• Journal of Animal Science and Technology
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• v.66 no.1
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• pp.31-56
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• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

• Toxicological Research
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• v.21 no.2
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• pp.121-128
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• 2005

Economic animal husbandry workers exposed to organic dust can be suffered from immunologic disorders. Our study was to determine immunological parameters related with occurrence of respiratory allergic diseases to animal husbandry workers in Korea for the first time. Peripheral blood were obtained from twenty-five pig barn workers, forty-nine chicken farming workers and fifty-one non-agricultural control workers. Significantly upregulated plasma IgE level was observed with pig-barn workers than that of chicken farming workers or healthy community control subjects. Furthermore, level of histamine, a hallmark of allergy induction, was upregulated in the pig and chicken farming workers in comparison with that of the control subjects. Downregulation of $IFN_\gamma$ and $TNF_{\alpha}$ production from T cells was apparent in the animal husbandry workers compared with the control subjects. Meanwhile, T cells collected from the pig barn workers demonstrated significantly higher production of IL-4 and IL-10 than the other groups. There were also alterations in IgG subclass distribution. In conclusion, immunological modulation probably leading to occupational allergic diseases can be occurred in the economic animal husbandry workers and the pig barn workers could be the most risky group to the work-related allergic disease.

• Journal of Animal Science and Technology
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• v.57 no.1
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• pp.1.1-1.11
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• 2015

Background: Due to increased interest in animal welfare, there is now a need for a comprehensive assessment protocol to be used in intensive pig farming systems. There are two current welfare assessment protocols for pigs: Welfare Quality$^{(R)}$ Assessment Protocols (applicable in the Europe Union), that mostly focuses on animal-based measures, and the Swine Welfare Assurance Program (applicable in the United States), that mostly focuses on management- and environment-based measures. In certain cases, however, animal-based measures might not be adequate for properly assessing pig welfare status. Similarly, welfare assessment that relies only on environment- and management-based measures might not represent the actual welfare status of pigs. Therefore, the objective of this paper was to develop a new welfare protocol by integrating animal-, environment-, and management-based measures. The background for selection of certain welfare criteria and modification of the scoring systems from existing welfare assessment protocols are described. Methods: The developed pig welfare assessment protocol consists of 17 criteria that are related to four main principles of welfare (good feeding, good housing, good health, and appropriate behavior). Good feeding, good housing, and good health were assessed using a 3-point scale: 0 (good welfare), 1 (moderate welfare), and 2 (poor welfare). In certain cases, only a 2-point scale was used: 0 (certain condition is present) or 2 (certain condition is absent). Appropriate behavior was assessed by scan sampling of positive and negative social behaviors based on qualitative behavior assessment and human-animal relationship tests. Results: Modification of the body condition score into a 3-point scale revealed pigs with a moderate body condition (score 1). Moreover, additional criteria such as feed quality confirmed that farms had moderate (score 1) or poor feed quality (score 2), especially those farms located in a high relative humidity region. Conclusions: The developed protocol can be utilized to assess welfare status in an intensive pig farming system. Although further improvements are still needed, this study is a first step in developing a pig welfare assessment protocol that combines animal-, environment-, and management-based measures.

• Korean Journal of Organic Agriculture
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• v.28 no.3
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• pp.367-386
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• 2020

The significance of this study was to analyze the quality value of organic livestock pork for the first time based on the results of managing and testing the cycling organic farming of black pork and vegetables within farm for two years. The results of analysis could be summarized as follows. First, the pork of experimental group with crop-livestock cycling farming showed the excellent quality and high consumer preference compared to the control group of general pork or pork from non-crop-livestock cycling organic farming. In the content ratio of Omega-3 as a representative essential fatty acid, it was 1.46 that was about 2.8 times more than general pork (0.52). In case of Omega-6, it had about 2.5 times more than general pork. Especially, the U/S ratio value which was the content ratio of Unsaturated Fatty Acid (UFA, U) of Saturated Fatty Acid (SFA, S), was largely shown in pork (2.93) from cycling organic farming. Second, it would be necessary to maintain the economies of scope shown in crop-livestock cycling organic farming, and the high quality value of livestock products. For this, there should be a value chain model that could realize the economies of scope and economies of scale at the same time based on scaling and diversification through cooperative organization between farmers. Through this, it would be possible to establish a cycling model called 'community cooperative agriculture' by forming local internal markets through cooperation of production-processing and integration of distribution-sale-consumption. For the managerial activation of this cooperative organization, the government should promote/support the small crop-livestock cycling organic farming cooperative organization in local unit. For securing the reliability of crop-livestock cycling organic agricultural products and crop-livestock cycling organic livestock products, it would be necessary to review the introduction of Participatory Guarantee System (PGS).

• Journal of Veterinary Science
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• v.25 no.3
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• pp.44.1-44.13
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• 2024

Importance: The emergence and rapid increase in the incidence of multidrug-resistant (MDR) bacteria in pig farms has become a serious concern and reduced the choice of effective antibiotics. Objective: This study analyzed the phylogenetics and diversity of antibiotic resistance genes (ARGs) and molecularly identified the source of ARGs in antibiotic-resistant Escherichia coli isolated from pig farms in Banten Province, Indonesia. Methods: Forty-four antibiotic-resistant E. coli isolates from fecal samples from 44 pig farms in Banten Province, Indonesia, were used as samples. The samples were categorized into 14 clusters. Sequencing was performed using the Oxford Nanopore Technologies MinION platform, with barcoding before sequencing with Nanopore Rapid sequencing gDNA-barcoding (SQK-RBK110.96) according to manufacturing procedures. ARG detection was conducted using ResFinder, and the plasmid replicon was determined using PlasmidFinder. Results: Three phylogenetic leaves of E. coli were identified in the pig farming cluster in Banten Province. The E. coli isolates exhibited potential resistance to nine classes of antibiotics. Fifty-one ARGs were identified across all isolates, with each cluster carrying a minimum of 10 ARGs. The ant(3'')-Ia and qnrS1 genes were present in all isolates. ARGs in the E. coli pig farming cluster originated mainly from plasmids, accounting for an average of 89.4%. Conclusions and Relevance: The elevated potential for MDR events, coupled with the dominance of ARGs originating from plasmids, increases the risk of ARG spread among bacterial populations in animals, humans, and the environment.

• 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.

• Korean Journal of Organic Agriculture
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• v.26 no.1
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• pp.57-72
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• 2018

Organic agriculture seeks sustainable agriculture. Organic agriculture is based on circulating agriculture of a family farm unit. However, as of the end of 2016, only 33 out of the total organic farming farms were implementing Crop-Livestock cycling organic farming. The reason seems to be a matter of income after all. The optimal size combination refers to the scale by which family farms can maintain their quality of life while engaging in farming activities. In other words. it is a farm scale that maintains optimal income through stable labor costs. In the meantime, there has been no previous study on the optimal economical combination of Crop-Livestock cycling farming. Choi (2016) analyzed whether the economies of scope (EOS) were realized in the combined production by using the management data of the farmers who practiced Crop-Livestock cycling organic farming for four years. As a result, it has been revealed that the EOS measurement value is 0 or more so the economies of scope are being realized. Therefore, the purpose of this empirical analysis is to identify farm incomes under this circumstance. It is assumed that the optimum production is achieved by balancing the total income curve and the total cost curve in the optimal scale production range. The results of the analysis are as follows. First, the income after the conversion to Crop-Livestock cycling farming was 44,789,280 won, the sum of the seedling-livestock sector, which was 17,873,120 won higher when the non-Crop-Livestock cycling farming was assumed. The same is true for 2014 and 2015. The reason for this is that pig droppings were composted from organic seedlings, and the cost of selling pork was 150,000 won/per pig more expensive even though the manufacturing cost of organic feeds was higher than the purchasing cost. Secondly, this study simulated the result that the economic index varies when the farm size combination is changed by the farm size of 100% standard (S100) as of 2014. S130 is the increase in size from 100% of 2014, whereas S30 is the result of 3ha crop and 66 livestock (pigs). As a result of this simulation, Crop-Livestock cycling farming income decreased more than non-Crop-Livestock cycling farming as the farm size decreased, whereas the income decreased as the farm size increased. When the size was reduced below S50, the income tended to decrease. In this situation, EOS changed in the same direction. The results showed that when the farming size was reorganized and reduced to 50% compared to 2014, the income and income difference was the highest. At the same time, economies of scope (EOS) were the highest at 0.12985. In other words, it was found that the income of farm houses in a family farm unit sector was the best in the combination of 1.5ha crop agriculture and 110 livestock (pigs).

• Asian-Australasian Journal of Animal Sciences
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• v.6 no.3
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• pp.347-360
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• 1993

The project was undertaken to provide information on the present system of traditional pig farming in the South Pacific region, to identify the problems currently limiting productivity of such pigs and to offer practical strategies which could be used for increasing productivity of the animals. The problems were identified by surveying some 220 subsistence pig farms in eleven island countries in the South Pacific region using a prepared questionnaire. The units were found to be generally small, consisting of about 2-4 sows per herd. The productivity of the units as assessed in terms of sow reproductive efficiency was rather low, being only about 7.5. Feed, housing, breeding, disease, marketing, lack of capital, technical know-how and existing social traditions were identified as current constraints. Based on three of the most limiting factors identified namely feed, housing and breeding, strategies for improvement were developed on the basis of better and more effective use of locally available feed resources, better housing and genetic improvement through crossbreeding programmes. These improvement strategies were tested as a package model on some ten farms in two of the island countries. The results of these on-farm trials indicated that using the improvement strategies increased sow reproductive efficiency by approximately 60 percent, to nearly 12. The significance of these findings in the overall management of traditionally raised pigs in the South Pacific region is discussed.

• Journal of the Korea Organic Resources Recycling Association
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• v.10 no.1
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• pp.75-86
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• 2002

This study was performed to investigate situation of livestock manure generated from Kangwon-do and to evaluate its composting probability. The scale of livesrock-farming is bigger and bigger in Korea. Regulation based on the heads of livestock is slightly different from that based on livestock-farming household. So it is needed ro evaluate regulations for livestock head and livestock-farming household. Composting and liquid fertilization were thought to be appropriate technologies to the trearment of Korean cattle and pig manures, respectively. Generation quantity of pig manure was the greatest among pig, Korean cattle, cow and chicken manures. Pig manure generated the greatest amounts of BOD in Kangwon-do. Pig manure contained nitrogen, Korean cattle manure contained $K_2O$, and chicken and pig manures contained $P_2O_5$ in great amount. Alternative ratio of livestock manure to crops-fertilizer was 51% for nitrogen, 38% for $K_2O$, and 34% for $P_2O_5$.

• 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.