Lee, Bae Hun;Kim, Ji Hye;Oh, Mirae;Lee, Ki Won;Park, Hyung Soo
Journal of The Korean Society of Grassland and Forage Science
/
v.41
no.1
/
pp.29-34
/
2021
Near infrared reflectance spectroscopy (NIRS) is routinely used for the determination of nutrient components of forages. However, little is known about the impact of sample preparation and wavelength on the accuracy of the calibration to predict minerals. This study was conducted to assess the effect of sample preparation and wavelength of near infrared spectrum for the improvement of calibration and prediction accuracy of Calcium (Ca) and Phosphorus (P) in imported hay using NIRS. The samples were scanned in reflectance in a monochromator instrument (680-2,500 nm). Calibration models (n = 126) were developed using partial least squares regression (PLS) based on cross-validation. The optimum calibrations were selected based on the highest coefficients of determination in cross validation (R2) and the lowest standard error of cross-validation (SECV). The highest R2 and the lowest SECV were obtained using oven-dry grinded sample preparation and 1,100-2,500 nm wavelength. The calibration (R2) and SECV were 0.99 (SECV: 468.6) for Ca and 0.91 (SECV: 224.7) for P in mg/kg DM on a dry weight, respectively. Results of this experiment showed the possibility of NIRS method to predict mineral (Ca and P) concentration of imported hay in Korea for routine analysis method to evaluate the feed value.
Chang, Sang Wu;Kim, Nam Yong;Choi, Ho Sung;Park, Yong Won;Yun, Keun Young
Korean Journal of Clinical Laboratory Science
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v.36
no.1
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pp.13-18
/
2004
This study was designed to establish working range for reoportable range in own laboratory in order to cover the upper and lower limits of the range in test method. We experimented ten times during 10 days for setting of reportable range with between run for method evaluation. It is generally assumed that the analytical method produces a linear response and that the test results between those upper and lower limits are then reportable. CLIA recommends that laboratories verify the reportable range of all moderate and high complexity tests. The Clinical Laboratory Improvement Amendments(CLIA) and Laboratory Accreditation Program of the Korean Society for Laboratory Medicine states reportable range is only required for "modified" moderately complex tests. Linearity requirements have been eliminated from the CLIA regulations and from others accreditation agencies, many inspectors continue to feel that linearity studies are a part of good lab practice and should be encouraged. It is important to assess the useful reportable range of a laboratory method, i.e., the lowest and highest test results that are reliable and can be reported. Manufacturers make claims for the reportable range of their methods by stating the upper and lower limits of the range. Instrument manufacturers state an operating range and a reportable range. The commercial linearity material can be used to verify this range, if it adequately covers the stated linear interval. CLIA requirements for quality control, must demonstrate that, prior to reporting patient test results, it can obtain the performance specifications for accuracy, precision, and reportable range of patient test results, comparable to those established by the manufacturer. If applicable, the laboratory must also verify the reportable range of patient test results. The reportable range of patient test results is the range of test result values over which the laboratory can establish or verify the accuracy of the instrument, kit or test system measurement response. We need to define the usable reportable range of the method so that the experiments can be properly planned and valid data can be collected. The reportable range is usually defined as the range where the analytical response of the method is linear with respect to the concentration of the analyte being measured. In conclusion, experimental results on reportable range using concentrated control sample and zero calibrators covering from highest to lowest range were salicylate $8.8{\mu}g/dL$, phenytoin $0.67{\mu}g/dL$, phenobarbital $1.53{\mu}g/dL$, primidone $0.16{\mu}g/dL$, theophylline $0.2{\mu}g/dL$, vancomycine $1.3{\mu}g/dL$, valproic acid $3.2{\mu}g/dL$, digitoxin 0.17ng/dL, carbamazepine $0.36{\mu}g/dL$ and acetaminophen $0.7{\mu}g/dL$ at minimum level and salicylate $969.9{\mu}g/dL$, phenytoin $38.1{\mu}g/dL$, phenobarbital $60.4{\mu}g/dL$, primidone $24.57{\mu}g/dL$, theophylline $39.2{\mu}g/dL$, vancomycine $83.65{\mu}g/dL$, valproic acid $147.96{\mu}g/dL$, digitoxin 5.04ng/dL, carbamazepine $19.76{\mu}g/dL$, acetaminophen $300.92{\mu}g/dL$ at maximum level.
Purpose: The conventional gamma camera is not ideal for scintimammography because of its large detector size (${\sim}500mm$ in width) causing high cost and low image quality. We are developing a small gamma camera dedicated for breast imaging. Materials and Methods: The small gamma camera system consists of a NaI (T1) crystal ($60 mm{\times}60 mm{\times}6 mm$) coupled with a Hamamatsu R3941 Position Sensitive Photomultiplier Tube (PSPMT), a resister chain circuit, preamplifiers, nuclear instrument modules, an analog to digital converter and a personal computer for control and display. The PSPMT was read out using a standard resistive charge division which multiplexes the 34 cross wire anode channels into 4 signals ($X^+,\;X^-,\;Y^+,\;Y^-$). Those signals were individually amplified by four preamplifiers and then, shaped and amplified by amplifiers. The signals were discriminated ana digitized via triggering signal and used to localize the position of an event by applying the Anger logic. Results: The intrinsic sensitivity of the system was approximately 8,000 counts/sec/${\mu}Ci$. High quality flood and hole mask images were obtained. Breast phantom containing $2{\sim}7 mm$ diameter spheres was successfully imaged with a parallel hole collimator The image displayed accurate size and activity distribution over the imaging field of view Conclusion: We have succesfully developed a small gamma camera using NaI(T1)-PSPMT and nuclear Instrument modules. The small gamma camera developed in this study might improve the diagnostic accuracy of scintimammography by optimally imaging the breast.
We, for the first time, retrieved sulfur dioxide (SO2) vertical column density (VCD) in industrial and volcanic areas from TROPOspheric Monitoring Instrument (TROPOMI) using the Principle component analysis(PCA) algorithm. Furthermore, SO2 VCDs retrieved by the PCA algorithm from TROPOMI raw data were compared with those retrieved by the Differential Optical Absorption Spectroscopy (DOAS) algorithm (TROPOMI Level 2 SO2 product). In East Asia, where large amounts of SO2 are released to the surface due to anthropogenic source such as fossil fuels, the mean value of SO2 VCD retrieved by the PCA (DOAS) algorithm was shown to be 0.05 DU (-0.02 DU). The correlation between SO2 VCD retrieved by the PCA algorithm and those retrieved by the DOAS algorithm were shown to be low (slope = 0.64; correlation coefficient (R) = 0.51) for cloudy condition. However, with cloud fraction of less than 0.5, the slope and correlation coefficient between the two outputs were increased to 0.68 and 0.61, respectively. It means that the SO2 retrieval sensitivity to surface is reduced when the cloud fraction is high in both algorithms. Furthermore, the correlation between volcanic SO2 VCD retrieved by the PCA algorithm and those retrieved by the DOAS algorithm is shown to be high (R = 0.90) for cloudy condition. This good agreement between both data sets for volcanic SO2 is thought to be due to the higher accuracy of the satellite-based SO2 VCD retrieval for SO2 which is mainly distributed in the upper troposphere or lower stratosphere in volcanic region.
In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.
This research aims to provide the characteristics of the world's first active lidar sensor Atmospheric Laser Doppler Instrument (ALADIN) wind data and Geostationary Korea Multi Purpose Satellite 2A (GK2A) Atmospheric Motion Vector (AMV) data by comparing two wind data. As a result of comparing the data from September 2019 to August 1, 2020, The total number of collocated data for the AMV (using IR channel) and Mie channel ALADIN data is 177,681 which gives the Root Mean Square Error (RMSE) of 3.73 m/s and the correlation coefficient is 0.98. For a more detailed analysis, Comparison result considering altitude and latitude, the Normalized Root Mean Squared Error (NRMSE) is 0.2-0.3 at most latitude bands. However, the upper and middle layers in the lower latitudes and the lower layer in the southern hemispheric are larger than 0.4 at specific latitudes. These results are the same for the water vapor channel and the visible channel regardless of the season, and the channel-specific and seasonal characteristics do not appear prominently. Furthermore, as a result of analyzing the distribution of clouds in the latitude band with a large difference between the two wind data, Cirrus or cumulus clouds, which can lower the accuracy of height assignment of AMV, are distributed more than at other latitude bands. Accordingly, it is suggested that ALADIN wind data in the southern hemisphere and low latitude band, where the error of the AMV is large, can have a positive effect on the numerical forecast model.
In this study, we investigated the performance of a portable colorimeter used for the measurements of atmospheric ammonia against the more reliable method like UV/VIS spectrophotometer. For the purpose of this study, we tested a portable colorimeter and UV/VIS spectrophotometer for such basic analytical parameters as detectibility, reproducibility, linearity, and accuracy. According to our study, the performance of the colorimeter was fairly good to show a good agreement with the UV/VIS system. However, the performance of colorimeter suffered from both low and high concentration ranges: it was found to have very poor reproducibility at lower concentration (below $10\mu}g$), while its linear dynamic range was limited at the upper end (e.g., near $100{\mu}g$). If we assume that air samples are collected up to 30 liter, it implies that the colorimeter can be used to measure samples containing NH3 in the range of 500 ppb to 5 ppm (without the aid of diluting technique). Consequently, we recommend the use of such instrument with the awareness of its basic properties pertaining to the fundamental performance (such as its detectable range).
Do, Jung-Ah;Kim, Jung Yeon;Choi, Ji Yeon;Lee, Ji Hyun;Kim, Hyung Joo;Noh, Eunyoung;Cho, So-Hyun;Yoon, Chang-Yong;Kim, Woo-Seong
Analytical Science and Technology
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v.28
no.2
/
pp.86-97
/
2015
Recently, the consumption of dietary supplements has increased because of people’s greater interest in health. Unfortunately, the sales of dietary supplements containing unauthorized substances such as drugs have also increased. We developed a rapid, accurate method for the simultaneous determination of antihistamines using liquid chromatography tandem mass spectrometry with a multiple reaction monitoring mode. The limit of detection (LOD) and limit of quantification (LOQ) of the instrument used in this method were in the ranges 0.0003-0.3 and 0.0009-0.6 µg mL−1, respectively. The linearity of the method was > 0.99. The precision levels of the method were 0.1-9.8% (intra-day) and 0.3-9.6% (inter-day), and the levels of accuracy of the method were 82.7-115.0% (intra-day) and 84.3-113.0% (inter-day). The mean of recovery of the method was in the range of 83.9-117.9% and the RSD of the stability was less than 5.9%.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
/
2001.06a
/
pp.1265-1265
/
2001
The organic materials included in excreta of livestock are important resources for organic manure and for improving soil quality, although there is still far from effective using. One reason for this is still unclearly standard of quality for evaluation of manure made from excreta of livestock. Therefore, the objective of this study is to develop rapid and accurate analytical method for analyzing organic compositions of manure made from excreta of livestock, and to establish quality evaluation method based on the compositions predicted by near infrared reflectance spectroscopy (NIRS). Sixteen samples of manure, each eight samples prepared from two treatments, were used in this study. The manure samples were prepared by mixing 560 kg feces of swine,60 kg sawdust with moisture content was adjusted to be 65%. The mixture was then keep under two kinds of shelter, black and clear sheets, as a treatment on the effect of sunlight. Samples were taken in every week (form week-0 to 7) during the process of manure making. Samples were analyzed to determine neutral detergent fiber (NDF), acid detergent fiber (ADF) and acid detergent lignin (ADL) by detergent methods, and organic cell wall (OCW) and fibrous content of low digestibility in OCW (Ob) by enzymatic methods. Biological oxygen demand (BOD) was analyzed by coulometric respirometer method. These compositions were carbohydrateds and lignin that were hardly digested. Spectra of samples were scanned by NIR instrument model 6500 (Pacific Scientific) and read over the range of wavelength between 400 and 2500nm. Calibration equations were developed using eight manure samples collected from black sheet shelter, while prediction was conducted to the other eight samples from clear sheet shelter. Accuracy of NTRS prediction was evaluated by correlation coefficients (r), standard error of prediction (SEP) and ration of standard deviation of reference data in prediction sample set to SEP (RPD). The r, SEP and RPD value of forage were 0.99, 0.69 and 7.6 for ADL, 0.96, 1.03 and 4.1 for NDF, 0.98, 0.60 and 4.9 for ADF, 0.92, 1.24 and 2.6 for Ob, and 0.91, 1.02 and 7.3 for BOD, respectively. The results indicated that NIRS could be used to measure the organic composition of forage used in manure samples.
Park, Mikyung;Park, Jin Su;Jo, Mira;Lee, Yong Hwan;Kim, Hyun Jae;Oh, Jun;Choi, Jin Soo;Ahn, Joon Young;Hong, You Deog
Journal of Korean Society for Atmospheric Environment
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v.33
no.6
/
pp.616-625
/
2017
Measurements using five real-time particle samplers were compared to measurements using three NRM (National Reference Method system) filter-based samplers(Gravimetric method) at Incheon, Korea, between May and August, 2014. The purpose of this study was to suggest the quality assurance/quality control (QA/QC) method of each instrument for use in a real-time continuous particle sampler to measure the mass of airborne particles with an aerodynamic diameter less than $2.5{\mu}m$ ($PM_{2.5}$). Five real-time particle samplers of BAM1020, FH62C_14, TEOM, PM-711 and SPM-613 were evaluated by comparing its measured 23 hr average $PM_{2.5}$ concentrations with those measured with NRM filter-based samplers simultaneously. The parameters(e.g. Inlet heating condition, Slope factor, Film response, Intercept, Background, Span value) of the real-time samplers were optimized respectively by conducting test performance evaluation during 7 days in field sampling. For example, inlet heating temperature of TEOM sampler controls $35{\sim}40^{\circ}C$ to minimize the fluctuation of the real-time measurement data and background value of BAM1020 is the key factor affecting the accuracy of $PM_{2.5}$ mass concentration. We classified the $PM_{2.5}$ concentration according to relative humidity (80%) to identify water absorbed in aerosols by measuring the ${\beta}$-ray samplers(BAM1020, FH62C_14) and TEOM. ${\beta}$-ray samplers were not strongly affected by relative humidity that the difference of the average $PM_{2.5}$ concentration was about 5%. On the other hand, The TEOM sampler overestimated $PM_{2.5}$ mass concentration about 15% at low relative humidity (<80%).
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