• 농업과학연구
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• 제46권1호
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• pp.183-194
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• 2019

Adulteration of argan oil with some other cheaper oils with similar chemical compositions has resulted in increasing demands for authenticity assurance and quality control. Fast and simple analytical techniques are thus needed for authenticity analysis of high-priced argan oil. Raman spectroscopy is a potent technique and has been extensively used for quality control and safety determination for food products In this study, Raman spectroscopy in combination with a net analyte signal (NAS)-based methodology, i.e., hybrid linear analysis method developed by Goicoechea and Olivieri in 1999 (HLA/GO), was used to predict the different concentrations of olive oil (0 - 20%) added to argan oil. Raman spectra of 90 samples were collected in a spectral range of $400-400cm^{-1}$, and calibration and validation sets were designed to evaluate the performance of the multivariate method. The results revealed a high coefficient of determination ($R^2$) value of 0.98 and a low root-mean-square error (RMSE) value of 0.41% for the calibration set, and an $R^2$ of 0.97 and RMSE of 0.36% for the validation set. Additionally, the figures of merit such as sensitivity, selectivity, limit of detection, and limit of quantification were used for further validation. The high $R^2$ and low RMSE values validate the detection ability and accuracy of the developed method and demonstrate its potential for quantitative determination of oil adulteration.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1276-1276
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• 2001

Polycyclic aromatic hydrocarbons(PAHs) are widely distributed in the environment and are often implicated as potential carcinogens. The chromatographic methods of detection and quantitative determination of PAHs in environmental samples are costly, time consuming, and do not account for all kinds of PAHs. This work describes a quantitative spectroscopic method for the analysis of mixtures of eight PAHs using multivariate calibration models for Fourier transform near infrared(FT-NIR) spectral data. The NIR spectra of mixtures of PAHs (anthracene, pyrene, 1,2-benzanthracene, perylene, chrysene, benzo(a)pyrene, 1-methylanthracene and benzo(ghi)perylene) were measured in the wavelength range from 1100 nm to 2500 nm. The spectral data were processed using a partial least squares regression. We have studied the spectral characteristics of NIR spectra of mixtures of PAHs. It was possible to determine each PAM used in this study at the environmental level(mg L-1) in the laboratory samples. Further development may lead to the rapid determination of more PAHs in typical environmental samples.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.II
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• pp.188-195
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• 2000

This study was conducted to measure the moisture content of powdered food using RF impedance spectroscopic method. In frequency range of 1.0 to 30㎒, the impedance such as reactance and resistance of parallel plate type sample holder filled with wheat flour and red-pepper powder of which moisture content range were 5.93∼-17.07%w.b. and 10.87 ∼ 27.36%w.b., respectively, was characterized using by Q-meter (HP4342). The reactance was a better parameter than the resistance in estimating the moisture density defined as product of moisture content and bulk density which was used to eliminate the effect of bulk density on RF spectral data in this study. Multivariate data analyses such as principal component regression, partial least square regression and multiple linear regression were performed to develop one calibration model having moisture density and reactance spectral data as parameters for determination of moisture content of both wheat flour and red-pepper powder. The best regression model was one by the multiple linear regression model. Its performance for unknown data of powdered food was showed that the bias, standard error of prediction and determination coefficient are 0.179% moisture content, 1.679% moisture content and 0.8849, respectively.

• Journal of Biosystems Engineering
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• 제26권5호
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• pp.475-480
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• 2001

Sensing soil organic matter is crucial for precision farming and environment friendly agriculture. Near infra-red(NIR) was utilized to measure the soil organic matter. Multivariate calibration methods, including stepwise multiple linear regression(MLR), principal components recession(PCR) and partial least squares regression(PLS), were applied to soil spectral reflectance data to predict the organic matter content. The effect of soil particle size and water content was studied. The range of soil organic matter contents was from 0.5 to 11%. Near infrared (NIR) region from 700 to 2,500nm was applied. For uniform soil particle size, result had good correlation (R$\^$2/ = 0.984, standard error of prediction= 0.596). The effect of soil particle size could be eliminated with 1st order derivative of the NIR signal. However. moist soil had a little lower correlation. R$\^$2/ was 0.95 and standard error of prediction was 0.94% using the PLS method. The results showed the possibility of soil organic matter measurement using NIR reflectance on the field.

• Ocean Systems Engineering
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• 제14권1호
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• pp.53-72
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• 2024

The interaction of the blade of surface-piercing propellers (SPPs) with the water/air surface is a physical phenomenon that is difficult to model mathematically, so that such propellers are usually designed using empirical approaches. In this paper, a newly developed mechanism for measuring the torque of SPPs in an open water circuit is presented. The mechanism includes a single-component load cell and a deformable torque sensor to detect the forces exerted on the propeller. Deformations in the sensor elements lead to changes in the strain gauge resistance, which are converted into voltage using a Wheatstone bridge. The amplified signal is then recorded by a 16-channel data recording system. The mechanism is calibrated using a 6-DoF calibration system and a Box-Behnken design, achieving 99% accuracy through multivariate regression and ANOVA. Finally, the results of performance tests on a 4-blade propeller were presented in the form of changes in the torque coefficient as a function of feed rate. The results show that the new mechanism is 8% more accurate than conventional empirical methods.

• 한국초지조사료학회지
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• 제26권1호
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• pp.45-52
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• 2006

본 시험의 목적은 옥수수 사일리지의 소화율 및 에너지가치를 신속하고 정확하게 평가하는 방법으로서 근적외선분광법(NIRS)의 이용성을 확대하고 동시에 더욱 정확한 검량식을 유도하기 위하여 수행되었다. 112점의 옥수수 사일리지 시료를 이용하여 근적외선분광기를 이용하여 스펙트럼을 수집하였다. 검량기법은 변형부분 최소자승회귀법(MPLS), 산란보정법은 SNV-D 또한 1,4,4,1 수처리 방법을 이용하여 검량식을 작성하였다. 옥수수 사일리지의 소화율 측정방법에 따른 근적외선분광법의 예측 능력은 IVDMD, IVTD 및 CDMD 함량에서 각각 $SEP=1.57% (R^2v=0.70),\;SEP=1.13%(R^2v=0.73)$ 및 $SECV=1.74%\;(R^2v=0.77)$로 나타났으며 에너지 가치를 예측하기 위한 검량식 작성 및 검증 결과는 TDN, NEL 및 ME 함량에서 각각 SECV=0.69% $(R^2v=0.85)$, SECV=0.02% (R2v=0.88) 및 SECV=0.02% $(R^2v=0.88)$로 비교적 양호한 결과를 나타냈다.

• 비파괴검사학회지
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• 제21권1호
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• pp.80-90
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• 2001

AE 신호와 재료의 기계적 물성과의 관계를 정량적으로 제시할 수 있는 방법을 개발하였다. 재료의 여러 가지 기계적 성질들 중 피로균열 거동에 관련된 응력확대계수를 중심으로 AE 신호와 같은 다변량 데이터의 처리에 많이 사용되고 있는 주성분 회귀분석과 비선형적 문제 해결에 적합한 신경회로망 기법을 이용하였다. 이를 위하여 강교량 부재인 SWS490B 강에 대한 피로균열전파 실험을 수행하였으며 표준 CT 시편에 대한 피로균열진전 시 발생하는 AE 신호의 각 변수와 응력확대계수와의 관계를 고찰하였다. 통계분석 방법인 변수선택법을 적용한 결과 AE 카운트(RC), 에너지(EN), 신호지속시간(ED)의 각각에 대한 유의성이 높은 것으로 나타났으나 전반적으로 전체 AE 변수를 모두 이용할 경우 통계적 유의성이 높은 것으로 나타났다. 부재의 반복하중 시 발생하는 피로균열진전을 정량적으로 도출할 수 있는 응력확대계수 추정모델을 개발하고 평가하였다. 미지 시료에 대하여 개발된 모델의 응력확대계수 예측 성능을 분석한 결과 주성분 회귀모델과 인공신경망 모델 모두 우수한 예측성능을 나타내었으나 전반적으로 인공신경망 모델이 주성분 회귀모델보다 다소 양호한 것으로 분석되었다.

• 산업식품공학
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• 제15권2호
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• pp.136-142
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• 2011

본 연구에서는 정상 콩과 이에 혼입되는 이물질을 판별하기 위해 900 nm에서 1800 nm의 파장대역에서 단색화장치가 장착된 근적외선 분광장치를 이용하여 획득된 콩과 이물질의 반사 스펙트럼의 세기를 이용하여 각각의 판별예측모델을 개발하고 그 성능과 판별정확도를 검증해보았다. 정상콩 60 립과 이물질 60 점을 각각 2 회 반복하여 측정한 총 240 개의 반사스펙트럼에 대해서 모델 개발용인 calibration group으로 168 개를, 나머지 72 개는 개발된 모델을 예측하는 prediction group으로 나누어 사용하였다. 획득된 스펙트럼은 광원의 불안정함, 시료의 크기와 형태에서 기인되는 여러 변이들을 최소화하기 위해 다양한 수학적인 전처리를 적용하였으며 판별예측모델의 개발을 위해 PLS-DA와 SIMCA 방법을 사용하여 모델의 예측 성능과 판별율을 검토하였다. PLS-DA에서 모델 개발에 사용된 84 개의 정상 콩 스펙트럼 CLASS I은 적용된 모든 전처리에서 100%의 판별율을 보여주었으며 이물질 스펙트럼 CLASS II에서도 SNV 전처리를 제외하고는 모두 100% 이물질로 판별하여 분류하였다. 개발된 PLS-DA의 모델에 대한 prediction group의 검증에 있어서는 평균값 정규화 전처리 방법이 정상 콩과 이물질에서 100% 판별율을 보여주었다. SIMCA를 이용한 이물질 판별예측모델 개발은 PLS-DA와 비교할 때 상대적으로 저조한 판별율 결과를 나타냈으며 최대값 정규화와 일정 범위값 정규화의 전처리 방법을 적용한 모델이 평균 판별율 94.4%로 다소 양호한 결과를 보여주었다. 따라서 콩에 혼입되어 있는 이물질을 판별하는 시스템을 개발하는 데 있어서 근적외선 분광장치를 이용하여 획득한 반사도 스펙트럼은 PLS-DA로 판별예측모델을 개발하고 최적의 전처리 방법을 적용한다면 콩과 이물질의 선별시에 보다 나은 판별율을 얻을 수 있을 것이다.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1247-1247
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• 2001

Constituents of animal biofluids such as milk, blood and urine contain information specifically related to metabolic and health status of the ruminant animals. Some changes in composition of biofluids can be attributed to disease response of the animals. Mastitis is a major problem for the global dairy industry and causes substantial economic losses from decreasing milk production and reducing milk quality. The purpose of this study was to investigate potential of NIRS combined with multivariate analysis for cow's mastitis diagnosis based on NIR spectra of milk, blood and urine. A total of 112 bulk milk, urine and blood samples from 4 Holstein cows were analyzed. The milk samples were collected from morning milking. The urine samples were collected before morning milking and stored at -35$^{\circ}C$ until spectral analysis. The blood samples were collected before morning milking using a catheter inserted into the carotid vein. Heparin was added to blood samples to prevent coagulation. All milk samples were analyzed for somatic cell count (SCC). The SCC content in milk was used as indicator of mastitis and as quantitative parameter for respective urine and blood samples collected at same time. NIR spectra of blood and milk samples were obtained by InfraAlyzer 500 spectrophotometer, using a transflectance mode. NIR spectra of urine samples were obtained by NIR System 6500 spectrophotometer, using 1 mm sample thickness. All samples were divided into calibration set and test set. Class variable was assigned for each sample as follow: healthy (class 1) and mastitic (class 2), based on milk SCC content. SIMCA was implemented to create models of the respective classes based on NIR spectra of milk, blood or urine. For the calibration set of samples, SIMCA models (model for samples from healthy cows and model for samples from mastitic cows), correctly classified from 97.33 to 98.67% of milk samples, from 97.33 to 98.61% of urine samples and from 96.00 to 94.67% of blood samples. From samples in the test set, the percent of correctly classified samples varied from 70.27 to 89.19, depending mainly on spectral data pretreatment. The best results for all data sets were obtained when first derivative spectral data pretreatment was used. The incorrect classified samples were 5 from milk samples,5 and 4 from urine and blood samples, respectively. The analysis of changes in the loading of first PC factor for group of samples from healthy cows and group of samples from mastitic cows showed, that separation between classes was indirect and based on influence of mastitis on the milk, blood and urine components. Results from the present investigation showed that the changes that occur when a cow gets mastitis influence her milk, urine and blood spectra in a specific way. SIMCA allowed extraction of available spectral information from the milk, urine and blood spectra connected with mastitis. The obtained results could be used for development of a new method for mastitis detection.

• 한국토양비료학회지
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• 제37권4호
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• pp.259-265
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• 2004

사과의 영양진단에서 사과잎 분석을 신속히 하기 위한 방법을 모색하기 위해 생잎과 건조잎을 이용해 근적의 스펙트럼을 측정하고 이를 질소 함량과의 최적의 상관관계를 도출하기 위해 부분소자승(PLS)과 주성분회귀(PCR)과 같은 다변량 분석법을 이용하여 비파괴 검량식을 작성하였다. 또한 검량식 작성에서 비파괴 측정 정확도를 향상시키기 위하여 smoothing, mean normalization, multiplicative scatter correction (MSC). derivative 등의 다양한 데이터 전처리 조작을 수행하여 정확도 향상 가능성을 조사하였다. 사과 건조잎의 비파괴 측정 가능성을 조사한 결과 PLS-1 모델에서 Norris first derivate하였을 태 RMSEP가 $0.6999g\;kg^{-1}$ 로 가장 좋았으며, 생잎은 Savitzky-Golay first derivate하였을 때에 RMSEP 가 $1.202g\;kg^{-1}$으로 가장 좋았다. 건조잎의 PCR 모델은 mean normalization 처리 후 Savitzky-Golay first derivative하였을 때가 RMSEP 가 $0.553g\;kg^{-1}$, 이었으며 생잎에서도 RMSEP는 $1.047g\;kg^{-1}$로 나타났다. 이와 같은 견과로서 사과의 생잎과 건조잎의 분석이 근적외분석기술에 의해 가능할 것으로 판단된다.