• Journal of Food Hygiene and Safety
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• v.37 no.4
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• pp.216-224
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• 2022

This study was aimed at validating the analysis methods for deacetylasperulosidic acid (DAA), total sugar, galacturonic acid, glucose, and galactose, which are the indicator components of fermented Morinda citrifolia polysaccharide extract (Vitalbos). We modified the previously reported methods for validating the analytical methods. The specificity, linearity, precision, accuracy, limit of detection (LOD), and limit of quantification (LOQ) were measured using phenol-sulfuric acid method and high-performance liquid chromatography (HPLC). The retention time and spectrum of the standard solution of Vitalbos coincided, confirming the specificity. The calibration curve correlation coefficient (R²), of five indicator components, ranged from 0.9995-0.9998, indicating excellent linearity of 0.99 or more. The intra-day and inter-day precision range of the assay was 0.14-3.01%, indicating a precision of less than 5%. The recovery rate was in the range of 95.13-105.59%, presenting excellent accuracy. The LOD ranged from 0.39 to 0.84 ㎍/mL and the LOQ ranged from 1.18 to 2.55 ㎍/mL. Therefore, the analytical method was validated for DAA, total sugar, galacturonic acid, glucose, and galactose, in Vitalbos. The indicator component content in Vitalbos was determined using a validated method. The contents of DAA, total sugar, galacturonic acid, glucose, and galactose were 2.31±0.06, 475.92±5.95, 72.83±1.05, 71.63±2.44, and 67.30±2.31 mg/g of dry weight, respectively. These results suggest that the developed analytical method is efficient and could contribute to the quality control of Vitalbos, as a healthy functional food material.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1273-1273
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• 2001

The efficiency of the luminal fermentation process influences overall efficiency of luminal production, animal health and reproduction. Ruminant production systems have a significant impact on the global environment, as well. Animal wastes contribute to pollution of the environment as ammonia volatilized to the air and nitrate leached to ground water. Microbial protein synthesis in the rumen satisfies a large proportion of the protein requirements of animals. Quantifying the microbial synthesis is possible by using markers for lumen bacteria and protozoa such as nucleic acids, purine bases, some specific amino acids, or by isotopic $^{15}N,^{32}P,\;and\;^{35}S$ labelled feeds. All those methods require cannulated animals, they are time-consuming and some methods are very expensive as well. Many attempts have been made to find an alternative method for indirect measurement of microbial synthesis in intact animals. The present investigations aimed to assess possibilities of NIRS for prediction of purine nitrogen excretion and ruminal microbial nitrogen synthesis by NIR spectra of urine. Urine samples were collected from 12 growing sheep,6 of them male, and 6- female. The sheep were included in feeding experiment. The ration consisted of sorghum silage and protein supplements -70:30 on dry matter basis. The protein supplements were chosen to differ in protein degradability. The urine samples were collected daily in a vessel containing $60m{\ell}$ 10% sulphuric acid to reduce pH below 3 and diluted with tap water to 4 liters. Samples were stored in plastic bottles and frozen at $-20^{\circ}C$ until chemical and NIRS analysis. The urine samples were analyzed for purine derivates - allantoin, uric acid, xantine and hypoxantine content. Microbial nitrogen synthesis in the lumen was calculated according to Chen and Gomes, 1995. Transmittance urine spectra with sample thickness 1mm were obtained by NIR System 6500 spectrophotometer in the spectral range 1100-2500nm. The calibration was performed using ISI software and PLS regression, respectively. The following statistical results of NIRS calibration for prediction of purine derivatives and microbial protein synthesis were obtained.(Table Omitted). The result of estimation of purine nitrogen excretion and microbial protein synthesis by NIR spectra of urine showed accuracy, adequate for rapid evaluation of microbial protein synthesis for a large number of animals and different diets. The results indicate that the advantages of the NIRS technology can be extended into animal physiological studies. The fast and low cost NIRS analyses could be used with no significant loss of accuracy when microbial protein synthesis in the lumen and the microbial protein flow in the duodenum are to be assessed by NIRS.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.4
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• pp.292-297
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• 2019

In this study, whole crop rice samples were used to develop near-infrared reflectance (NIR) equations to estimate six forage quality parameters: Moisture, crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), Ash and relative feed value (RFV). A population of 564 whole crop rice representing a wide range in chemical parameters was used in this study. Undried finely chopped whole crop rice samples were scanned at 1 nm intervals over the wavelength range 680-2500 nm and the optical data recorded as log 1/Reflectance (log 1/R). NIRS calibrations were developed by means of partial least-squares (PLS) regression. The correlation coefficients of cross-validation (R²_cv) and standard error of cross-validation (SECV) for whole crop rice calibration were 0.98 (SECV 1.81%) for moisture, 0.89 (SECV 0.50%) for CP, 0.86 (SECV 1.79%) for NDF, 0.89 (SECV 0.86%) for ash, and 0.84 (SECV 5.21%) for RFV on a dry matter (%), respectively. The NIRS calibration equations developed in this study will be useful in predicting whole crop rice quality for these six quality parameters.

• Journal of the Korean Vacuum Society
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• v.19 no.4
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• pp.243-248
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• 2010

Sonic nozzles have been a standard device for measurement of steady state gas flow, as recommended in ISO 9300. This paper introduces two sonic nozzles of diameter ${\Phi}$ 0.03 mm and ${\Phi}$ 0.2 mm precisely machined according to ISO 9300. The constant volume flow meter(CVFM), readily set up in the Vacuum center of KRISS. was used to calibrate the discharge coefficients of both nozzles. The calibration results were shown to determine them within the 3% expanded measurement uncertainty. Calibrated sonic nozzles were found to be applicable for precision measurement of steady state gas flow in the vacuum process in the ranges of 0.6~1,800 cc/min. Those flow conditions are equivalent to the fine gas flow with Reynolds numbers of 26~12,100. Those encouraging results confirm that calibrated sonic nozzles enable precision measurement of extremely low gas flow encountered very often in th vacuum processes. Both calibrated sonic nozzles are proven to provide the precision measurement of the volume flow rate of the dry vacuum pump within one percent difference in reference to CVFM. Calibrated sonic nozzles are applied to a new 'in-situ and in-field' equipment designed to measure the volume flow rate of vacuum pumps in the semiconductor and flat display processes. Furthermore, they can provide other applications to flow control devices in vacuum, such as MFC, etc.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.3
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• pp.13-20
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• 2009

Techniques for change detection using satellite images enable efficient detection of natural and artificial changes in use of land through multi-phase images. As for change detection, different results are made based on methods of calibration of satellite images, types of input data, and techniques in change analysis. Thus, an analytic technique that is appropriate to objectives of a study shall be applied as results are different based on diverse conditions even when an identical satellite and an identical image are used for change detection. In this study, Normalized Difference Vegetation Index (NDVI) and Principal Component Analysis (PCA) were conducted after geometric calibration of satellite images which went through absolute and relative radiometric calibrations and change detection analysis was conducted using Image Difference (ID) and Image Rationing (IR). As a result, ID-NDVI showed excellent accuracy in change detection related to vegetation. ID-PCA showed 90% of accuracy in all areas. IR-NDVI had 90% of accuracy while it was 70% and below as for paddies and dry fields${\rightarrow}$grassland. IR-PCA had excellent change detection over all areas.

• Journal of The Korean Society of Grassland and Forage Science
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• v.26 no.1
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• pp.45-52
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• 2006

This study was carried out to explore the accuracy of Near Infrared Reflectance Spectroscopy (NIRS) fer the prediction of digestibility and energy value of corn silages. The spectral data were regressed against a range of digestibility and energy parameters using modified partial least squares(MPLS) multivariate analysis in conjunction with first and second order derivatization, with scatter correction procedure(SNV-Detrend) to reduce the effect of extraneous noise. Calibration models for NIRS measurements gave multivariate correlation coefficients of determination$(R^2)$ and standard errors of cross validation of 0.92(SECV 1.73), 0.91(SECV 1.13) and 0.93(SECV 1.74) for in vitro dry matter digestibility(IVDMD), in vitro true digestibility(IVTD), and cellulase dry matter digestibility(CDMD), respectively. The standard error of prediction(SEP) and the multiple correlation coefficient of validation$(R^2v)$ on the validation set(n=39) was used in comparing the prediction accuracy. The SEP value was 0.30(TDN), 0.01(NEL), and 0.01(ME). The relative ability of NIRS to predict digestibility and energy value was very good for CDMD, total digestible nutrients(TDN), net energy fer lactation(NEL) and metabolizable energy(ME). This paper shows the potential of NIRS to predict the digestibility and energy value of con silage as a routine method in feeding programmes and for giving advice to farmers.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1612-1612
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• 2001

The production of grain for export and domestic use is one of Australia's most important agricultural industries, and the NIR technique has been used extensively over many years for the routine monitoring of grain quality, particularly moisture and protein content. Because most Australian grain is intended for human food production, the determinants of grain quality for livestock feed, apart from protein, have been largely ignored. However the increasing use of grain for feeding to pigs, poultry, beef cattle and dairy cows has led to an important national research project entitled “Premium Grains for Livestock”. Two of the objectives of this project are to determine the compositional and functional characteristics of grains which influence their nutritional quality for the various classes of livestock, and to adopt rapid and objective analytical tests for these quality criteria. NIR has been used in this project firstly to identify a set of grain samples from a large population of breeders' lines which showed a wide spectral variation, and hence a potentially wide variation in nutritional value. The selected samples were not only subjected to an extensive array of chemical, physical and in vitro analyses, but also were grown out to produce sufficient quantities of grain to feed to animals in vivo studies. Additional grains were also strategically selected from farms in order to include the effect of weather damage, such as rain, drought and frost. In this study to date, NIR calibrations have been derived or attempted, on both ground and whole grains, for in vivo dry matter digestibility (DMD), pepsin-cellulase dry matter disappearance, protein, fat, acid detergent fibre, neutral detergent fibre, starch, in sacco DMD and in vitro assays to simulate starch digestion in the lumen and small intestine. Results so far indicate high calibration accuracy for chemical components (SECV 0.3 to 2.6%) and very promising statistics for in vivo DMD (SECV 1.8, $R^2$ 0.93, SD 7.0, range 61.9 to 92.3, n=60). There appears to be some potential for NIR to estimate some in vitro properties, depending upon the accuracy of reference methods and appropriate sample populations. Current work is in progress to extend the range of grains with in vivo DMD values (a very laborious and expensive process) and to increase the robustness of the various NIR calibrations, with the aim of implementing uniform testing procedures for nutritional value of grains throughout Australia.

• Journal of Microbiology and Biotechnology
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• v.17 no.12
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• pp.1922-1929
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• 2007

A simple whole-cell-based sensing system is proposed for determining the cell mass of H. pluvialis using ultraviolet fluorescence spectroscopy. An emission signal at 368 nm was used to detect the various kinds of green, green-brown, brown-red, and red H. pluvialis cells. The fluorescence emission intensities of the cells were highest at 368 nm with an excitation wavelength of 227 nm. An excitation wavelength of 227 nm was then selected for cell-mass sensing, as the emission fluorescence intensities of the cell suspensions were highest at this wavelength after subtracting the background interference. The emission fluorescence intensities of HPLC-grade water, filtered water, and HPLC-grade water containing a modified Bold's basal medium (MBBM) were measured and the difference was less than 1.6 for the selected wavelengths. Moreover, there was no difference in the emission intensity at 368 nm among suspensions of the various morphological states of the cells. A calibration curve of the fluorescence emission intensities. and cell mass was obtained with a high correlation ($R^2=0.9938$) for the various morphological forms of H. pluvialis. Accordingly, the proposed method showed no significant dependency on the various morphological cell forms, making it applicable for cell-mass measurement. A high correlation was found between the fluorescence emission intensities and the dry cell weight with a mixture of green, green-brown, brown-red, and red cells. In conclusion, the proposed model can be directly used for cell-mass sensing without any pretreatment and has potential use as a noninvasive method for the online determination of algal biomass.

• Environmental Engineering Research
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• v.16 no.3
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• pp.121-129
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• 2011

The completely mixed flow and plug flow (CAP) water quality model was developed for streams with discontinuous flows, a condition that often occurs in low base flow streams with in-stream hydraulic structures, especially during dry seasons. To consider the distinct physical properties of each reach effectively, the CAP model stream network can include both plug flow (PF) segments and completely mixed flow (CMF) segments. Many existing water quality models are capable of simulating various constituents and their interactions in surface water bodies. More complicated models do not necessarily produce more accurate results because of problems in data availability and uncertainties. Due to the complicated and even random nature of environmental forcing functions, it is not possible to construct an ideal model for every situation. Therefore, at present, many governmental level water quality standards and decisions are still based on lumped constituents, such as the carbonaceous biochemical oxygen demand (CBOD), the total nitrogen (TN) or the total phosphorus (TP). In these cases, a model dedicated to predicting the target concentration based on available data may provide as equally accurate results as a general purpose model. The CAP model assumes that its water quality constituents are independent of each other and thus can be applied for any constituent in waters that follow first order reaction kinetics. The CAP model was applied to the Geum River in Korea and tested for CBOD, TN, and TP concentrations. A trial and error method was used for parameter calibration using the field data. The results agreed well with QUAL2EU model predictions.

• Tunnel and Underground Space
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• v.13 no.6
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• pp.465-475
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• 2003

Groundwater inflow into the caverns constructed in fractured rock mass was simulated by numerical modeling, NAPSAC (DFN, discrete fracture network model) and NAMMU (CPM, continuous porous media model), a finite-element software package for groundwater flow in 3D fractured media developed by AEA Technology, UK. The input parameters for modeling were determined on surface fracture survey, core logging and single hole hydraulic test data. In order to predict the groundwater inflow more accurately, the anisotropic hydraulic conductivity was considered. The anisotropic hydraulic conductivities were calculated from the fracture network properties. With a minor adjustment during model calibration, the numerical modeling is able to reproduce reasonably groundwater inflows into cavern and the travel length and times to the ground surface along the flow paths in the normal, dry and rainy seasons.