• Title/Summary/Keyword: Partial least squares method

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Determination of individual sugars in different varieties of persian grape using Near Infrared spectroscopy

  • Kargosha, Kazem;Azad, Jila;Lary, Abas Motamed
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1527-1527
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    • 2001
  • Glucose, fructose and sucrose being the main sugars that can be found in natural fruit juice. Many instrumental methods, such as GC, LC, electrochemical or spectrometric methods provide information about both the total content of sugars and the specific concentration of each carbohydrate[1]. The simplicity of sample handling and measurement in the near IR(NIR) wavelength region, which allows the use of long pathlength, optical glass cells and optical fibers, makes NIR a good alternative for sugar determination [2]. In the present study, six varieties of persian grapes were harvested at intervals through august to october and analysed for sugars by NIR. The results were processed by principal component regression (PCR) and partial least squares (PLS) analysis. Sample juice was prepared by squeezing through gauze from crashed grape. This solution was treated by zinc ferrocyanide prior to analysis in order to eliminate colored compounds and all optically active nonsugar substances. For glucose and fructose the most characteristic wavelengths were 1456nm corresponding to the first harmonic O-H stretching and the second at 2062nm corresponding to O-H stretching and deformation; secondary characteristic combination bands were also seen at 2265 nm (O-H and C-C stretching) and at 2240 nm (C-H and C-C stretching). However these spectra were taken over a wavelength range from 1100-2500nm at room temperature of 25-$30^{\circ}C$. To test the accuracy of the described procedure, samples of six varieties of grape were analysed by the proposed NIR and a standard method[2]. Good agreement were found between these two sets of the results. To perform the recovery studies , samples of grape juices previously analysed by the proposed method, were spiked with known amounts of each individual sugars and then analysed again. Relative standard deviations varied from 1.4 to 1.8% for six independent measurements of individual and total sugar concentration. In the analysis of real and synthetic samples, precise and accurate results were obtained , providing accuracy errors lower than 1.9% in all cases. Average recoveries of ${97}{\pm}{4%}$ for total sugar and between ${95}{\pm}{5%}$ and ${99}{\pm}{2%}$ for sing1e sugars demonstrate the applicability of the methodology developed to the direct analysis of grape Juice.

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The Role of Relational Capital in Supply Chain Management for Distribution Service Firms (유통서비스 기업의 공급사슬 운영성과 경로에서 파트너 관계자산의 역할)

  • Cho, Yeon-Sung
    • 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.

Rapid Measure of Color and Catechins Contents in Processed Teas Using NIRS (근적외선 분광광도계를 이용한 차 제품의 색상 및 카테킨류의 신속 측정)

  • Chun, Jong-Un
    • Korean Journal of Plant Resources
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    • v.23 no.4
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    • pp.386-392
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    • 2010
  • This study was done to measure the color and catechins contents in processed teas using the whole bands (400~2500 nm) with near-infrared spectroscopy(NIRS). The powder colors of 109 processed teas were measured with a colorimeter. The a/b ratios in Hunter color scale in processed teas accounted for about 98.9% of the variation in the fermentation degree(FD), indicating that the a/b ratio was a very useful trait for assessing fermentation degree. Also tea powders were scanned in the visible bands used with NIRSystem. The calibration equations for powder colors were developed using the regression method of modified partial least squares(MPLS) with the internal cross validation. The equations had low SECV (standard errors of cross-validation), and high $R^2$ (coefficient of determination in calibration) values with 0.996~1.00, indicating that the visible bands(400~700 nm) with NIRS could be used to rapidly measure the variables related to powder color and fermentation degree. Also another powders of 137 processed teas were scanned at 780~2500 nm bands in the reflectance mode. The calibration equations were developed using the regression method of MPLS with the internal cross validation. The equations had low SECV, and high $R^2$ (0.896~0.983) values, showing that NIRS could be used to rapidly discriminate the contents of EGC($R^2$=0.919), EC(0.896), EGCg(0.978), ECg(0.905) and total catechins(0.983) in processed teas with high precision and ease.

Determination of Baicalin and Baicalein Contents in Scutellaria baicalensis by NIRS (근적외선분광분석기를 이용한 황금(Scutellaria baicalensis)의 baicalin 및 baicalein 함량 분석)

  • Kim, Hyo-Jae;Kim, Se-Young;Lee, Young-Sang;Kim, Yong-Ho
    • Korean Journal of Plant Resources
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    • v.27 no.4
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    • pp.286-292
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    • 2014
  • Near infrared reflectance spectroscopy (NIRS) is a rapid and accurate analytical method for determining the composition of agricultural products and feeds. This study was conducted to measure baicalin, baicalein, and wogonin contents in Scutellaria baicalensis by using NIRS system. Total 63 samples previously were analyzed by HPLC, which showed baicalin, baicalein, and wogonin contents ranging 4.56 to 13.59%, 0.28 to 5.54%, and 0.50 to 1.63% with an average of 9.66%, 2.09% and 0.52%, respectively. Each sample was scanned by NIRS and calculated for calibration and validation equation. A calibration equation calculated by modified partial least squares(MPLS) regression technique was developed in which the coefficient of determination for baicalin, baicalein, and wogonin content was 0.958, 0.944, and 0.709, respectively. Each calibration equation was applied to validation set that was performed with the remaining samples not included in the calibration set, which showed high positive correlation both in baicalin and baicalein content file. In case of wogonin, the prediction model was needed more accuracy because of low $R^2$ value in validation set. These results demonstrate that the developed NIRS equation can be practically used as a rapid screening method for quantification of baicalin and baicalein contents in Scutellaria baicalensis.

Comparative molecular similarity indices analyses (CoMSIA) and hologram quantitative structure activity relationship (HQSAR) on the fungicial activity of 2-N-benzyl-5-phenoxy-3-isothiazolone derivatives against phytophthora blight fungus (고추역병균에 대한 2-N-benzyl-5-Phenoxy-3-isothiazolone 유도체의 살균활성에 관한 비교분자 유사성 지수분석(CoMSIA)과 홀로그램 구조-활성 관계(HQSAR))

  • Sung, Nack-Do;Kim, Ki-Hyun
    • The Korean Journal of Pesticide Science
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    • v.6 no.3
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    • pp.209-217
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    • 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.

A Study on the Effects of Determinants of Casino Security Management Service Quality on Organizational Trust and Loyalty of Internal Customers (카지노 보안관리 서비스품질 결정요인이 내부고객의 조직신뢰 및 충성도에 미치는 영향)

  • Lee, Seung-Hoon;Kang, Min-Wan;Chun, Yong-Tae
    • Korean Security Journal
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    • no.42
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    • pp.115-153
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    • 2015
  • This study identified the cause-and-effect relationship of security management service quality by empirically analyzing whether the performance factors affecting the casino industry are improved when the quality of the security management service is improved. For this, Partial Least Squares (PLS) that can deduce the structural relationship between variables was used. To verify the representativeness of the population, SPSS 19.0 was utilized in a demographic analysis, a independent T-test and Scheffe test. The analysis of the data revealed that the casino industry must preferentially manage assurance, empathy, and security to improve the casino security management service quality, and that, of these, security was the most important factor. To help improve service quality, a theoretical and empirical basis that can consider the importance and priority of individual factors was presented based on the result of this analysis. It also revealed that the security management service is an essential factor for stable business activities of casinos. Further, the importance of the role of the security management service in business strategy formulation for improving the industry performance was recognized through the study results. A service quality improvement method was provided by focusing on the factors that must be preferentially considered for service quality improvement; moreover, implications that can predict the results of such method were presented.

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Predicting Calcium and Phosphorus Concentrations in Imported Hay by near Infrared Reflectance Spectroscopy (근적외선분광법을 이용한 수입건초의 Ca과 P 함량 예측)

  • Lee, Bae Hun;Kim, Ji Hye;Oh, Mirae;Lee, Ki Won;Park, Hyung Soo
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.41 no.1
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    • pp.29-34
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    • 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.

Prediction of the Digestibility and Energy Value of Corn Silage by Near Infrared Reflectance Spectroscopy (근적외선분광법을 이용한 옥수수 사일리지의 소화율 및 에너지 평가)

  • Park Hyung-Soo;Lee Jong-Kyung;Lee Hyo-Won;Kim Su-Gon;Ha Jong-Kyu
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.26 no.1
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    • pp.45-52
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    • 2006
  • This study was carried out to explore the accuracy of Near Infrared Reflectance Spectroscopy (NIRS) fer the prediction of digestibility and energy value of corn silages. The spectral data were regressed against a range of digestibility and energy parameters using modified partial least squares(MPLS) multivariate analysis in conjunction with first and second order derivatization, with scatter correction procedure(SNV-Detrend) to reduce the effect of extraneous noise. Calibration models for NIRS measurements gave multivariate correlation coefficients of determination$(R^2)$ and standard errors of cross validation of 0.92(SECV 1.73), 0.91(SECV 1.13) and 0.93(SECV 1.74) for in vitro dry matter digestibility(IVDMD), in vitro true digestibility(IVTD), and cellulase dry matter digestibility(CDMD), respectively. The standard error of prediction(SEP) and the multiple correlation coefficient of validation$(R^2v)$ on the validation set(n=39) was used in comparing the prediction accuracy. The SEP value was 0.30(TDN), 0.01(NEL), and 0.01(ME). The relative ability of NIRS to predict digestibility and energy value was very good for CDMD, total digestible nutrients(TDN), net energy fer lactation(NEL) and metabolizable energy(ME). This paper shows the potential of NIRS to predict the digestibility and energy value of con silage as a routine method in feeding programmes and for giving advice to farmers.

DETERMINATION OF MOISTURE AND NITROGEN ON UNDRIED FORAGES BY NEAR INFRARED REFLECTANCE SPECTROSCOPY(NIRS)

  • Cozzolino, D.;Labandera, M.;Inia La Estanzuela
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1620-1620
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    • 2001
  • Forages, both grazed and conserved, provide the basis of ruminant production systems throughout the world. More than 90 per cent of the feed energy consumed by herbivorous animals world - wide were provided by forages. With such world - wide dependence on forages, the economic and nutritional necessity of been able to characterize them in a meaningful way is vital. The characterization of forages for productive animals is becoming important for several reasons. Relative to conventional laboratory procedures, Near Infrared Reflectance Spectroscopy (NIRS) offers advantages of simplicity, speed, reduced chemical waste, and more cost-effective prediction of product functionality. NIR spectroscopy represents a radical departure from conventional analytical methods, in that entire sample of forage is characterized in terms of its absorption properties in the near infrared region, rather than separate subsamples being treated with various chemicals to isolate specific components. This forces the analyst to abandon his/her traditional narrow focus on the sample (one analyte at a time) and to take a broader view of the relationship between components within the sample and between the sample and the population from which it comes. forage is usually analysed by NIRS in dry and ground presentation. Initial success of NIRS analysis of coarse forages suggest a need to better understand the potential for analysis of minimally processed samples. Preparation costs and possible compositional alterations could be reduced by samples presented to the instrument in undried and unground conditions. NIRS has gained widespread acceptance for the analysis of forage quality constituents on dry material, however little attention has been given to the use of NIRS for chemical determinations on undried and unground forages. Relatively few works reported the use of NIRS to determine quality parameters on undried materials, most of them on both grass and corn silage. Only two works have been found on the determination of quality parameters on fresh forages. The objectives of this paper were (1) to evaluate the use of NIRS for determination of nitrogen and moisture on undried and unground forage samples and (2) to explore two mathematical treatments and two NIR regions to predict chemical parameters on fresh forage. Four hundred forage samples (n: 400) were analysed in a NIRS 6500 instrument (NIR Systems, PA, USA) in reflectance mode. Two mathematical treatments were applied: 1,4,4,1 and 2,5,5,2. Predictive equations were developed using modified partial least squares (MPLS) with internal cross - validation. Coefficient of determination in calibration (${R^2}_{CAL}$) and standard error in cross-validation (SECV) for moisture were 0.92 (12.4) and 0.92 (12.4) for 1,4,4,1 and 2,5,5,2 respectively, on g $kg^{-1}$ dry weight. For crude protein NIRS calibration statistics yield a (${R^2}_{CAL}$) and (SECV) of 0.85 (19.8) and 0.85 (19.6) for 1,4,4,1 and 2,5,5,2 respectively, on a dry weight. It was concluded that NIRS is a suitable method to predict moisture and nitrogen on fresh forage without samples preparation.

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The Use of Near Infrared Reflectance Spectroscopy (NIRS) for Broiler Carcass Analysis

  • Hsu, Hua;Zuidhof, Martin J.;Recinos-Diaz, Guillermo;Wang, Zhiquan
    • 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.

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