• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.216-224
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• 2017

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. Recently, some advances have been made in pig monitoring; however, detecting each pig is still challenging problem. In this paper, we propose a new color image-based monitoring system for the detection of the individual pig using a fast region-based convolution neural network with consideration of detecting touching pigs in a crowed pigsty. The experimental results with the color images obtained from a pig farm located in Sejong city illustrate the efficiency of the proposed method.

• 한국축산시설환경학회지
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• 제15권2호
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• pp.171-182
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• 2009

일반적으로 올인-올아웃 시스템은 농장에서 양돈 생산성을 개선할 수 있는 최선의 사양관리방법으로 알려져 있으며, 그룹관리 방식은 질병의 전파를 차단하고, 질병 순환 고리를 제거할 수 있는 올인-올아웃 시스템을 자연스럽게 적용할 수 있는 사양 관리 방법 중 하나이다. 그룹관리는 양돈장의 모든 총두수, 돈사 시설 등을 고려하였을 때, 그룹의 크기와 관리 주간의 차이에 따라 다양한 방식이 존재한다. 모돈의 주간관리와 그룹관리 방법은 농장의 상황에 따라 다양한 장단점이 존재하며, 시설과 모돈 수 등을 고려하여 가장 적합한 관리 방법을 농장에 적용하여야 할 것이다. 모돈의 그룹관리는 형태에 따라 2, 3, 5, 7 주간 그룹관리 등으로 나눌 수 있지만, 이중에서도 3주간 그룹관리는 주간관리, 2, 5, 7 주간 관리에 비해 돈군의 흐름과 모돈의 번식 생리를 적절히 활용하고, 관리자의 작업효율을 높일 수 있는 관리 방법이라고 할 수 있겠다. 임신이 되지 않은 모돈은 3주 간격의 발정주기를 갖게 되므로, 이 같은 모돈의 생리를 효과적으로 이용하는 방법이 모돈들을 3주간 그룹관리체계로 관리하는 것이다. 3주간 그룹관리는 모돈의 번식능력 향상은 물론, 전체 양돈장에 올인-올아웃에 의한 사양 관리가 이루어질 수 있도록 하여 PMWS, PRRS, PRDC, PED 등 국내에 만연하고 있는 질병을 예방하고, 유럽의 양돈선진국들에 비해 현저히 낮은 국내의 양돈 생산성을 개선시킬 수 있는 대안이 될 수 있다고 하겠다.

• 농업생명과학연구
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• 제44권1호
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• pp.33-42
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• 2010

본 연구는 일당증체량, 90kg 도달일령, 등지방두께, 등심단면적 및 정육율에 영향을 미치는 품종, 성, 농장 규모 및 환경요인의 효과를 추정하였다. 2004년부터 2008년까지 농장 검정된 Landrace종 5,902 두 Yorkshire종 18,022두 및 Duroc종 6,601두 등의 3개 품종 총 30,525두의 자료를 이용하였다. 검정종료일령에 대한 보정을 위하여 모델에 공분산 항목을 포함하여 분석하였다. 일당증체량, 90kg 도달일령 및 정육율은 중간규모의 농장에서 유의적으로 우수하게 나타났다. 반면 등지방두께와 등심단면적은 소규모의 농장에서 유의적으로 우수하게 나타났다. 결론적으로 본 연구에서는 품종, 성, 검정종료년도, 검정종료계절 및 농장 규모간의 유의적 차이를 나타내었고, 추후 농장규모에 관한 더 많은 연구가 이루어져야 할 것으로 사료되어지며, 이러한 연구가 양돈 산업의 발전에 이바지 할 수 있을 것이다.

• 한국농공학회논문집
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• 제62권1호
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• pp.71-81
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• 2020

Enclosed pig house are creating an environment with high concentrations of gas and dust. Poor conditions in pig farms reduce pig weight and increase disease and accidents for livestock workers. In the pig house, the high concentration of harmful gas may cause asphyxiation accidents to workers and chronic respiratory disease by long-term exposure. As pig farm workers have been aging and feminized, the damage to the health of the harsh environment is getting serious, and real-time monitoring is needed to prevent the damage. However, most of the measuring devices related to humidity, harmful gas, and fine dust except temperature sensors are exposed to high concentrations of gas and dust inside pig house and are difficult to withstand for a long time. The purpose of this study is to develop an wearable based device to monitor the hazardous environment exposed to workers working in pig farms. Based on the field monitoring and previous researches, the measurement range and basic specifications of the equipment were selected, and wearable based device was designed in terms of utilization, economic efficiency, size and communication performance. Selected H₂S and NH₃ sensors showed the average error of 5.3% comparing to standard gas concentrations. The measured data can be used to manage the working environment according to the worker's location and to obtain basic data for work safety warning.

• 한국멀티미디어학회논문지
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• 제25권4호
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• pp.583-599
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• 2022

Although the object detection accuracy with a single image has been significantly improved with the advance of deep learning techniques, the detection accuracy for pig monitoring is challenged by occlusion problems due to a complex structure of a pig room such as food facility. These detection difficulties with a single image can be mitigated by using a video data. In this research, we propose a method in pig detection for video monitoring environment with a static camera. That is, by using both image processing and deep learning techniques, we can recognize a complex structure of a pig room and this information of the pig room can be utilized for improving the detection accuracy of pigs in the monitored pig room. Furthermore, we reduce the execution time overhead by applying a pruning technique for real-time video monitoring on an embedded board. Based on the experiment results with a video data set obtained from a commercial pig farm, we confirmed that the pigs could be detected more accurately in real-time, even on an embedded board.

• 한국동물위생학회지
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• 제47권3호
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• pp.133-142
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• 2024

The purpose of this study was to investigate seroprevalence of porcine respiratory diseases including porcine reproductive and respiratory syndrome (PRRS), porcine circovirus-2 (PCV-2), Mycoplasma hyopneumonia (MH), Pasteurella multocisa A (PMA), Haemophilus parasuis (HP), Actinobacillus pleuropneumonia type 2 (APP2), and Actinobacillus pleuropneumonia type 5 (APP5) in Jeonbuk state by enzyme-linked immunosorbent assay (ELISA). Total 5488 samples collected from four breeding pig farms and 55 commercial pig farms were tested. The overall seroprevalence of PCV-2, APP2, APP5, PMA, and HP was higher in breeding pig farms than in commercial pig farms, with higher antibody positivity rate (more than 97%) in breeding pig farms. Seroprevalence of MH or PRRS were 68.4% and 48.7% or 79.4% and 58.2% in commercial pig farms or breeding pig farms, respectively. The overall seroprevalence of the porcine respiratory diseases tested in this study varied depending on the age group of pigs, with the 40-day-old pig group showing the lowest seroprevalence and mean S/P titer ratio.

• 한국유기농업학회지
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• 제25권2호
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• pp.489-498
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• 2017

본 연구는 양돈농장에 HACCP 제도 도입이 폐사두수에 미치는 영향과 HACCP 제도 적용 목적 및 장 단점을 분석하기 위한 목적으로 실시하였다. HACCP 제도 적용 전 후에 따른 돼지의 폐사두수 변화는 HACCP 제도 적용 전 호흡기와 설사로 인한 폐사두수가 각각 288.30두와 122.90두로 나타났으나 HACCP 적용 후에는 각각 261.60두와 101.10두로 감소하는 것으로 나타났다. 또한 유 사산, 사고사 및 기타 폐사두수는 HACCP 적용 전에 각각 91.08두, 18.22두, 108.10두로 나타났으나 HACCP 적용 후에는 85.91두, 16.37두, 108.60두로 조사되었다. 따라서 총 폐사두수는 HACCP 적용 전 628.70두에서 HACCP 적용 후 573.60두로 감소하였다. 양돈농장의 HACCP 적용 목적 중 1순위와 2순위는 각각 농장의 경쟁력 향상(26.92%)와 위생적이고 안전한 돼지생산(23.43%)인 것으로 나타났다. 또한 HACCP 적용에 따른 가장 큰 장점으로는 농장의 위생관리 수준 향상(20.90%)이었으며, 단점은 HACCP 기록(23.10%)으로 조사되었다.

• 한국임상수의학회지
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• 제18권2호
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• pp.185-188
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• 2001

A weakened wild feral pig (a boar of about 15 kg) with snout distortion and characteristic external lesion of infectious atrophic rhinitis was captured at farm land near low mountains in Chinju, Kyeongnam province. This pig was necropsied and then the snout parts and the parenchymal organs were removed. The snout and nose were transversely sectioned at thickness of 1.5 cm interval. Grossly, the right side of the snout was shorted than that of left by reduction of right nasal turbinate length, but the nasal opening exudate was not observed. At necropsy, degeneration, adhesion, occlusion, and asymmetry of left and right sides on the meatus and turbinate were observed and findings of mild pneumonia were observed. Microscopically, the leukocyte infiltration, hyperemia and hyperplasia on the mucosa of the turbinates and septum were observed. The atrophied periosteum and osseous tissue were also observed. But Bordetella bronchiseptica was not identified in culture from nasal swabs. We expect the possibility that the snout distortion of this pig was due to infectious atrophic rhinitis according to these findings.

• Journal of Veterinary Science
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• 제19권6호
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• pp.855-857
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• 2018

Porcine parvovirus 7 (PPV7) was first detected in Korean pig farms in 2017. The detection rate of PPV7 DNA was 24.0% (30/125) in aborted pig fetuses and 74.9% (262/350) in finishing pigs, suggesting that PPV7 has circulated among Korean domestic pig farms. Phylogenetic analysis based on capsid protein amino acid sequences demonstrated that the nine isolated Korean strains (PPV-KA1-3 and PPV-KF1-6) were closely related to the previously reported USA and Chinese PPV7 strains. In addition, the Korean strains exhibit genetic diversity with both insertion and deletion mutations. This study contributes to the understanding of the molecular epidemiology of PPV7 in Korea.

• 한국멀티미디어학회논문지
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• 제22권2호
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• pp.136-145
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• 2019

The crowded environment of a domestic pig farm is highly vulnerable to the spread of infectious diseases such as foot-and-mouth disease, and studies have been conducted to automatically analyze behavior of pigs in a crowded pig farm through a video surveillance system using a camera. Although it is required to correctly separate occluding pigs for tracking each individual pigs, extracting the boundaries of the occluding pigs fast and accurately is a challenging issue due to the complicated occlusion patterns such as X shape and T shape. In this study, we propose a fast and accurate method to separate occluding pigs not only by exploiting the characteristics (i.e., one of the fast deep learning-based object detectors) of You Only Look Once, YOLO, but also by overcoming the limitation (i.e., the bounding box-based object detector) of YOLO with the test-time data augmentation of rotation. Experimental results with two-pigs occlusion patterns show that the proposed method can provide better accuracy and processing speed than one of the state-of-the-art widely used deep learning-based segmentation techniques such as Mask R-CNN (i.e., the performance improvement over Mask R-CNN was about 11 times, in terms of the accuracy/processing speed performance metrics).