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Reza MN, Ali MR, Samsuzzaman, Kabir MSN, Karim MR, Ahmed S, Kyoung H, Kim G, Chung SO. Thermal imaging and computer vision technologies for the enhancement of pig husbandry: a review. JOURNAL OF ANIMAL SCIENCE AND TECHNOLOGY 2024; 66:31-56. [PMID: 38618025 PMCID: PMC11007457 DOI: 10.5187/jast.2024.e4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 01/03/2024] [Accepted: 01/03/2024] [Indexed: 04/16/2024]
Abstract
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.
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Affiliation(s)
- Md Nasim Reza
- Department of Smart Agricultural Systems,
Graduate School, Chungnam National University, Daejeon 34134,
Korea
- Department of Agricultural Machinery
Engineering, Graduate School, Chungnam National University,
Daejeon 34134, Korea
| | - Md Razob Ali
- Department of Agricultural Machinery
Engineering, Graduate School, Chungnam National University,
Daejeon 34134, Korea
| | - Samsuzzaman
- Department of Agricultural Machinery
Engineering, Graduate School, Chungnam National University,
Daejeon 34134, Korea
| | - Md Shaha Nur Kabir
- Department of Agricultural Industrial
Engineering, Faculty of Engineering, Hajee Mohammad Danesh Science and
Technology University, Dinajpur 5200, Bangladesh
| | - Md Rejaul Karim
- Department of Agricultural Machinery
Engineering, Graduate School, Chungnam National University,
Daejeon 34134, Korea
- Farm Machinery and Post-harvest Processing
Engineering Division, Bangladesh Agricultural Research
Institute, Gazipur 1701, Bangladesh
| | - Shahriar Ahmed
- Department of Agricultural Machinery
Engineering, Graduate School, Chungnam National University,
Daejeon 34134, Korea
| | - Hyunjin Kyoung
- Division of Animal and Dairy Science,
Chungnam National University, Daejeon 34134, Korea
| | - Gookhwan Kim
- National Institute of Agricultural
Sciences, Rural Development Administration, Jeonju 54875,
Korea
| | - Sun-Ok Chung
- Department of Smart Agricultural Systems,
Graduate School, Chungnam National University, Daejeon 34134,
Korea
- Department of Agricultural Machinery
Engineering, Graduate School, Chungnam National University,
Daejeon 34134, Korea
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Kazama K, Onda K, Arai S, Shinozuka Y, Kawai K, Kaneko K, Kondo T, Yamada K. A case report: Characteristic plain radiographic findings of a displaced abomasum in a heifer. VET MED-CZECH 2022; 67:46-50. [PMID: 39169957 PMCID: PMC11334956 DOI: 10.17221/83/2021-vetmed] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 08/24/2021] [Indexed: 08/23/2024] Open
Abstract
A 9-month-old Holstein heifer with a history of severely poor growth presented with diarrhoea. On physical examination, a metallic pinging sound was heard on the simultaneous percussion and auscultation of the left trunk. On the cranial abdominal radiography, the contour of a gas-filled balloon-like abomasum wall was delineated, which elevated to the dorsal abdomen. Radiopaque sand at the bottom of the abomasum had been pulled up caudodorsally by the gas-filled abomasum. After surgery, the gas-filled balloon-like appearance of the abomasum wall disappeared and the radiopaque sand was located in the normal position. To our knowledge, no reports on a displaced abomasum on plain radiographs are available. The radiographic findings described herein are characteristic imaging findings of a displaced abomasum. Abdominal radiography could be a new option as an auxiliary diagnostic approach for a displaced abomasum.
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Affiliation(s)
- Kei Kazama
- School of Veterinary Medicine, Department of Veterinary Medicine, Azabu University, Fuchinobe, Chuo-ku, Sagamihara, Kanagawa, Japan
| | - Ken Onda
- School of Veterinary Medicine, Department of Veterinary Medicine, Azabu University, Fuchinobe, Chuo-ku, Sagamihara, Kanagawa, Japan
| | - Sachiko Arai
- School of Veterinary Medicine, Department of Veterinary Medicine, Azabu University, Fuchinobe, Chuo-ku, Sagamihara, Kanagawa, Japan
| | - Yasunori Shinozuka
- School of Veterinary Medicine, Department of Veterinary Medicine, Azabu University, Fuchinobe, Chuo-ku, Sagamihara, Kanagawa, Japan
| | - Kazuhiro Kawai
- School of Veterinary Medicine, Department of Veterinary Medicine, Azabu University, Fuchinobe, Chuo-ku, Sagamihara, Kanagawa, Japan
| | - Kazuyuki Kaneko
- School of Veterinary Medicine, Department of Veterinary Medicine, Azabu University, Fuchinobe, Chuo-ku, Sagamihara, Kanagawa, Japan
| | - Taro Kondo
- School of Veterinary Medicine, Department of Veterinary Medicine, Azabu University, Fuchinobe, Chuo-ku, Sagamihara, Kanagawa, Japan
| | - Kazutaka Yamada
- School of Veterinary Medicine, Department of Veterinary Medicine, Azabu University, Fuchinobe, Chuo-ku, Sagamihara, Kanagawa, Japan
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Correction: Antanaitis, R., et al. Preliminary Experiment Using Sensors for Cow Health Monitoring after Surgical Treatment for the Left Displacement of the Abomasum. Sensors 2020, 20, 4416. SENSORS 2021; 21:s21030918. [PMID: 33573108 PMCID: PMC7866389 DOI: 10.3390/s21030918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 11/23/2020] [Accepted: 12/03/2020] [Indexed: 11/30/2022]
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