• Journal of Korea Water Resources Association
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• v.37 no.2
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• pp.133-144
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• 2004

A Tank Model composed of 4 tanks with soil moisture structure was applied to Daecheong Dam and Soyanggang Dam watersheds. Calibration and verification were repeated 332 and 472 times for each watershed using SCE-UA global optimization method for different calibration periods and objective functions. Four different methods of evapotranspiration calculation were used and evaluated. They are pan evaporation, 1963 Penman, FAO-24 Penman-Monteith, and FAO-56 Penman-Monteith methods. Tank model with soil moisture structure showed better results than the standard tank model for daily rainfall-runoff simulation. Two types of objective function for model calibration were found. Proper calibration period are 3 years, in which dry year and flood year are included. If a calibrationperiod has an inadequate runoff rate, the period should be more than 8 years. The four methods of eyapotranspiraton computation showed similar results, but 1963 Penman method was slightly inferior to the other methods.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.37 no.5
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• pp.17-24
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• 2000

Complex permittivity of dry sand is measured by using an open-ended coaxial probe, which was self-designed and manufactured. As a simple calibration scheme of the probe, the phase difference between the measured and the calculated reflection coefficients of pure water is subtracted from the phase of the measured reflection coefficient for dry sand. And then the complex permittivity of dry sand is reconstructed by applying its measured reflection coefficient into an improved imaginary transmission-line model. The accuracy of our measurement scheme is verified by showing that its reconstructed complex permittivity approaches the precise value of dry sand.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1268-1268
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• 2001

The availability of in vivo and in sacco degradability values are limited because those methods require work with fistulated animals and are rather complicated, labour intensive and expensive. That is to say, the dynamics and logistics of the methodology result in considerable work, due to limitations on the amount of samples, number of bags that can be placed in an animal and different time intervals to perform kinetic studies. Therefore, a simpler method is necessary to estimate the degradation characteristics of the feed. In this way, near infrared reflectance spectroscopy has been used to predict degradation characteristics of forages. In other hand, the possibility of achieving successful transfer of spectra and equations between instruments is closely related. The objective of this study was to confirm the potential of NIR to optimize work conditions to avoid duplicated efforts in collaborative trials on animal feeds evaluation between research institutions. For this purpose, one set with forty hays and dehydrated forages samples from SERIDA and ten samples with the same characteristics from SIA, were be used to create a spectral database. A calibration was developed using samples from degradation essays made in SERIDA to predict dry matter and crude protein degradability. With the addition of five samples from SIA in original calibration set, the effect of different origin and location was compensated.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.474-477
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• 2005

The Industrial development and the Increase in population have brought out a rapid increase of wastewater discharge. To deal with this matter, much estimate has been spend on construction and management of a large scale sewage treatment plant. Although every effort has been carried out, river water quality has no significantly improved. Especially. the aggravation of the water quality in dry season is brought out a serious social problem. The purpose of this study Is the development of an optimal water quality management technique considering the efficient control of the multiple pollutant load associated with the total pollutant load control. A GUI(Graphical User Interface) system named 'QL2-XP' model is developed by object-oriencted language for the user convenience and practical usage. Suggested GUI system consist of hydraulic analysis. water quality analysis, optimized model calibration processes, and postprocessing the simulation results.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1127-1127
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• 2001

The transfer of predictive models using various chemometric techniques has been reported for FTNIR and scanning-grating based NIR instruments with respect relatively dry samples (<10% water). Some of the currently used transfer techniques include slope and bias correction (SBC), direct standardization (DS), piecewise direct standardization (PDS), orthogonal signal correction (OSC), finite impulse transform (FIR) and wavelet transform (WT) and application of neural networks. In a previous study (Greensill et at., 2001) on calibration transfer for wet samples (intact melons) across silicon diode array instrumentation, we reported on the performance of various techniques (SBC, DS, PDS, double window PDS (DWPDS), OSC, FIR, WT, a simple photometric response correction and wavelength interpolative method and a model updating method) in terms of RMSEP and Fearns criterion for comparison of RMSEP. In the current study, we compare these melon transfer results to a similar study employing pairs of spectrometers for non-invasive prediction of soluble solid content of peaches.

• Korean Journal of Soil Science and Fertilizer
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• v.37 no.4
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• pp.259-265
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• 2004

A quicker method was developed for foliar analysis in diagnosis of nitrogen in apple trees based on multivariate calibration procedure using partial least squares regression (PLSR) and principal component regression (PCR) to establish the relationship between reflectance spectra in the near infrared region and nitrogen content of fresh- and dry-leaf. Several spectral pre-processing methods such as smoothing, mean normalization, multiplicative scatter correction (MSC) and derivatives were used to improve the robustness and performance of the calibration models. Norris first derivative with a seven point segment and a gap of six points on MSC gave the best result of partial least squares-1 PLS-1) model for dry-leaf samples with root mean square error of prediction (RMSEP) equal to $0.699g\;kg^{-1}$, and that the Savitzky-Golay first derivate with a seven point convolution and a quadratic polynomial on MSC gave the best results of PLS-1 model for fresh-samples with RMSEP of $1.202g\;kg^{-1}$. The best PCR model was obtained with Savitzky-Golay first derivative using a seven point convolution and a quadratic polynomial on mean normalization for dry leaf samples with RMSEP of $0.553g\;kg^{-1}$, and obtained with the Savitzky-Golay first derivate using a seven point convolution and a quadratic polynomial for fresh samples with RMSEP of $1.047g\;kg^{-1}$. The results indicate that nitrogen can be determined by the near infrared reflectance (NIR) technology for fresh- and dry-leaf of apple.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1251-1251
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• 2001

The routine analysis of milk chemical components is of major importance both for the management of animals in dairy farms and for quality control in dairy industries. NIRS technology is an analytical technique which greatly simplifies this routine. One of the most critical aspects in NIRS analysis of milk is sample preparation and analysis modes which should be fast and straightforward. An important difficulty when obtaining NIR spectra of milk is the high water content (80 to 90%) of this product, since water absorbs most of the infrared radiation, and, therefore, limits the accuracy of calibrating for other constituents. To avoid this problem, the DESIR system was set up. Other ways of radiation-sample interaction adapted for liquids or semi-liquids exist, which are practically instantaneous and with limited or null necessity of sample preparation: Transmission and Folded Transmission or Transflectance. The objective of the present work is to compare the precision and accuracy of milk calibration equations in two analysis modes: Reflectance (dry milk) and Folded Transmission (liquid milk). A FOSS-NIR Systems 6500 I spectrophotometer (400-2500 nm) provided with a spinning module was used. Two NIR spectroscopic methods for milk analysis were compared: a) folded transmission: liquid milk samples in a 0.1 pathlength sample cell (ref. IH-0345) and b) reflectance: dried milk samples in glass fibre filters placed in a standard ring cell. A set of 101 milk samples was used to develop the calibration equations, for the two NIR analysis modes, to predict casein, protein, fat and dry matter contents, and 48 milk samples to predict Somatic Cell Count (SCC). The calibrations obtained for protein, fat and dry matter have an excellent quantitative prediction power, since they present $r^2$ values higher than 0.9. The $r^2$ values are slightly lower for casein and SCC (0.88 and 0.89 respectively), but they still are sufficiently high. The accuracy of casein, protein and SCC equations is not affected by the analysis modes, since their ETVC values are very similar in reflectance and folded transmission (0.19% vs 0.21%; 0.16% vs 0.19% and 55.57% vs 53.11% respectively), Lower SECV values were obtained for the prediction of fat and dry matter with the folded transmission equations (0.14% and 0.25% respectively) compared to the results with the reflectance ones (0.43% and 0.34% respectively). In terms of accuracy and speed of analytical response, NIRS analysis of liquid milk is recommended (folded transmission), since the drying procedure takes 24 hours. However, both analysis modes offer satisfactory results.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1510-1510
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• 2001

NIRS uses reflectance signals resulting from bending and stretching vibrations in chemical bonds between carbon, nitrogen, hydrogen, sulfur and oxygen. These reflectance signals are used to measure the concentration of major chemical composition and other descriptors of homogenized and freeze-dried whole broiler carcasses. Six strains of chicken were analyzed and the NIRS model predictions compared to reference data. The results of this comparison indicate that NIRS is a rapid tool for predicting dry matter (DM), fat, crude protein (CP) and ash content in the broiler carcass. Males and females of six commercial strain crosses of broiler chicken (Gallus domesticus) were used in this study (6$\times$2 factorial design). Each strain was grown to 16 weeks of age, and duplicate serial samples were taken for body composition analysis. Each whole carcass was pressure-cooked, homogenized, and a representative sample was freeze-dried. Body composition determined as follows: DM by oven dried method at 105$^{\circ}C$ for 3 hours, fat by Mojonnier diethyl ether extraction, CP by measuring nitrogen content using an auto-analyzer with Kjeldhal digest and ash by combustion in a muffle furnace for 24 hour at 55$0^{\circ}C$. These homogenized and freeze-dried carcass samples were then scanned with a Foss NIR Systems 6500 visible-NIR spectrophotometer (400-2500nm) (Foss NIR Systems, Silver Spring, MD., US) using Infra-Soft-International, ISI, WinISl software (ISI, Port Matilda, US). The NIRS spectra were analyzed using principal component (PC) analysis. This data was corrected for scatter using standard normal “Variate” and “Detrend” technique. The accuracy of the NIRS calibration equations developed using Partial Least Squares (PLS) for predicting major chemical composition and carcass descriptors- such as body mass (BM), bird dry matter and moisture content was tested using cross validation. Discrimination analysis was also used for sex and strain identification. According to Dr John Shenk, the creator of the ISI software, the calibration equations with the correlation coefficient, $R^2$, between reference data and NIRS predicted results of above 0.90 is excellent and between 0.70 to 0.89 is a good quantifying guideline. The excellent calibration equations for DM ($R^2$= 0.99), fat (0.98) and CP (0.92) and a good quantifying guideline equation for ash (0.80) were developed in this study. The results of cross validation statistics for carcass descriptors, body composition using reference methods, inter-correlation between carcass descriptors and NIRS calibration, and the results of discrimination analysis for sex and strain identification will also be presented in the poster. The NIRS predicted daily gain and calculated daily gain from this experiment, and true daily gain (using data from another experiment with closely related broiler chicken from each of the six strains) will also be discussed in the paper.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.1
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• pp.29-34
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• 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.

• Magazine of the Korean Society of Agricultural Engineers
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• v.33 no.4
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• pp.84-95
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• 1991

The compaction ratio of the field dry density to the maximum dry density is generally adopted as the index of quality control for embankment of earthfill structures such as Earth Dam, Sea Dike, River Bank and Road. In case of coarse materials are included in the earth material, the compaction ratio will be varied in wide range since the dry density is influenced by quantity of coarse material in the soil. The treatment for the coarse material should be controlled carefully in testing. In this study, the compaction characteristics of the soil contained the coarse materials were researched and calibration of the suitability of field quality control methods were carried out. 28 Samples were made of clay(CL) and sandy soil (SM) mixed with gravel whose content were 0, 4, 6, 8, 10, 12, 15, 20, 25, 30, 35, 40, 45, and 60% in Weight. The compaction characteristics depending on the coarse material content were analysed through 4 types of compaction tests which are A-1, B-i, C-i and D-1. The adjusting coefficients for density and moisture content namely a and ${\beta}$ respectively were proposed in order to consider the effects depending on content of the coarse materials. The test methods to control reasonably and promptly the quality of earthfill were proposed after analysing the ranges of possible errors on the relative compaction ratio between laboratory compaction methods and field density testing methods.