• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.1
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• pp.50-57
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• 2016

This study was conducted to determine the effect of mathematical transformation on near infrared spectroscopy (NIRS) calibrations for the prediction of chemical composition and fermentation parameters in corn silage. Corn silage samples (n=407) were collected from cattle farms and feed companies in Korea between 2014 and 2015. Samples of silage were scanned at 1 nm intervals over the wavelength range of 680~2,500 nm. The optical data were recorded as log 1/Reflectance (log 1/R) and scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with several spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation ($R^2{_{cv}}$) and the lowest standard error of cross validation (SECV). Results of this study revealed that the NIRS method could be used to predict chemical constituents accurately (correlation coefficient of cross validation, $R^2{_{cv}}$, ranging from 0.77 to 0.91). The best mathematical treatment for moisture and crude protein (CP) was first-order derivatives (1, 16, 16, and 1, 4, 4), whereas the best mathematical treatment for neutral detergent fiber (NDF) and acid detergent fiber (ADF) was 2, 16, 16. The calibration models for fermentation parameters had lower predictive accuracy than chemical constituents. However, pH and lactic acids were predicted with considerable accuracy ($R^2{_{cv}}$ 0.74 to 0.77). The best mathematical treatment for them was 1, 8, 8 and 2, 16, 16, respectively. Results of this experiment demonstrate that it is possible to use NIRS method to predict the chemical composition and fermentation quality of fresh corn silages as a routine analysis method for feeding value evaluation to give advice to farmers.

• Asian-Australasian Journal of Animal Sciences
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• v.8 no.3
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• pp.281-287
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• 1995

A study was conducted to investigate the effect of different inclusion levels of urea treated whole-crop wheat silage (UWCWS) in grass silage based rations on the performance of growing beef cattle. The winter wheat (variety, Riband) was harvested (in the summer of 1991) at a dry matter proportion of 520 g/kg and treated with feed grade urea at the rate of 37 kg/tonne crop dry matter and preserved in a heavy duty plastic bag using a silo press. The urea treated whole crop wheat silage (UWCWS) was mixed with grass silage to replace 0.00 (S100), 0.33 (S33) and 0.67 (S67) parts of the forage dry matter and fed ad libitum in a cross over design to 18 Simmental X Holstein Friesian growing beef animals. Two energy sources {one high in starch, rolled barley (RB) and one high in digestible fibre, sugar beet pulp (SBP)} were fed to supply sufficient energy for the efficient use of nitrogen by the rumen micro-organisms. The data on DMIF (dry matter intake of forage), TDMI (total dry matter intake), DLWG (daily live weight gain), FCR (feed conversion ratio) were recorded and faecal samples were collected to determine the digestibility coefficients. Results revealed that with the inclusion of UWCW in the animals' diets the DMI of the forage was significantly increased (p < 0.05). The highest DMIF was found in the treatment "S33" ($6.28{\pm}0.25kg$) where 67% of the silage dry matter was replaced with the UWCW and the lowest value for DMIF was observed in the control treatment ($5.03{\pm}0.23kg$). The DLWG did not differ significantly between the treatments. However, treatment "S100" showed a trend towards a superior DLWG. Feed conversion ratio in the control treatment differed significantly from "S67" and "S33". The addition of the UWCW in the animals' diet resulted in the lower FCR There was no effect of type of energy supplement on any aspect of performance either overall or in interaction with grass silage: UWCWS ratio. The regression and correlation coefficients for DMIF (r = 5.22 + 0.0184x*), DLWG (r = $1.04-0.00086x^{NS}$) and FCR (r = 4.78 = 0.022x*) on the inclusion of UWCW in the diet were calculated. The effect of the inclusion of UWCW on the overall digestibility coefficients was significant (p < 0.05). The addition of the UWCWS in the diet decreased the digestibility of the DM, OM, ADF and NFE but effect on the protein digestibility was non significant. The results of present study suggests that a DLWG slightly over 1 kg can be achieved with UWCW during the store period (period in which animal performance targets are low especially during winter) and the prediction of ME was overestimated as the high intake of DM did not reflect in improved animal performance.

• Journal of Korea Water Resources Association
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• v.40 no.12
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• pp.957-968
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• 2007

It is essential to obtain accurate and highly reliable streamflow data for quantitative management for water resources. Thereafter such real-time streamflow gauging methods as ultrasonic flowmeter and index-velocity are introduced recently. Since these methods calculate flowrate through entire cross-section by measuring partial velocities of it, rational and theoretical basis are necessary for accurate estimation of discharge. The purpose of the present study lies in analysis on the applicability of Chiu#s(1987, 1988) two dimensional velocity distribution equations by applying them to natural rivers and by comparing simulated velocity distributions with observed ones obtained with ADCP. Maximum and mean velocities are calculated from observed data to estimate entropy parameter M. Such isovel shape parameters as h and $\beta_i$ are estimated by object function based on least squares criterion. In case optimized parameters are applied, Chiu#s velocity distributions fairly well simulate observed ones. By using 14 simulated data sets which have relatively high correlation coefficients, properties of parameters are analyzed and h, $\beta_i$ are estimated for velocity-unknown river sections. When estimated parameters are adopted for verification, simulated velocity distributions well reproduce real ones. Finally, calculated discharges display rough agreement with measured data. The results of the present study mean that if parameters related are properly estimated, Chiu#s velocity distribution is likely to reproduce the real one of natural rivers.

• Journal of Korean Society of Forest Science
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• v.89 no.3
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• pp.397-404
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• 2000

This study was carried out to investigate the influence of the road structure and site conditions on side-ditch stability of forest road. For experimental purposes, the forest road in the Kwangrung Experimental Forest, Korea Forestry Research Institute, was chosen as a study site. A total of 556 plots wes set up as every longitudinal gradient changing points by belt-transect method. Data of 10 road structural characteristics and side-ditch stability were collected from each plot and analysed by Quantification II. The main factors in order of partial correlation coefficient were longitudinal gradient, road position, inclination of cut-slope, constituent material of cut-slopes, distance of surface flow, cross-sectional shape of road, pavement material, vegetation of cut-slopes and length of cut-slope. The erosion of side-ditch of forest road occurred in the following cases; more than 8% of the longitudinal gradient, road position of hill under side and foot hill, more than $50^{\circ}$ of inclination of cut-slope, constituent material of cut-slopes of hard soil and gravel soil, more than 80m of distance of surface flow, pavement material with earth or gravel, more than medium covered of vegetation of cut-slopes, and the straight and convex form of road-bed.

• Food Science and Preservation
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• v.24 no.1
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• pp.145-152
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• 2017

In this study, near infrared (NIR) spectroscopy known as a non-destructive analysis technique was applied to investigate peptide cleavage and consequent release of amino acids in soybean lumps as affected by its moisture content and incubation time during fermentation at 25 for 3 weeks. The NIR spectra of the soybean lump semi-dried and soaked in saline water showed that absorption intensity around 1,400 nm originating from hydrogen bonds of water decreased and absorption band shifted to 1,430 nm as moisture content decreased during incubation at 25 for 3 weeks. In addition, absorption around 2,050 nm which was assigned to amino groups increased as incubation time increased. NIR spectra data from 1,000 to 2,250 nm showed higher accuracy in the discriminant analysis between outside and inside parts of fermented soybean lumps than visible spectra result. NIR spectroscopy for the amino acid and moisture contents in traditional fermented soybean lumps showed relatively good accuracy with the multiple correlation coefficient ($R^2$) of 0.91 and 0.81, respectively, and root mean square error of cross validation (RMSECv) of 0.23 and 0.83%, respectively, in partial least square regression (PLSR). These results indicate that NIR spectral observations could be applicable to control the fermentation process for preparation of soybean products.

• The Korean Journal of Pesticide Science
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• v.6 no.3
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• pp.209-217
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• 2002

Two different QSAR methods, the comparative molecular similarity indices analyses (CoMSIA) and hologram quantitative structure activity relationship (HQSAR) are studied for the fungicidal activities ($pI_{50}$) of 2-N-benzyl-5-phenoxy-3-isothiazolone derivatives against sensitive (SPC: 95CC7105) and resisitive (RPC: 95CC7303) phytophthora blight fungus (Phytaphthora capsici). According to the findings from these QSAR investigation, the cross-validation value, $q^2$ and Pearson correlation coefficient, $r^2$ in the two methods were CoMSIA: RPC; $q^2=0.675,\;r^2=0.942$, SPC; $q^2=0.350,\;r^2=0.876$ and HQSAR: RPC; $q^2=0.519,\;r^2=0.869$, SPC; $q^2=0.483,\;r^2=0.990$, respectively. Therefore, the two models of comparative statistical significance were obtained. From the CoMSIA contour maps, the important factors for selective fungicidal activity against RPC are to be expected that the lower hydrophobic and not bulkiness substituent as hydrogen bonding acceptor have to introduce to meta and para-position (C1-C6) on the phenoxy moiety. And the results of prediction suggest that HQSAR method showed higher fungicidal activity than CoMSIA method.

• Journal of Chest Surgery
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• v.35 no.3
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• pp.177-181
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• 2002

Background: Follow-up studies have shown that although outcomes have improved substantially over time, results of the Fontan operation and its modifications remain suboptimal. In this study, we reviewed our experience with the extracardiac conduit Fontan operation, with a focus early and midterm change of internal diameter of PTFE conduit. Material and Method: Between April 1997 and July 2000 were reviewed. Twelve patients (M:6, F:6, mean age 42.04 $\pm$ 12.43months, mean body weight 13.80$\pm$ 1.94kg) underwent extracardiac conduit Fontan operation with expanded PTFE graft. Mean cardiopulmonary bypass time was 109.7$\pm$26.99minute and mean operation time was 455$\pm$89.51minute. Intraoperative fenestration was performed in 10 patients. The aortic cross clamping was not performed in all patients. Result: There was no early deaths and no postoperative dysrhythmia. Postoperative protein losing enteropathy and prolonged pleural effusion occurred in 1(8.3%) and 4 patients(33.3%). Conduit patency was evaluated by magnetic resonance imaging studies. A 9.84$\pm$3.84% mean reduction in conduit internal diameter and there was no statistical correlation between the change of internal diameter of conduit and the postoperative duration after partial correlation analysis(r=0.019, p=0.955). Conclusion: These results demonstrate that the extracardiac conduit Fontan operation provies good early and midterm results and may reduce the prevalence of late arrhythmia. And there is no correlation between the change of internal diameter of conduit and the postoperative duration after extracardiac conduit Fontan operation with the expanded PTFE graft conduit.

• Journal of Plant Biotechnology
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• v.42 no.1
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• pp.60-70
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• 2015

The aim of this study was to investigate whether fourier transform infrared (FT-IR) spectroscopy can be applied to simultaneous determination of fatty acids contents in different soybean cultivars. Total 153 lines of soybean (Glycine max Merrill) were examined by FT-IR spectroscopy. Quantification of fatty acids from the soybean lines was confirmed by quantitative gas chromatography (GC) analysis. The quantitative spectral variation among different soybean lines was observed in the amide bond region ($1,700{\sim}1,500cm^{-1}$), phosphodiester groups ($1,500{\sim}1,300cm^{-1}$) and sugar region ($1,200{\sim}1,000cm^{-1}$) of FT-IR spectra. The quantitative prediction modeling of 5 individual fatty acids contents (palmitic acid, stearic acid, oleic acid, linoleic acid, linolenic acid) from soybean lines were established using partial least square regression algorithm from FT-IR spectra. In cross validation, there were high correlations ($R^2{\geq}0.97$) between predicted content of 5 individual fatty acids by PLS regression modeling from FT-IR spectra and measured content by GC. In external validation, palmitic acid ($R^2=0.8002$), oleic acid ($R^2=0.8909$) and linoleic acid ($R^2=0.815$) were predicted with good accuracy, while prediction for stearic acid ($R^2=0.4598$), linolenic acid ($R^2=0.6868$) had relatively lower accuracy. These results clearly show that FT-IR spectra combined with multivariate analysis can be used to accurately predict fatty acids contents in soybean lines. Therefore, we suggest that the PLS prediction system for fatty acid contents using FT-IR analysis could be applied as a rapid and high throughput screening tool for the breeding for modified Fatty acid composition in soybean and contribute to accelerating the conventional breeding.

• Journal of The Korean Society of Grassland and Forage Science
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• v.26 no.1
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• pp.53-62
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• 2006

Near infrared reflectance spectroscopy (NIRS) has been increasingly used as a rapid, accurate method of evaluating some chemical compositions in forages. Analysis of forage quality by NIRS usually involves dry ground samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations and spectral math treatments on prediction ability of chemical composition for corn silage by NIRS. A population of 112 corn silage representing a wide range in chemical parameters were used in this investigation. Samples of com silage were scanned at 2nm intervals over the wavelength range 400-2500nm and the optical data recorded as log l/Reflectance(log l/R) and scanned in overt-dried grinding(ODG), liquid nitrogen grinding(LNG) or intact fresh(IF) condition. Samples were analysed for neutral detergent fiber(NDF), acid detergent fiber(ADF), acid detergent lignin(ADL), crude protein(CP) and crude ash content were expressed on a dry-matter(DM) basis. The spectral data were regressed against a range of chemical parameters using modified partial least squares(MPLS) multivariate analysis in conjunction with four spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation(SECV). The results of this study show that NIRS predicted the chemical parameters with very high degree of accuracy(the correlation coefficient of cross validation$(R^2cv)$ range from $0.70{\sim}0.95$) in ODG. The optimum equations were selected on the basis of minimizing the standard error of prediction(SEP). The Optimum sample preparation methods and spectral math treatment were for ADF, the ODG method using 2,10,5 math treatment(SEP = 0.99, $R^2v=0.93$), and for CP, the ODG method using 1,4,4 math treatment(SEP = 0.29. $R^2v=0.91$).

• Journal of Animal Environmental Science
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• v.18 no.3
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• pp.257-266
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• 2012

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid, accurate method of evaluating some chemical constituents in cereal and dired animal forages. Analysis of forage quality by NIRS usually involves dry grinding samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations on prediction ability of chemical composition and fermentation parameter for Italian ryegrass silages by NIRS. A population of 147 Italian ryegrass silages representing a wide range in chemical parameters were used in this investigation. Samples were scanned at 1nm intervals over the wavelength range 680-2500 nm and the optical data recorded as log 1/Reflectance (log 1/R) and scanned in oven-dried grinding and fresh ungrinding condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with four spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation (SECV) and maximizing the correlation coefficient of cross validation (${R^2}_{CV}$). The results of this study show that NIRS predicted the chemical parameters with high degree of accuracy in oven-dried grinding treatment except for moisture contents. Prediction accuracy of the moisture contents was better for fresh ungrinding treatment (SECV 1.37%, $R^2$ 0.96) than for oven-dried grinding treatments (SECV 4.31%, $R^2$ 0.68). Although the statistical indexes for accuracy of the prediction were the lower in fresh ungrinding treatment, fresh treatment may be acceptable when processing is costly or when some changes in component due to the processing are expected. Results of this experiment showed the possibility of NIRS method to predict the chemical composition and fermentation parameter of Italian ryegrass silages as routine analysis method in feeding value evaluation and for farmer advice.