• 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.

• Journal of Biosystems Engineering
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• 제38권1호
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• pp.48-54
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• 2013

Purpose: This study evaluated the feasibility of using a discrete wavelet transform (DWT) method as a preprocessing tool for visible/near-infrared spectroscopy (VIS/NIRS) with a spectroscopic transmittance dataset for predicting the internal quality of cherry tomatoes. Methods: VIS/NIRS was used to acquire transmittance spectrum data, to which a DWT was applied to generate new variables in the wavelet domain, which replaced the original spectral signal for subsequent partial least squares (PLS) regression analysis and prediction modeling. The DWT concept and its importance are described with emphasis on the properties that make the DWT a suitable transform for analyzing spectroscopic data. Results: The $R^2$ values and root mean squared errors (RMSEs) of calibration and prediction models for the firmness, sugar content, and titratable acidity of cherry tomatoes obtained by applying the DWT to a PLS regression with a set of spectra showed more enhanced results than those of each model obtained from raw data and mean normalization preprocessing through PLS regression. Conclusions: The developed DWT-incorporated PLS models using the db5 wavelet base and selected approximation coefficients indicate their feasibility as good preprocessing tools by improving the prediction of firmness and titratable acidity for cherry tomatoes with respect to $R^2$ values and RMSEs.

• 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.1516-1516
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• 2001

During the recent years, wine analysis has played an increasing role due the health benefits of phenolic ingredients in red wine [1]. On the other hand there is the need to be able to distinguish between different wine varieties. Consumers want to know if a wine is an adulterated one or if it is based on the pure grape. Producers need to certificate their wines in order to ensure compliance with legal regulations. Up to now, the attempts to investigate the origin of wines were based on high-performance liquid chromatography (HPLC), gas chromatography (GC) and pyrolysis mass spectrometry (PMS) [l,2,3]. These methods need sample pretreatment, long analysis times and therefore lack of high sample throughput. In contradiction to these techniques using near infrared spectroscopy (NIRS), no sample pretreatment is necessary and the analysis time for one sample is only about 10 seconds. Hence, a near infrared spectroscopic method is presented that allows a fast classification of wine varieties in bottled red wines. For this, the spectra of 50 bottles of Cabernet Sauvignon, Lagrein and Sangiovese (Chianti) were recorded without any sample pretreatment over a wavelength range from 1000 to 2500 nm with a resolution of 12 cm$\^$-1/. 10 scans were used for an average spectrum. In order to yield best reproducibility, wines were thermostated at 23$^{\circ}C$ and a optical layer thickness of 3 mm was used. All recorded spectra were partitioned into a calibration and validation set (70% and 30%). Finally, a 3d scatter plot of the different investigated varieties allowed to distinguish between Cabernet Sauvignon, Lagrein and Sangiovese (Chianti). Considering the short analysis times this NRS-method will be an interesting tool for the quality control of wine verification and also for experienced sommeliers.

• Asian-Australasian Journal of Animal Sciences
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• 제18권7호
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• pp.1036-1040
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• 2005

Near-infrared reflectance spectroscopic (NIRS) calibrations were developed for accurate and fast prediction of whole broiler chicken carcass composition. The Feed and Forage Foss systems Model 5000 Reflectance Transport Model 5000 with near-infrared reflectance spectroscopy (NIRS)-WinISI II windows software was used for this purpose. One equation was developed for the prediction of each carcass component. One hundred and fifty freeze dried broiler whole carcass samples were ground in a Cyclotech 1,093 sample mill and analyzed for dry matter, protein, fat, calcium and phosphate. Samples were divided into two sets: a calibration set from which equations were derived and a prediction set used to validate these equations. The chemical analysis values (mean${\pm}$SD) were calculated based on dry matter basis as follows: dry matter: 33.41${\pm}$2.78 (range: 26.41-43.47), protein: 54.04${\pm}$6.63 (range: 36.20-76.09), fat 35.44${\pm}$8.34 (range: 7.50-55.03), calcium 2.55${\pm}$0.65 (range: 0.99-4.41), phosphorus 1.38${\pm}$0.26 (range: 0.60-2.28). One hundred and three samples were used to calibrate the equations and prediction values. The software used was modified to obtain partial least square regression statistics, as it is the most suitable for natural products analysis. The coefficients of determination ($R^2$) and the standard errors of prediction were 0.82 and 1.83 for the dry matter, 0.96 and 1.98 for protein, 0.99 and 1.07 for fat, 0.90 and 0.30 for calcium and 0.91 and 0.11 for phosphorus, respectively. The present study indicated that NIRS can be calibrated to predict the whole broiler carcass chemical composition, including minerals in a rapid, accurate, and cost effective manner. It neither requires skilled operators nor generates hazardous waste. These findings may have practical importance to improve instrumental procedures for quick evaluation of broiler carcass composition.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1182-1182
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• 2001

In this study, the newly constructed optical measurement system, which was mainly composed of a parametric tunable laser and a near infrared photoelectric multiplier, was introduced to clarify the optical characteristics of wood as discontinuous body with anisotropic cellular structure from the viewpoint of the time-of-flight near infrared spectroscopy (TOF-NIRS). The combined effects of the cellular structure of wood sample, the wavelength of the laser beam λ, and the detection position of transmitted light on the time resolved profiles were investigated in detail. The variation of the attenuance of peak maxima At, the time delay of peak maxima Δt and the variation of full width at half maximum Δw were strongly dependent on the feature of cellular structure of a sample and the wavelength of the laser beam. The substantial optical path length became about 30 to 35 times as long as sample thickness except the absorption band of water. Δt ${\times}$ Δw representing the light scattering condition increased exponentially with the sample thickness or the distance between the irradiation point and the end of sample. Around the λ=900-950 nm, there may be considerable light scattering in the lumen of tracheid, which is multiple specular reflection and easy to propagate along the length of wood fiber. Such tendency was remarkable for soft wood with the aggregate of thin layers of cell walls. When we apply TOF-NIRS to the cellular structural materials like wood, it is very important to give attention to the difference in the light scattering within cell wall and the multiple specular-like reflections between cell walls. We tried to express the characteristics of the time resolved profile on the basis of the optical parameters for light propagation determined by the previous studies, which were absorption coefficient K and scattering coefficient S from Kubelka-Munk theory and n from nth power cosine model of radiant intensity. The wavelength dependency of the product of K/S and n, which expressed the light-absorbing and -scattering condition and the degree of anisotropy, respectively, was similar to that of the time delay of peak maxima Δt. The variation of the time resolved profile is governed by the combination of these parameters. So, we can easily find the set of parameters for light propagation synthetically from Δt.

• 한국초지조사료학회지
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• 제37권4호
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• pp.350-357
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• 2017

Near infrared spectroscopy (NIRS) is a rapid and accurate method for analyzing the quality of cereals, and dried animal forage. However, one limitation of this method is its inability to measure fermentation parameters in dried and ground samples because they are volatile, and therefore, respectively lost during the drying process. In order to overcome this limitation, in this study, fresh coarse haylage was used to test the potential of NIRS to accurately determine chemical composition and fermentation parameters. Fresh coarse Italian ryegrass haylage samples were scanned at 1 nm intervals over a wavelength range of 680 to 2500 nm, and optical data were recorded as log 1/reflectance. Spectral data, together with first- and second-order derivatives, were analyzed using partial least squares (PLS) multivariate regressions; scatter correction procedures (standard normal variate and detrend) were used in order to reduce the effect of extraneous noise. Optimum calibrations were selected based on their low standard error of cross validation (SECV) values. Further, ratio of performance deviation, obtained by dividing the standard deviation of reference values by SECV values, was used to evaluate the reliability of predictive models. Our results showed that the NIRS method can predict chemical constituents accurately (correlation coefficient of cross validation, $R_{cv}^2$, ranged from 0.76 to 0.97); the exception to this result was crude ash ($R_{cv}^2=0.49$ and RPD = 2.09). Comparison of mathematical treatments for raw spectra showed that second-order derivatives yielded better predictions than first-order derivatives. The best mathematical treatment for DM, ADF, and NDF, respectively was 2, 16, 16, whereas the best mathematical treatment for CP and crude ash, respectively was 2, 8, 8. The calibration models for fermentation parameters had low predictive accuracy for acetic, propionic, and butyric acids (RPD < 2.5). However, pH, and lactic and total acids were predicted with considerable accuracy ($R_{cv}^2$ 0.73 to 0.78; RPD values exceeded 2.5), and the best mathematical treatment for them was 1, 8, 8. Our findings show that, when fresh haylage is used, NIRS-based calibrations are reliable for the prediction of haylage characteristics, and therefore useful for the assessment of the forage quality.

• 전기학회논문지
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• 제61권7호
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• pp.1049-1055
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• 2012

We measure the hemodynamic responses during the 4 kinds of tasks on the motor cortex in the right and left human brain by using near-infrared spectroscopy. The experimental results show that the change of concentration of oxy-hemoglobin is larger than that of deoxy-hemoglobin and the change of concentration of chromophores induced by finger and arm related task show more activations than that of leg.

• 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.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1511-1511
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• 2001

Energy content, expressed as calories per gram, is an important part of the evaluation and marketing of foods in developed countries. Currently accepted methods of measurement of energy by U.S. food labeling legislation include measurement of gross calories by bomb calorimetry with an adjustment for undigested protein and by calculation using specific factors for the energy values of protein, carbohydrate less the amount of insoluble dietary fiber, and total fat. The ability of NIRS to predict the energy value of diverse, processed and unprocessed cereal food products was investigated. NIR spectra of cereal products were obtained with an NIR Systems monochromator and the wavelength range used for analysis was 1104-2494 nm. Gross energy of the foods was measured by oxygen bomb calorimetry (Parr Manual No. 120) and expressed as calories per gram (CPGI, range 4.05-5.49 cal/g). Energy value was adjusted for undigested protein (CPG2, range 3.99-5.38 cal/g) and undigested protein and insoluble dietary fiber (CPG3, range 2.42-5.35 cal/g). Using a multivariate analysis software package (ISI International, Inc.) partial least squares models were developed for the prediction of energy content. The standard error of cross validation and multiple coefficient of determination for CPGI using modified partial least squares regression (n=127) was 0.060 cal/g and 0.95, respectively, and the standard error of performance, coefficient of determination, bias and slope using an independent validation set (n=59) were 0.057 cal/g, 0.98, -0.027 cal/g and 1.05 respectively. The PLS loading for factor 1 (Pearson correlation coefficient 0.92) had significant absorption peaks correlated to C-H stretch groups in lipid at 1722/1764 nm and 2304/2346 nm and O-H groups in carbohydrate at 1434 and 2076 nm. Thus the model appeared to be predominantly influenced by lipid and carbohydrate. Models for CPG2 and CPG3 showed similar trends with standard errors of performance, using the independent validation set, of 0.058 and 0.088 cal/g, respectively, and coefficients of determination of 0.96. Thus NIRS provides a rapid and efficient method of predicting energy content of diverse cereal foods.