• Animal Bioscience
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• v.34 no.4
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• pp.567-574
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• 2021

Objective: In this study we investigated the effect of seasonal thermal stress on milk production and milk compositions between Holstein and Jersey dairy cows under the temperate-climate in Korea. Methods: A total of 9 Holstein lactating dairy cows (2.0±0.11 parity) which had a daily milk yield of 29.77±0.45 kg, and days in milk of 111.2±10.29 were selected similarly at the beginning of the experiments in each season. Also, a total of 9 Jersey lactating dairy cows (1.7±0.12 parity) which had a daily milk yield of 20.01±0.43 kg, and days in milk of 114.0±9.74 were selected similarly at the beginning of the experiments. Results: Results showed that the average ambient temperature (℃) and temperature-humidity index (THI) were higher in summer, and were lower in winter (p<0.05). The average relative humidity (RH, %) was higher in autumn than that of other seasons (p<0.05). Milk production was significantly decreased (Holstein 29.02 kg/d and Jersey 19.75 kg/d) in autumn than in other seasons (Holstein 30.14 kg/d and Jersey 20.96 kg/d). However, the milk production was negatively correlated in Holstein cows, and positively correlated in Jersey cows with THI values increased from 16 to 80. In addition, milk yield was increased by 15% in Holstein cows and decreased by 11% in Jersey cows with the THI values increased from 16 to 20. The fat and protein content percentage was significantly higher in Jersey milk than in Holstein milk, furthermore the fat and protein content yield was higher in Jersey cow milk than that of Holstein cow's milk with all THIs. Conclusion: From the study results, we concluded that Jersey cows might be less adaptable to low temperature of the winter, and this would have a negative impact on dairy farmer income since Korea's milk price estimation system places a higher value on milk yield than on milk compositions or sanitary grades.

• Journal of Environmental Impact Assessment
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• v.14 no.4
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• pp.157-164
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• 2005

Existing models that predict of Daily water supply include statistical models and neural network model. The neural network model was more effective than the statistical models. Only neural network model, which predict of Daily water supply, is focused on estimation of the operational control. Neural network model takes long learning time and gets into local minimum. This study proposes Neuro Genetic hybrid model which a combination of genetic algorithm and neural network. Hybrid model makes up for neural network's shortcomings. In this study, the amount of supply, the mean temperature and the population of the area supplied with water are use for neural network's learning patterns for prediction. RMSE(Root Mean Square Error) is used for a MOE(Measure Of Effectiveness). The comparison of the two models showed that the predicting capability of Hybrid model is more effective than that of neural network model. The proposed hybrid model is able to predict of Daily water, thus it can apply real time estimation of operational control of water works and water drain pipes. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 11.81% and the average error was lower than 1.76%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• Korean Journal of Soil Science and Fertilizer
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• v.27 no.2
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• pp.125-135
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• 1994

Field experiment was carried out in order to clarify effects of plastic film mulching on temperature and moisture of rhizosphere soil and their subsequent effects on seedling emergence, earlier growth, vegetative growth and grain yield of sesame. The textural class of the experimental field soil was the sandy loam(Bonyang series) and the variety of sesame planted was "Ansan-ggae". The experiment was conducted by combining four sowing dates of April 25, May 10, May 25, June 10 and two mulching treatments(mulching, non-mulching) over two year of 1991 and 1992. The results were summarized as follows : 1. The daily mean soil temperature of 5cm deep soil was increased by 1.4 to $2.8^{\circ}C$ by plastic film mulching. The average soil water content was increased by 0.5 to 3.0%(V/V) in the drier season, while decreased by 1.0 to 2.0%(V/V) in the rainy season by mulching. 2. The establishment rate of sesame seedling was very sensitive to soil temperature. For normal seedling emergence, from the seeding date to the 7th date after sowing, the daily mean soil temperature higher than $21.0^{\circ}C$ was required at the experimental field conditions. 3. The average soil water content in the range of 14.0 to 21.0%(V/V) at 5cm deep soil seemed not to be limiting for the germination and emergence of sesame. The effect of soil water content on seedling establishment was very small in this range, but the optimum level of soil water content ranged from 14.0 to 15.0%(V/V) in the experimented sandy loam. 4. The wetter the soil profile was, the larger the gap of soil temperature between the mulched and non-mulched condition was. The effect of mulching on the establishment rate of sesame seedlings was much greater in the lower air temperature conditions. However, when the sowing of sesame came earlier than at the date with the daily mean air temperature below $19.0^{\circ}C$, the effects of earlier sowing and mulching were offsetted by the retarded seedling growth due to the low air temperature, and thus earlier sowing with mulching did not enhance the grain yield of sesame.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.3 no.3
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• pp.161-171
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• 1970

1. The higher the temperature of the sea water, and the smaller the size of the oriental brown shrimp, the higher the feeding rate of the shrimp will be as long as the temperature ranges from $19^{\circ}\;to\;30^{\circ}C$, and each shrimp weighs from 1.6 to 14.9 grams. The average daily feeding rate is between 18 to 44 percent. 2. The nighttime feeding rate is always higher than the daytime feeding rate. However, the daytime feeding rate can be raised to from 22 to 37 percent of the daily feeding rate iii the non-sediment, dark or direct-sunshine-shielded conditions. Growth can thus be accelerated to that extent under such conditions. 3. When anchovy and short-necked clam meats were simultaneously used as food, a greater quantity of anchovy meat was consumed than short-necked clam meat both during the daytime and nighttime. When anchovy and short-necked clam meats were simultaneously given, the averaged daily feeding rates of anchovy and short-necked clam meats were 12.9 percent and 10.3 percent, respectively. 4. The following equation applies to the relationship between the freight of the oriental brown shrimp (W in grams) and their daily growth rate (DGR in percent): log DGR=0.7035-0.7864 log W. The daily growth rate is in inverse proportion to the size of the shrimp. 5. The efficiency of food conversion of the oriental brown shrimp fluctuates between 2.8 and 7.8 percent without extensive difference depending on the size of the shrimp. This was very small as compared with the corresponding figures so far known for fish and cuttlefish.

• Journal of Environmental Science International
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• v.19 no.11
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• pp.1397-1405
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• 2010

Mass mortalities of cultivated organisms have occurred frequently in Korean coastal waters causing enormous losses to cultivating industry. The preventive measures require continuous observation of farm environment and real-time provision of data. However, line hanging aquaculture farm are generally located far from monitoring buoys and has limitations on installation of heavy equipments. Substituting battery pack for solar panels and miniaturizing size of buoy, newly developed system can be attached to long line hanging aquaculture farm. This system could deliver measured data to users in real-time and contribute to damage mitigation and prevention from mass mortalities as well as finding their causes. The system was installed off Gijang and Yeongdeck in Korea, measuring and transmitting seawater temperature at the sea surface every 30 minutes. Short term variation of seawater temperature, less than one day, in Gijang from June to July 2009 corresponded tidal period of about 12 hours and long term variation seemed to be caused by cold water southeast coast of Korea, particularly northeast of Gijang. Seawater temperature differences between Gijang station and the other station that is about 500 m away from Gijang station were $1^{\circ}C$ on average. This fact indicates that it is need to be pay attention to use substitute data even if it is close to the station. Daily range of seawater temperature, one of crucial information to aquaculture, can be obtained from this system because temperature were measured every 30 minutes. Averages of daily range of temperature off Gijang and Yeongdeok during each observation periods were about $2.9^{\circ}C$ and $4.7^{\circ}C$ respectively. Dominant period of seawater temperature variation off Yeongdeok was one day with the lowest peak at 5 a.m. and the highest one at 5 p.m. generally, resulting from solar radiation.

• Journal of Apiculture
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• v.35 no.1
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• pp.9-19
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• 2020

The questionnaire survey for Apis cerana beekeepers and professionals on improved native bee hives was carried out and we compared the temperature, relative humidity(RH), and weight changes of 4 improved hives(Chungju, Miryang, Hanam, and Suwon) from May 1, 2019 to January 31, 2020. Beekeepers need vertical feeder, hive stand, entrance block, and separating panel as hive accessory devices. The average temperatures within brood area were kept constantly (31.3~35.1℃) and the low daily variances of temperature (≤1℃) in Chungju hive among tested hives were observed. The daily temperature variances in the separated space and on the top of winter cluster were not different among 4 hives. In correlation between the temperature of brood area and the number of combs, Chungju hive showed the highest correlation(80.4%) and between the temperature on top of winter clusters and outside temperature, 4 hives showed high positive correlation(76.8~87.1%). RH of brood area(45~60%) in all hives were kept relatively low and constant compared to the outside RH(60~85%). The stablest RH on the top of winter cluster was observed in Suwon hives (65~75%) The highest cumulative weight increase among hives and the high positive correlation(65~67%) between the change of cumulative hive weight and combs number of hives were shown in the Miryang and Chungju. Based on these results, A. cerana bees are able to manage constant temperature and RH within hives area for their colony life, which also effected by the types of hive.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.5
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• pp.37-48
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• 2013

The objective of this study is to assess the impact of potential climate change on the hydrological components, especially on the streamflow, evapotranspiration and snowmelt, by using the Soil Water Assessment Tool (SWAT) for 17 Hanriver middle watersheds of South Korea. For future assessment, the SWAT model was calibrated in multiple sites using 4 years (2006-2009) and validated by using 2 years (2010-2011) daily observed data. For the model validation, the Nash-Sutcliffe model efficiency (NSE) for streamflow were 0.30-0.75. By applying the future scenarios predicted five future time periods Baseline (1992-2011), 2040s (2021-2040), 2060s (2041-2060), 2080s (2061-2080) and 2100s (2081-2100) to SWAT model, the 17 middle watersheds hydrological components of evapotranspiration, streamflow and snowmelt were evaluated. For the future precipitation and temperature of RCP 4.5 scenario increased 41.7 mm (2100s), $+3^{\circ}C$ conditions, the future streamflow showed +32.5 % (2040s), +24.8 % (2060s), +50.5 % (2080s) and +55.0 % (2100s). For the precipitation and temperature of RCP 8.5 scenario increased 63.9 mm (2100s), $+5.8^{\circ}C$ conditions, the future streamflow showed +35.5 % (2040s), +68.9 % (2060s), +58.0 % (2080s) and +63.6 % (2100s). To determine the impact on snowmelt for Hanriver middle watersheds, snowmelt parameters of SWAT model were determined through evaluating observed streamflow data during snowmelt periods (November-April). The results showed that average SMR (snowmelt / runoff) of 17 Hanriver middle watersheds was 62.0 % (Baseline). The annual average SMR were 42.0 % (2040s), 39.8 % (2060s), 29.4 % (2080s) and 27.9 % (2100s) by applying RCP 4.5 scenario. Also, the annual average SMR by applying RCP 8.5 scenario were 40.1 % (2040s), 29.4 % (2060s), 18.3 % (2080s) and 12.7 % (2100s).

• New & Renewable Energy
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• v.8 no.2
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• pp.14-23
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• 2012

The TMY (Typical Meteorological Year) for the solar energy study is generated using observation data with 22 solar sites from KMA (Korea Meteorological Administration) during 11 years (2000-2010). The meteorological data for calculation the TMY are used solar radiation, temperature, dew point temperature, wind speed and humidity data. And the TMY is calculated to apply the FS (Finkelstein and Schafer) statistics and RMSE (Root Mean Squared Error) methods. FS statistics performed with each point and each variable and then selected top five candidate TMM months with statistical analysis and normalization. Finally TMY is generated to select the highest TMM score with evaluation the average errors for the 22 whole points. The TMY data is represented average state and long time variations with 22 sites and meteorological data. When TMY validated with the 11-year daily solar radiation data, the correlation coefficient was about 0.40 and the highest value is 0.57 in April and the lowest value is 0.23 in May. Mean monthly solar radiation of TMY is 411.72 MJ which is 4 MJ higher than original data. Average correlation coefficient is 0.71, the lowest correlation is 0.43 in May and the highest correlation is 0.90 in January. Accumulated annual solar radiation by TMY have higher value in south coast and southwestern region and have relatively low in middle regions. And also, differences between TMY and 11-year mean of is distributed lower 100 MJ in Kyeongbuk, higher 200 MJ in Jeju and higher 125 MJ in Jeonbuk and Jeonnam, respectively.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.77-77
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• 2017

The sensitivities to photoperiod and temperature give guidance to choose an adaptable genotype for specific area in soybean production. However, there is insufficient information about the variation of sensitivities to photoperiod and temperature with wide genetic background. We investigated the sensitivities to photoperiod and temperature using 82 soybean mini core collection lines provided by NIAS gene bank of Japan. The seeds were sown on 28 May and 4 August in 2015, 24 May and 5 August in 2016 at field in Saga, Japan ($33^{\circ}$ 14' 32'' N, $130^{\circ}$ 17' 28'' E) for the early (average photoperiod and temperature: 15.2 h and $25.1^{\circ}C$) and late (13.6 h and $27.2^{\circ}C$) sowing respectively. The plants were also grown in the growth chamber under 12 h photoperiod with three temperature regimes (day/night temperature: $25/18^{\circ}C$, $28/22^{\circ}C$ and $33/28^{\circ}C$). Emergence date, days to first flower were recorded with 10 plants in the field and 2 plants in the growth chamber for each line. The data for daily average temperatures and photoperiodic hours were collected from weather station. The days from emergence to first flower open (DEF) were varied from 23-92 (2015 and 2016) in early sowing whereas 18-68 (2015) and 18-59 (2016) in late sowing. The shortened DEF in late sowing could be caused by both short photoperiod and high temperature in late sowing. However, the accumulated temperatures during emergence to first flower open (ATEF) were less variable in comparison with DEF, suggesting the ATEF is dependent mostly on the photoperiod. The ATEF were found same between early and late sowing in some early flowering lines (e.g. $686.7^{\circ}C$ and $687.6^{\circ}C$ in HEUKDAELIPS, $728.8^{\circ}C$ and $706.3^{\circ}C$ in WILLIAMS'82) which indicated that these would be insensitive to day length. In the growth chamber experiment, the variation in both DEF and ATEF was a little greater at low temperature ($25/18^{\circ}C$) but almost same at middle ($28/22^{\circ}C$) and high ($33/28^{\circ}C$) temperatures. Since the less differences in ATEF were found between the three temperatures, it is suggested that the temperature plays only a quantitative effect on the flower initiation, and the large ATEF in some lines may indicate the stronger photosensitivity even at 12 h or longer juvenile phase. Some lines with the lowest ATEF regardless of growth conditions, such as FISKEBY V, KE 32 (ATEF: 559.6-666.5, 587.7-709.5) might lack the sensitivities to both photoperiod and temperature. The results suggested that soybean genotypes has wider variation in sensitivity to photoperiod, whereas less variation to temperature.