• 한국토양비료학회지
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• 제44권3호
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• pp.331-336
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• 2011

최근 편리함과 측정의 정확성으로 인해 Capacitance sensor가 토양수분 연구나 물관리에 국제적으로도 널리 이용되고 있다. 이 연구는 Capacitance sensor (EnviroSCAN, Sentek Ltd.)가 화산회토양이 많이 분포하는 제주도 지역에서도 활용성이 있는 지를 알아보기 위해 유기물함량이 다른 제주도의 대표적인 토양 종류를 이용하여 Calibration 시험을 수행하였다. 시험 결과 화산회토양에서는 비화산회토양과 달리 센서의 Scaled frequency와 토양의 용적수분함량 간에 Calibration식이 로그식 형태로 나타내는 것이 일반적으로 적용되는 지수식 형태로 나타내는 것보다 상관이 더 높게 나타났다. 또한 화산회토양이 많이 분포하는 지역에 서는 토양수분함량이 높아 습하거나 매우 적어 건조할 경우에는 Capacitance sensor에 의한 수분함량 측정값이 건조기를 이용한 수분함량 값보다 과소하게 측정될 수 있었다. Capacitance sensor를 이용하여 화산회토양에서 토양 수분함량을 정확하게 측정하기 위해서 Calibration식에 적용될 수 있는 현실적인 계수값을 제시하였다. 또 현재 이용되는 EnviroSCAN capacitance probes의 활용성을 제고하기 위해서 계수값을 유기물함량별로 추정하는 식을 제시 하였다. Capacitance sensor를 이용하여 토양수분함량을 정확하게 측정하기 위해서는 사전에 토양의 공극분포, 유기물함량, EC 등 측정여건을 파악하여 조절하는 것이 필요하였다.

• Asian-Australasian Journal of Animal Sciences
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• 제18권5호
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• pp.643-648
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• 2005

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid, accurate method of evaluating some chemical constituents in cereal grains and forages. If samples could be analyzed without drying and grinding, then sample preparation time and costs may be reduced. This study was conducted to develop robust NIRS equations to predict fermentation quality of corn (Zea mays) silage and to select acceptable sample preparation methods for prediction of fermentation products in corn silage by NIRS. Prior to analysis, samples (n = 112) were either oven-dried and ground (OD), frozen in liquid nitrogen and ground (LN) and intact fresh (IF). Samples were scanned from 400 to 2,500 nm with an NIRS 6,500 monochromator. The samples were divided into calibration and validation sets. The spectral data were regressed on a range of dry matter (DM), pH and short chain organic acids using modified multivariate partial least squares (MPLS) analysis that used first and second order derivatives. All chemical analyses were conducted with fresh samples. From these treatments, calibration equations were developed successfully for concentrations of all constituents except butyric acid. Prediction accuracy, represented by standard error of prediction (SEP) and $R^2_{v}$ (variance accounted for in validation set), was slightly better with the LN treatment ($R^2$ 0.75-0.90) than for OD ($R^2$ 0.43-0.81) or IF ($R^2$ 0.62-0.79) treatments. Fermentation characteristics could be successfully predicted by NIRS analysis either with dry or fresh silage. Although statistical results for the OD and IF treatments were the lower than those of LN treatment, intact fresh (IF) treatment may be acceptable when processing is costly or when possible component alterations are expected.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1620-1620
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• 2001

Forages, both grazed and conserved, provide the basis of ruminant production systems throughout the world. More than 90 per cent of the feed energy consumed by herbivorous animals world - wide were provided by forages. With such world - wide dependence on forages, the economic and nutritional necessity of been able to characterize them in a meaningful way is vital. The characterization of forages for productive animals is becoming important for several reasons. Relative to conventional laboratory procedures, Near Infrared Reflectance Spectroscopy (NIRS) offers advantages of simplicity, speed, reduced chemical waste, and more cost-effective prediction of product functionality. NIR spectroscopy represents a radical departure from conventional analytical methods, in that entire sample of forage is characterized in terms of its absorption properties in the near infrared region, rather than separate subsamples being treated with various chemicals to isolate specific components. This forces the analyst to abandon his/her traditional narrow focus on the sample (one analyte at a time) and to take a broader view of the relationship between components within the sample and between the sample and the population from which it comes. forage is usually analysed by NIRS in dry and ground presentation. Initial success of NIRS analysis of coarse forages suggest a need to better understand the potential for analysis of minimally processed samples. Preparation costs and possible compositional alterations could be reduced by samples presented to the instrument in undried and unground conditions. NIRS has gained widespread acceptance for the analysis of forage quality constituents on dry material, however little attention has been given to the use of NIRS for chemical determinations on undried and unground forages. Relatively few works reported the use of NIRS to determine quality parameters on undried materials, most of them on both grass and corn silage. Only two works have been found on the determination of quality parameters on fresh forages. The objectives of this paper were (1) to evaluate the use of NIRS for determination of nitrogen and moisture on undried and unground forage samples and (2) to explore two mathematical treatments and two NIR regions to predict chemical parameters on fresh forage. Four hundred forage samples (n: 400) were analysed in a NIRS 6500 instrument (NIR Systems, PA, USA) in reflectance mode. Two mathematical treatments were applied: 1,4,4,1 and 2,5,5,2. Predictive equations were developed using modified partial least squares (MPLS) with internal cross - validation. Coefficient of determination in calibration (${R^2}_{CAL}$) and standard error in cross-validation (SECV) for moisture were 0.92 (12.4) and 0.92 (12.4) for 1,4,4,1 and 2,5,5,2 respectively, on g $kg^{-1}$ dry weight. For crude protein NIRS calibration statistics yield a (${R^2}_{CAL}$) and (SECV) of 0.85 (19.8) and 0.85 (19.6) for 1,4,4,1 and 2,5,5,2 respectively, on a dry weight. It was concluded that NIRS is a suitable method to predict moisture and nitrogen on fresh forage without samples preparation.

• Journal of Biosystems Engineering
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• 제27권5호
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• pp.425-432
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• 2002

This study was carried out to develop an automatic mixing system of nutrient solution for closed-loop hydroponics using ion electrodes. The results of the study are summarized as follows: 1. It appeared that ion-electrodes had not to be soaked into nutrient solution for a long time since it was much less durable than EC or PH sensors. Once ion-electrodes were soaked into real nutrient solution for a long time, they became unstable. 2. ion measurement modules, which were able to sample recirculated nutrient solution and easily wash and dry ion-electrodes, were developed in order to use ion-electrodes continuously. 3. The results of calibration tests on three kinds of ion electrodes presented that the time required to read measurement data was over 30 seconds. Using the calibration data the regression equations for the ion electrodes were developed. 4. An automatic nutrient-solution mixing system using the three kinds of ion electrodes was developed and then its accuracy was examined. The control errors of the mixing system using ion electrodes were in the range of 9.8 to 12%.

• 한국해양학회지:바다
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• 제4권3호
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• pp.246-253
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• 1999

퇴적물 입도분석 방식에 따른 분석결과의 편차를 비교하였다. 한반도 주변해역에서 기존에 보고된 퇴적물 입도자료들은 연구기관에 따라 상당한 편차가 나타났으며, 실험실간 편차보정작업(Inter-lab calibration)이 요구된다. 퇴적물 입도분석 결과는 분석방식에 따라 상이하게 나타났다. 레이저 회절방식은 반복측정의 정확도가 매우 우수하였지만, 2-3 ${\mu}m$보다 세립한 계층의 함량을 과소측정하였다. 이와 반면에 입자침전속도에 근거한 입도분석 방식은 조립실트(5-6 ${\phi}$) 계층의 오차가 크게 나타났으며, 점토질 함량이 다소 과다하게 측정되었다. 퇴적물 입도분석에 가장 일반적으로 활용되는 체질과 피켓법은 0.5 ${\phi}$ 간격의 분석작업이 가장 효과적인 것으로 나타났다. 특히 피켓법의 경우 조립실트 계층의 영역에서 0.5 ${\phi}$ 간격의 분석작업이 요구되었다. 또한 사질 퇴적물의 체질방식에서는 하나의 체에 걸러지는 퇴적물 양에 따른 오차가 매우 중요한 것으로 나타났다.

• 한국축산식품학회지
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• 제40권6호
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• pp.896-907
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• 2020

Imaging technique or computer vision (CV) technology has received huge attention as a rapid and non-destructive technique throughout the world for measuring quality attributes of agricultural products including meat and meat products. This study was conducted to test the ability of CV technology to predict the quality attributes of beef. Images were captured from longissimus dorsi muscle in beef at 24 h post-mortem. Traits evaluated were color value (L*, a*, b*), pH, drip loss, cooking loss, dry matter, moisture, crude protein, fat, ash, thiobarbituric acid reactive substance (TBARS), peroxide value (POV), free fatty acid (FFA), total coliform count (TCC), total viable count (TVC) and total yeast-mould count (TYMC). Images were analyzed using the Matlab software (R2015a). Different reference values were determined by physicochemical, proximate, biochemical and microbiological test. All determination were done in triplicate and the mean value was reported. Data analysis was carried out using the programme Statgraphics Centurion XVI. Calibration and validation model were fitted using the software Unscrambler X version 9.7. A higher correlation found in a* (r=0.65) and moisture (r=0.56) with 'a*' value obtained from image analysis and the highest calibration and prediction accuracy was found in lightness (r²_c=0.73, r²_p=0.69) in beef. Results of this work show that CV technology may be a useful tool for predicting meat quality traits in the laboratory and meat processing industries.

• 대한화학회지
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• 제65권4호
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• pp.254-259
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• 2021

The purpose of this work is the development of a method for an effective, less expensive, rapid, and simultaneous determination of three phenolic compounds (caffeic acid, gallic acid, and quercetin) widely present in food resources and known for their antioxidant powers. The method relies on partial least squares (PLS) calibration of UV-visible spectroscopic data. This model was applied to simultaneously determine, the concentrations of caffeic acid (CA), gallic acid (GA), and quercetin (Q) in six herb infusion extracts: basil, chive, laurel, mint, parsley, and thyme. A wavelength range (250-400) nm, and an experimental calibration matrix with 21 samples of ternary mixtures composed of CA (6.0-21.0 mg/L), GA (10.0-35.2 mg/L), and Q (6.4-17.5 mg/L) were chosen. Spectroscopic data were mean-centered before calibration. Two latent variables were determined using the contiguous block cross-validation procedure after calculating the root mean square error cross-validation RMSECV. Other statistic parameters: RMSEP, R², and Recovery (%) were used to determine the predictive ability of the model. The results obtained demonstrated that UV-visible spectrometry and PLS regression were successfully applied to simultaneously quantify the three phenolic compounds in synthetic ternary mixtures. Moreover, the concentrations of CA, GA and Q in herb infusion extracts were easily predicted and found to be 3.918-18.055, 9.014-23.825, and 9.040-13.350 mg/g of dry sample, respectively.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1266-1266
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• 2001

Pasture composition, an important attribute determining sward condition and value, is normally assessed by hand separation, drying and measuring weight contribution of each species in the mixture. This is a tedious, time and labour consuming procedure. NIRS has demonstrated the potential for predicting botanical composition of swards, but most of the work has been carried out on dry samples. The aim of this work was to evaluate the feasibility of developing NIR models for predicting the white clover and ryegrass content in fresh or dry mixtures artificially prepared from pure samples of both species. Mixtures from pure stands of white clover(Trifolium repens) and perennial ryegrass (Lolium perenne) were prepared with different proportions (0 to 100%) of each species (fresh weight). A total of 55 samples were made (11 mixtures,5 cuts). Spectra (400 to 2500 nm) were taken from fresh chopped (rectangular cuvettes, transport sample module) samples, in a NIR Systems 6500 scanning monochromator controlled by the software NIRS 3 (Infrasoft International), which was also utilized for calibration development. Different math treatments (derivative order, subtraction gap and smooth segment) and a scatter correction treatment of the spectra (SNV and Detrend) were tested. Equations were developed by modified partial least squares. Prediction accuracy evaluated by cross-validation, showed that percentage of clover or ryegrass, as contribution in dry weight, can be successfully percentage of clover or ryegrass, as contribution in dry weight, can be successfully predicted either on fresh or dried samples, with equations developed by different math treatments. Best equations for fresh samples were developed including a first, second, or third derivative, whereas for dry samples best equations included a second or third derivative. Standard errors of ross validation were about 6% for fresh and 3.6% for dry samples, Coefficient of determination of cross validation (1-VR) were over 0.95 times the value of SECV for fresh samples and over 8 times the value of SECV for dry samples. Scatter correction (SNV and Detrend) in general improved prediction accuracy. It is concluded more precise on dried and ground samples, it can be used with an acceptable error level and less time and labour, on fresh samples.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1121-1121
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• 2001

A previous study (Berzaghi et al., 2001) evaluated the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural networks (ANN) on the prediction of the chemical composition of forages, using a large NIR database. The study used forage samples (n=25,977) from Australia, Europe (Belgium, Germany, Italy and Sweden) and North America (Canada and U.S.A) with reference values for moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected using 10 different Foss NIR Systems instruments, only some of which had been standardized to one master instrument. The aim of the present study was to evaluate the behaviour of these different calibration methods when predicting the same samples measured on different instruments. Twenty-two sealed samples of different kind of forages were measured in duplicate on seven instruments (one master and six slaves). Three sets of near infrared spectra (1100 to 2500nm) were created. The first set consisted of the spectra in their original form (unstandardized); the second set was created using a single sample standardization (Clone1); the third was created using a multiple sample procedure (Clone6). WinISI software (Infrasoft International Inc., Port Mathilda, PA, USA) was used to perform both types of standardization, Clone1 is just a photometric offset between a “master” instrument and the “slave” instrument. Clone6 modifies both the X-axis through a wavelength adjustment and the Y-axis through a simple regression wavelength by wavelength. The Clone1 procedure used one sample spectrally close to the centre of the population. The six samples used in Clone 6 were selected to cover the range of spectral variation in the sample set. The remaining fifteen samples were used to evaluate the performances of the different models. The predicted values for dry matter, protein and neutral detergent fibre from the master Instrument were considered as “reference Y values” when computing the statistics RMSEP, SEPC, R, Bias, Slope, mean GH (global Mahalanobis distance) and mean NH (neighbourhood Mahalanobis distance) for the 6 slave instruments. From the results we conclude that i) all the calibration techniques gave satisfactory results after standardization. Without standardization the predicted data from the slaves would have required slope and bias correction to produce acceptable statistics. ii) Standardization reduced the errors for all calibration methods and parameters tested, reducing not only systematic biases but also random errors. iii) Standardization removed slope effects that were significantly different from 1.0 in most of the cases. iv) Clone1 and Clone6 gave similar results except for NDF where Clone6 gave better RMSEP values than Clone1. v) GH and NH were reduced by half even with very large data sets including unstandardized spectra.

• 한국지반공학회논문집
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• 제32권4호
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• pp.5-14
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• 2016

건조토 지반에 근입된 지반-말뚝 시스템의 동적 거동을 정확히 예측하기 위해 3차원 수치 모델링을 수행하였다. 제안된 모델은 강진 시 지반의 비선형 거동을 적절하게 모사하기 위해 상용 유한 차분 프로그램인 FLAC3D를 이용하여 시간 영역에서 해석이 수행되었다. 모델링 방법론으로써 지반 구성 모델은 Mohr-Coulomb 탄소성 모델을 적용하였으며 지반 전단 탄성 계수의 비선형적인 감소를 모사할 수 있는 이력 감쇠 모델을 적용하였다. 진동 시 지반-말뚝 간의 완전 접촉, 미끄러짐, 분리 현상을 모두 모사하는 경계요소 모델을 적용하였으며 경계요소 모델을 구성하는 스프링 계수는 탄성이론에 기초하여 결정되어, 내장 함수인 FISH를 통해 깊이에 따라 연속적으로 입력되었다. 경계 조건의 경우, 지반-말뚝 상호작용의 영향을 받는 근역 지반만 메쉬를 생성하고 근역 지반의 경계부에 원역 지반의 가속도-시간 이력을 입력하는 방식인 단순화 연속체 모델링 기법(Kim et al., 2012)을 적용함으로써 해석 효율을 증가 시키고자 하였으며 적절한 최대지반탄성계수와 항복 깊이의 설정으로 지반의 비선형 거동을 더욱 정확히 모사하고자 하였다. 수치 해석의 오차를 최소화하고 모델의 신뢰성을 확보하기 위해, Yoo(2013)이 수행한 원심모형시험 결과와 수치 해석 결과와의 비교를 통해 제안된 기법의 캘리브레이션을 수행하였으며, 말뚝 최대 휨 모멘트와 말뚝 횡방향 최대 변위의 깊이 별 분포가 다양한 입력 하중 조건에서 실험 결과를 적절히 모사하고 있는 것을 확인하였다. 또한, 제안된 수치 모델의 적용성 평가를 위해 다른 실험 결과와의 비교 검증을 수행하였다.