• Korean Journal of Food Science and Technology
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• v.47 no.3
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• pp.401-404
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• 2015

A sandwich ELISA (sELISA) to detect pork in processed foods was developed using goat anti-pig IgG antibodies. From the sELISA standard curve, the detection range of pork was $3-1,000{\mu}g/mL$. The cross-reactivity between the pig IgG antibodies, pork, and other meats (beef, chicken, fish, and crustaceas) was 100, 0.18, and 0%, respectively. When pork was heated for 10 min, the mean assay recoveries of pig-IgG were 79-32% at $60-70^{\circ}C$ and less than 0.11% at $80^{\circ}C$ or higher. When pork was spiked into cream soup, weaning food, fish paste, and sauce, the mean assay recoveries were 8.8, 45, 36, and 39%, respectively. In 12 commercial processed foods, the assay results coincided qualitatively with the food labels on the packages.

• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.1-10
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• 2018

Aggression among pigs adversely affects economic returns and animal welfare in intensive pigsties. Recently, some studies have applied information technology to a livestock management system to minimize the damage resulting from such anomalies. Nonetheless, detecting each pig in a crowed pigsty is still challenging problem. In this paper, we propose a new Kinect camera and deep learning-based monitoring system for the detection of the individual pigs. The proposed system is characterized as follows. 1) The background subtraction method and depth-threshold are used to detect only standing-pigs in the Kinect-depth image. 2) The standing-pigs are detected by using YOLO (You Only Look Once) which is the fastest and most accurate model in deep learning algorithms. Our experimental results show that this method is effective for detecting individual pigs in real time in terms of both cost-effectiveness (using a low-cost Kinect depth sensor) and accuracy (average 99.40% detection accuracies).

• Journal of Biosystems Engineering
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• v.38 no.2
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• pp.121-128
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• 2013

Purpose: Porcine proliferative enteropathy (PPE), caused by the obligate intracellular bacterium Lawsonia intracellularis, is a widely distributed disease throughout the world causing substantial economic loss. In order to diagnose PPE rapidly, the rapid kit was developed and tested. Methods: In this study, a rapid kit was developed to screen the PPE rapidly at the pig farm. Also, occult blood test with fecal occult blood (FOB) kit was done for detecting the blood in pig feces which might be the evident of hemorrhagic PPE. For developing the kit, we tested fecal samples of PPE infected pigs diagnosed by polymerase chain reaction (PCR) method. Results: With the developed rapid kit, Lawsonia intracellularis was detected in high density emulsion of ileum. On the other hand, the test result of detecting Lawsonia in feces showed too high non-specific response. In addition, nevertheless the FOB test result showed that blood evident could be founded in pig feces, the diagnosing result was not fit to PCR test result, which shows blood in pig feces could be from not only hemorrhagic PPE but also many reasons. Conclusions: To deal with the PPE effectively, it will be better for farmers to screen the PPE in earlier stage with easy and rapid diagnosing tool on farm. This study found out that the rapid kit could detect the Lawsonia intracellularis and hemoglobin in pig feces. However, the non-specific response to negative samples of PPE was too high to use at a pig farm. Further research is needed for lowering the non-specific response with the rapid kit.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.4
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• pp.311-316
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• 2010

Defects positioning of underground gas pipelines using MFL(magnetic flux leakage) inspection which is one of non-destructive evaluation techniques is proposed in this paper. MFL signals acquired from MFL PIG(pipeline inspection gauge) have nonlinearity and distortion caused by various external disturbances. SQI(self quotient image), a compensation technique for nonlinearity and distortion of MFL signal, is used to correct positioning of pipeline defects. Through the experiments using artificial defects carved in the KOGAS pipeline simulation facility, it is found that the performance of proposed defect detection is greatly improved compared to that of the conventional DCT(discrete cosine transform) coefficients based detection.

• 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%.

• 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.

• Animal Bioscience
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• v.35 no.12
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• pp.1839-1849
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• 2022

Objective: The study aims to uncover the genetic diversity and unique genetic structure of the Min pig conserved population, divide the nucleus conservation population, and construct the molecular pedigree. Methods: We used KPS Porcine Breeding Chip v1 50K for SNP detection of 94 samples (31♂, 63♀) in the Min pig conserved population from Lanxi breeding Farm. Results: The polymorphic marker ratio (PN), the observed heterozygosity (Ho), and the expected heterozygosity (He) were 0.663, 0.335, and 0.330, respectively. The pedigree-based inbreeding coefficients (F_PED) was significantly different from those estimated from runs of homozygosity (F_ROH) and single nucleotide polymorphism (F_SNP) based on genome. The Pearson correlation coefficient between F_ROH and F_SNP was significant (p<0.05). The effective population content (Ne) showed a continuously decreasing trend. The rate of decline was the slowest from 200 to 50 generations ago (r = 0.95), then accelerated slightly from 50 to 5 generations ago (1.40

• Korean Journal of Veterinary Service
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• v.35 no.4
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• pp.255-261
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• 2012

Foot and mouth disease (FMD) is highly infectious disease of cloven-hoofed animals, particularly cattle, sheep, pigs and goats. Last outbreak reported in November, 2010 induced the enormous social and economical impacts. Culling of infected animals, movement control, and vaccination are the major control measures of FMD. The aim of this study was to detection foot-and-mouth disease virus (FMDV) in the soil and leachate from modeling burial for pig carcass as measured by real-time reverse transcriptase polymerase chain reaction (RT-PCR). FMDV and Coxsakievirus B1 (CVB1) were detected in soil by week 16 and Coxsakievirus B1 (CVB1) by weeks 12, respectively. FMDV and CVB1 also detected by weeks 8 in the leachate. Results from this study provides an evidence that FMDV could be inactivated for safe of pig carcasses infected with FMDV within 4 month in the carcass burial site.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.91-98
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• 2018

Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. In particular, porcine respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this paper, we propose a noise-robust system for the early detection and recognition of pig wasting diseases using sound data. In this method, first we convert one-dimensional sound signals to two-dimensional gray-level images by normalization, and extract texture images by means of dominant neighborhood structure technique. Lastly, the texture features are then used as inputs of convolutional neural networks as an early anomaly detector and a respiratory disease classifier. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (low-cost sound sensor) and accurately (over 96% accuracy) even under noise-environmental conditions, either as a standalone solution or to complement known methods to obtain a more accurate solution.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.319-326
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• 2016

Abnormal situation caused by aggressive behavior of pigs adversely affects the growth of pigs, and comes with an economic loss in intensive pigsties. Therefore, IT-based video surveillance system is needed to monitor the abnormal situations in pigsty continuously in order to minimize the economic demage. In this paper, we propose a new Kinect camera-based monitoring system for the detection of the individual pigs. The proposed system is characterized as follows. 1) The background subtraction method and depth-threshold are used to detect only standing-pigs in the Kinect-depth image. 2) The moving-pigs are labeled as regions of interest. 3) A contour method is proposed and applied to solve the touching-pigs problem in the Kinect-depth image. The experimental results with the depth videos obtained from a pig farm located in Sejong illustrate the efficiency of the proposed method.