• Journal of Crop Science and Biotechnology
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• 제10권1호
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• pp.13-18
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• 2007

Near-infrared spectroscopy(NIRS) was used as a rapid and nondestructive method to determine the fatty acid composition in intact seed samples of rapeseed(Brassica napus L.). A total of 349 samples(about 2 g of intact seeds) were scanned in the reflectance mode of a scanning monochromator, and the reference values for fatty acid composition were measured by gas-liquid chromatography. Calibration equations for individual fatty acids were developed using the regression method of modified partial least-squares with internal cross validation(n=249). The equations had low SECV(standard errors of cross-validation), and high $R^2$(coefficient of determination in calibration) values(>0.8) except for palmitic and eicosenoic acid. Prediction of an external validation set(n=100) showed significant correlation between reference values and NIRS estimated values based on the SEP(standard error of prediction), $r^2$(coefficient of determination in prediction), and the ratio of standard deviation(SD) of reference data to SEP. The models developed in this study had relatively higher values(> 3.0 and 0.9, respectively) of SD/SEP(C) and $r^2$ for oleic, linoleic, and erucic acid, characterizing those equations as having good quantitative information. The results indicated that NIRS could be used to rapidly determine the fatty acid composition in rapeseed seeds in the breeding programs for high quality rapeseed oil.

• Asian-Australasian Journal of Animal Sciences
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• 제17권12호
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• pp.1736-1740
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• 2004

Since the application of relatively high levels of heavy metals in the compost poses a potential hazard to plants and animals, the content of heavy metals in the compost with animal manure is important to know if it is as a fertilizer. Measurement of heavy metals content in the compost by chemical methods usually requires numerous reagents, skilled labor and expensive analytical equipment. The objective of this study, therefore, was to explore the application of near-infrared reflectance spectroscopy (NIRS), a nondestructive, cost-effective and rapid method, for the prediction of heavy metals contents in compost. One hundred and seventy two diverse compost samples were collected from forty-seven compost facilities located along the Han river in Korea, and were analyzed for Cr, As, Cd, Cu, Zn and Pb levels using inductively coupled plasma spectrometry. The samples were scanned using a Foss NIRSystem Model 6500 scanning monochromator from 400 to 2,500 nm at 2 nm intervals. The modified partial least squares (MPLS), the partial least squares (PLS) and the principal component regression (PCR) analysis were applied to develop the most reliable calibration model, between the NIR spectral data and the sample sets for calibration. The best fit calibration model for measurement of heavy metals content in compost, MPLS, was used to validate calibration equations with a similar sample set (n=30). Coefficient of simple correlation (r) and standard error of prediction (SEP) were Cr (0.82, 3.13 ppm), As (0.71, 3.74 ppm), Cd (0.76, 0.26 ppm), Cu (0.88, 26.47 ppm), Zn (0.84, 52.84 ppm) and Pb (0.60, 2.85 ppm), respectively. This study showed that NIRS is a feasible analytical method for prediction of heavy metals contents in compost.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1251-1251
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• 2001

The routine analysis of milk chemical components is of major importance both for the management of animals in dairy farms and for quality control in dairy industries. NIRS technology is an analytical technique which greatly simplifies this routine. One of the most critical aspects in NIRS analysis of milk is sample preparation and analysis modes which should be fast and straightforward. An important difficulty when obtaining NIR spectra of milk is the high water content (80 to 90%) of this product, since water absorbs most of the infrared radiation, and, therefore, limits the accuracy of calibrating for other constituents. To avoid this problem, the DESIR system was set up. Other ways of radiation-sample interaction adapted for liquids or semi-liquids exist, which are practically instantaneous and with limited or null necessity of sample preparation: Transmission and Folded Transmission or Transflectance. The objective of the present work is to compare the precision and accuracy of milk calibration equations in two analysis modes: Reflectance (dry milk) and Folded Transmission (liquid milk). A FOSS-NIR Systems 6500 I spectrophotometer (400-2500 nm) provided with a spinning module was used. Two NIR spectroscopic methods for milk analysis were compared: a) folded transmission: liquid milk samples in a 0.1 pathlength sample cell (ref. IH-0345) and b) reflectance: dried milk samples in glass fibre filters placed in a standard ring cell. A set of 101 milk samples was used to develop the calibration equations, for the two NIR analysis modes, to predict casein, protein, fat and dry matter contents, and 48 milk samples to predict Somatic Cell Count (SCC). The calibrations obtained for protein, fat and dry matter have an excellent quantitative prediction power, since they present $r^2$ values higher than 0.9. The $r^2$ values are slightly lower for casein and SCC (0.88 and 0.89 respectively), but they still are sufficiently high. The accuracy of casein, protein and SCC equations is not affected by the analysis modes, since their ETVC values are very similar in reflectance and folded transmission (0.19% vs 0.21%; 0.16% vs 0.19% and 55.57% vs 53.11% respectively), Lower SECV values were obtained for the prediction of fat and dry matter with the folded transmission equations (0.14% and 0.25% respectively) compared to the results with the reflectance ones (0.43% and 0.34% respectively). In terms of accuracy and speed of analytical response, NIRS analysis of liquid milk is recommended (folded transmission), since the drying procedure takes 24 hours. However, both analysis modes offer satisfactory results.

• 한국작물학회지
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• 제39권5호
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• pp.489-494
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• 1994

맥주보리 품질에서 중요한 성분인 단백질함량을 NIRS를 이용하여 신원하고 정확하게 분석하기 위해 최적의 검양식 작성에 관한 일련의 시험을 실시한 결과는 다음과 같다. 1. Micro-Kjeldahl법에 의해 분석한 단백질함량을 이용하여 작성된 NIRS의 검양식중 2095 /1941/ 2282/ 2086nm 파장으로 구성된 검양식에서 결정계수($R^2$)가 0.95로서 가장 높았다. 2. NIRS의 2095/1941/2282/2086nm 파장으로 구성된 검양식으로 '92년도에 생산된 18품종을 분석한 결과 SDD가 0.47, SEP가 0.43, r이 0.95로서 매우 우수하였으며 평균 단백질함량도 Micro-Kjeldahl법의 10.25%와 동일하였다. 3. NIRS의 2095/1941/2282/2086nm 파장으로 구성된 검양식으로 '93년에 생산된 미지의 시료 31품종을 Micro-Kjeldahl법과 비교분석한 결과 SDD가 0.69, SEP가 0.67, r(simple correlation)이 0.91이었다. 4. 본 시험에서 작성된 NIRS의 검양식을 이용할 경우 Micro-Kjeldahl 분석치와 r값이 0.91로서 고도의 유의성이 인정되었으며 bias값을 보정해 주면 단백질함량의 평균값이 Micro-Kjeldahl법과 매우 근접된 값을 얻을 수 있어서 맥주보리 육종의 초기세대에서 단기간 다량의 계통을 분석할 수 있을 것으로 기대되었다.

• Current Optics and Photonics
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• 제6권5호
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• pp.489-496
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• 2022

Our previous study on monitoring cerebral oxygenation with a variation of isoflurane concentration in a rat model showed that near-infrared spectroscopy (NIRS) signals have potential as a new depth of anesthesia (DOA) index. However, that study obtained results from the brain in a completely invasive way, which is inappropriate for clinical application. Therefore, in this follow-up study, it was investigated whether the NIRS signals measured in a minimally invasive model including the skull and cerebrospinal fluid layer (CSFL) are similar to the previous study used as a gold standard. The experimental method was the same as the previous study, and only the subject model was different. We continuously collected NIRS signals before, during, and after isoflurane anesthesia. The isoflurane concentration started at 2.5% (v/v) and decreased to 1.0% by 0.5% every 5 min. The results showed a positive linear correlation between isoflurane concentration and ratio of reflectance intensity (RRI) increase, which is based on NIRS signals. This indicates that the quality of NIRS signals passed through the skull and CSFL in the minimally invasive model is as good as the signal obtained directly from the brain. Therefore, we believe that the results of this study can be easily applied to clinics as a potential indicator to monitor DOA.

• 한국초지조사료학회지
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• 제34권3호
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• pp.214-218
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• 2014

This study was conducted to assess the feasibility of near-infrared reflectance spectroscopy (NIRS) as a rapid and reliable method for the estimation of crude protein (CP) fractions in forage legume mixtures (sudangrass and pea mixture, and kidney bean and potato mixture). A total of 178 samples were collected and their spectral reflectance obtained in the range of 400~2,500 nm. Of these, 50 samples were selected for calibration and validation, and 35 samples were used for calibration of the data set, and the modified partial least square regression (MPLSR) analysis was performed. The correlation coefficient ($r^2$) and the standard error of cross-validation (SECV) of the calibration models in the CP fractions, A, B1, B2, B3, and C, were 0.94 (1.05), 0.92 (0.74), 0.96 (0.95), 0.91 (0.42), and 0.83 (0.38), respectively. Fifteen samples were used for equation validation, and the $r^2$ and the standard error of prediction (SEP) were 0.87 (1.45), 0.91 (0.49), 0.94 (1.13), 0.36 (0.96), and 0.74 (0.67), respectively. This study showed that NIRS could be an effective tool for the rapid and precise estimation of CP fractions in forage legume mixtures.

• 한국응용과학기술학회지
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• 제16권2호
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• pp.155-161
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• 1999

Red pepper powder (Capsicum annum L.) is an important seasoning as a kimchi ingredient in korea and most korean consumer tend to eat the korean red pepper powder as the better than other oriental country such as China. Near infrared reflectance spectroscopy (NIRS) was applied for discrimination according to geographical origin (Korea, China) of red pepper powder. The objective of this study is to determine if NIR technique could be used to discriminate between the korean red pepper powder and non-korean red pepper powder according to seed content and maxing ratio in red pepper powder by using the new method. Rapid, precise and nondestructive analysis method for determination of the geographical origin of red pepper powder by near infrared spectroscopy and chemometrics were performed. It has been observed discriminant analysis with PLS is adequate to determinate the geographical origin of red pepper powder. It tend to difficult the discrimination of geographical origin according to increase the seed content of red pepper powder. The accuracy of discrimination in mixed red pepper powder was range from 95.2% to 100%.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2001년도 춘계 학술대회지
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• pp.84-85
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• 2001

• 한국작물학회지
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• 제64권4호
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• pp.353-365
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• 2019

본 연구는 근적외선 분광분석기(NIRS) 예측모델을 설정하여 유전자원 대량분석 체계를 확립하고 그에 따른 국내 외 밀 자원의 단백질 함량에 관한 기초 정보를 제공하고자 하였다. 1. 농업유전자원센터에 보유하고 있는 20,000여 자원 중 1,798자원을 검량 자원으로 선발하였다. 검량자원의 NIR 스펙트럼을 측정하였고, 단백질 함량 습식분석 데이터 입력 등 일련의 통계적 처리 과정을 거쳐 NIRS 예측모델을 설정했다. 검량 자원의 다양성 지수는 0.80이었고, 습식 분석법에 의한 단백질 평균은 13.2%, 함량 구간은 7.0-20.8%였다. 최적화된 NIRS 모델의 R², SEC, Slope은 0.997, 0.132, 1.000이었다. 300자원을 사용하여 외부 검정 과정을 실시하였고 R², SEP, Slope은 0.994, 0.191, 1.013이었다. 최적화된 NIRS 모델과 외부검정 결과의 통계치가 상호 유사하였고, 1에 가까운 R²와 Slope 값, 낮은 SEC와 SEP 값을 볼 때 본 연구에서 설정한 NIRS 모델은 습식 분석법을 대체하여 밀 자원의 단백질 함량 분석에 적용 가능할 것으로 판단되었다. 2. 국내외 수집된 밀 6,794자원의 NIRS 단백질 함량 측정값을 정규분포로 작성하여 특성을 파악했다. 자원의 다양성 지수는 0.79, 단백질 평균은 12.1%, 전체 자원의 임의구간 42.1% 단백질 함량자원 범위는 10-13%이었으며, 68.0%를 차지하는 자원들의 단백질 함량 범위는 9.5-14.7%였다. 3. 전체 6,794자원의 품종 집단 구성은 육성계통 3,128자원, 재래종 2,705자원, 육성품종 961자원이었다. 육성계통 자원의 다양성 지수는 0.80, 단백질 평균은 11.8%, 전체 자원의 68%를 차지하는 자원들의 함량 범위는 9.2-14.5%였다. 재래종 자원의 다양성 지수는 0.76, 단백질 평균은 12.1%, 전체 자원의 68.0%를 차지하는 자원들의 함량 범위는 9.8-14.4%였다. 육성품종 자원의 다양성 지수는 0.80, 단백질 평균은 12.8%, 전체 자원의 68.0%를 차지하는 자원들의 함량 범위는 10.2-15.4%였다. 재래종 자원은 가장 낮은 다양성 지수를 나타냈고, 육성계통과 육성품종은 동일한 다양성 지수를 나타냈다. 육성계통은 가장 낮은 단백질 평균을 나타냈고, 육성품종은 가장 높은 단백질 평균을 나타냈다.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1265-1265
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• 2001

The organic materials included in excreta of livestock are important resources for organic manure and for improving soil quality, although there is still far from effective using. One reason for this is still unclearly standard of quality for evaluation of manure made from excreta of livestock. Therefore, the objective of this study is to develop rapid and accurate analytical method for analyzing organic compositions of manure made from excreta of livestock, and to establish quality evaluation method based on the compositions predicted by near infrared reflectance spectroscopy (NIRS). Sixteen samples of manure, each eight samples prepared from two treatments, were used in this study. The manure samples were prepared by mixing 560 kg feces of swine,60 kg sawdust with moisture content was adjusted to be 65%. The mixture was then keep under two kinds of shelter, black and clear sheets, as a treatment on the effect of sunlight. Samples were taken in every week (form week-0 to 7) during the process of manure making. Samples were analyzed to determine neutral detergent fiber (NDF), acid detergent fiber (ADF) and acid detergent lignin (ADL) by detergent methods, and organic cell wall (OCW) and fibrous content of low digestibility in OCW (Ob) by enzymatic methods. Biological oxygen demand (BOD) was analyzed by coulometric respirometer method. These compositions were carbohydrateds and lignin that were hardly digested. Spectra of samples were scanned by NIR instrument model 6500 (Pacific Scientific) and read over the range of wavelength between 400 and 2500nm. Calibration equations were developed using eight manure samples collected from black sheet shelter, while prediction was conducted to the other eight samples from clear sheet shelter. Accuracy of NTRS prediction was evaluated by correlation coefficients (r), standard error of prediction (SEP) and ration of standard deviation of reference data in prediction sample set to SEP (RPD). The r, SEP and RPD value of forage were 0.99, 0.69 and 7.6 for ADL, 0.96, 1.03 and 4.1 for NDF, 0.98, 0.60 and 4.9 for ADF, 0.92, 1.24 and 2.6 for Ob, and 0.91, 1.02 and 7.3 for BOD, respectively. The results indicated that NIRS could be used to measure the organic composition of forage used in manure samples.