• Natural Product Sciences
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• 제25권1호
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• pp.44-48
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• 2019

Nelumbo nucifera Gaertn. (Nymphaeaceae) is commonly called lotus and its leaves are widely been used as functional ingredients due to its antioxidant activity. For maximum efficacy, optimized extraction condition was established using response surface methodology. The high F-values, low p-values and insignificant p-value for lack-of-fit supported the fitness of the model and yielded the second-order polynomial regression for the antioxidant activity. The optimized extract was obtained by the extraction of 1 g of lotus leaves with 40 mL of 50% MeOH at $10.0^{\circ}C$, which exerted 70.1% antioxidant activity. Close correlation between phenolic content and antioxidant activity suggested phenolic compounds as active constituents of lotus leaves. In addition, comparison of different parts of lotus demonstrated the most potent antioxidant activity of flowers, followed by leaves and roots. Taken together, these results provide useful information about lotus leaves for the development as antioxidant ingredients. In addition, flowers and roots as well as leaves are suggested as good sources for antioxidant activity.

• Journal of Preventive Veterinary Medicine
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• 제42권4호
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• pp.143-147
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• 2018

The present study aimed to develop growth prediction models of Listeria monocytogenes in processed meat products, such as mixed pressed hams, to perform accurate microbial risk assessments. Considering cold storage temperatures and the amount of time in the stages of consumption after opening, the growth of L. monocytogenes was determined as a function of temperature at 0, 5, 10, and $15^{\circ}C$, and time at 0, 1, 3, 6, 8, 10, 15, 20, 25, and 30 days. Based on the results of these measurements, a Baranyi model using the primary model was developed. The input parameters of the Baranyi equation in the variable temperature for polynomial regression as a secondary model were developed: $SGR=0.1715+0.0199T+0.0012T^2$, $LT=5.5730-0.3215T+0.0051T^2$ with $R^2$ values 0.9972 and 0.9772, respectively. The RMSE (Root mean squared error), $B_f$ (bias factor), and $A_f$ (accuracy factor) on the growth prediction model were determined to be 0.30, 0.72, and 1.50 in SGR (specific growth rate), and 0.10, 0.84, and 1.35 in LT (lag time), respectively. Therefore, the model developed in this study can be used to determine microorganism growth in the stages of consumption of mixed pressed hams and has potential in microbial risk assessments (MRAs).

• Journal of Animal Science and Technology
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• 제63권3호
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• pp.603-613
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• 2021

This research improved the growth potential of Bifidobacterium animalis subsp lactis strain JNU306, a commercial medium that is appropriate for large-scale production, in yeast extract, soy peptone, glucose, L-cysteine, and ferrous sulfate. Response surface methodology (RSM) was used to optimize the components of this medium, using a central composite design and subsequent analyses. A second-order polynomial regression model, which was fitted to the data at first, significantly lacked fitness. Thus, through further analyses, the model with linear and quadratic terms plus two-way, three-way, and four-way interactions was selected as the final model. Through this model, the optimized medium composition was found as 2.8791% yeast extract, 2.8030% peptone soy, 0.6196% glucose, 0.2823% L-cysteine, and 0.0055% ferrous sulfate, w/v. This optimized medium ensured that the maximum biomass was no lower than the biomass from the commonly used blood-liver (BL) medium. The application of RSM improved the biomass production of this strain in a more cost-effective way by creating an optimum medium. This result shows that B. animalis subsp lactis JNU306 may be used as a commercial starter culture in manufacturing probiotics, including dairy products.

• 대한조선학회논문집
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• 제58권6호
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• pp.382-390
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• 2021

The present study suggests the application of a depth camera for wave height field measurement, focusing on the calibration procedure and test setup. Azure Kinect system is used to measure the water surface elevation, with a field of view of 800 mm × 800 mm and repetition rate of 30 Hz. In the optimal optical setup, the spatial resolution of the field of view is 288 × 320 pixels. To detect the water surface by the depth camera, tracer particles that float on the water and reflects infrared is added. The calibration consists of wave height scaling and correction of the barrel distortion. A polynomial regression model of image correction is established using machine learning. The measurement results by the depth camera are compared with capacitance type wave height gauge measurement, to show good agreement.

• Structural Engineering and Mechanics
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• 제88권6호
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• pp.521-533
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• 2023

In the present study, the finite volume method is applied for the thermal performance prediction of the natural ventilation system using vertical solar chimney whereas, design parameters are optimized through the response surface methodology (RSM). The computational simulations are performed for various parameters of the solar chimney such as absorber temperature (40≤T_abs≤70℃), inlet temperature (20≤T₀≤30℃), inlet height of (0.1≤h≤0.2 m) and chimney width (0.1≤d≤0.2 m). Analysis of variance (ANOVA) was carried out to identify the design parameters that influence the average Nusselt number (Nu) and mass flow rate (ṁ). Then, quadratic polynomial regression models were developed to predict of all the response parameters. Consequently, numerical and graphical optimizations were performed to achieve multi-objective optimization for the desired criteria. According to the desirability function approach, it can be seen that the optimum objective functions are Nu=25.67 and ṁ=24.68 kg/h·m, corresponding to design parameters h=0.18 m, d=0.2 m, T_abs=46.81℃ and T₀=20℃. The optimal ventilation flow rate is enhanced by about 96.65% compared to the minimum ventilation rate, while solar energy consumption is reduced by 49.54% compared to the maximum ventilation rate.

• Asian-Australasian Journal of Animal Sciences
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• 제29권5호
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• pp.607-614
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• 2016

The objectives of the study were to estimate genetic parameters for milk production traits of Holstein cattle using random regression models (RRMs), and to compare the goodness of fit of various RRMs with homogeneous and heterogeneous residual variances. A total of 126,980 test-day milk production records of the first parity Holstein cows between 2007 and 2014 from the Dairy Cattle Improvement Center of National Agricultural Cooperative Federation in South Korea were used. These records included milk yield (MILK), fat yield (FAT), protein yield (PROT), and solids-not-fat yield (SNF). The statistical models included random effects of genetic and permanent environments using Legendre polynomials (LP) of the third to fifth order (L3-L5), fixed effects of herd-test day, year-season at calving, and a fixed regression for the test-day record (third to fifth order). The residual variances in the models were either homogeneous (HOM) or heterogeneous (15 classes, HET15; 60 classes, HET60). A total of nine models (3 orders of $polynomials{\times}3$ types of residual variance) including L3-HOM, L3-HET15, L3-HET60, L4-HOM, L4-HET15, L4-HET60, L5-HOM, L5-HET15, and L5-HET60 were compared using Akaike information criteria (AIC) and/or Schwarz Bayesian information criteria (BIC) statistics to identify the model(s) of best fit for their respective traits. The lowest BIC value was observed for the models L5-HET15 (MILK; PROT; SNF) and L4-HET15 (FAT), which fit the best. In general, the BIC values of HET15 models for a particular polynomial order was lower than that of the HET60 model in most cases. This implies that the orders of LP and types of residual variances affect the goodness of models. Also, the heterogeneity of residual variances should be considered for the test-day analysis. The heritability estimates of from the best fitted models ranged from 0.08 to 0.15 for MILK, 0.06 to 0.14 for FAT, 0.08 to 0.12 for PROT, and 0.07 to 0.13 for SNF according to days in milk of first lactation. Genetic variances for studied traits tended to decrease during the earlier stages of lactation, which were followed by increases in the middle and decreases further at the end of lactation. With regards to the fitness of the models and the differential genetic parameters across the lactation stages, we could estimate genetic parameters more accurately from RRMs than from lactation models. Therefore, we suggest using RRMs in place of lactation models to make national dairy cattle genetic evaluations for milk production traits in Korea.

• 한국자원식물학회지
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• 제23권2호
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• pp.172-178
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• 2010

천연집단에 서식하는 개비자나무 개체들을 이용해 무생물 및 생물적 환경인자가homoharringtonine(HHT) 함량에 미치는 영향을 조사하여 향후 항암제 가능성이 있는 HHT의 고부가가치 산업적인 생산이 기대되는 연구에 기초자료를 제공하고자 본 연구를 수행하였다. 무생물적 환경인자(토양습도, 토양pH, 서식밀도, 기온)와 HHT 함량과의 상관관계에 있어 HHT 는 토양습도(0.77)와 토양pH(-0.68)에서 높은 상관을 보였다. 고도에 따른 무생물적 환경인자 (토양습도, 토양pH)와 HHT 의 함량 관계에 관해 다중회귀 분석을 실시한 결과, 토양 습도의 회귀계수($26.48^{***}$) 만 유의하여 토양 습도가 상대적으로 HHT 함량에 높은 영향을 미치는 것으로 나타났다. 생물적 환경인자(damage index)에 따른 HHT 함량에 미치는 영향을 살펴 본 결과, HHT는 2차곡선회귀적으로 증가하다 감소하는($H=278.23+1242D-398.87D^2$) 경향을 보였고 damage index는 HHT 함량에 높은 영향을 미치는 것으로 분석되었다. 마지막으로 HHT 의 함량에 영향을 미치는 최적환경인자를 분석한 결과, damage index와 토양 습도 모두가 2차다항회귀식으로 가장 적합하였고 결정계수는 각각 0.73와 0.67로 damage index가 상대적으로 HHT 함량에 높은 영향을 미치는 것으로 나타났다. 이는 섭식자 또는 균류와 같은 스트레스로 인한 방어기작이 HHT 의 생성에 높은 영향을 미치는 것으로 판단된다.

• 한국산림과학회지
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• 제78권2호
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• pp.143-150
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• 1989

본(本) 연구(硏究)는 무기적(無機的) 환경요인(環境要因)이 잣나무 유묘(幼苗)의 생육(生育)에 마치는 영향(影響)에 관(關)한 연구(硏究)의 일환(一環)으로 이식상(移植床)에서 상대광도(相對光度)와 식재밀도(植栽密度)를 달리하여 생육(生育)시킨 잣나무 묘(苗)의 엽(葉) 중량생장(重量生長)과 타(他) 기관(器官) 생장간(生長間)의 관계(關係)를 조사(調査) 것으로 그 결과(結果)를 요약(要約)하면 다음과 같다. 1. 상대광도별(相對光度別)에 있어서 엽건중(葉乾重)과 타(他) 생장(生長)(지상부(地上部) 건중(乾重), 지하부(地下部) 건중(乾重), 묘(苗) 건중(乾重), 묘경(苗徑)) 간(間)에는 정(正)의 상관관계(相關關係)에 있었고, 또 이들 간(間)에는 1차회귀(次回歸) 관계(關係)도 인정(認定)할 수 있었다. 그러나 엽(葉) 건중(乾重)과 묘장(苗長) 간(間)에는 2차(次) 곡선회귀(曲線回歸) 관계(關係)에 있었다. 식재밀도(植栽密度) 별(別)에 있어서는 엽건중(葉乾重)과 지상부(地上部) 건중(乾重) 및 묘장(苗長) 간(間)에는 2차(次) 곡선회귀관계(曲線回歸關係)에 있었고, 지하부(地下部) 건중(乾重) 및 묘건중(苗乾重) 간(間)에는 1차회귀(次回歸) 관계(關係)에 있었다. 그러나 묘경(苗徑) 간(間)에는 상관(相關)을 인정(認定)할 수 없었다. 2. 상대광도(相對光度) 별(別)에 있어서 엽면적(葉面積)과 지상부(地上部) 건중(乾重) 및 묘(苗) 건중(乾重) 간(間)에는 1차회귀(次回歸) 관계(關係)에 있었고, 지하부(地下部) 건중(乾重) 간(重)과는 지수곡선(指數曲線) 관계(關係), 그리고 엽면적(葉面積)과 묘장(苗長) 간(間)에는 2차곡선(次曲線) 관계(關係)에 있음을 알 수 있었다. 그러나 묘경(苗徑) 간(間)에는 대수(代數) 곡선적(曲線的) 경향(傾向)이었다. 식재밀도(植栽密度) 별(別)에 있어서는 엽면적(葉面積)과 지상부(地上部) 건중(乾重) 간(間)에는 대수곡선(代數曲線) 회귀관계(回歸關係)에 있었고, 지하부(地下部) 건중(乾重) 및 묘(苗) 건중(乾重) 간(間)에는 직선회귀(直線回歸) 관계(關係)에 그리고 엽면적(葉面積)과 묘장(苗長) 및 묘경(苗徑) 간(間)에는 2차곡선(次曲線) 회귀(回歸) 관계(關係)에 있었다.

• 한국초지조사료학회지
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• 제40권3호
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• pp.167-176
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• 2020

The objective of the present study was to determine the best model to describe and quantify the changes in live body weight, height at withers, height at rump, body length and chest girth of Holstein cows raised under Korean feeding conditions for 50 months. The five standard growth models namely polynomial linear regression models, regression of growth variables on the first and second-order of ages in days (model 1) and regression of growth variables on age covariates from first to the third-order (model 2) as well as non-linear models were fitted and evaluated for representing growth pattern of Holstein cows raised in Korean feeding circumstances. Nonlinear models fitted were three exponential growth curve models; Brody, Gompertz, and von Bertalanffy functional models. For this purpose, a total of 22 Holstein cows raised in Korea used in the period from April 2016 to May 2020. Each model fitted to monthly growth curve records of dairy cows by using PROC NLIN procedure in SAS program. On the basis of the results, nonlinear models showed the lower root mean square of error (RMSE) for live body weight, height at withers, height at rump, body length and chest girth (12.22, 1.95, 1.55, 4.04, 2.06) with higher correlation coefficiency (R²) values for live body weight, height at withers, height at rump, body length and chest girth (0.99, 0.99, 0.99, 1.00, 1.00). Overall, the evaluation of the different growth models indicated that the Gompertz model used in the study seemed to be the most appropriate one for standard growth of Holstein cows raised under Korean feeding system.

• 한국수자원학회논문집
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• 제43권12호
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• pp.1083-1091
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• 2010

분포형 수문 모형의 일강우 입력 자료는 불가피하게 불규칙하고 밀도가 낮은 관측망에서 기록된 값을 내삽해 사용하게 되나, 흔히 사용되는 대부분의 내삽법들은 실제 일강우의 다양한 공간적 분포를 잘 재현하지 못하는 문제가 있다. 본 연구에서는 널리 사용되는 다섯 가지의 강우 내삽 방법을 두개의 유역에 사용하여 비교하고 실제 공간적 분포를 보다 잘 나타낼 수 있는 2단계 내삽법을 제안하였다. 비교에 사용된 내삽법은 (1) 역가중치 방법(IDW), (2) 다중회귀분석 (MLR), (3) 월강우를 이용한 다중회귀분석법(CMLR), (4) 국지가중치 다중회귀분석(LWP) 등이다. 보다 향상된 내삽을 위한 2단계 내삽법은 먼저 로지스틱 회귀분석으로 강우-비강우 지역을 구분하고 강우 지역에서만 기존의 내삽법을 적용하여 강우량을 구하는 방법이다. 기존 방법과의 비교결과 공간적인 편차가 심한 일강우의 특성을 2단계 내삽법에서 잘 표현하고 있는 것으로 나타났다. 제안된 방법은 수문모형에의 적용뿐만 아니라 유출량의 예보 및 대기 순환 모형의 다운 스케일링에도 효과적으로 사용될 수 있을 것으로 기대된다.