• Korean Journal of Plant Resources
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• v.27 no.4
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• pp.286-292
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• 2014

Near infrared reflectance spectroscopy (NIRS) is a rapid and accurate analytical method for determining the composition of agricultural products and feeds. This study was conducted to measure baicalin, baicalein, and wogonin contents in Scutellaria baicalensis by using NIRS system. Total 63 samples previously were analyzed by HPLC, which showed baicalin, baicalein, and wogonin contents ranging 4.56 to 13.59%, 0.28 to 5.54%, and 0.50 to 1.63% with an average of 9.66%, 2.09% and 0.52%, respectively. Each sample was scanned by NIRS and calculated for calibration and validation equation. A calibration equation calculated by modified partial least squares(MPLS) regression technique was developed in which the coefficient of determination for baicalin, baicalein, and wogonin content was 0.958, 0.944, and 0.709, respectively. Each calibration equation was applied to validation set that was performed with the remaining samples not included in the calibration set, which showed high positive correlation both in baicalin and baicalein content file. In case of wogonin, the prediction model was needed more accuracy because of low $R^2$ value in validation set. These results demonstrate that the developed NIRS equation can be practically used as a rapid screening method for quantification of baicalin and baicalein contents in Scutellaria baicalensis.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.369-377
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• 2011

Since well-calibrated satellite data is critical for their applications, calibration and validation of COMS science data was one of the key activities during the IOT. COMS MI radiometric calibration process was divided into two phases according to the out-gassing of the sensor: calibrations of the visible (VI) and infrared (IR) channels. Different from the VIS calibration, the calibration steps for the IR channels followed additional processes to secure their radiometric performances. Primary calibration steps of the IR were scan mirror emissivity correction, midnight effect compensation, slope averaging and 1/f noise compensation after a nominal calibration. First, the scan mirror emissivity correction was conducted to compensate the variability of the scan mirror emissivity driven by the coating material on the scan mirror. Second, the midnight effect correction was performed to remove unreasonable high spikes of the slope values caused by the excessive radiative sources during the local midnight. After these steps, the residual (difference between the previous slope and the given slope) was filtered by a smoothing routine to eliminate the remnant random noises. The 1/f noise compensation was also carried out to filter out the lower frequency noises caused from the electronics in the Imager. With through calibration processes during the entire IOT period, the calibrated IR data showed excellent performances.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1091-1091
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• 2001

Previous reports have shown that Near Infrared Spectroscopy (NIRS) can be used to assess physical and chemical properties of flax fibre and fabric quality. Currently, spinners assess yarn quality mainly based on strength and regularity measurements. There two key characteristics are influenced by quality of raw fibres used, especially the degree of rotting and strength. The aim of this investigation was to evaluate the use of NIRS for assessing quality of weft grade yarn available on the commercial market. In order to develop the NIR calibrations, a range of samples representing poor, medium and good quality weft yarn samples was included in the calibration and validation sample sets. The samples were analysed for physical and chemical parameters including caustic weight loss, fibre fractions, lipid, ash and minerals. A detailed protocol for assessing yarn quality has been developed to maximize the accuracy of the reflectance spectra. The development of partial least squares regression models and validation of the calibration equations using blind samples will be presented and discussed.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.5
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• pp.9-16
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• 2011

Curve Numbers (CN) for the combination of land use and hydrologic soil group were regionalized at Imha Watershed using Long-term Hydrologic Impact Assessment (L-THIA) coupled with SCE-UA. The L-THIA was calibrated during 1991-2000 and validated during 2001-2007 using monthly observed direct runoff data. The Nash-Sutcliffe (NS) coefficients for calibration and validation were 0.91 and 0.93, respectively, and showed high model efficiency. Based on the criteria of model calibration, both calibration and validation represented 'very good' fit with observe data. The spatial distribution of direct surface runoff by L-THIA represented runoff from Thiessen pologen at Subi and Sukbo rain gage station much higher than other area due to the combination of poor hydrologic condition (hydrologic soil C and D group) and locality heavy rainfall. As a results of hydrologic condition and treatment for land use type based on calibrated CNs, forest is recommended to be hydrologically modelled dived into deciduous, coniferous, and mixed forest due to the hydrological difference. The CNs for forest and upland showed the poor hydrologic condition. The steep slope of forest and alpine agricultural field make high runoff rate which is the poor hydrologic condition because CN method can not consider field slope. L-THIA linded with SCE-UA could generated a regionalized CNs for land use type with minimized time and effort, and maximized model's accuracy.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.171-183
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• 2011

Temporal and spatical surface runoff by heavy rainfall during 25~28 July, 2011 causing urban flooding at Seoul were analyzed using Long-Term Hydrologic Impact Assessment (L-THIA). L-THIA was calibrated for 1988~1997 and validated for 1998~2007 using monthly observed data at Hangangseoul watershed which covers 90 % of Seoul city. As a results of calibration and validation of L-THIA at Hangangseoul watershed, Nash-Sutcliffe coefficients were 0.99 for calibration and 0.99 for validation. The simulated values were good agreement with observed data and both calibrated and validated levels were "very good" based on calibration criteria. The calibrated curve number (CN) values of residential and other urban area represented 87 % and 93 % of impervious area, respectively, which were maximum percentage of impervious area. As a result of L-THIA application at Seoul city during 25~28 July, 2011, most of rainfall (54 %, 287.49 mm) and surface runoff (65 %, 247.32) were generated at 27 July, 2011 and a significant amount of rainfall and surface runoff were occurred at southeastern Seoul city. As a result of bi-hourly spatial and temporal analysis during 27 July, 2011, surface runoff during 2:00~4:00 and 8:00~10:00 were much higher than those during other times and surface runoff located at Seocho-gu during 6:00~8:00 represented maximum value with maximum rainfall intensity which caused landslide from Umyun mountain.

• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.161-166
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• 2008

The major purpose of this paper is to develop an uncertainty estimate for the calibration of thermopile instruments used to measure solar radiation parameters. We briefly describe the solar radiation parameters most often measured, instrumentation, reference standards, and calibration techniques. The bulk of the paper describes elemental sources of error and their magnitude. We then apply a standard error analysis methodology to combine these elemental error estimates into a statement of total uncertainty for the instrument calibration factor. Our results allow one to evaluate the accuracy of a radiometric measurement using thermopile instrumentation in the light of the application, such as engineering test evaluation or for validation of theoretical models.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.448-448
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• 2018

In this study, the regression models (Load ESTimator and eight-parameter model) were evaluated to estimate instantaneous pollutant loads under various criteria and optimization methods. As shown in the results, LOADEST commonly used in interpolating pollutant loads could not necessarily provide the best results with the automatic selected regression model. It is inferred that the various regression models in LOADEST need to be considered to find the best solution based on the characteristics of watersheds applied. The recently developed eight-parameter model integrated with Genetic Algorithm (GA) and Gradient Descent Method (GDM) were also compared with LOADEST indicating that the eight-parameter model performed better than LOADEST, but it showed different behaviors in calibration and validation. The eight-parameter model with GDM could reproduce the nitrogen loads properly outside of calibration period (validation). Furthermore, the accuracy and precision of model estimations were evaluated using various criteria (e.g., $R^2$ and gradient and constant of linear regression line). The results showed higher precisions with the $R^2$ values closed to 1.0 in LOADEST and better accuracy with the constants (in linear regression line) closed to 0.0 in the eight-parameter model with GDM. In hence, based on these finding we recommend that users need to evaluate the regression models under various criteria and calibration methods to provide the more accurate and precise results for pollutant load estimations.

• Journal of Environmental Impact Assessment
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• v.22 no.6
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• pp.695-703
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• 2013

Soil erosion and sediment delivery ratio(SDR) were estimated by using HSPF model in 3 tributaries of upper stream of Geum river-basin. Meteorological data and other input data were constructed from 2006 to 2011 year by the HSPF model. Flow and suspended solid results were relatively matched with the measurement data through the calibration and validation of the model. Soil erosion was proportional to the amount of rainfall and the area of watershed based on the results of model calibration and validation. SDR in Moojunamdea stream was the highest and one in Cho stream was the lowest. This was effected by the geographical characteristic. SDR was 17.6% Moojunamdea stream, 9.1% Cho stream and 13.2 % Bocheong stream. As the SDR was effected by watershed area and shape factor in this study area.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1512-1512
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• 2001

The University of Cordoba conducts since 1991 a breeding program to obtain new olive cultivars from intraspecific crosses. The objective is to obtain new early bearing and high-quality cultivars. In plant breeding, many seedlings must be tested to increased the chance of getting desirable genotypes. Therefore, fast, cheap and accurate methods of analysis are necessary. The conventional laboratory techniques are costly and time-consuming. Near Infrared Spectroscopy (NIRS) can satisfy the characteristics requested by plant breeders and offers many advantages such as the simultaneous analysis of many traits and cheap cost. The objective of this work was to asses the performance of NIRS to estimate oil fruit components (fruit weight, flesh moisture, flesh/stone ratio and oil flesh content in dry weight basis) and fatty acid composition in olive fruit. Genotypes from reciprocal crosses between ‘Arbequina’, ‘Frantoio’ and ‘Picual’ cultivars have been used in this study. A total of 287 samples, each from a single plant, were scanned using a DA-7000 Diode Array VIS/NIR Analysis System (Perten Instruments), which covers the visible and NIR range from 400-1700 nm. All samples were analysed for fatty acid composition (gas chromatography) and 220 for oil fruit components (oil content by nuclear magnetic resonance), 70% and 30% of samples were randomly assign for the calibration and validation sets respectively. The preliminary results shows that calibration for palmitic, oleic and linoleic acids were highly accurate with calibration and validation values of $r^2$ from 0.85 to 0.95 and 0.76 to 0.91 respectively. Calibration for palmitoleic and estearic acids were less accurate, probably because of the narrow range of variability available for these fatty acids. For the oil fruit components, calibration were high accurate for flesh moisture and oil flesh content in dry weight basis ($r^2$ higher than 0.90 in both calibration and validation sets) and less accurate for the other characteristics evaluated. The first results obtained indicate that NIRS analysis could be an ideal technique to reduce the cost, time and chemical wasted necessary to evaluate a large number of genotypes and it is accurate enough to use for pre-selecting genotypes in a breeding program.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.63-70
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• 2017

The purpose of this study was to calibrate the hydrologic parameters of SWAT model and analyze the daily runoff for the study watershed using SWAT-CUP. The Hardware watershed is located in Virginia, USA. The watershed area is $356.15km^2$, and the land use accounts for 73.4 % of forest and 23.2 % of pasture. Input data for the SWAT model were obtained from the digital elevation map, landuse map, soil map and others. Water flow data from 1990 to 1994 was used for calibration and from 1997 to 2005 was for validation. The SUFI-2 module of the SWAT-CUP program was used to calibrate the hydrologic parameters. The parameters were calibrated for the highly sensitive parameters presented in previous studies. The P-factor, R-factor, $R^2$, Nash-Sutcliffe efficiency (NS), and average flow were used for the goodness-of-fit measures. The applicability of the model was evaluated by sequentially increasing the number of applied parameters from 4 to 11. In this study, 10-parameter set was accepted for calibration in consideration of goodness-of-fit measures. For the calibration period, P-factor was 0.85, R-factor was 1.76, $R^2$ was 0.51 and NS was 0.49. The model was validated using the adjusted ranges of selected parameters. For the validation period, P-factor was 0.78, R-factor was 1.60, $R^2$ was 0.60 and NS was 0.57.