• Asian-Australasian Journal of Animal Sciences
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• v.17 no.12
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• pp.1736-1740
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• 2004

Since the application of relatively high levels of heavy metals in the compost poses a potential hazard to plants and animals, the content of heavy metals in the compost with animal manure is important to know if it is as a fertilizer. Measurement of heavy metals content in the compost by chemical methods usually requires numerous reagents, skilled labor and expensive analytical equipment. The objective of this study, therefore, was to explore the application of near-infrared reflectance spectroscopy (NIRS), a nondestructive, cost-effective and rapid method, for the prediction of heavy metals contents in compost. One hundred and seventy two diverse compost samples were collected from forty-seven compost facilities located along the Han river in Korea, and were analyzed for Cr, As, Cd, Cu, Zn and Pb levels using inductively coupled plasma spectrometry. The samples were scanned using a Foss NIRSystem Model 6500 scanning monochromator from 400 to 2,500 nm at 2 nm intervals. The modified partial least squares (MPLS), the partial least squares (PLS) and the principal component regression (PCR) analysis were applied to develop the most reliable calibration model, between the NIR spectral data and the sample sets for calibration. The best fit calibration model for measurement of heavy metals content in compost, MPLS, was used to validate calibration equations with a similar sample set (n=30). Coefficient of simple correlation (r) and standard error of prediction (SEP) were Cr (0.82, 3.13 ppm), As (0.71, 3.74 ppm), Cd (0.76, 0.26 ppm), Cu (0.88, 26.47 ppm), Zn (0.84, 52.84 ppm) and Pb (0.60, 2.85 ppm), respectively. This study showed that NIRS is a feasible analytical method for prediction of heavy metals contents in compost.

• Korean Journal of Agricultural Science
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• v.39 no.4
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• pp.603-612
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• 2012

In this research, the feasibility of non-destructive measurement technique of pungency measurement was investigated for the red-pepper powders produced in different domestic areas in South Korea. The near-infrared absorption spectra in the range of 1100 nm~2300 nm was used to measure capsaicinoids content in red-pepper powders by using a NIR spectroscopy equipped with Acousto-optic tunable filters (AOTF). Fourth three different red-pepper powders from 14 different locations were collected and separated in three different particle size (below 0.425 mm, 0.425~0.71 mm, 0.71~1.4 mm) for the spectral measurements. The partial least square regression (PLSR) models to predict the capsaicinoids content depends on particle size were developed with the measured spectra. The determinant coefficients and standard errors of the developed models for the red-pepper powders of below 0.425 mm, 0.425~0.71 mm, and 0.71~1.4 mm were in the range of 0.859~0.887 and 12.90~12.99 mg/100 g, respectively. The PLS model with the pretreatment of Standard Normal Variate (SNV) for the red-pepper powders below 1.4 mm particle size showed the best performance with the determinant coefficient of 0.844 and the standard error of 14.63 mg/100 g.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1041-1041
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• 2001

Removal of variability in spectra data before the application of chemometric modeling will generally result in simpler (and presumably more robust) models. Particularly for sparsely sampled data, such as typically encountered in diode array instruments, the use of Savitzky-Golay (S-G) derivatives offers an effective method to remove effects of shifting baselines and sloping or curving apparent baselines often observed with scattering samples. The application of these convolution functions is equivalent to fitting a selected polynomial to a number of points in the spectrum, usually 5 to 25 points. The value of the polynomial evaluated at its mid-point, or its derivative, is taken as the (smoothed) spectrum or its derivative at the mid-point of the wavelength window. The process is continued for successive windows along the spectrum. The original paper, published in 1964 [1] presented these convolution functions as integers to be used as multipliers for the spectral values at equal intervals in the window, with a normalization integer to divide the sum of the products, to determine the result for each point. Steinier et al. [2] published corrections to errors in the original presentation [1], and a vector formulation for obtaining the coefficients. The actual selection of the degree of polynomial and number of points in the window determines whether closely situated bands and shoulders are resolved in the derivatives. Furthermore, the actual noise reduction in the derivatives may be estimated from the square root of the sums of the coefficients, divided by the NORM value. A simple technique to evaluate the actual convolution factors employed in the calculation by the software will be presented. It has been found that some software packages do not properly account for the sampling interval of the spectral data (Equation Ⅶ in [1]). While this is not a problem in the construction and implementation of chemometric models, it may be noticed in comparing models at differing spectral resolutions. Also, the effects on parameters of PLS models of choosing various polynomials and numbers of points in the window will be presented.

• Korean Journal of Materials Research
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• v.19 no.4
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• pp.179-185
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• 2009

We fabricated thermally evaporated 30 nm-Ni/(20 nm or 60 nm)a-Si:H/Si films to investigate the energy-saving property of silicides formed by rapid thermal annealing (RTA) at temperatures of $350^{\circ}C$, $450^{\circ}C$, $550^{\circ}C$, and $600^{\circ}C$ for 40 seconds. A transmission electron microscope (TEM) and a high resolution X-ray diffractometer (HRXRD) were used to determine the cross-sectional microstructure and phase changes. A UVVIS-NIR and FT-IR (Fourier transform infrared spectroscopy) were employed for near-IR and middle-IR absorbance. Through TEM and HRXRD analysis, for the nickel silicide formed at low temperatures below $450^{\circ}C$, we confirmed columnar-shaped structures with thicknesses of $20{\sim}30\;nm$ that had ${\delta}-Ni^2Si$ phases. Regarding the nickel silicide formed at high temperatures above $550^{\circ}C$, we confirmed that the nickel silicide had more than 50 nm-thick columnar-shaped structures with a $Ni_{31}Si_{12}$ phase. Through UV-VIS-NIR analysis, nickel silicide showed almost the same absorbance in the near IR region as well as ITO. However, in the middle IR region, the nickel silicides with low temperature showed similar absorbance to those from high temperature silicidation.

• Proceedings of the Optical Society of Korea Conference
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• 2008.02a
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• pp.455-456
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• 2008

근적외선 분광법(Near-infrared spectroscopy, NIRS)은 대뇌피질에서의 혈류변화(oxy-, deoxyhemoglobin의 농도변화)를 비침습적으로 측정할 수 있는 방법이다. 본 논문에서는 향후 뇌-컴퓨터 접속기술(Brain computer interface)에 적용하기위한 초기 연구단계로, 쥐의 수염을 자극시 활성화되는 대뇌수염피질 영역에서의 혈류변화 및 전기신호를 동시에 측정하고 두 신호의 패턴을 분석한다.

• Journal of the Korean Chemical Society
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• v.49 no.6
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• pp.531-536
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• 2005

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.407-408
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• 2009

fNIRS(functional Near Infrared Spectroscopy)는 비침습형 뇌기능 분석 시스템으로 뇌활성화 시 옥시 헤모글로빈(oxy-hemoglobin)과 디옥시헤모글로빈(deoxy-hemoglobin) 변화량을 측정할 수 있는 장치이다. 본 논문에서는 뇌기능 분석 장치인 fNIRS를 이용하여 피험자가 컴퓨터 게임 중에 어떤 뇌활성화 패턴을 보이는지를 실험하였다. 컴퓨터 게임 주의 및 집중 시 뇌의 전두엽(Frontal Lobe) 영역이 활성화 및 변화되는 것을 실험결과로 확인하였다. 그리고 게임 중 다른 사람이 피험자에게 개입을 하였을 때 전두엽의 활성화 영역이 다른 패턴을 보이는 것을 실험결과로 확인하였다.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.1
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• pp.61-66
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• 2022

Sesamin and sesamolin are major lignan components with a wide range of potential biological activities of sesame seeds. Near infrared reflectance spectroscopy (NIRS) is a rapid and non-destructive analysis method widely used for the quantitative determination of major components in many agricultural products. This study was conducted to develop a screening method to determine the lignan contents for sesame breeding. Sesamin and sesamolin contents of 482 sesame samples ranged from 0.03-14.40 mg/g and 0.10-3.79 mg/g with an average of 4.93 mg/g and 1.74 mg/g, respectively. Each sample was scanned using NIRS and calculated for the calibration and validation equations. The optimal performance calibration model was obtained from the original spectra using partial least squares (PLS). The coefficient of determination in calibration (R²) and standard error of calibration (SEC) were 0.963 and 0.861 for sesamin and 0.875 and 0.292 for sesamolin, respectively. Cross-validation results of the NIRS equation showed an R² of 0.889 in the prediction for sesamin and 0.781 for sesamolin and a standard error of cross-validation (SECV) of 1.163 for sesamin and 0.417 for sesamolin. The results showed that the NIRS equation for sesamin and sesamolin could be effective in selecting high lignan sesame lines in early generations of sesame breeding.

• Food Science of Animal Resources
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• v.31 no.1
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• pp.115-121
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• 2011

The objective of this study was to develop models to predict freshness factors (total viable counts (TVC), pH, volatile basic nitrogen (VBN), trimethylamine (TMA), and thiobarbituric acid (TBA) values) and the storage period in beef using a visible and near-infrared (NIR) spectroscopic technique. A total of 216 beef spectra were collected during the storage period from 0 to 14 d at a $10^{\circ}C$ storage. A spectrophotometer was used to measure reflectance spectra from beef samples, and beef freshness spectra were divided into a calibration set and a validation set. Multi-linear regression (MLR) models using the stepwise method were developed to predict the factors. The MLR results showed that beef freshness had a good correlation between the predicted and measured factors using the selected wavelength. The correlation of determination ($r^2$), standard error of prediction (SEP), and ratio of standard deviation to SEP (RPD) of the prediction set for TVC was 0.74, 0.64, and 2.75 Log CFU/$cm^2$, respectively. The $r^2$, SEP, and RPD values for pH were 0.43, 0.10, and 1.10; those for VBN were 0.73, 1.45, and 2.00 mg%; those for TMA were 0.70, 0.19, and 2.58 mg%; those for TBA values were 0.73, 0.13, and 2.77 mg MA/kg; and those for storage period were 0.77, 1.94, and 2.53 d, respectively. The results indicate that visible and NIR spectroscopy can predict beef freshness during storage.

• Journal of Powder Materials
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• v.19 no.3
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• pp.177-181
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• 2012

Copper composite materials have attracted wide attention for energy applications. Especially $CuInS_2$ has a desirable direct band gap of 1.5 eV, which is well matched with the solar spectrum. $CuInS_2$ nanoparticles could make it possible to develop color-tunable $CuInS_2$ nanoparticle emitter in the near-infrared region (NIR) for energy application and bio imaging sensors. In this paper, $CuInS_2$ nanoparticles were successfully synthesized by thermo-decomposition methods. Surface modification of $CuInS_2$ nanoparticles were carried out with various semiconductor materials (CdS, ZnS) for enhanced optical properties. Surface modification and silica coating of hydrophobic nanoparticles could be dispersed in polar solvent for potential applications. Their optical properties were characterized by UV-vis spectroscopy and photoluminescence spectroscopy (PL). The structures of silica coated $CuInS_2$ were observed by transmission electron microscopy (TEM).