• Journal of Agricultural Extension & Community Development
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• v.4 no.1
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• pp.97-120
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• 1997

This study intends to develop a computer software for an efficient swineherd production and management. Current softwares are concerned on the sow management and ignore the actual farm environment. This study focuses on the farm environment in developing the software and covers the production management financial management, marketing management, and business planning for swineherd farm. The FSR(Farming Systems Research) analysis and interview survey aye applied to collect the data for the system planning, farmer's demand and analysis on the system, system design and program development. The systems are designed to meet the needs for the progressive swineherd farmers. Visual FoxPro 5.1 is used to develop the system. The developed system includes pig farm financial records keeping and management, pig farm production management program, pig farm marketing management program, and pig farm business diagnosis and planning program to meet the scope of the study. The weekly maintenance records and financial records are adopted for the input interface since most of farmers use their computer less than 5 hours a week. Pulldown Menu systems are adopted and designed for easy use by structuring to meet the pig farm and system demands. The manu system allocates the input-output screen based on the sectors, scopes, users, frequencies, importances, and the usages of the information. The GUI(Graphic User Interface) method is used to develop input-output screens for easy use. Backward Chaining mechanism fo the Expert System is used in the diagnosis of the pig farm management and the Systems Simulators Approach is used in the pig farm management planning.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1560-1566
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• 2017

Recently, accumulation of data on pig farm is enabled through the wide spread of smart pig farm equipped with Internet-of-Things based sensors, and various machine learning algorithms are applied on the data in order to improve the productivity of pig farm. Herein, multiple machine learning schemes are used to predict the water usage in pig farm which is known to be one of the most important element in pig farm management. Especially, regression algorithms, which are linear regression, regression tree and AdaBoost regression, and classification algorithms which are logistic classification, decision tree and support vector machine, are applied to derive a prediction scheme which forecast the water usage based on the temperature and humidity of pig farm. Through performance evaluation, we find that the water usage can be predicted with high accuracy. The proposed scheme can be used to detect the malfunction of water system which prevents the death of pigs and reduces the loss of pig farm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.130-133
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• 2020

Smart pig farm which is based on IoT has been widely adopted by many pig farmers. In order to achieve optimal control of smart pig farm, the relation between environmental conditions and performance metric should be characterized. In this study, the relation between multiple environmental conditions including temperature, humidity and various performance metrics, which are daily gain, feed intake, and MSY, is analyzed based on data obtained from 55 real pig farm. Especially, based on preprocessing of data, various regression based machine learning algorithms are considered. Through performance evaluation, we show that the performance can be predicted with high precision, which can improve the efficiency of management.

• Journal of Veterinary Clinics
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• v.32 no.1
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• pp.78-84
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• 2015

Although researches have highlighted the important role of enhanced farm biosecurity to reduce the severity and prevalence of diseases in livestock, to date there has been little study in Korea on farmers' adoption of biosecurity measures to control porcine reproductive and respiratory syndrome virus (PRRSV) infection. To mitigate the risk of PRRSV infection in pigs, the risk factors by which PRRSV is introduced in pig farms must be determined. The primary aim of this study was to investigate pig producers' perceptions about on-farm biosecurity practices. We also analyzed data obtained from a cross-sectional study on 196 farrow-to-finish farms conducted between March 2013 and February 2014 to identify risk factors for PRRSV infection at farm level. Standardized questionnaires with information about basic demographical data and management practices were collected in each farm by on-site visit of trained veterinarians. Farms were classified as negative or positive through the use of infection profiles that combined data on PCR positive pigs and serological testing including antibody titer, sero-conversion pattern at each age category, and vaccination status. Data on biosecurity practices, farm management and environmental characteristics were analyzed using multivariate ordinal logistic regression. Generally, the biosecurity level in the pig farms included in this study were insufficient to reduce/prevent the risk of PRRSV infection given the high pig density areas and the considerable extent of vehicle movement. Factors associated with PRRSV infection were those where owners used on-farm vaccination programs had a lower risk of infection (OR = 0.19, 95% CI 0.06-0.61). The results from the analysis may guide to tailor biosecurity measures in the reduction or prevention of PRRS to the specific circumstances of pig farms in different localities of the world. To the best knowledge of the authors, this is the first study to report information on the biosecurity practices currently implemented on Korean pig farms.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.31-40
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• 2020

As a result of reenforcement of livestock industry licensing and livestock related vehicle registration system, pig farm are mandatory for setting stop bar before pig farm entrance and maintaining the records of inlet and outlet to and from pig farm. Also, the first step to the pig farm biosecurity is the control of entrance human, vehicles, animals and the related records including entrance and sterilization. In this study, the pig farm entrance control system using RFID technology and web-server system was developed. For human entrance, contact type RFID reading system(13.56MHz) was developed. And the 900MHz RFID system was used to detect vehicle entrance. The test result shows that system actuating, recognition, saving records to the web server was successful. Then, the full system of human entrance recording unit, vehicle entrance recording unit, entrance control system, human sterilizing booth containing a tablet for inputting visitor's record and sterilization record was tested. The records were wrote to web server DB through the data management web-program. Performance test shows the entrance control and data management in server was successfully operated.

• Journal of Veterinary Clinics
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• v.16 no.1
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• pp.182-188
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• 1999

This study was performed to determine the causes of the bursting casualties such as death of sows and piglets, abortion, still birth and infertility in a pig farm after consecutive detonation for three months to construct 345 KV in Kimje area. 1. Temperatures in Kimje district, management condition, microorganism in the feed, inbreeding, hematological conditions, and viral agent causing abortion were not proved as the factors of acute occurrence of abortion and infertility in the pig farm. 2. The amount of explosive was increased from 250 kg to 1,100 kg from 23 Dec. 1996 to 28 Jan. 1997 and at the same time the distance between the spot of detonation and the pig farm got closer, from 200 m at the begining to 100 m at the last detonation. 3. Theoretical concussion and sound values were 0.66 kine and 89.39 ㏈, respectively, in the case of 100 m distance between the detonation spot and the pig farm. In conclusion, death of 675 piglets and 11 sows and infertility of 69 sows in the pig farm were assumed to be caused by the concussion or sound stress after detonation.

• Korean Journal of Veterinary Service
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• v.15 no.2
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• pp.174-183
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• 1992

This study was conducted to determine the serum antibodies against toxoplasma in swine from breeding-pig farm, pig farm and abattoir by latex agglutination(LA) test. LA test was carried out with commercial Toxo-MT kit (Eiken chemical co.). The results obtained were summerized as follows : 1. The cut-off titer of positive and negative reactions by Toxo-MT antigen used in this experiment was determined as the serum dilution of 1 ; 32. 2. positive rates of toxoplasma antibodies in 823 swine sera were 17.0%(140 cases) by LA test. 3. The toxoplasma antibody detection rates against 194 swine sera in breeding-pig farm, 273 swine sera in pig farm and 356 swine in abattoir were 46.9%(91 cases), 8.4%(23 cases) and 7.3% (26 cases) , respectively. 4. In LA test serum antibody titers in 823 test sera were shown as 51 cases (36.4%) in 1 : 32, 40(28.6%) in 1；64, 17(12.1%) in 1:128, 14(10.0%) in 1：256, 10(7.1%) in 1:512, 5(3.6%) in 1：1,024, and 3(2.1%) in 1 : 2,048. 5. Positive rates of toxoplasma antibodies in swine sera from each breeding-pig farm were 20.0∼61.9%.

• Korean Journal of Organic Agriculture
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• v.25 no.1
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• pp.233-246
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• 2017

This study was conducted to improve the score of HACCP evaluation items in pig farm. The importance and score of each HACCP evaluation item was derived through the non-compliance rate and severity of hazard. The total score of evaluation items of the pre-requisite section was 200 points and the HACCP section was developed to have a total of 100 points. Implementation of the result of this study to pig farm may help to improve more safety and hygienic pig production. With the result of this study, it is expected that the propose of HACCP system implementation in pig farm will be achieved.

• Journal of Life Science
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• v.19 no.10
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• pp.1451-1455
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• 2009

Porcine cytomegalovirus (PCMV) is a betaherpesvirus which causes reproductive failure in breeding sows and generalized infection in newborn piglets. It has worldwide distribution including Korea. Serological survey on this virus has been reported in 76.3% of pigs, but virological survey and epidemiological analysis on PCMV distribution have been reported in only a few papers in Korea. In this study, we investigated the virological prevalence and infection status of PCMV on a farm level in selected swine farms with respiratory diseases. A total of 1,938 blood samples taken from groups of pigs of different ages were collected from 31 farms distributed nationwide in 2006 and 2007 and tested by PCR to detect the presence of PCMV. Virological prevalence at farm level and pig level were 96.8% and 17.5%, respectively, suggesting that PCMV has endemically infected Korean pig herds. The prevalence at farm level in gilts, sows and suckling piglet groups were 16.7%, 36.7% and 56.7%, indicating that vertical infections frequently occurred in conception or newborn stage. Thereafter, detection rates of PCMV were slightly increased in pig groups aged 40 and 70 days (70.0% and 73.3%), and then gradually decreased as they aged - 33.3% in 100, 26.7% in 130 and 16.7% in 160 day old pig groups. The prevalence at pig level has similar patterns to that at farm level. With the passage of time, the variation of infection patterns of PCMV was investigated in four PCMV-positive farms. Three blood samples were collected at intervals of 6 months in each farm, and examined for presence of PCMV using PCR. The results revealed that once PCMV was introduced to the pig farms, it continuously circulated between and within groups of sows and piglets in those farms. Taken together, it can be concluded that PCMV has endemically infected Korean pig farms and has the potential risk for emerging pathogen in combination with the known endemic pathogens including porcine reproductive, respiratory syndrome virus and porcine circovirus type 2. Therefore, more research is needed on diagnosis, epidemiology and control strategy for PCMV on the field.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.1
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• pp.41-49
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• 2014

Pig chronic wasting disease, including porcine reproductive and respiratory syndrome (PRRS) and postweaning multisystemic wasting syndrome (PMWS), have made a continuous economic damage in pig farms. Airborne spread of livestock viruses are an important spread factor which is difficult to analyze due to invisible airflow and limitation of measurement. The objective of this study is to analyze airborne disease spread between buildings in the experimental pig farm by means of field experiment and computational fluid dynamics (CFD). The field experiments were conducted to capture airborne virus using air sampler and teflon filter along multi points in the experimental pig farm. The samples were tested in terms of virus detection resulting in positive reaction for PRRS and PCV-2 viruses, which can be a firm evidence of airborne virus spread. The CFD simulation model was developed by considering complex topography, wind conditions, building arrangement, and ventilation systems and was used to analyze airborne virus spread according to different wind conditions. The CFD computed result showed a possibility of airborne virus spread via livestock aerosol from infected pig house to neighboring pig houses according to wind directions. The CFD simulation technique is expected to provide significant data for estimating and making a counterplan against airborne disease spread.