{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T21:17:27Z","timestamp":1792790247710,"version":"4.5.0"},"reference-count":97,"publisher":"Korean Society of Animal Science and Technology","issue":"1","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0"}],"funder":[{"name":"Rural Development Administration","award":["421044-04"],"award-info":[{"award-number":["421044-04"]}],"id":[{"id":"https:\/\/ror.org\/03xs9yg50","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["www.ejast.org"],"crossmark-restriction":true},"short-container-title":["J Anim Sci Technol"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:p>The growing demands of sustainable, efficient, and welfare-conscious pig\n                    husbandry have necessitated the adoption of advanced technologies. Among these,\n                    RGB imaging and machine vision technology may offer a promising solution for\n                    early disease detection and proactive disease management in advanced pig\n                    husbandry practices. This review explores innovative applications for monitoring\n                    disease symptoms by assessing features that directly or indirectly indicate\n                    disease risk, as well as for tracking body weight and overall health. Machine\n                    vision and image processing algorithms enable for the real-time detection of\n                    subtle changes in pig appearance and behavior that may signify potential health\n                    issues. Key indicators include skin lesions, inflammation, ocular and nasal\n                    discharge, and deviations in posture and gait, each of which can be detected\n                    non-invasively using RGB cameras. Moreover, when integrated with thermal\n                    imaging, RGB systems can detect fever, a reliable indicator of infection, while\n                    behavioral monitoring systems can track abnormal posture, reduced activity, and\n                    altered feeding and drinking habits, which are often precursors to illness. The\n                    technology also facilitates the analysis of respiratory symptoms, such as\n                    coughing or sneezing (enabling early identification of respiratory diseases, one\n                    of the most significant challenges in pig farming), and the assessment of fecal\n                    consistency and color (providing valuable insights into digestive health). Early\n                    detection of disease or poor health supports proactive interventions, reducing\n                    mortality and improving treatment outcomes. Beyond direct symptom monitoring,\n                    RGB imaging and machine vision can indirectly assess disease risk by monitoring\n                    body weight, feeding behavior, and environmental factors such as overcrowding\n                    and temperature. However, further research is needed to refine the accuracy and\n                    robustness of algorithms in diverse farming environments. Ultimately,\n                    integrating RGB-based machine vision into existing farm management systems could\n                    provide continuous, automated surveillance, generating real-time alerts and\n                    actionable insights; these can support data-driven disease prevention\n                    strategies, reducing the need for mass medication and the development of\n                    antimicrobial resistance.<\/jats:p>","DOI":"10.5187\/jast.2024.e111","type":"journal-article","created":{"date-parts":[[2024,11,20]],"date-time":"2024-11-20T00:30:53Z","timestamp":1732062653000},"page":"17-42","update-policy":"https:\/\/doi.org\/10.5187\/crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["RGB-based machine vision for enhanced pig disease symptoms monitoring\n                    and health management: a review"],"prefix":"10.5187","volume":"67","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7793-400X","authenticated-orcid":false,"given":"Md Nasim","family":"Reza","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/0227as991","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Korea"},{"id":[{"id":"https:\/\/ror.org\/0227as991","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Smart Agricultural Systems, Graduate School, Chungnam National University, Daejeon 34134, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3186-8975","authenticated-orcid":false,"given":"Kyu-Ho","family":"Lee","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/0227as991","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Korea"},{"id":[{"id":"https:\/\/ror.org\/0227as991","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Smart Agricultural Systems, Graduate School, Chungnam National University, Daejeon 34134, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0364-420X","authenticated-orcid":false,"given":"Eliezel","family":"Habineza","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/0227as991","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Smart Agricultural Systems, Graduate School, Chungnam National University, Daejeon 34134, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-3976-8975","authenticated-orcid":false,"family":"Samsuzzaman","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/0227as991","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5742-5374","authenticated-orcid":false,"given":"Hyunjin","family":"Kyoung","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/0227as991","id-type":"ROR","asserted-by":"publisher"}],"name":"Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-9398-5626","authenticated-orcid":false,"given":"Young Kyoung","family":"Choi","sequence":"additional","affiliation":[{"name":"Dawoon Co., Ltd., Incheon 22847, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7278-3476","authenticated-orcid":false,"given":"Gookhwan","family":"Kim","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03xs9yg50","id-type":"ROR","asserted-by":"publisher"}],"name":"National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54875, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7629-7224","authenticated-orcid":false,"given":"Sun-Ok","family":"Chung","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/0227as991","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Korea"},{"id":[{"id":"https:\/\/ror.org\/0227as991","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Smart Agricultural Systems, Graduate School, Chungnam National University, Daejeon 34134, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"3132","published-online":{"date-parts":[[2025,1,31]]},"reference":[{"key":"key2.0261002113259e+13_B1","doi-asserted-by":"crossref","first-page":"3575","DOI":"10.1002\/jsfa.10338","article-title":"Prospects for sustainability of pig production in relation to\n                        climate change and novel feed resources","volume":"100","author":"Rauw","year":"2020","journal-title":"J Sci Food Agric."},{"key":"key2.0261002113259e+13_B2","doi-asserted-by":"crossref","first-page":"074003","DOI":"10.1088\/1748-9326\/ac74d7","article-title":"Global assessment of land and water resource demand for pork\n                        supply","volume":"17","author":"Govoni","year":"2022","journal-title":"Environ Res Lett."},{"key":"key2.0261002113259e+13_B3","first-page":"121","article-title":"Pork production and consumption issues from the perspective of\n                        the religion and the World\u2019s growing population","volume":"14","author":"Vida","year":"2020","journal-title":"Appl Stud Agribus Commer."},{"key":"key2.0261002113259e+13_B4","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.applanim.2018.02.004","article-title":"Pre-weaning environmental enrichment increases piglets\u2019\n                        object play behaviour on a large scale commercial pig farm","volume":"202","author":"Yang","year":"2018","journal-title":"Appl Anim Behav Sci."},{"key":"key2.0261002113259e+13_B5","doi-asserted-by":"crossref","first-page":"106283","DOI":"10.1016\/j.compag.2021.106283","article-title":"Using imagery and computer vision as remote monitoring methods\n                        for early detection of respiratory disease in pigs","volume":"187","author":"Jorquera-Chavez","year":"2021","journal-title":"Comput Electron Agric."},{"key":"key2.0261002113259e+13_B6","first-page":"159","article-title":"Pig diseases and crush monitoring visual symptoms detection using\n                        engineering approaches: a review","volume":"3","author":"Habineza","year":"2021","journal-title":"Precis Agric Sci Technol."},{"key":"key2.0261002113259e+13_B7","doi-asserted-by":"crossref","first-page":"261","DOI":"10.3390\/agriculture10070261","article-title":"Pig farming in alternative systems: strengths and challenges in\n                        terms of animal welfare, biosecurity, animal health and pork\n                        safety","volume":"10","author":"Delsart","year":"2020","journal-title":"Agriculture."},{"key":"key2.0261002113259e+13_B8","doi-asserted-by":"crossref","first-page":"1512","DOI":"10.3390\/ani10091512","article-title":"Transforming the adaptation physiology of farm animals through\n                        sensors","volume":"10","author":"Neethirajan","year":"2020","journal-title":"Animals."},{"key":"key2.0261002113259e+13_B9","doi-asserted-by":"crossref","first-page":"904834","DOI":"10.3389\/fanim.2022.904834","article-title":"A review of monitoring techniques for livestock respiration and\n                        sounds","volume":"3","author":"Handa","year":"2022","journal-title":"Front Anim Sci."},{"key":"key2.0261002113259e+13_B10","doi-asserted-by":"crossref","first-page":"1642","DOI":"10.3390\/atmos13101642","article-title":"Non-invasive methods of quantifying heat stress response in farm\n                        animals with special reference to dairy cattle","volume":"13","author":"Sejian","year":"2022","journal-title":"Atmosphere."},{"key":"key2.0261002113259e+13_B11","doi-asserted-by":"crossref","first-page":"31","DOI":"10.5187\/jast.2024.e4","article-title":"Thermal imaging and computer vision technologies for the\n                        enhancement of pig husbandry: a review","volume":"66","author":"Reza","year":"2024","journal-title":"J Anim Sci Technol."},{"key":"key2.0261002113259e+13_B12","doi-asserted-by":"crossref","first-page":"1504","DOI":"10.3390\/s24051504","article-title":"Computer-vision-based sensing technologies for livestock body\n                        dimension measurement: a survey","volume":"24","author":"Ma","year":"2024","journal-title":"Sensors."},{"key":"key2.0261002113259e+13_B13","doi-asserted-by":"crossref","first-page":"360","DOI":"10.59400\/cai.v1i1.360","article-title":"Application of computer vision in livestock and crop\n                        production\u2014a review","volume":"1","author":"Petrovic","year":"2023","journal-title":"Comput Artif Intell."},{"key":"key2.0261002113259e+13_B14","doi-asserted-by":"crossref","first-page":"15","DOI":"10.3390\/technologies12020015","article-title":"A review of machine learning and deep learning for object\n                        detection, semantic segmentation, and human 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disease complex","volume":"26","author":"Fachinger","year":"2008","journal-title":"Vaccine."},{"key":"key2.0261002113259e+13_B21","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1186\/s40813-017-0065-2","article-title":"Etiology of acute respiratory disease in fattening pigs in\n                        Finland","volume":"3","author":"Haimi-Hakala","year":"2017","journal-title":"Porcine Health Manag."},{"key":"key2.0261002113259e+13_B22","doi-asserted-by":"crossref","first-page":"419","DOI":"10.1016\/j.cvex.2021.02.001","article-title":"Respiratory diseases in guinea pigs, chinchillas and\n                        degus","volume":"24","author":"Ardiaca Garc\u00eda","year":"2021","journal-title":"Vet Clin North Am Exot Anim Pract."},{"key":"key2.0261002113259e+13_B23","doi-asserted-by":"crossref","first-page":"771682","DOI":"10.3389\/fvets.2021.771682","article-title":"The evidence for a causal link between disease and damaging\n                        behavior in pigs","volume":"8","author":"Boyle","year":"2022","journal-title":"Front Vet Sci."},{"key":"key2.0261002113259e+13_B24","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1186\/s13028-023-00693-y","article-title":"Gastro-intestinal lesions are not relatable to diarrhoea or\n                        specific pathogens in post-weaning diarrhoea (PWD) in pigs","volume":"65","author":"Blirup-Plum","year":"2023","journal-title":"Acta Vet Scand."},{"key":"key2.0261002113259e+13_B25","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1186\/s40813-023-00315-z","article-title":"Risk factors associated with post-weaning diarrhoea in Austrian\n                        piglet-producing farms","volume":"9","author":"Ren\u00e9","year":"2023","journal-title":"Porcine Health Manag."},{"key":"key2.0261002113259e+13_B26","article-title":"Enhancing piglet survival and welfare in different farrowing\n                        systems [Ph.D. dissertation]","volume-title":"Newcastle upon 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crates","volume":"92","author":"Meli\u0161ov\u00e1","year":"2014","journal-title":"J Anim Sci."},{"key":"key2.0261002113259e+13_B30","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1017\/S146625232000002X","article-title":"A review of congenital tremor type A-II in\n                        piglets","volume":"21","author":"Stenberg","year":"2020","journal-title":"Anim Health Res Rev."},{"key":"key2.0261002113259e+13_B31","doi-asserted-by":"crossref","first-page":"105385","DOI":"10.1016\/j.applanim.2021.105385","article-title":"Tail-biting behaviour pre-weaning: association between other\n                        pig-directed and general behaviour in piglets","volume":"241","author":"Hakansson","year":"2021","journal-title":"Appl Anim Behav Sci."},{"key":"key2.0261002113259e+13_B32","first-page":"72","article-title":"Nervous and locomotor system","volume":"339","author":"Madson","year":"2019","journal-title":"Dis Swine."},{"key":"key2.0261002113259e+13_B33","doi-asserted-by":"crossref","first-page":"551269","DOI":"10.3389\/fvets.2020.551269","article-title":"Image analysis and computer vision applications in animal\n                        sciences: an overview","volume":"7","author":"Fernandes","year":"2020","journal-title":"Front Vet Sci."},{"key":"key2.0261002113259e+13_B34","doi-asserted-by":"crossref","first-page":"2343","DOI":"10.3390\/ani11082343","article-title":"The application of cameras in precision pig farming: an overview\n                        for swine-keeping professionals","volume":"11","author":"Arulmozhi","year":"2021","journal-title":"Animals."},{"key":"key2.0261002113259e+13_B35","doi-asserted-by":"crossref","first-page":"133","DOI":"10.3390\/ani9040133","article-title":"Precision livestock farming in swine welfare: a review for swine\n                        practitioners","volume":"9","author":"Benjamin","year":"2019","journal-title":"Animals."},{"key":"key2.0261002113259e+13_B36","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.livsci.2017.05.014","article-title":"Implementation of machine vision for detecting behaviour of\n                        cattle and pigs","volume":"202","author":"Nasirahmadi","year":"2017","journal-title":"Livest Sci."},{"key":"key2.0261002113259e+13_B37","doi-asserted-by":"crossref","first-page":"692","DOI":"10.3390\/su13020692","article-title":"Information technologies for welfare monitoring in pigs and their\n                        relation to Welfare Quality\u00ae","volume":"13","author":"Larsen","year":"2021","journal-title":"Sustainability."},{"key":"key2.0261002113259e+13_B38","first-page":"69","article-title":"An emerging trend of feature extraction method in video\n                        processing","volume-title":"The Second International Conference on Computer Science, Engineering and\n                        Applications (CCSEA-2012)","author":"Revathi","year":"2012"},{"key":"key2.0261002113259e+13_B39","doi-asserted-by":"crossref","first-page":"4345","DOI":"10.1109\/TII.2020.3012496","article-title":"PigTalk: an AI-based IoT platform for piglet crushing\n                        mitigation","volume":"17","author":"Chen","year":"2021","journal-title":"IEEE Trans Ind Inform."},{"key":"key2.0261002113259e+13_B40","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.isprsjprs.2019.02.009","article-title":"Segmentation for object-based image analysis (OBIA): a review of\n                        algorithms and challenges from remote sensing perspective","volume":"150","author":"Hossain","year":"2019","journal-title":"ISPRS J Photogramm Remote Sens."},{"key":"key2.0261002113259e+13_B41","doi-asserted-by":"crossref","first-page":"2027","DOI":"10.3390\/agriculture13102027","article-title":"The development of a weight prediction system for pigs using\n       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automatically\n                        using machine vision technology: a systematic review","author":"Wurtz","year":"2019","journal-title":"PLOS ONE."},{"key":"key2.0261002113259e+13_B45","doi-asserted-by":"crossref","first-page":"107227","DOI":"10.1016\/j.compag.2022.107227","article-title":"Barriers to computer vision applications in pig production\n                        facilities","volume":"200","author":"Li","year":"2022","journal-title":"Comput Electron Agric."},{"key":"key2.0261002113259e+13_B46","doi-asserted-by":"crossref","first-page":"6541","DOI":"10.3390\/s22176541","article-title":"The research progress of vision-based artificial intelligence in\n                        smart pig farming","volume":"22","author":"Wang","year":"2022","journal-title":"Sensors."},{"key":"key2.0261002113259e+13_B47","doi-asserted-by":"crossref","first-page":"2607","DOI":"10.3390\/su14052607","article-title":"Applications of smart technology as a sustainable strategy in\n                        modern swine farming","volume":"14","author":"Mahfuz","year":"2022","journal-title":"Sustainability."},{"key":"key2.0261002113259e+13_B48","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1146\/annurev-animal-020518-114851","article-title":"Smart animal agriculture: application of real-time sensors to\n                        improve animal well-being and production","volume":"7","author":"Halachmi","year":"2019","journal-title":"Annu Rev Anim Biosci."},{"key":"key2.0261002113259e+13_B49","doi-asserted-by":"crossref","first-page":"9605","DOI":"10.1007\/s10462-023-10405-7","article-title":"Deep learning: survey of environmental and camera impacts on\n                        internet of things images","volume":"56","author":"Kaur","year":"2023","journal-title":"Artif Intell Rev."},{"key":"key2.0261002113259e+13_B50","doi-asserted-by":"crossref","first-page":"1199","DOI":"10.3390\/electronics12051199","article-title":"Techniques and challenges of image segmentation: a\n         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