• Clean Technology
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• v.18 no.3
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• pp.265-271
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• 2012

The use of renewable energies has been required to diminish the dependency on fossil fuels. As one of clean energy sources biomass has been extensively studied because various biomass resources necessitated rapid characterization of their chemical and physical properties in an on-line or real-time basis. For such an analysis near-infrared (NIR) spectroscopy has been successfully applied because of its non-invasive and informative characteristics. In this work, the applicability of nonlinear chemometric techniques based on biomass near infrared (NIR) data is evaluated for the rapid prediction of ash/char contents in different types of biomass. The prediction results of various prediction models and the effect of using preprocessing methods for NIR data are compared using six types of biomass NIR data. The results showed that nonlinear prediction models yielded better prediction performance than linear ones. It also turned out that by adopting the use of proper preprocessing methods the performance of prediction of biomass properties improved.

• Analytical Science and Technology
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• v.24 no.6
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• pp.519-526
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• 2011

Chemometrics using near-infrared (NIR) and Raman spectroscopy have found significant uses in a variety quantitative and qualitative analyses of pharmaceutical products in complex matrixes. Most of the pharmaceutical can be measured directly with little or no sample preparation using these spectroscopic methods. During pharmaceutical manufacturing process, analytical techniques with no or less sample preparation are very critical to confirm the quality. This study showed NIR and Raman spectroscopy with principal component analysis (PCA) was very effective for the blending processing control. It is of utmost importance to evaluate critical parameters related to quality of products during pharmaceutical processing. The blending is confirmed by off-line determination of active pharmaceutical ingredient (API) by a conventional method such as high performance liquid chromatography (HPLC) and UV spectroscopy. These analytical methods are time-consuming and ineffective for real time control. This study showed the possibility for the determination of blend uniformity end-point of CR tablets with the use of both NIR and Raman spectroscopy. The samples were acquired from six positions during blending processing with U-type blender from 0 to 30 min. Using both collected NIR and Raman spectral data, principal component analysis (PCA) was used to follow the uniformity of blending and finally determine the end-point. The variation of homogeneity of six samples during blending was clearly found and blend uniformity end-point was successfully confirmed in the domains of principal component (PC) scores.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1162-1162
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• 2001

Whereas NIR spectroscopy has been applied in agriculture for more than 20 years, few studies refer to those plant substances occurring only in smaller amounts. Nevertheless there is a growing interest today to support efficiently activities in the production of high-quality medicinal and spice plants by this fast and non-invasive method. Therefore, it was the aim of this study to develop new NIR methods for the reliable prediction of secondary metabolites found as valuable substances in various plant species. First, sophisticated NIR methods were established to perform fast quality analyses of intact fennel, caraway and dill fruits deriving from single-plants [1]. Later on, a characterization of several leaf drugs and the corresponding fresh material has been successfully performed. In this context robust calibrations have been developed for dried peppermint, rosemary and sage leaves for the determination of their individual essential oil content and composition [2]. A specially adopted NIR method has been developed also for the analysis of carnosic acid in the leaves of numerous rosemary and sage gene bank accessions. Carnosic acid is an antioxidative substance for which several health promoting properties including cancer preservation are assumed. Also some other calibrations have been developed for non-volatile substances such as aspalathin (in unfermented rooibos leaves), catechins (in green tea) and echinacoside (in different Echinacea species) [3]. Some NIR analyses have also been successfully performed on fresh material, too. In spite of the fact that these measurements showed less accuracy in comparison to dried samples, the calibration equations are precise enough to register the individual plant ontogenesis and genetic background. Based on the information received, the farmers and breeders are able to determine the right harvest time (when the valuable components have reached their optimum profile) and to select high-quality genotypes during breeding experiments, respectively. First promising attempts have also been made to introduce mobile diode array spectrometers to collect the spectral data directly on the field or in the individual natural habitats. Since the development of reliable NIRS methods in this special field of application is very time-consuming and needs continuous maintenance of the calibration equations over a longer period, it is convenient to supply the corresponding calibration data to interested user via NIRS network. The present status of all activities, preformed in this context during the last three years, will be presented in detail.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.416-422
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• 2016

Lots of plastics are widely used in a variety of industrial field. And the amount of plastic waste is massively produced. In the study of waste recycling, it is emerged as an important issue to prevent the waste of potentially useful resource materials as well as to reduce ecological damage. So, the recycling of plastic waste has been currently paid attention to from the view point of reuse. Existing automatic sorting system consist of near infrared ray (NIR) sensors to classify the types of plastics. But the classification of black plastics still remains a challenge. Black plastics which contains carbon black are not almost classified by NIR because of the characteristic of the light absorption of black plastics. This study is focused on handling how to identify black plastics instead of NIR. Raman spectroscopy is used to get qualitative as well as quantitative analysis of black plastics. In order to improve the performance of identification, Support Vector Machine(SVM) classifier and Principal Component Analysis(PCA) are exploited to more preferably classify some kinds of the black plastics, and to analyze the characteristic of each data.

• Korean Journal of Remote Sensing
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• v.31 no.4
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• pp.281-291
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• 2015

Sun glint correction methods of hyperspectral data that have been developed so far have not considered the various situations and are often adequate for only certain conditions. Also there is an inaccurate assumption that the signal in NIR wavelength is zero. Therefore, this study attempts to analyze the NIR spectral properties of sun glint effect in coastal waters. For the analysis, CASI-1500 airborne hyperspectral data, bathymetry data and in-situ data obtained at coastal area near Sin-Cheon, Jeju Island, South Korea were used. The spectral characteristics of radiance and reflectance at the five NIR wavelengths (744 nm, 758 nm, 772 nm, 786 nm, and 801 nm) are analyzed by using various statistics, spatial and spectral variation of sun-glinted area under conditions of the bottom types of benthos, barren rocks and sand with similar water depth. Through the quantitative analysis, we found that the relation of water depth or bottom type with sun glint is relatively less which is a similar result with the previous studies. However the sun glint are distributed similarly with the patterns of the direction of wave propagation. It is confirmed that the areas with changed direction of wave propagation were not affected by the sun glint. The spatial and spectral variations of radiance and reflectance are mainly caused by the effect of sun glint and waves. The radiance or reflectance of more sun-glinted areas are increased approximately 1.5 times and the standard deviations are also increased three times compared to the less sun glinted areas. Through this study, the further studies of sun glint correction method in coastal water using the patterns of wave propagation and diffraction will be placed.

• Applied Biological Chemistry
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• v.37 no.5
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• pp.349-355
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• 1994

The present study was conducted to develop the automatic analytical method for determining moisture, nicotine, reducing sugar and total nitrogen contents and color(L, a, b) value in domestic tobacco leaves using near infrared(NIR) spectroscopy. The results of multiple linear regression analysis between chemical and NIR data showed that NIR spectro-scopy can determine those quality components of tobacco samples in 30 seconds, non-destructively. The results using developed calibrations are summarized as follows; The standard error of prediction(SEP) for moisture, nicotine. total nitrogen, reducing sugar contents and color(L, a, b) value in domestic tobacco leaves was 0.28%, 0.25%, 0.07%, 0.75%, 1.25, 0.44 and 1.07, respectively. In addition, The possibility of developing the cheaper filter type NIR instrument, for quality evaluation in the procurement from leaf tobacco cultivators and process control was investigated.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.spc1
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• pp.250-258
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• 2004

• Proceedings of the PSK Conference
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• 2000.10a
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• pp.251.1-251.1
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• 2000

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1251-1251
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• 2001

The routine analysis of milk chemical components is of major importance both for the management of animals in dairy farms and for quality control in dairy industries. NIRS technology is an analytical technique which greatly simplifies this routine. One of the most critical aspects in NIRS analysis of milk is sample preparation and analysis modes which should be fast and straightforward. An important difficulty when obtaining NIR spectra of milk is the high water content (80 to 90%) of this product, since water absorbs most of the infrared radiation, and, therefore, limits the accuracy of calibrating for other constituents. To avoid this problem, the DESIR system was set up. Other ways of radiation-sample interaction adapted for liquids or semi-liquids exist, which are practically instantaneous and with limited or null necessity of sample preparation: Transmission and Folded Transmission or Transflectance. The objective of the present work is to compare the precision and accuracy of milk calibration equations in two analysis modes: Reflectance (dry milk) and Folded Transmission (liquid milk). A FOSS-NIR Systems 6500 I spectrophotometer (400-2500 nm) provided with a spinning module was used. Two NIR spectroscopic methods for milk analysis were compared: a) folded transmission: liquid milk samples in a 0.1 pathlength sample cell (ref. IH-0345) and b) reflectance: dried milk samples in glass fibre filters placed in a standard ring cell. A set of 101 milk samples was used to develop the calibration equations, for the two NIR analysis modes, to predict casein, protein, fat and dry matter contents, and 48 milk samples to predict Somatic Cell Count (SCC). The calibrations obtained for protein, fat and dry matter have an excellent quantitative prediction power, since they present $r^2$ values higher than 0.9. The $r^2$ values are slightly lower for casein and SCC (0.88 and 0.89 respectively), but they still are sufficiently high. The accuracy of casein, protein and SCC equations is not affected by the analysis modes, since their ETVC values are very similar in reflectance and folded transmission (0.19% vs 0.21%; 0.16% vs 0.19% and 55.57% vs 53.11% respectively), Lower SECV values were obtained for the prediction of fat and dry matter with the folded transmission equations (0.14% and 0.25% respectively) compared to the results with the reflectance ones (0.43% and 0.34% respectively). In terms of accuracy and speed of analytical response, NIRS analysis of liquid milk is recommended (folded transmission), since the drying procedure takes 24 hours. However, both analysis modes offer satisfactory results.

• Korean Journal of Soil Science and Fertilizer
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• v.33 no.4
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• pp.242-246
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• 2000

The Near Infrared Reflectance Spectroscopy(NIR) was used to evaluate nutritional diagnosis for rapid leaf analysis method, 177 'Fuji' apple and 130 'Campbell Early' grape leaves were measured by Near Infrared reflectance spectra in the NIR region(1,100~2.500nm). Total nitrogen content was measured by kjelldhal distillation, after salycilic acid-sulfuric acid digestion. An empirical equation to predict total nitrogen content from its spectral signature was developed by adapting the Near Infrared Reflectance Spectroscopy analysis(NIRa) technique and the results were apple-0.965(R). 0.086(SEC), grape-0.926(R), 0.152(SEC). Standard Error of Prediction(SEP) of NIRa for predicting the total nitrogen of apple and grape leaves was 0.360 and 0.210, respectively. It was concluded that Near infrared reflectance spectroscopy analysis is promising method for rapid analysis of apple and grape leaves.