• Journal of The Korean Society of Grassland and Forage Science
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• v.29 no.3
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• pp.253-262
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• 2009

The present study was conducted to develop a rapid and accurate method of evaluating chemical composition of total mixed ration (TMR) for dairy cows using near infrared reflectance spectroscopy (NIRS). A total of 253 TMR samples were collected from TMR manufacturers and dairy farms in Korea. Prior to NIR analysis, TMR samples were dried at $65^{\circ}C$ for 48 hour and then ground to 2 mm size. The samples were scanned at 2 nm interval over the wavelength range of 400-2500 nm on a FOSS-NIR Systems Model 6500. The values obtained by NIR analysis and conventional chemical methods were compared. Generally, the relationship between chemical analysis and NIR analysis was linear: $R^2$ and standard error of calibration (SEC) were 0.701 (SEC 0.407), 0.965 (SEC 0.315), 0.796 (SEC 0.406), 0.889 (SEC 0.987), 0.894 (SEC 0.311), 0.933 (SEC 0.885) and 0.889 (SEC 1.490) for moisture, crude protein, ether extract, crude fiber, crude ash, acid detergent fiber (ADF) and neutral detergent fiber (NDF), respectively. In addition, the standard error of prediction (SEP) value was 0.371, 0.290, 0.321, 0.380, 0.960, 0.859 and 1.446 for moisture, crude protein, ether extract, crude fiber, crude ash, ADF and NDF, respectively. The results of the present study showed that the NIR analysis for unknown TMR samples would be relatively accurate. Use of the developed NIR calibration curve can obtain fast and reliable data on chemical composition of TMR. Collection and analysis of more TMR samples will increase accuracy and precision of NIR analysis to TMR.

• Food Science and Preservation
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• v.6 no.1
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• pp.29-36
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• 1999

Using Fuji apple fruits cultivated in Kyungpook prefecture, the calibration model for firmness evaluation of fruits by near infrared(NIR) reflectance spectroscopy was developed, and the various influence factors such as instrument variety, measuring method, sample group, apple peel and selection of firmness point were investigated. Spectra of sample were recorded in wavelength range of 1100∼2500nm using NIR spectrometer (InfraAlyzer 500), and data were analyzed by stepwise multiple linear regression of IDAS program. The accuracy of calibration model was the highest when using sample group with wide range, and the firmness mean values obtained in graph by texture analyser(TA) were used as standard data. Chemometrics models were developed using a calibration set of 324 samples and an independent validation set of 216 samples to evaluate the predictive ability of the models. The correlation coefficients and standard error of prediction were 0.84 and 0.094kg, respectively. Using developed calibration model, it was possible to monitor the firmness change of fruits during storage frequently. Time, which was reached to firmness high value in graph by TA, is possible to use as new parameter for freshness of fruit surface during storage.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1252-1252
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• 2001

The aim of this study was to evaluate the possibility to characterize and classify waxes applied on some type of cheeses to obtain good stability during handling and transportation. Generally, waxes are obtained from the petrochemical industry, nowadays there is the possibility to also use biodegradable waxes produced from microorganisms. Preliminary studies were carried out to optimize sample presentation in NIR analysis, such as melting conditions (influence of temperature) and coat thickness of wax. 12 waxes (biodegradable or not) were analysed by using an InfraAlyzer 500 (Bran+Luebbe). The sample size was performed cutting pieces of 1.5 cm (height) x 1.5 cm (width) x 1.5 mm (thickness), previously melted at 9$0^{\circ}C$. NIR spectra were collected at room temperature, and data were processed by Sesame Software (Bran+Luebbe) to evaluate qualitative differences among samples by cluster analysis. Waxes were gathered on the basis of their origin (petrochemical or microbial). To better understand the significance of the NIRS bands discriminating among waxes, a two-dimensional correlation with FT-IR spectra, collected by a FT-IR/ATR 420 (JASCO) instrument, was made using 2DCORR program (Galactic Industries). On the basis of its classification power, NIRS appears to be a promising tool when used in routine analysis for a qualitative control of raw materials.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1284-1284
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• 2001

The transesterification of molten ethylene/vinylacetate (EVA) copolymers by octanol as a reagent and sodium methoxide as a catalyst in an extruder has been monitored by on-line near infrared (NIR) spectroscopy. A total of 60 NIR spectra were acquired for 37 minutes with the last spectrum recorded 31 minutes after the addition of octanol and catalyst was stopped. The experimental spectra show strong baseline fluctuations which are corrected for by multiplicative scatter correction (MSC). The chemometric methods of orthogonal projection approach (OPA) and multivariate curve resolution (MCR) were used to resolve the spectra and to derive concentration profiles of the species. The detailed analysis reveals the absence of completely pure variables that leads to small errors in the calculation of pure spectra. The initial estimation of a concentration that is necessary as an input parameter for MCR also presents a non-trivial task. We obtained results that were not ideal but applicable for practical concentration control. They enable a fast monitoring of the process in real-time and resolve the spectra of the EVA copolymer and the ethylene/vinyl alcohol (EVAL) copolymer to be very close to the reference spectra. The chemometric methods used and the decomposed spectra are discussed in detail.

• Journal of the Korean Ceramic Society
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• v.51 no.4
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• pp.350-356
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• 2014

Recently, Chemical Vapor Deposition (CVD) synthetic diamonds have been introduced to the jewelry gem market, as CVD technology has been making considerable advances. Unfortunately, CVD diamonds are not distinguishable from natural diamonds when using the conventional gemological characterization method. Therefore, we need to develop a new identification method that is non-destructive, fast, and inexpensive. In our study, we employed optical microscopy and spectroscopy techniques, including Fourier transform infra-red (FT-IR), UV-VIS-NIR, photoluminescence (PL), micro Raman, and cathodoluminescent (CL) spectroscopy, to determine the differences between a natural diamond (0.30 cts) and a CVD diamond (0.43 cts). The identification of a CVD diamond was difficult when using standard gemological techniques, UV-VIS-NIR, or micro-Raman spectroscopy. However, a CVD diamond could be identified using a FT-IR by the Type II peaks. In addition, we identified a CVD diamond conclusively with the uneven UV fluorescent local bands, additional satellite PL peaks, longer phosphorescence life time, and uneven streaks in the CL images. Our results suggest that using FT-IR combined with UV fluorescent images, PL, and CL analysis might be an appropriate method for identifying CVD diamonds.

• Journal of Biosystems Engineering
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• v.35 no.6
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• pp.450-457
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• 2010

Although cherry tomato is one of major vegetables consumed in fresh vegetable market, the quality grading method is mostly dependant on size measurement using drum shape sorting machines. Using Visible/Near-infrared spectroscopy, apparatus to be able to acquire transmittance spectrum data was made and used to estimate firmness, sugar content, and acidity of cherry tomatoes grown at hydroponic and soil culture. Partial least square (PLS) models were performed to predict firmness, sugar content, and acidity for the acquired transmittance spectra. To enhance accuracy of the PLS models, several preprocessing methods were carried out, such as normalization, multiplicative scatter correction (MSC), standard normal variate (SNV), and derivatives, etc. The coefficient of determination ($R^2_p$) and standard error of prediction (SEP) for the prediction of firmness, sugar, and acidity of cherry tomatoes from green to red ripening stages were 0.859 and 1.899 kgf, with a preprocessing of normalization, 0.790 and $0.434^{\circ}Brix$ with a preprocessing of the 1st derivative of Savitzky Golay, and 0.518 and 0.229% with a preprocessing normalization, respectively.

• Korean Journal of Agricultural Science
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• v.43 no.5
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• pp.715-722
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• 2016

Rapid determination of food quality is important in food distribution. In this study, the chemical properties of oats were analyzed using visible-near infrared (VIS-NIR) spectroscopy. The objective of this study was to develop and validate a predictive model of oat quality by VIS-NIR spectroscopy. A total of 200 oat samples were collected from domestic and import markets. Reflectance spectra, moisture, protein, fat, Fe, and K of oat samples were measured. Reflectance spectra were measured in the wavelength range of 400 - 2,500 nm at 2 nm intervals. The reflectance spectrum of an oat sample was measured after sample cell and reflectance plate spectrum measurement. Preprocessing methods such as normalization and $1^{st}$ and $2^{nd}$ derivations were used to minimize the spectroscopic noise. The partial-least-square (PLS) models were developed to predict chemical properties of oats using a commercial software package, Unscrambler. The PLS models showed the possibility to predict moisture, protein, and fat content of oat samples. The coefficient of determination ($R^2$) of moisture, protein, and fat was greater than 0.89. However, it was hard to predict Fe and K concentrations due to their low concentrations in the oat samples. The coefficient of determinations of Fe and K were 0.57 and 0.77, respectively. In future studies, the stability and practicability of these models should be improved by using a high accuracy spectrophotometer and by performing calibrations with a wider range of oat chemicals.

• Food Science and Preservation
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• v.21 no.6
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• pp.838-843
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• 2014

In this study, near-infrared spectroscopy was used to observe the drying non-uniformity of vegetables such as spring onions, onions, and garlic, which are commonly used for seasoning. For the warm-air convection drying method, the vegetables showed drying non-uniformity, which is due to the unevenness of the wind temperature and humidity depending on the height and position of the drying tray. The second derivative spectra between the vegetable samples with different drying degrees were compared. The peak at around 1,390~1,400 nm, which is assigned to weak hydrogen bonds of water, was changed during drying whereas the peak near 1,420 nm, which represents strong hydrogen (H-) bonds of water, was not changed, indicating that water with weak H-bonds evaporates first during drying, and that water with strong H-bonds remains after drying. The hyperspectral NIR imaging technique combined with principal-component analysis made it possible to discriminate the dried vegetables according to their drying degree.

• Carbon letters
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• v.10 no.1
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• pp.14-18
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• 2009

We measured the degree of macrodispersion of the various single-walled carbon nanotubes (SWCNTs) and multi-walled carbon nanotubes (MWCNTs) using UV-VIS-NIR absorption spectroscopy. CNTs were dispersed with SDS of 2 wt % in deionized water using the homogenizer and then were further centrifugated at 6000 g for 10 min. The degree of macrodispersion, expressed by $D_m({\lambda})=A_a({\lambda})/A_b({\lambda})^*100$ (%), where ${\lambda}$ is the wavelength and $A_a({\lambda})$ and $A_b({\lambda})$ are the absorbance of the sample after and before centrifugation, respectively. In the case of MWCNTs, we evaluated the degree of macrodispersion by the average degree of macrodispersion ($D_m({\lambda})$) between 1000 and 1200 nm. The degree of macrodispersion of SWCNTs was evaluated at the wavelength in which van Hove singularity-related transition regions were excluded, i.e., the range was chosen between ${E_{11}}^S$ and ${E_{22}}^S$ peaks. We have estimated six samples with the same method. The standard deviation of each sample was lower than 5. Therefore, we presented a reliable evaluation method for the macrodispersion of CNTs for standardization.

• Publications of The Korean Astronomical Society
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• v.32 no.1
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• pp.77-81
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• 2017

A wide spectral coverage from near-infrared (NIR) to far-infrared (FIR) of AKARI both for imaging and spectroscopy enables us to efficiently study the emission from gas and dust in the interstellar medium (ISM). In particular, the Infrared Camera (IRC) onboard AKARI offers a unique opportunity to carry out sensitive spectroscopy in the NIR ($2-5{\mu}m$) for the first time from a spaceborn telescope. This spectral range contains a number of important dust bands and gas lines, such as the aromatic and aliphatic emission bands at 3.3 and $3.4-3.5{\mu}m$, $H_2O$ and $CO_2$ ices at 3.0 and $4.3{\mu}m$, CO, $H_2$, and H I gas emission lines. In this paper we concentrate on the aromatic and aliphatic emission and ice absorption features. The balance between dust supply and destruction suggests significant dust processing taking place as well as dust formation in the ISM. Detailed analysis of the aromatic and aliphatic bands of AKARI observations for a number of H ii regions and H ii region-like objects suggests processing of carbonaceous dust in the ISM. The ice formation process can also be studied with IRC NIR spectroscopy efficiently. In this review, dust processing in the ISM divulged by recent analysis of AKARI data is discussed.