• Journal of Biosystems Engineering
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• 제40권1호
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• pp.47-60
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• 2015

Purpose: The purpose of this study was to non-destructively and quickly predict the capsaicinoid content of domestic red pepper powders from various areas of Korea using a pungency measurement system in combination with visible and near-infrared (VNIR) spectroscopic techniques. Methods: The reflectance spectra of 149 red pepper powder samples from 14 areas of Korea were obtained in the wavelength range of 450-950 nm and partial least squares regression (PLSR) models for the prediction of capsaicinoid content were developed using area models. Results: The determination coefficient of validation (RV2), standard error of prediction (SEP), and residual prediction deviation (RPD) for the capsaicinoid content prediction model for the Namyoungyang area were 0.985, ${\pm}2.17mg/100g$, and 7.94, respectively. Conclusions: These results show the possibility of VNIR spectroscopy combined with PLSR models in the non-destructive and facile prediction of capsaicinoid content of red pepper powders from Korea.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1530-1530
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• 2001

The objectives of this study were to develop models to predict quality parameters of Korean bee-honeys by visible and NIR spectroscopic technique. Two kinds of bee-honey fronl acacia and polyflower sources were tested in this study. The honeys were harvested in the spring of 2000 and stored in the storage facility at 20$^{\circ}C$ during experiments. Total of 394 samples of honey were analyzed. Reflectance spectra, moisture contents, ash, invert sugar, sucrose, F/G (fructose/glucose) ratio, HMF (hydroxymethyl furfural), and C12/C13 ratio of honeys were measured. The average values for the tested honeys were 19.9% of moisture contents, 0.12% of ash, 68.4% of invert sugar, 5.7% of sucrose, 1.27 of F/G(fructose/glucose) ratio, 14.4 mg/kg of HMF, and -19.1 of C12/C13 ratio. A spectrophotometer, equipped with a single-beam scanning monochromator (NIR Systems, Model 6500, USA) and a horizontal setup module, was used to collect reflectance data from honey. The reflectance spectra were measured in wavelength ranges of 400∼2,498 nm. with 2 nm of interval. Thirty-two repetitive scans were averaged, transformed to log(1/Reflectance), and then were stored in a microcomputer file, forming one spectrum per measurement. A sample cell and reflectance plate were made to hold honey samples constantly. Spectra of honey samples were divided into a calibration set and a validation set. The calibration set was used during model development, and the validation set was used to predict quality parameters from unknown spectra. The PLS(Partial Least Square) models were developed to predict the quality parameters of honeys. The first and the second derivatives of raw spectra were also used to develop the models with proper smoothing gap. The MSC (multiplicative scatter correction) and the SNV & Dtr.(standard normal variate and detranding) preprocessing were applied to all spectra to minimize sample-to-sample light scatter differences. The PLS models showed good relationships between predicted and measured quality parameters of honeys in the wavelength range of 1100∼2200 nm. However, the PLS analysis was not good enough to predict HMF of honeys.

• 대한지리학회지
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• 제51권4호
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• pp.509-523
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• 2016

토양 예측은 지속가능한 산지관리 측면에서 필요한 토양특성자료를 제공할 수 있다. 이중 가시 근적외선 분광반사 특성을 이용한 토양 예측은 저비용, 빠른 분석과 비파괴 측정, 비교적 높은 정확도로 관심을 받고 있다. 일반적으로 토양 분광반사특성 측정 과정에서 잡음이 나타날 수 있어 전처리 과정이 필요하다. 하지만 이러한 전처리 방법을 비교하고 평가하는 작업이 거의 이루어지지 못 했다. 본 연구에서는 토양 탄소와 질소 예측을 위해 5가지 전처리 방법을 비교하였다. 이는 연속체 제거, Savitzky-Golay 변환, 이산 웨이블렛(wavelet) 변환, 1차와 2차 도함수 변환이다. 토양예측 모델로 부분 최소제곱 회귀모형을 사용하였고, 총 153개 시료 중에서 검증을 위해 122개 훈련자료와 31개의 검증자료로 나누어 평가하였다. 전반적으로 토양시료의 탄소 함량이 높을수록 토양에 대한 입사 에너지의 흡수가 커지는 특성을 보였다. 파장별로는 가시광선 영역(650nm와 700nm)이 토양 탄소 그리고 질소와 가장 높은 상관관계를 보였다. 전처리 비교에서 연속체 제거가 토양 탄소(9.53mg/g)와 질소(0.79mg/g)에 대해 가장 높은 정확도(Root Mean Square Error)를 보였다. 따라서 토양 탄소와 질소 예측을 위해 연속체 제거가 가장 효과적인 분광반사특성 분석의 전처리 방법으로 판단되었다. 시각적인 평가에서 웨이블릿 변환이나 Savitzky-Golay 변환은 차이가 거의 없었고, 평가 결과도 유사했다. 따라서 다소 계산과정이 간단한 Savitzky-Golay 변환이 선호될 수 있다.

• Journal of Biosystems Engineering
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• 제33권6호
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• pp.430-437
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• 2008

Optical diffuse reflectance sensing in visible and near-infrared wavelength ranges is one approach to rapidly quantify soil properties for site-specific management. The objectives of this study were to investigate effects of preprocessing of reflectance data and determine the accuracy of the reflectance approach for estimating physical and chemical properties of selected Missouri and Illinois, USA surface soils encompassing a wide range of soil types and textures. Diffuse reflectance spectra of air-dried, sieved samples were obtained in the laboratory. Calibrations relating spectra to soil properties determined by standard methods were developed using partial least squares (PLS) regression. The best data preprocessing, consisting of absorbance transformation and mean centering, reduced estimation errors by up to 20% compared to raw reflectance data. Good estimates ($R^2=0.83$ to 0.92) were obtained using spectral data for soil texture fractions, organic matter, and CEC. Estimates of pH, P, and K were not good ($R^2$ < 0.7), and other approaches to estimating these soil chemical properties should be investigated. Overall, the ability of diffuse reflectance spectroscopy to accurately estimate multiple soil properties across a wide range of soils makes it a good candidate technology for providing at least a portion of the data needed in site-specific management of agriculture.

• 한국토양비료학회지
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• 제42권6호
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• pp.522-528
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• 2009

농경지에서 채취한 30개의 토양 Profile에 대해 깊이별로 채취한 시료를 이용하여 pH, CEC, Ca, Mg, Org.C항목에 대해 분광 스펙트럼과 화학분석에 의한 토양 특성값의 통계적 정량화를 수행하였다. 추정모델의 신뢰도를 높이기 위해 원시 반사 스펙트럼 외에도 Log, 도함수, Continuum 제거 등의 변환을 거친 스펙트럼을 입력변수로 이용하였고 그 중에서CR스펙트럼은 각 토양 특성 항목과 일괄 추정, 유형별 추정식의 모든 경우에서 통계적 유의성을 가진 추정 결과를 보였다. 특정 토양 특성 항목에서는 다른 변환 스펙트럼이 더 유의한 결과를 나타내었지만, 동시 다항목 분석을 하는 경우 CR 스펙트럼을 이용하는 것이 분석의 신속성과 용이성을 제공할 것으로 사료된다. 추정모델 성능 향상을 위해 토양의 여러 특성에 의한 스펙트럼의 변화 중에서 큰 요인 중 하나인 토색과 관련된 Fe에 의한 500-1200 nm 영역에서의 흡수 스펙트럼 특징에 의해 유형을 나누어 추정모델을 도출하였다. 유형별 추정모델 적용 결과가 일괄 추정값보다 월등히 높은 결과를 나타내지는 않았지만, 대체적으로 유형별 추정모델이 약간 높은 유의성을 나타내었고, 특히 Ca와 CEC의 경우 상당히 향상된 결과를 보였다. 이러한 스펙트럼의 처리와 스펙트럼의 유형 분류 등을 고려한 정량 추정 모델을 통해 가시 근적 외 영역의 스펙트럼을 이용하여 토양의 특성을 동시에 다항목에 대한 분석을 신속하게 수행할 수 있을 것으로 판단된다. 이러한 추정 모델은 토양 특성에 대해 광역 단위에서 다량의 시료 분석에 유용하므로 지역, 세계 규모의 디지털 토양 매핑, 토양 분류 및 원격탐사 자료와의 연계 분석에 활용될 수 있을 것으로 사료된다.

• Agricultural and Biosystems Engineering
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• 제6권1호
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• pp.15-21
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• 2005

This study was conducted to develop a nondestructive grouping system for soil organic matter using visible (VIS) and near infrared (NIR) spectroscopic method. The artificial light was irradiated on the cut soil surface at 15 to 20 cm depths to reduce the errors of light at open field. The reflectance energy from the cut soil surface was measured to group the soil organic matter using VIS/NIR light sensor with narrow band pass filter. From reflectance spectra of soil samples, the sensitive wavelengths for measuring the soil organic matter were selected and compared to previous research results. The grouping system for soil organic matter consisted of light sensor with band pass filter measuring the reflectance energy of the cut soil surface, global positing system (GPS), analog-to-digital (AD) converter, computer and operating software. The regression models to predict the soil organic matter were developed and evaluated. From field test, the accuracies of the developed light sensor system were 81.3% for five-stage grouping of the soil organic matters and 91.0% for three-stages grouping of the soil organic matters, respectively. It could be possible to support the decision making for variable rate applications with the developed grouping system for soil organic matter in precision agriculture.

• Journal of Biosystems Engineering
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• 제33권3호
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• pp.210-215
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• 2008

The objective of this study was to develop models to predict SCC (somatic cell count) in unhomogenized milk by visible and near-infrared (NIR) spectroscopic technique. Total of 100 milk samples were collected from dairy farms and preserved to minimize propagation of bacteria cells during transportation. Reductive reagents such as methyl red, methylene blue, bromcresol purple, phenol red and resazurin were added to milk samples, and then colors of milk were changed based on SCC of milk. For optimal reductive reagents, reaction time was controlled at 3 level of reaction time. A spectrophotometer was used to measure reflectance spectra from milk samples. The partial least square (PLS) models were developed to predict SCC of unhomogenized milk. The PLS results showed that milk samples with reductive reagents had a good correlation between predicted and measured SCC at 5 minutes of reaction time in the visible range. The PLS models with resazurin reagent had the best performance in $400{\sim}600\;nm$. The prediction results of milk samples with resazurin had 0.86 of correlation coefficient and 14,184 cell/mL of SEP.

• Journal of Biosystems Engineering
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• 제34권5호
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• pp.382-389
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• 2009

An in-situ probe-based spectrophotometer has been developed. This system used two spectrometers to measure soil reflectance spectra from 450 nm to 2200 nm. It collects soil electrical conductivity (EC) and insertion force measurements in addition to the optical data. Six fields in Kansas were mapped with the VIS-NIR (visible-near infrared) probe module and sampled for calibration and validation. Results showed that VIS-NIR correlated well with carbon in all six fields, with RPD (the ratio of standard deviation to root mean square error of prediction) of 1.8 or better, RMSE of 0.14 to 0.22%, and $R^2$ of 0.69 to 0.89. From the investigation of carbon variability within the soil profile and by tillage practice, the 0-5 cm depth in a no-till field contained significantly higher levels of carbon than any other locations. Using the selected calibration model with the soil NIR probe data, a soil profile map of estimated carbon was produced, and it was found that estimated carbon values are highly correlated to the lab values. The array of sensors (VIS-NIR, electrical conductivity, insertion force) used in the probe allowed estimating bulk density, and three of the six fields were satisfactory. The VIS-NIR probe also showed the obtained spectra data were well correlated with nitrogen for all fields with RPD scores of 1.84 or better and coefficient of determination ($R^2$) of 0.7 or higher.

• 농업과학연구
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• 제39권3호
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• pp.413-420
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• 2012

Spectroscopic measurement method based on visible and near-infrared wavelengths was prominent technology for rapid and non-destructive evaluation of internal quality of fruits. Reflectance measurement was performed to evaluate firmness, soluble solid content, and acid content of truss tomatoes by hyperspectral reflectance imaging system. The Vis/NIR reflectance spectra was acquired from truss tomatoes sorted by 6 ripening stages. The multivariable analysis based on partial least square (PLS) was used to develop regression models with several preporcessing methods, such as smoothing, normalization, multiplicative scatter correction (MSC), and standard normal variate (SNV). The best model was selected in terms of coefficient of determination of calibration ($R_c^2$) and full cross validation ($R_{cv}^2$), and root mean standard error of calibration (RMSEC) and full cross validation (RMSECV). The results of selected models were 0.8976 ($R_p^2$), 6.0207 kgf (RMSEP) with gaussian filter of smoothing, 0.8379 ($R_p^2$), $0.2674^{\circ}Bx$ (RMSEP) with the mean of normalization, and 0.7779 ($R_p^2$), 0.1033% (RMSEP) with median filter of smoothing for firmness, soluble solid content (SSC), and acid content, respectively. Results show that Vis / NIR hyperspectral reflectance imaging technique has good potential for the measurement of internal quality of truss tomato.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1510-1510
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• 2001

NIRS uses reflectance signals resulting from bending and stretching vibrations in chemical bonds between carbon, nitrogen, hydrogen, sulfur and oxygen. These reflectance signals are used to measure the concentration of major chemical composition and other descriptors of homogenized and freeze-dried whole broiler carcasses. Six strains of chicken were analyzed and the NIRS model predictions compared to reference data. The results of this comparison indicate that NIRS is a rapid tool for predicting dry matter (DM), fat, crude protein (CP) and ash content in the broiler carcass. Males and females of six commercial strain crosses of broiler chicken (Gallus domesticus) were used in this study (6$\times$2 factorial design). Each strain was grown to 16 weeks of age, and duplicate serial samples were taken for body composition analysis. Each whole carcass was pressure-cooked, homogenized, and a representative sample was freeze-dried. Body composition determined as follows: DM by oven dried method at 105$^{\circ}C$ for 3 hours, fat by Mojonnier diethyl ether extraction, CP by measuring nitrogen content using an auto-analyzer with Kjeldhal digest and ash by combustion in a muffle furnace for 24 hour at 55$0^{\circ}C$. These homogenized and freeze-dried carcass samples were then scanned with a Foss NIR Systems 6500 visible-NIR spectrophotometer (400-2500nm) (Foss NIR Systems, Silver Spring, MD., US) using Infra-Soft-International, ISI, WinISl software (ISI, Port Matilda, US). The NIRS spectra were analyzed using principal component (PC) analysis. This data was corrected for scatter using standard normal “Variate” and “Detrend” technique. The accuracy of the NIRS calibration equations developed using Partial Least Squares (PLS) for predicting major chemical composition and carcass descriptors- such as body mass (BM), bird dry matter and moisture content was tested using cross validation. Discrimination analysis was also used for sex and strain identification. According to Dr John Shenk, the creator of the ISI software, the calibration equations with the correlation coefficient, $R^2$, between reference data and NIRS predicted results of above 0.90 is excellent and between 0.70 to 0.89 is a good quantifying guideline. The excellent calibration equations for DM ($R^2$= 0.99), fat (0.98) and CP (0.92) and a good quantifying guideline equation for ash (0.80) were developed in this study. The results of cross validation statistics for carcass descriptors, body composition using reference methods, inter-correlation between carcass descriptors and NIRS calibration, and the results of discrimination analysis for sex and strain identification will also be presented in the poster. The NIRS predicted daily gain and calculated daily gain from this experiment, and true daily gain (using data from another experiment with closely related broiler chicken from each of the six strains) will also be discussed in the paper.