (Younggwang-gun. Korea) were mixed with spicy one (var. Chungyang) to make samples separated by particle size (below 0.425 mm, 0.425-0.71 mm, and 0.71- 1.4 mm). The Partial Least Squares Regression (PLSR) model to predict the capsaicinoid content on particle sizes was developed with measured spectra by AOTF spectrometer and used to analyze the amount of capsaicinoids by HPLC. The PLSR Model of red-pepper powder of below 0.425 mm, 0.425-0.71 mm, and 0.71-1.4 mm with cross validation had ${R_V}^2$ = 0.948-0.979 and Standard Error of Prediction (SEP) = 6.56-7.94 mg%. The prediction error of smaller particle size of red-pepper powder was low. The best PLSR model was found in pretreatment of Range Normalization, Standard Normal Variate, and 1st Derivatives of red-pepper powder of below 1.4 mm with cross validation, having ${R_V}^2$ = 0.959 and SEP = 8.82 mg%.