• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1620-1620
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• 2001

Forages, both grazed and conserved, provide the basis of ruminant production systems throughout the world. More than 90 per cent of the feed energy consumed by herbivorous animals world - wide were provided by forages. With such world - wide dependence on forages, the economic and nutritional necessity of been able to characterize them in a meaningful way is vital. The characterization of forages for productive animals is becoming important for several reasons. Relative to conventional laboratory procedures, Near Infrared Reflectance Spectroscopy (NIRS) offers advantages of simplicity, speed, reduced chemical waste, and more cost-effective prediction of product functionality. NIR spectroscopy represents a radical departure from conventional analytical methods, in that entire sample of forage is characterized in terms of its absorption properties in the near infrared region, rather than separate subsamples being treated with various chemicals to isolate specific components. This forces the analyst to abandon his/her traditional narrow focus on the sample (one analyte at a time) and to take a broader view of the relationship between components within the sample and between the sample and the population from which it comes. forage is usually analysed by NIRS in dry and ground presentation. Initial success of NIRS analysis of coarse forages suggest a need to better understand the potential for analysis of minimally processed samples. Preparation costs and possible compositional alterations could be reduced by samples presented to the instrument in undried and unground conditions. NIRS has gained widespread acceptance for the analysis of forage quality constituents on dry material, however little attention has been given to the use of NIRS for chemical determinations on undried and unground forages. Relatively few works reported the use of NIRS to determine quality parameters on undried materials, most of them on both grass and corn silage. Only two works have been found on the determination of quality parameters on fresh forages. The objectives of this paper were (1) to evaluate the use of NIRS for determination of nitrogen and moisture on undried and unground forage samples and (2) to explore two mathematical treatments and two NIR regions to predict chemical parameters on fresh forage. Four hundred forage samples (n: 400) were analysed in a NIRS 6500 instrument (NIR Systems, PA, USA) in reflectance mode. Two mathematical treatments were applied: 1,4,4,1 and 2,5,5,2. Predictive equations were developed using modified partial least squares (MPLS) with internal cross - validation. Coefficient of determination in calibration (${R^2}_{CAL}$) and standard error in cross-validation (SECV) for moisture were 0.92 (12.4) and 0.92 (12.4) for 1,4,4,1 and 2,5,5,2 respectively, on g $kg^{-1}$ dry weight. For crude protein NIRS calibration statistics yield a (${R^2}_{CAL}$) and (SECV) of 0.85 (19.8) and 0.85 (19.6) for 1,4,4,1 and 2,5,5,2 respectively, on a dry weight. It was concluded that NIRS is a suitable method to predict moisture and nitrogen on fresh forage without samples preparation.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1131-1131
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• 2001

To develop a nondestructive quality evaluation technique of fruits, a K-mean algorism is applied to near infrared (NIR) spectroscopy of apples. The K-mean algorism is one of neural network partition methods and the goal is to partition the set of objects O into K disjoint clusters, where K is assumed to be known a priori. The algorism introduced by Macqueen draws an initial partition of the objects at random. It then computes the cluster centroids, assigns objects to the closest of them and iterates until a local minimum is obtained. The advantage of using neural network is that the spectra at the wavelengths having absorptions against chemical bonds including C-H and O-H types can be selected directly as input data. In conventional multiple regression approaches, the first wavelength is selected manually around the absorbance wavelengths as showing a high correlation coefficient between the NIR $2^{nd}$ derivative spectrum and Brix value with a single regression. After that, the second and following wavelengths are selected statistically as the calibration equation shows a high correlation. Therefore, the second and following wavelengths are selected not in a NIR spectroscopic way but in a statistical way. In this research, the spectra at the six wavelengths including 900, 904, 914, 990, 1000 and 1016nm are selected as input data for K-mean analysis. 904nm is selected because the wavelength shows the highest correlation coefficients and is regarded as the absorbance wavelength. The others are selected because they show relatively high correlation coefficients and are revealed as the absorbance wavelengths against the chemical structures by B. G. Osborne. The experiment was performed with two phases. In first phase, a reflectance was acquired using fiber optics. The reflectance was calculated by comparing near infrared energy reflected from a Teflon sphere as a standard reference, and the $2^{nd}$ derivative spectra were used for K-mean analysis. Samples are intact 67 apples which are called Fuji and cultivated in Aomori prefecture in Japan. In second phase, the Brix values were measured with a commercially available refractometer in order to estimate the result of K-mean approach. The result shows a partition of the spectral data sets of 67 samples into eight clusters, and the apples are classified into samples having high Brix value and low Brix value. Consequently, the K-mean analysis realized the classification of apples on the basis of the Brix values.

• Korean Journal of Optics and Photonics
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• v.28 no.4
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• pp.153-157
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• 2017

An infrared camera and laser common-path optical system is applied to DIRCM (directional infrared countermeasures), to increase boresighting accuracy and decrease weight. Thermal effects of a laser beam in a common-path optical system are analyzed and evaluated, to predict any degradation in image quality. A laser beam with high energy density is absorbed by and heats the optical components, and then the surface temperature of the optical components increases. The heated optical components of the common-path optical system decrease system transmittance, which can degrade image quality. For analysis, the assumed simulation condition is that the laser is incident for 10 seconds on the mirror (aluminum, silica glass, silicon) and lens (sapphire, zinc selenide, silicon, germanium) materials, and the surface temperature distribution of each material is calculated. The wavelength of the laser beam is $4{\mu}m$ and its output power is 3 W. According to the results of the calculations, the surface temperature of silica glass for the mirror material and sapphire for the lens material is higher than for other materials; the main reason for the temperature increase is the absorption coefficient and thermal conductivity of the material. Consequently, materials for the optical components with high thermal conductivity and low absorption coefficient can reduce the image-quality degradation due to laser-beam thermal effects in an infrared camera and laser common-path optical system.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1523-1523
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• 2001

The wine industry requires practical methods for objectively measuring the composition of both red wine grapes on the vine to determine optimal harvest time; and of freshly harvested grapes for efficient allocation to vinery process streams for particular red wine products, and to determine payment of contract grapegrowers. To be practical for industry application these methods must be rapid, inexpensive and accurate. In most cases this restricts the analyses available to measurement of TSS (total soluble solids, predominantly sugars) by refractometry and pH by electropotentiometry. These two parameters, however, do not provide a comprehensive compositional characterization for the purpose of winemaking. The concentration of anthocyanin pigment in red wine grapes is an accepted indicator of potential wine quality and price. However, routine analysis for total anthocyanins is not considered as a practical option by the wider wine industry because of the high cost and slow turnaround time of this multi-step wet chemical laboratory analysis. Recent work by this ${group}^{l,2}$ has established the capability of near infrared (NIR) spectroscopy to provide rapid, accurate and simultaneous measurement of total anthocyanins, TSS and pH in red wine grapes. The analyses may be carried out equally well using either research grade scanning spectrometers or much simpler reduced spectral range portable diode-array based instrumentation. We have recently expanded on this work by collecting thousands of red wine grape samples in Australia. The sample set spans two vintages (1999 and 2000), five distinct geographical winegrowing regions and three main red wine grape varieties used in Australia (Cabernet Sauvignon, Shiraz and Merlot). Homogenized grape samples were scanned in diffuse reflectance mode on a FOSE NIR Systems6500 spectrometer and subject to laboratory analysis by the traditional methods for total anthocyanins, TSS and pH. We report here an analysis of the correlations between the NIR spectra and the laboratory data using standard chemometric algorithms within The Unscrambler software package. In particular, various subsets of the total data set are considered in turn to elucidate the effects of vintage, geographical area and grape variety on the measurement of grape composition by NIR spectroscopy. The relative ability of discrete calibrations to predict within and across these differences is considered. The results are then used to propose an optimal calibration strategy for red wine grape analysis.

• Economic and Environmental Geology
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• v.49 no.5
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• pp.335-347
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• 2016

The mineralogical and geochemical characteristics of diverse carbonate rocks can be investigated by using VNIRSWIR(visible near infrared-short wavelength infrared) spectroscopic analysis as a rapid, nondestructive, and inexpensive tool. Comparing whole rock analysis to VNIR-SWIR spectroscopic analysis, the analytical method was investigated to estimate CaO contents, mud impurity, and whiteness of carbonate rocks involved in high-grade limestones in the field. We classify typical carbonate rocks in the upper Pungchon Formation in high-grade limestone mine area such as the Gangweon, Chungmu and Baegun mine in the Jeongseon area. The results show that powdered specimen has much higher reflectance than cutted specimen between the same sample. Whiteness is highly correlated with reflectance(0.99) for powdered specimen. The absorption of mineral mixtures shifts in position as a result of the mass ratio of calcite and dolomite in the Chungmu mine by changing to 75:25, 50:50, and 25:75. The absorption peak position in carbonate mixtures is highly correlated with CaO contents(0.98~0.99). Based on color system, the carbonate rocks are grouped into (milky) white, light grey, light brown, grey, and dark grey. The absorption peak position shifts from 2340 nm to 2320 nm as CaO contents decrease from 55.86 wt.% to 29.71 wt.%. We confirmed that absorption peak position shifts depending on the amount of Ca, which is bonded to $CO{_3}^{-2}$, Mg, and Fe contents replacing Ca. This result suggests that CaO contents in carbonate rocks can be considered to quantitative analysis in the field by spectroscopic analysis.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1246-1246
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• 2001

The quality of meat is highly variable in many properties. This variability originates from both animal production and meat processing. At the pre-slaughter stage, animal factors such as breed, sex, age contribute to this variability. Environmental factors include feeding, rearing, transport and conditions just before slaughter (Hildrum et al., 1995). Meat can be presented in a variety of forms, each offering different opportunities for adulteration and contamination. This has imposed great pressure on the food manufacturing industry to guarantee the safety of meat. Tissue and muscle speciation of flesh foods, as well as speciation of animal derived by-products fed to all classes of domestic animals, are now perhaps the most important uncertainty which the food industry must resolve to allay consumer concern. Recently, there is a demand for rapid and low cost methods of direct quality measurements in both food and food ingredients (including high performance liquid chromatography (HPLC), thin layer chromatography (TLC), enzymatic and inmunological tests (e.g. ELISA test) and physical tests) to establish their authenticity and hence guarantee the quality of products manufactured for consumers (Holland et al., 1998). The use of Near Infrared Reflectance Spectroscopy (NIRS) for the rapid, precise and non-destructive analysis of a wide range of organic materials has been comprehensively documented (Osborne et at., 1993). Most of the established methods have involved the development of NIRS calibrations for the quantitative prediction of composition in meat (Ben-Gera and Norris, 1968; Lanza, 1983; Clark and Short, 1994). This was a rational strategy to pursue during the initial stages of its application, given the type of equipment available, the state of development of the emerging discipline of chemometrics and the overwhelming commercial interest in solving such problems (Downey, 1994). One of the advantages of NIRS technology is not only to assess chemical structures through the analysis of the molecular bonds in the near infrared spectrum, but also to build an optical model characteristic of the sample which behaves like the “finger print” of the sample. This opens the possibility of using spectra to determine complex attributes of organic structures, which are related to molecular chromophores, organoleptic scores and sensory characteristics (Hildrum et al., 1994, 1995; Park et al., 1998). In addition, the application of statistical packages like principal component or discriminant analysis provides the possibility to understand the optical properties of the sample and make a classification without the chemical information. The objectives of this present work were: (1) to examine two methods of sample presentation to the instrument (intact and minced) and (2) to explore the use of principal component analysis (PCA) and Soft Independent Modelling of class Analogy (SIMCA) to classify muscles by quality attributes. Seventy-eight (n: 78) beef muscles (m. longissimus dorsi) from Hereford breed of cattle were used. The samples were scanned in a NIRS monochromator instrument (NIR Systems 6500, Silver Spring, MD, USA) in reflectance mode (log 1/R). Both intact and minced presentation to the instrument were explored. Qualitative analysis of optical information through PCA and SIMCA analysis showed differences in muscles resulting from two different feeding systems.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.41 no.3
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• pp.354-361
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• 1996

Near Infrared Reflectance Spectroscopy(NIRS) is accepted as today's most versatile method for rapid chemical analysis. The technique offers rapid multicomponent analysis. This study was conducted to improve the efficiency of quality analysis in covered barley grain, and to search for the effects of chemical components variation in covered barley grain on NIRS. Among the three groups with different range in the contents, each equation for starch contents increased standard error of prediction(SEP) and increased correlation coefficient from 0.872 to 0.883. According as, $\beta$-glucan and protein contents decreased SEP and increased correlation coefficient by expanded chemical components variation. Effective equation for ash contents analysis was obtained from group 3. Among the covered barley chemical components, starch and ash contents were required to conduct futher studies in term of accuracy and variation of contents. It was concluded that NIRS method would be applicable for the rapid determination of $\beta$-glucan and protein contents in covered barley grains.

• The Korean Journal of Physiology and Pharmacology
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• v.23 no.2
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• pp.141-150
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• 2019

Despite increased evidence of bio-activity following far-infrared (FIR) radiation, susceptibility of cell signaling to FIR radiation-induced homeostasis is poorly understood. To observe the effects of FIR radiation, FIR-radiated materials-coated fabric was put on experimental rats or applied to L6 cells, and microarray analysis, quantitative real-time polymerase chain reaction, and wound healing assays were performed. Microarray analysis revealed that messenger RNA expressions of rat muscle were stimulated by FIR radiation in a dose-dependent manner in amount of 10% and 30% materials-coated. In 30% group, 1,473 differentially expressed genes were identified (fold change [FC] > 1.5), and 218 genes were significantly regulated (FC > 1.5 and p < 0.05). Microarray analysis showed that extracellular matrix (ECM)-receptor interaction, focal adhesion, and cell migration-related pathways were significantly stimulated in rat muscle. ECM and platelet-derived growth factor (PDGF)-mediated cell migration-related genes were increased. And, results showed that the relative gene expression of actin beta was increased. FIR radiation also stimulated actin subunit and actin-related genes. We observed that wound healing was certainly promoted by FIR radiation over 48 h in L6 cells. Therefore, we suggest that FIR radiation can penetrate the body and stimulate PDGF-mediated cell migration through ECM-integrin signaling in rats.

• Journal of Animal Science and Technology
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• v.64 no.3
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• pp.531-538
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• 2022

In Italy, buffalo mozzarella is a largely sold and consumed dairy product. The fraudulent adulteration of buffalo milk with cheaper and more available milk of other species is very frequent. In the present study, Fourier transform infrared spectroscopy (FTIR), in combination with multivariate analysis by partial least square (PLS) regression, was applied to quantitatively detect the adulteration of buffalo milk with cow milk by using a fully automatic equipment dedicated to the routine analysis of the milk composition. To enhance the heterogeneity, cow and buffalo bulk milk was collected for a period of over three years from different dairy farms. A total of 119 samples were used for the analysis to generate 17 different concentrations of buffalo-cow milk mixtures. This procedure was used to enhance variability and to properly randomize the trials. The obtained calibration model showed an R² ≥ 0.99 (R² cal. = 0.99861; root mean square error of cross-validation [RMSEC] = 2.04; R² val. = 0.99803; root mean square error of prediction [RMSEP] = 2.84; root mean square error of cross-validation [RMSECV] = 2.44) suggesting that this method could be successfully applied in the routine analysis of buffalo milk composition, providing rapid screening for possible adulteration with cow's milk at no additional cost.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.23 no.8
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• pp.1010-1021
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• 1999

Camouflage measures in military purpose utilize the apparent temperature difference between target and background, so it is essential to develop a thermal analysis program for apparent temperature predictions and to apply some camouflage measures to real military targets for camouflage purpose. In this study, a thermal analysis program including conduction, convection and radiation is developed and the validity of radiation heat transfer terms is examined. The results show that longwave radiation along with solar radiation should be included in order to predict the apparent temperature as well as the physical temperature precisely. Longwave emissivity variation as an effective camouflage measures is applied to a real M2 tank. From the simulation results, it is found that an effective surface treatment, such as painting of a less emissive material or camouflage clothing, may provide a temperature similarity or a spatial similarity, resulting in an effective camouflage.