• 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.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1245-1245
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• 2001

Food adulteration is a serious consumer fraud and a matter of concern to food processors and regulatory agencies. A range of analytical methods have been investigated to facilitate the detection of adulterated or mis-labelled foods & food ingredients but most of these require sophisticated equipment, highly-qualified staff and are time-consuming. Regulatory authorities and the food industry require a screening technique which will facilitate fast and relatively inexpensive monitoring of food products with a high level of accuracy. Near infrared spectroscopy has been investigated for its potential in a number of authenticity issues including meat speciation (McElhinney, Downey & Fearn (1999) JNIRS, 7(3), 145-154; Downey, McElhinney & Fearn (2000). Appl. Spectrosc. 54(6), 894-899). This report describes further analysis of these spectral sets using a hierarchical approach and binary decisions solved using logistic regression. The sample set comprised 230 homogenized meat samples i. e. chicken (55), turkey (54), pork (55), beef (32) and lamb (34) purchased locally as whole cuts of meat over a 10-12 week period. NIR reflectance spectra were recorded over the wavelength range 400-2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. The problem was defined as a series of binary decisions i. e. is the meat red or white\ulcorner is the red meat beef or lamb\ulcorner, is the white meat pork or poultry\ulcorner etc. Each of these decisions was made using an individual binary logistic model based on scores derived from principal component or partial least squares (PLS1 and PLS2) analysis. The results obtained were equal to or better than previous reports using factorial discriminant analysis, K-nearest neighbours and PLS2 regression. This new approach using a combination of exploratory and logistic analyses also appears to have advantages of transparency and the use of inherent structure in the spectral data. Additionally, it allows for the use of different data transforms and multivariate regression techniques at each decision step.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1269-1269
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• 2001

The Bovine Spongiform Encephalopathy (BSE) is one of the more important problems that have affected the economy of european cattles and the Public Safety. Their transmission is mainly through digestive system, and the compound feeds made with animal proteins are one source of infection for healthy cows. Nowadays the official method for meat and bone meal (MBM) detection in compound feeds is a microscopy technique. However, this methodology is subjective, and that alter the fact to make one exhaustive quantitative analysis and one differentiation between mammalian and poultry bones. In addition, the separation of the differents fractions in a sample by density before the analysis, requires the use of organochlorates products as $CCl_4$, which produce serious damages in the atmosphere ozone content. NIR methodology is another possible way to confirm and identifying animal ingredients in compound feeds, Its capabilities for quantitative and qualitative analysis of foods and feeds has been enought demonstrated. The objective of this work was to use NIR as a tool to make an qualitative and quantitative analysis and a prediction of the meat and bone meal presence in compound feeds from North Spain cattle farms. Using a global population of compound feeds, on make three different groups depending of MBM percentage presence (0, 0-100, 100), to build and validate one calibration equation to determine MBM content and make one discriminant analysis between these three groups. The preliminary dates obtained with another differents samples of known composition showed promising results.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1152-1152
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• 2001

Food adulteration is a serious consumer fraud and a matter of concern to food processors and regulatory agencies. A range of analytical methods have been investigated to facilitate the detection of adulterated or mis-labelled foods & food ingredients but most of these require sophisticated equipment, highly-qualified staff and are time-consuming. Regulatory authorities and the food industry require a screening technique which will facilitate fast and relatively inexpensive monitoring of food products with a high level of accuracy. Near infrared spectroscopy has been investigated for its potential in a number of authenticity issues including meat speciation (McElhinney, Downey & Fearn (1999) JNIRS, 7(3), 145 154; Downey, McElhinney & Fearn (2000). Appl. Spectrosc. 54(6), 894-899). This report describes further analysis of these spectral sets using a hierarchical approach and binary decisions solved using logistic regression. The sample set comprised 230 homogenized meat samples i. e. chicken (55), turkey (54), pork (55), beef (32) and lamb (34) purchased locally as whole cuts of meat over a 10-12 week period. NIR reflectance spectra were recorded over the wavelength range 400-2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. The problem was defined as a series of binary decisions i. e. is the meat red or white\ulcorner is the red meat beef or lamb\ulcorner, is the white meat pork or poultry\ulcorner etc. Each of these decisions was made using an individual binary logistic model based on scores derived from principal component or partial least squares (PLS1 and PLS2) analysis. The results obtained were equal to or better than previous reports using factorial discriminant analysis, K-nearest neighbours and PLS2 regression. This new approach using a combination of exploratory and logistic analyses also appears to have advantages of transparency and the use of inherent structure in the spectral data. Additionally, it allows for the use of different data transforms and multivariate regression techniques at each decision step.

• Journal of Crop Science and Biotechnology
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• 제10권3호
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• pp.185-192
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• 2007

Near-infrared spectroscopy(NIRS) was used to develop a rapid and efficient method to determine lignan glucosides in intact seeds of sesame(Sesamum indicum L.) germplasm accessions in Korea. A total of 93 samples(about 2 g of intact seeds) were scanned in the reflectance mode of a scanning monochromator, and the reference values for lignan glucosides contents were measured by high performance liquid chromatography. Calibration equations for sesaminol triglucoside, sesaminol($1{\rightarrow}2$) diglucoside, sesamolinol diglucoside, sesaminol($1{\rightarrow}6$) diglucoside, and total amount of lignan glucosides were developed using modified partial least square regression with internal cross validation(n=63), which exhibited lower SECV(standard errors of cross-validation), higher $R^2$(coefficient of determination in calibration), and higher 1-VR(ratio of unexplained variance divided by variance) values. Prediction of an external validation set(n=30) showed a significant correlation between reference values and NIRS estimated values based on the SEP(standard error of prediction), $r^2$(coefficient of determination in prediction), and the ratio of standard deviation(SD) of reference data to SEP, as factors used to evaluate the accuracy of equations. The models for each glucoside content had relatively higher values of SD/SEP(C) and $r^2$(more than 2.0 and 0.80, respectively), thereby characterizing those equations as having good quantitative information, while those of sesaminol($1{\rightarrow}2$) diglucoside showing a minor quantity had the lowest SD/SEP(C) and $r^2$ values(1.7 and 0.74, respectively), indicating a poor correlation between reference values and NIRS estimated values. The results indicated that NIRS could be used to rapidly determine lignan glucosides content in sesame seeds in the breeding programs for high quality sesame varieties.

• 한국초지조사료학회지
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• 제34권3호
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• pp.209-213
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• 2014

This study was carried out to explore the accuracy of near infrared spectroscopy (NIRS) for the prediction of chemical and fermentation parameters of whole crop winter rye silages. A representative population of 216 fresh winter rye silages was used as database for studying the possibilities of NIRS to predict chemical composition and fermentation parameters. Samples of silage were scanned at 1 nm intervals over the wavelength range 680~2,500 nm and the optical data recorded as log 1/Reflectance (log 1/R) and scanned in fresh condition. NIRS calibrations were developed by means of partial least-squares (PLS) regression. NIRS analysis of fresh winter rye silages provided accurate predictions of moisture, acid detergent fiber (ADF), neutral detergent fiber (NDF), crude protein (CP) and pH as well as lactic acid content with correlation coefficients of cross-validation ($R^2cv$) of 0.96, 0.86, 0.79, 0.85, 0.82 and 0.78 respectively and standard error of cross-validation (SECV) of 1.89, 2.02, 2.79, 1.14, 1.47 and 0.46 % DM respectively. Results of this experiment showed the possibility of NIRS method to predict the chemical parameters of winter rye silages as routine analysis method in feeding value evaluation and for farmer advice.

• Journal of Crop Science and Biotechnology
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• 제10권1호
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• pp.13-18
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• 2007

Near-infrared spectroscopy(NIRS) was used as a rapid and nondestructive method to determine the fatty acid composition in intact seed samples of rapeseed(Brassica napus L.). A total of 349 samples(about 2 g of intact seeds) were scanned in the reflectance mode of a scanning monochromator, and the reference values for fatty acid composition were measured by gas-liquid chromatography. Calibration equations for individual fatty acids were developed using the regression method of modified partial least-squares with internal cross validation(n=249). The equations had low SECV(standard errors of cross-validation), and high $R^2$(coefficient of determination in calibration) values(>0.8) except for palmitic and eicosenoic acid. Prediction of an external validation set(n=100) showed significant correlation between reference values and NIRS estimated values based on the SEP(standard error of prediction), $r^2$(coefficient of determination in prediction), and the ratio of standard deviation(SD) of reference data to SEP. The models developed in this study had relatively higher values(> 3.0 and 0.9, respectively) of SD/SEP(C) and $r^2$ for oleic, linoleic, and erucic acid, characterizing those equations as having good quantitative information. The results indicated that NIRS could be used to rapidly determine the fatty acid composition in rapeseed seeds in the breeding programs for high quality rapeseed oil.

• 농업과학연구
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• 제41권1호
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• pp.59-63
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• 2014

Precision farming aims at reduced environmental impacts with increased productivity. Soils are multi-functional media in which air, water and biota occur together and form an essential part of the landscape with a fundamental role in the environment. The requirement for herbicides and fertilizers can vary within a field in response to spatial differences in soil properties. Near infrared (NIR) spectroscopy is widely used today as a nondestructive analytical technique which is capable of determining a number of physio-chemical parameters. The objectives of this study were to develop optimal models to predict chemical properties of paddy soils by visible and NIR reflectance spectra. Total of 60 soil samples were collected in spring from 20 paddy fields within central regions in Korea. Reflectance spectra, moisture contents, pH, total nitrogen (N), organic matter, available phosphate ($P_2O_5$) of soil samples were measured. The reflectance spectra were measured in wavelength ranges of 400-2,500 nm with 2 nm interval. The method of partial least square (PLS) analysis was used to determine the soil properties. The PLS analyses showed good correlation between predicted and measured chemical properties of paddy soils in the wavelength range of 1,800-2,400 nm. Especially, it showed better performance than the previous results which used the entire wavelength range of the spectrophotometer, without considering the optimal wavelength of each soil properties.

• Journal of the Korean Wood Science and Technology
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• 제44권6호
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• pp.852-863
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• 2016

Wood-plastic composite (WPC) is a promising and sustainable material, and refers to a combination of wood and plastic along with some binding (adhesive) materials. In comparison to pure wood material, WPCs are in general have advantages of being cost effective, high durability, moisture resistance, and microbial resistance. The properties of WPCs come directly from the concentration of different components in composite; such as wood flour concentration directly affect mechanical and physical properties of WPCs. In this study, wood powder concentration in WPC was determined by Fourier transform near-infrared (FT-NIR) and Fourier transform infrared (FT-IR) spectroscopy. The reflectance spectra from WPC in both powdered and tableted form with five different concentrations of wood powder were collected and preprocessed to remove noise caused by several factors. To correlate the collected spectra with wood powder concentration, multivariate calibration method of partial least squares (PLS) was applied. During validation with an independent set of samples, good correlations with reference values were demonstrated for both FT-NIR and FT-IR data sets. In addition, high coefficient of determination (${R^2}_p$) and lower standard error of prediction (SEP) was yielded for tableted WPC than powdered WPC. The combination of FT-NIR and FT-IR spectral region was also studied. The results presented here showed that the use of both zones improved the determination accuracy for powdered WPC; however, no improvement in prediction result was achieved for tableted WPCs. The results obtained suggest that these spectroscopic techniques are a useful tool for fast and nondestructive determination of wood concentration in WPCs and have potential to replace conventional methods.

• 대한화장품학회:학술대회논문집
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• 대한화장품학회 2003년도 IFSCC Conference Proceeding Book II
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• pp.218-218
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• 2003

Recently we showed the prototype portable device for the determination of human skin moisture by using near infrared spectroscopy. In order to optimize the acquiring condition of NIR spectrum of skin and control the target information of water depending the site such as epidermis and dermis, skin depth profiling was investigated changing the distance between illuminations and receiving of radiation in the terminal of fiber probe. The colleted light information could be controlled by changing the distance of the fiber optic probes. It was confirmed that the longer distance we used, the deeper site from the skin surface we could get information from in this study. Four kinds of probes with distances such as 0.03 mm, 0.1 mm, 0.5 mm, and 1.0 mm were used. In addition, the gap size from 0.3 mm to 3.0 mm was studied to control the intensity of water absorbance effectively and to avoid saturation of water absorption. We also investigated the reference materials depending the reflectance ratio for water absorption not to be saturated because of the strong absorptivity of water. Furthermore, spectroscopic information regarding free water and bound water around 1850 nm was investigated by using the different distance of fiber optic probes. This study would be great help to control the spectroscopic information of water to be measured depending the site where water exists.