• Proceeding of EDISON Challenge
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• 2015.03a
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• pp.575-579
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• 2015

본 연구에서는 스파이럴 보강을 한 원형 실린더 주위의 유동를 분석하였다. 이를 위해 스파이럴 보강 부분을 사각형 부착물로 분리해서 나타내었다. EDISON_CFD의 가상 경계법을 이용하여 원형 실린더와 부착물 주위의 유동 현상을 해석하였다. 부착물의 두께와 각도를 다르게 하여 각각의 공력 계수와 총 합력을 구하고 이에 따른 특성을 분석하였다.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.4
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• pp.485-490
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• 2001

Farmers in the centre of Vietnam have a tradition of dosing young cattle with groundnut oil before fattening them on a diet of rice straw and road-side grass. These farmers claim the cattle grow faster. It was hypothesized that the effect of the oil could be to eliminate the protozoa from the rumen. This is known to increase the net microbial growth efficiency in the rumen and increase the protein supply to the animal. To test this hypothesis, two experiments were undertaken; one on-station with four cattle fitted with rumen cannulae and the second a growth trial with 25 young cattle in smallholder farms. When the cannulated animals were drenched with groundnut oil, the protozoa were eliminated from the rumen and animals could be kept free of protozoa by isolation. The ammonia concentration in the rumen fluid was decreased when the protozoa were eliminated and there was an indication of improved rumen dry matter degradability of the forage components of the diet. In the practical condition on the smallholder farms, the growth rates of cattle drenched with groundnut oil were increased considerably (65%) compared with untreated control animals. The laboratory results when taken together with the on-farm results indicate that these resource-poor farmers had been able to defaunate their cattle and to maintain the fauna-free state by isolation of their animals from extraneous stock. This traditional practice in Central Vietnam, whereby one family keeps only one or two animals that are hand fed and tethered, has quite a large potential for all of those countries where animals are fed agro-industrial by-products, as it is highly economic. The use of 1 litre of oil compared with 1 kg of rice polishing per day (300 kg over 300 days), would be highly profitable in all countries of South-East Asia.

• 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.1621-1621
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• 2001

The quality of sugarcane grown on the NE Australian tropical coast ($16^{\circ}$15'- $18^{\circ}$15' S Lat.) has declined markedly in the past seven years. This has been linked to dilution of mill-supply cane with increasing levels of non mature-stalk material consisting of leaves and sucker culms. The prime research objective was to examine the transition from the pre-harvest, in-field crop to harvested material sent for processing, in terms of quality and crop fraction proportions. A secondary objective was to quantify the effects of preharvest-season crop habit and culm condition on crop quality. Ten quadrat samples from each of 54 random crop sites (17 in 1999 and 37 in 2000), covering a wide range of variables (cultivar, crop class, and edaphic, topographic, climatic, and temporal factors) were collected immediately before harvest. Samples were partitioned into four fractions:- sound and unsound mature stalks (culms), sucker culms, and extraneous matter (leaves). Material harvested from each site was sampled and partitioned into four fractions:- sound and unsound billets (culm pieces), culm-spindle pieces, and leaf. In 2000, before harvest, 14 additional sites were sampled monthly, on three occasions, from March - June. Erect and non-erect culms were divided into sound and unsound classes. All samples were disintegrated and presented to a remote reflectance module of a scanning spectrophotometer using the BSES large cassette module. Near infra-red spectroscopic (NIS) analyses were developed for the rapid determination of quality components (Brix, commercial cane sugar (CCS), fibre, moisture, and polariscope reading). Calibrations for three material groups (culm (n = 639), non-culm (n = 496), and combined) were developed for all components using the 1999 data set. Two sub-sets (n = 178, and 190) of about 10% of the preharvest-season and harvest populations scanned in 2000 also were subjected to full routine laboratory analyses. The 1999 combined calibrations were excellent, but the culm calibrations produced consistently lower standard errors. Non-culm calibrations were marginally better than the combined for only CCS and pol. reading. Analysis of the 2000 culm data with calibrations using all 1999 and 2000 culm data resulted in better predictions relative to the 1999 culm calibrations. This also was true for the combined calibrations. Assessment of quality components in pre- and post-harvest sugarcane using NIS calibrations was more cost effective than using routine laboratory techniques. Outcomes from this NIS-facilitated research will have important economic consequences for the Australian sugarcane industry. Potential CCS present in mature culms is being discounted by dilution with leaves and sucker culms, threatening farm viability. The results question the efficacy of current harvesting technology. The CCS of harvested cane is improved only marginally over that of the in-field crop. Current harvesting technology requires either supplementary, innovative pre-mill processing or a design revolution to improve mill-supply cane quality, and therefore whole of industry economics. NIS-facilitated analyses, before the harvest season, highlighted the benefits of growing erect, sound crops. Loss of CCS then, can be minimized only by a combination of crop improvement and agronomic solutions, applied as part of sound on-farm management.

• Korea Science and Art Forum
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• v.37 no.5
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• pp.239-248
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• 2019

This study started from the need to improve one of shortcomings of synthetic PVAc adhesives - potential physical harm and environmental hazards to the workers or their users. As a matter of fact, PVAc adhesives are currently mainly used because of their convenience and economy for the production of woodcrafts. The purpose of this study was to develop natural adhesives through research on natural adhesives in step with the current increase of societal attention to environmental friendliness and rapid surge in their demand in the face of such problems. So, the study attempted research on the bases to develop natural adhesives for woodcraft, using cellulose extracts from wood - natural adhesive material. The findings of the study were as follows. Firstly, natural adhesives showed the improved effect in the field of adhesive strength, a basic physical property by 0.2 - 4 times compared with the existing materials and the study confirmed they had the similar or stable pH value. Besides, they had good reversibility, demonstrating their basic physical property as a natural adhesive for woodcraft. While, their durability to ultraviolet ray degradation also showed an excellent result value being better by 1.5 - 8.5 times than the existing materials. The study expects natural adhesives with improved and better performances compared with the existing materials could be developed, if further research on adhesive strength, antibiosis, conservative property were to continue by developing refinery technology for cellulose extracts from wood and rendering the functionality to them.

• 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 The Korean Society of Grassland and Forage Science
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• v.39 no.4
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• pp.258-263
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• 2019

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid and accurate method of evaluating some chemical compositions in forages. The objective of this study was to evaluate the potential of NIRS, applied to imported forage, to estimate the moisture and chemical parameters for imported hays. A population of 392 imported hay representing a wide range in chemical parameters was used in this study. Samples of forage were scanned at 1 nm intervals over the wavelength range 680-2500nm and the optical data was recorded as log 1/Reflectance(log 1/R), which 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 spectral math treatments to reduced the effect of extraneous noise. 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 results of this study showed that NIRS predicted the chemical parameters with very high degree of accuracy. The R² and SECV for imported hay calibration were 0.92(SECV 0.61%) for moisture, 0.98(SECV 0.65%) for acid detergent fiber, 0.97(SECV 0.40%) for neutral detergent fiber, 0.99(SECV 0.06%) for crude protein and 0.97(SECV 3.04%) for relative feed value on a dry matter(%), respectively. Results of this experiment showed the possibility of NIRS method to predict the moisture and chemical composition of imported hay in Korea for routine analysis method to evaluate the feed value.

• Journal of The Korean Society of Grassland and Forage Science
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• v.32 no.3
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• pp.301-308
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• 2012

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid and accurate method of evaluating some chemical compositions in forages. This study was carried out to explore the accuracy of near infrared spectroscopy (NIRS) for the prediction of chemical parameters of Italian ryegrass silages. A population of 267 Italian ryegrass silages representing a wide range in chemical parameters and fermentative characteristics was used in this investigation. Samples of silage were scanned at 2 nm intervals over the wavelength range 680~2,500 nm and the optical data 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 spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected on the basis of the highest coefficients of determination in cross validation ($R^2$) and the lowest standard error of cross validation (SECV). The results of this study showed that NIRS predicted the chemical parameters with very high degree of accuracy. The $R^2$ and SECV were 0.98 (SECV 1.27%) for moisture, 0.88 (SECV 1.26%) for ADF, 0.84 (SECV 2.0%), 0.93 (SECV 0.96%) for CP and 0.78 (SECV 0.56), 0.81 (SECV 0.31%), 0.88 (SECV 1.26%) and 0.82 (SECV 4.46) for pH, lactic acid, TDN and RFV on a dry matter (%), respectively. Results of this experiment showed the possibility of NIRS method to predict the chemical composition and fermentation quality of Italian ryegrass silages as routine analysis method in feeding value evaluation and for farmer advice.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.2
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• pp.114-120
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• 2019

This study was carried out to explore the accuracy of near infrared spectroscopy(NIRS) for the prediction of moisture content and chemical parameters on winter annual forage crops. A population of 2454 winter annual forages representing a wide range in chemical parameters was used in this study. Samples of forage were scanned at 1nm intervals over the wavelength range 680-2500nm and the optical data was recorded as log 1/Reflectance(log 1/R), which 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 spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation($R^2$) and the lowest standard error of cross-validation(SECV). The results of this study showed that NIRS calibration model to predict the moisture contents and chemical parameters had very high degree of accuracy except for barely. The $R^2$ and SECV for integrated winter annual forages calibration were 0.99(SECV 1.59%) for moisture, 0.89(SECV 1.15%) for acid detergent fiber, 0.86(SECV 1.43%) for neutral detergent fiber, 0.93(SECV 0.61%) for crude protein, 0.90(SECV 0.45%) for crude ash, and 0.82(SECV 3.76%) for relative feed value on a dry matter(%), respectively. Results of this experiment showed the possibility of NIRS method to predict the moisture and chemical composition of winter annual forage for routine analysis method to evaluate the feed value.