• Journal of the Korean Society of Tobacco Science
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• v.20 no.2
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• pp.183-190
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• 1998

This study was conducted to analyze chemical components in flue-cured tobacco using near infrared spectroscopy(NIRS). Samples were collected in '96 and '97 crop year and were scanned in the wavelengths of 400 ～ 2500 nm by near infrared analyzer(NIRSystem Co., Model 6500). Calibration equations were developed and then analyzed flue-cured samples by NIRS. The standard error of calibration(SEC) and performance (SEP) of '96 crop year samples between NIRS and standard laboratory analysis(SLA) were 0.18% and 0.24% for nicotine, 1.60% and 1.77% for total sugar, 0.13% and 0.15% for total nitrogen, 0.58% and 0.68% for crude ash, 0.23% and 0.28% for ether extracts, and 0.09% and 0.08% for chlorine, respectively. The coefficient of determination($R^2$) of calibration and prediction samples between NIRS and SLA of '96 crop year samples was 0.94～0.99 and 0.83～0.97 depending on chemical components, respectively. The SEC and SEP of '97 crop year samples were similar to those of '96 crop year samples. The SEP of '97 crop year samples which were analyzed using '96 calibration equation was 0.32 % for nicotine, 2.72% for total sugar, 0.14 % for total nitrogen, 1.00 % for crude ash, 0.48 for ether extracts and 0.17% for chlorine, respectively. The prediction result was more accurate when calibration and prediction samples were produced in the same crop year than those of the different crop year. The SEP of '96 and '97 crop year samples using calibration equation which was developed '96 plus '97 crop year samples was similar to that of '96 crop year samples using 96 calibration equation and that of '97 crop year samples using '97 calibration equation, respectively. The SEP of '97 crop year samples using calibration equation which was developed '96 plus '97 crop year samples was lower than that of '97 crop year samples analyzed by '96 calibration equation. To improve the analytical inaccuracy caused by the difference of crop year between calibration and prediction samples, we need to include the prediction sample spectra which are different from calibration sample spectra in recalibration sample spectra, and then develop recalibration equation. Although the analytical result using NIR is not as good as SLA, the chemical component analysis using NIR can apply to tobacco leaves, leaf process or tobacco manufacturing process which demand the rapid analytical result.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.39 no.5
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• pp.489-494
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• 1994

Near Infrared Reflectance Spectroscopy(NIRS) has been used as a tool for the rapid, accurate, protein assay of malting barley. NIRS used in this study was filter type instruments, Neotec 102. The objective of this study was to obtain the best calibration equation, for the rapid, ease and accurate protein content analysis of malting barley using NIRS system. The optimum wavelength for protein content analysis used NIRS were 2095nm, 2095/1941nm, 2095/1941/2282nm, 2905/1941/2282/2086nm, respectively. Mean protein content with this calibration equation in NIRS analysis was 10.59%, while 10.60% in Micro-Kjeldahl one. The range of protein content in Micro-Kjeldahl was 8.66~12.66% and that in NIRS was 8.80~12.35%. When 18 other varieties produced in 1992 were analysed with 2095nm, 2095/1941nm, 2095/1941/2282nm, 2095/1941/2282/2086nm equation, standard deviation of difference (SDD)and standard error of performence(SEP) and $R^2$ values were 0.47, 0.43, 0.95, respectively. Both the mean protein content by Micro-Kjeldahl and by NIRS was 10.25%. With this equation, analysied 31 varities produced in 1993, SDD and SEP and r values were 0.69, 0.67, 0.91, respectively, and that bias value was 0.65. In this analysis, mean protein content by Micro-Kjeldahl was 10.17% and by NIRS was 10.81%. The range of protein content in Micro-Kjeldahl was 7.58~14.29%, What that in NIRS was 8.63~13.93%. After adjusted bias in the best calibration equation, mean protein content of Micro-Kjeldahl was 10.17% and that of NIRS was 10.09%, without variance of SDD, SEP and r values.

• Journal of The Korean Society of Grassland and Forage Science
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• v.29 no.3
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• pp.253-262
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• 2009

The present study was conducted to develop a rapid and accurate method of evaluating chemical composition of total mixed ration (TMR) for dairy cows using near infrared reflectance spectroscopy (NIRS). A total of 253 TMR samples were collected from TMR manufacturers and dairy farms in Korea. Prior to NIR analysis, TMR samples were dried at $65^{\circ}C$ for 48 hour and then ground to 2 mm size. The samples were scanned at 2 nm interval over the wavelength range of 400-2500 nm on a FOSS-NIR Systems Model 6500. The values obtained by NIR analysis and conventional chemical methods were compared. Generally, the relationship between chemical analysis and NIR analysis was linear: $R^2$ and standard error of calibration (SEC) were 0.701 (SEC 0.407), 0.965 (SEC 0.315), 0.796 (SEC 0.406), 0.889 (SEC 0.987), 0.894 (SEC 0.311), 0.933 (SEC 0.885) and 0.889 (SEC 1.490) for moisture, crude protein, ether extract, crude fiber, crude ash, acid detergent fiber (ADF) and neutral detergent fiber (NDF), respectively. In addition, the standard error of prediction (SEP) value was 0.371, 0.290, 0.321, 0.380, 0.960, 0.859 and 1.446 for moisture, crude protein, ether extract, crude fiber, crude ash, ADF and NDF, respectively. The results of the present study showed that the NIR analysis for unknown TMR samples would be relatively accurate. Use of the developed NIR calibration curve can obtain fast and reliable data on chemical composition of TMR. Collection and analysis of more TMR samples will increase accuracy and precision of NIR analysis to TMR.

• Journal of the Korean Society of Tobacco Science
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• v.22 no.1
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• pp.76-83
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• 2000

This study was carried out to predict blending ratio of cut tobacco(CT), expanded stem(ES), and expanded cut tobacco(ECT) in cigarettes. CT, ES, and ECT samples from A brand were, ground and blended with reference to A blending ratio, and scanned by near infrared spectroscopy(NIRSystem Co., Model 6500). Calibration equations were developed and then determined blending ratio by NIRS. The standard error of calibration(SEC) and performance(SEP) of C factory samples between NIRS and known blending ratio were 0.97%, 1.93% for CT, 0.50%, 1.12 % for ES and 0.68%, 1.10% for ECT, respectively. The SEP of CT, ES and ECT of Band D factory samples determined by C factory calibration equation were more inaccurate than those of C factory samples determined by C factory calibration equations. These results were caused by the difference of CT, ES and ECT spectra followed by each factory. The SEP of CT, ES and ECT of Band D factories determined by calibration equations derived from each factory samples were more accurate than those of determined by calibration equation derived from C factory samples. Each factory SEP of CT, ES and ECT determined by calibration equation derived from all calibration samples(B+C+D factory) was similar to that determined by calibration equation derived from each factory samples. To improve the analytical inaccuracy caused by spectra difference, we need to apply a specific calibration equation for each factory sample. Data in development of specific calibrations between sample and NIRS spectra might supply a method for rapid determination of blending ratio of CT, ES, and ECT.

• The Korean Journal of Food And Nutrition
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• v.23 no.4
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• pp.582-587
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• 2010

본 연구에서는 녹두 유전자원의 지방산 함량을 신속 대량 검정하는 기술을 개발하여 유전자원 활용 및 육종 촉진에 기여하고자 하였다. 유전자원 평가에 적합한 신속하고 비파괴적인 지방산 함량 평가기술을 개발하기 위해 공시자원 1,125점의 녹두 종자를 종실상태와 분쇄한 분말상태로 근적외선분광분석기(NIR)를 이용하여 1,104~2,494 nm에서의 스펙트럼을 얻고 이들 중 스펙트럼이 중복되지 않는 원산지가 다양한 대표자원 106점을 선발하여 일반적인 방법으로 지방산 함량을 분석하고, 이 값과 NIR 스펙트럼 흡광도값 간의 상관분석을 위한 calibration set로 활용하였다. 그 결과 palmitic acid, stearic acid, oleic acid, linoleic acid, linolenic acid 및 total fatty acid에 대한 NIR 흡광도와의 상관계수 $R^2$이 각각 0.74, 0.18, 0.12, 0.72, 0.48 및 0.78로 나타났고, 이들 중 $R^2$가 높은 검량식을 미지의 시료 10점으로 검증한 결과, palmitic, linoleic 및 total fatty acid에 대한 검증 상관계수 $R^2$이 0.96, 0.74, 0.81로 나타나, 다양한 녹두 유전자원의 지방산함량 신속 대량 예측에 유효하게 활용될 수 있는 것으로 나타났다. 한편, 공시된 녹두 유전자원 115점 중에서 자원번호 IT208075 자원은 저 지방산 자원($14.24\;mg\;g^{-1}$)으로 선발되었고, IT163279 자원은 고 지방산 자원($18.43\;mg\;g^{-1}$)으로 선발되어 향후 녹두작물의 성분육종에 유용할 것으로 생각된다.