• 한국작물학회지
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• 제46권5호
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• pp.401-406
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• 2001

The applicability of non-destructive near infrared reflectance spectroscopic (NIRS) method was tested to determine the protein and oil contents of intact soybean [Glycine max (L.) Merr.] seeds. A total of 198 soybean calibration samples and 101 validation samples were used for NIRS equation development and validation, respectively. In the developed non-destructive NIRS equation for analysis of protein and oil contents, the most accurate equation was obtained at 2, 8, 6, 1(2nd derivative, 8 nm gap, 6 points smoothing, and 1 point second smoothing) and 2, 1, 20, 10 math treatment conditions with Standard Normal Variate and Detrend (SNVD) scatter correction method and entire spectrum (400-2500 nm) by using Modified Partial Least Squares (MPLS) regression, respectively. Validation of these non-destructive NIRS equations showed very low bias (protein: 0.060%, oil: -0.017%) and standard error of prediction (SEP, protein: 0.568 %, oil : 0.451 %) as well as high coefficient of determination ($R^2$, protein: 0.927, oil: 0.906). Therefore, these non-destructive NIRS equations can be applicable and reliable for determination of protein and oil content of intact soybean seeds, and non-destructive NIRS method could be used as a mass screening technique for selection of high protein and oil soybean in breeding programs.

• Food Science and Biotechnology
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• 제18권1호
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• pp.60-65
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• 2009

Near infrared reflectance spectroscopy (NIRS) was used as a rapid and non-destructive method to determine the protein content in intact and ground seeds of pea (Pisum sativum L.) germplasms grown in Korea. A total of 115 samples were scanned in the reflectance mode of a scanning monochromator at intact seed and flour condition, and the reference values for the protein content was measured by auto-Kjeldahl system. In the developed ground and intact NIRS equations for analysis of protein, the most accurate equation were obtained at 2, 8, 6, 1 math treatment conditions with standard normal variate and detrend scatter correction method and entire spectrum (400-2,500 nm) by using modified partial least squares regression (n=78). External validation (n=34) of these NIRS equations showed significant correlation between reference values and NIRS estimated values based on the standard error of prediction (SEP), $R^2$, and the ratio of standard deviation of reference data to SEP. Therefore, these ground and intact NIRS equations can be applicable and reliable for determination of protein content in pea seeds, and non-destructive NIRS method could be used as a mass analysis technique for selection of high protein pea in breeding program and for quality control in food industry.

• 식품과학과 산업
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• 제55권1호
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• pp.2-22
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• 2022

Near-infrared spectroscopy (NIRS) is one of the representative non-destructive and eco-friendly analysis methods used for rapid analysis of various ingredients in the food industry. To develop analysis model with NIRS, Chemometrics are applied after pre-treatment of spectrum. Many studies have been reviewed on the analysis of general and functional components for agricultural and livestock products. In the case of livestock products, some studies have been conducted for on-line analysis. This study investigated results on various samples and component applying near-infrared spectroscopy. Furthermore, the results according to sample condition were compared. It was confirmed that NIRS is applied to various fields in the food industry.

• 한국초지조사료학회지
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• 제24권1호
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• pp.81-90
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• 2004

Farmers need timely information on the nutritional status of their animals and the nutritive value of pastures and supplementary feeds if they are to apply successfully this existing nutritional information. Near infrared reflectance(NIR) spectroscopy has been used over the last forty years to analyse accurately protein, fiber, and other organic components in animal foods. NIR spectroscopy is a rapid, non-destructive, and non-polluting technology. When properly calibrated, NIR spectroscopy is used successfully with both concentrate and forage feeds. NIR methods predict in vitro digestibility accurately and precisely, and can predict in vivo digestibility at least as well as conventional "wet chemistry" methods such as in vivo digestion or the pepsin-cellulase method, and much more rapidly. NIR technology has been applied to the routine monitoring (through analysis of feces samples) of the nutritional status of cattle and other grazing animals. This report reviews the use of near infrared reflectance(NIR) spectroscopy to monitor the nutritive value of animal feeds and the nutritional status of grazing animals.

• 한국식품과학회지
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• 제22권6호
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• pp.675-680
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• 1990

관능검사에 의존하여 오던 종래의 고추 품질평가법을 탈피하여 매운맛 성분인 capsaicin, 적색색소인 capsanthin, total sugar 및 수분함량을 근적외 분광분석법으로 화학약품을 사용하지 않고 신속, 정확하게, 동시에 측정 할 수 있는 방법을 조사하였다. 기존의 화학분석 방법에 의해 측정한 상기 성분들의 함량치와 근적외 스펙트럼 데이타간에 중회귀분석을 행하여 각각의 성분측정을 위한 검량식을 작성하였다. 이들 검량식을 미지의 고추시료에 적용시켜 구한 분석치와 기존 분석법으로 구한 분석치를 비교한 결과, capsanthin과 total sugar는 근적외 분광분석법에 의해 정량적으로 측정할 수 있음을 알 수 있었다.

• 한국작물학회지
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• 제56권1호
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• pp.88-93
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• 2011

This experiment was carried out to find suitable sample type for the more accurate prediction and non-destructive way in the application of near infrared reflectance spectroscopy (NIRS) technique for estimation the protein, total amino acids, and total isoflavone of soybean by comparing three different sample types, single seed, whole seeds, and milled seeds powder. The coefficient of determination in calibration ($R^2$) and coefficient of determination in cross-validation (1-VR) for three components analyzed using NIRS revealed that milled powder sample type yielded the highest, followed by single seed, and the whole seeds as the lowest. The coefficient of determination in calibration for single seed was moderately low($R^2$ 0.70-0.84), while the calibration equation developed with NIRS data scanned with whole seeds showed the lowest accuracy and reliability compared with other sample groups. The scatter plot for NIRS data versus the reference data of whole seeds showed the widest data cloud, in contrary with the milled powder type which showed flatter data cloud. By comparison of NIRS results for total isoflavone, total amino acids, and protein of soybean seeds with three sample types, the powder sample could be estimated for the most accurate prediction. However, based from the results, the use of single bean samples, without grinding the seeds and in consideration with NIRS application for more nondestructive and faster prediction, is proven to be a promising strategy for soybean component estimation using NIRS.

• 한국작물학회지
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• 제51권spc1호
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• pp.283-291
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• 2006

To investigate seed non destructive and fast determination technique utilizing near infrared reflectance spectroscopy (NIRs) for screening ultra high oleic (C18:1) and linoleic (C18:2) fatty acid content sesame varieties among genetic resources and lines of pedigree generations of cross and mutation breeding were carried out in National Institute of Crop Science (NICS). 150 among 378 landraces and introduced cultivars were released to analyse fatty acids by NIRs and gas chromatography (GC). Average content of each fatty acid was 9.64% in palmitic acid (C16:0), 4.73% in stearic acid (C18:0), 42.26% in oleic acid and 43.38% in linoleic acid by GC. The content range of each fatty acid was from 7.29 to 12.27% in palmitic, 6.49% from 2.39 to 8.88% in stearic, 12.59% of wider range compared to that of stearic and palmitic from 37.36 to 49.95% in oleic and of the widest from 30.60 to 47.40% in linoleic acid. Spectrums analyzed by NIRs were distributed from 400 to 2,500 nm wavelengths and varietal distribution of fatty acids were appeared as regular distribution. Varietal differences of oleic acid content good for food processing and human health by NIRs was 14.08% of which 1.49% wider range than that of GC from 38.31 to 52.39%. Varietal differences of linoleic acid content by NIRs was 16.41% of which 0.39% narrower range than that of GC from 30.60 to 47.01%. Varietal differences of oleic and linoleic acid content in NIRs analysis were appeared relatively similar inclination compared with those of GC. Partial least square regression (PLSR) among multiple variant regression (MVR) in NIRs calibration statistics was carried out in spectrum characteristics on the wavelength from 700 to 2,500 nm with oleic and linoleic acids. Correlation coefficient of root square (RSQ) in oleic acid content was 0.724 of which 72.4 percent of sample varieties among all distributed in the range of 0.570 percent of standard error when calibrated (SEC) which were considerably acceptable in statistic confidence significantly for analysis between NIRs and GC. Standard error of cross validation (SECV) of oleic acid was 0.725 of which distributed in the range of 0.725 percent standard error among the samples of mother population between analyzed value by NIRs analysis and analyzed value by GC. RSQ of linoleic acid content was 0.735 of which 73.5 percent of sample varieties among all distributed in the range of 0.643 percent of SEC. SECV of linoleic acid was 0.711 of which distributed in the range of 0.711 percent standard error among the samples of mother population between NIRs analysis and GC analysis. Consequently, adoption NIR analysis for fatty acids of oleic and linoleic instead that of GC was recognized statistically significant between NIRs and GC analysis through not only majority of samples distributed in the range of negligible SEC but also SECV. For enlarging and increasing statistic significance of NIRs analysis, wider range of fatty acids contented sesame germplasm should be kept on releasing additionally for increasing correlation coefficient of RSQ and reducing SEC and SECV in the future.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1514-1514
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• 2001

In this paper a fast non-destructive analytical method to measure various nutrients in the intact tomato---Near infrared Spectrometry NIRs was introduced Using this method the content of some organic acid, vitamin C, reductive sugar, and solid soluble were determined simultaneously. Screen out four wavelengths at 916nm, 1000nm, 1004nm and 832nm to present optimum four optical terms of d$^2$ log(1/R) with second derivative spectra treating data scanned under these wavelengths. The multiple correlation coefficients between these values and those obtained on chemical analysis were 0.983, 0.990, 0.987, and 0.994, respectively, and the standard errors of prediction (SEP) were 0.007, 0.440, 0.037, and 0.057, respectively. These results indicate that NIRs is comparable to chemical methods in both accuracy and precision and is reliable method for determination of nutrients in intact tomato.

• 한국식품위생안전성학회지
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• 제22권4호
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• pp.257-267
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• 2007

근적외선 분광분석법을 이용하여 참기름에 혼입된 식용유지를 정성판별 및 정량할 수 있는 가능성을 조사하였다. MPLS를 이용하여 도출된 들기름, 옥수수기름, 콩기름, 채종유 검량선의 상관도는 각각 0.9992, 0.9694, 0.9795, 0.9790이었으며 검증했을때의 상관도는 각각 0.997, 0.848, 0.957, 0.968이었으며 SEP는 0.747, 5.069, 3.063, 3.000로 나타나 참기름 중 이종식용유지 분석에 활용할 수 있는 방법임이 입증되었다. 참기름에 혼입된 각 식용유지는 들기름 약 2%, 옥수수기름 및 콩기름 약 $15{\sim}20%$, 채종유 약 10% 수준에서 정성 판별 및 정량 분석이 가능한 것으로 나타났으며 이 방법을 이용하여 규격기준을 초과한 제품 48건의 이종식용유 혼입비율을 측정한 결과 들기름은 $1{\sim}16%$의 비율로 40건(22.1%), 옥수수기름은 약 40%의 비율로 3건(1.66%), 콩기름은 약 40%의 비율로 1건(0.55%)이 혼입된 것으로 나타났다. 채종유가 혼입된 참기름은 없는 것으로 나타났으며 확인이 불가능한 것이 4건으로 나타났다.

• Applied Biological Chemistry
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• 제41권2호
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• pp.153-159
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• 1998

국내산 후지 사과의 주요 내부 품질 요인인 당도, 수분 함량, 경도 및 산 함량을 근적외 분광분석법에 의해 동시에 신속, 정확하게 비파괴 측정할 수 있는지의 가능성을 조사하였다. 굴절당도계에 의한 당도, 동결 건조법에 의한 수분 함량, texture analyzer에 의한 경도 및 알칼리 적정법에 의해 얻어진 산 함량 데이터와 근적외 영역의 흡광도 데이터 사이에 각각 중회귀분석을 행한 결과, 당도, 수분 함량, 경도 및 산 함량의 측정 오차(SEP)는 각각 $0.50^{\circ}Brix,\;0.64%,\;0.14kg/cm^2$ 및 0.07%이었다. 이로서 근적외 분광 분석법을 응용하여 사과의 당도와 수분 함량은 비파괴적으로 신속, 정확하게 측정 가능함을 알 수 있었으나, 경도와 산 함량의 측정 정확도는 다소 낮은 편이었다.