論文 - 小林 郁雄
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カンショデンプン粕を給与した肥育豚の発育成績と肉質 査読あり
川島知之, 林田 良, 河原 聡, 小林郁雄, 高橋俊浩
日本暖地畜産学会報 67 ( 2 ) 101 - 109 2024年9月
記述言語：日本語 掲載種別：研究論文（学術雑誌） 出版者・発行元：日本暖地畜産学会
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AI-enhanced real-time cattle identification system through tracking across various environments 査読あり
Larb Mon, S., Onizuka, T., Pyke, T., Aikawa, M., Kobayashi, I., Thi Thi, Z.
Scientific Reports 14 ( 1 ) 17779 2024年8月
記述言語：英語 掲載種別：研究論文（学術雑誌） 出版者・発行元：Scientific Reports
Video-based monitoring is essential nowadays in cattle farm management systems for automated evaluation of cow health, encompassing body condition scores, lameness detection, calving events, and other factors. In order to efficiently monitor the well-being of each individual animal, it is vital to automatically identify them in real time. Although there are various techniques available for cattle identification, a significant number of them depend on radio frequency or visible ear tags, which are prone to being lost or damaged. This can result in financial difficulties for farmers. Therefore, this paper presents a novel method for tracking and identifying the cattle with an RGB image-based camera. As a first step, to detect the cattle in the video, we employ the YOLOv8 (You Only Look Once) model. The sample data contains the raw video that was recorded with the cameras that were installed at above from the designated lane used by cattle after the milk production process and above from the rotating milking parlor. As a second step, the detected cattle are continuously tracked and assigned unique local IDs. The tracked images of each individual cattle are then stored in individual folders according to their respective IDs, facilitating the identification process. The images of each folder will be the features which are extracted using a feature extractor called VGG (Visual Geometry Group). After feature extraction task, as a final step, the SVM (Support Vector Machine) identifier for cattle identification will be used to get the identified ID of the cattle. The final ID of a cattle is determined based on the maximum identified output ID from the tracked images of that particular animal. The outcomes of this paper will act as proof of the concept for the use of combining VGG features with SVM is an effective and promising approach for an automatic cattle identification system
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Identifying Black Cow Actions Using Kalman Filter Velocity and Multi-Stage Classification 査読あり
Cho Cho, A., Thi Thi, Z., Aikawa, M., Kobayashi, I.
Journal of Signal Processing 28 ( 4 ) 183 - 186 2024年7月
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Precision Livestock Tracking: Advancements in Black Cattle Monitoring for Sustainable Agriculture 査読あり
Myat Noe, S., Thi Thi, Z., Pyke, T., Kobayashi, I.
Journal of Signal Processing 28 ( 4 ) 179 - 182 2024年7月
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Development of a real-time cattle lameness detection system using a single side-view camera 査読あり
Bo Bo, M., Onizuka, T., Pyke, T., Aikawa, M., Kobayashi, I., Thi Thi, Z.
Scientific Reports 14 ( 1 ) 13734 2024年6月
記述言語：英語 掲載種別：研究論文（学術雑誌） 出版者・発行元：Scientific Reports
Recent advancements in machine learning and deep learning have revolutionized various computer vision applications, including object detection, tracking, and classification. This research investigates the application of deep learning for cattle lameness detection in dairy farming. Our study employs image processing techniques and deep learning methods for cattle detection, tracking, and lameness classification. We utilize two powerful object detection algorithms: Mask-RCNN from Detectron2 and the popular YOLOv8. Their performance is compared to identify the most effective approach for this application. Bounding boxes are drawn around detected cattle to assign unique local IDs, enabling individual tracking and isolation throughout the video sequence. Additionally, mask regions generated by the chosen detection algorithm provide valuable data for feature extraction, which is crucial for subsequent lameness classification. The extracted cattle mask region values serve as the basis for feature extraction, capturing relevant information indicative of lameness. These features, combined with the local IDs assigned during tracking, are used to compute a lameness score for each cattle. We explore the efficacy of various established machine learning algorithms, such as Support Vector Machines (SVM), AdaBoost and so on, in analyzing the extracted lameness features. Evaluation of the proposed system was conducted across three key domains: detection, tracking, and lameness classification. Notably, the detection module employing Detectron2 achieved an impressive accuracy of 98.98%. Similarly, the tracking module attained a high accuracy of 99.50%. In lameness classification, AdaBoost emerged as the most effective algorithm, yielding the highest overall average accuracy (77.9%). Other established machine learning algorithms, including Decision Trees (DT), Support Vector Machines (SVM), and Random Forests, also demonstrated promising performance (DT: 75.32%, SVM: 75.20%, Random Forest: 74.9%). The presented approach demonstrates the successful implementation for cattle lameness detection. The proposed system has the potential to revolutionize dairy farm management by enabling early lameness detection and facilitating effective monitoring of cattle health. Our findings contribute valuable insights into the application of advanced computer vision methods for livestock health management.
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Mekata, H., Yamada, K., Umeki, K., Yamamoto, M., Ochi, A., Umekita, K., Kobayashi, I., Hirai, T., Okabayashi, T.
BMC Veterinary research 20 ( 1 ) 190 2024年5月
記述言語：英語 掲載種別：研究論文（学術雑誌） 出版者・発行元：BMC Veterinary Research
Severe fever with thrombocytopenia syndrome (SFTS) is a fatal zoonosis caused by ticks in East Asia. As SFTS virus (SFTSV) is maintained between wildlife and ticks, seroepidemiological studies in wildlife are important to understand the behavior of SFTSV in the environment. Miyazaki Prefecture, Japan, is an SFTS-endemic area, and approximately 100 feral horses, called Misaki horses (Equus caballus), inhabit Cape Toi in Miyazaki Prefecture. While these animals are managed in a wild-like manner, their ages are ascertainable due to individual identification. In the present study, we conducted a seroepidemiological survey of SFTSV in Misaki horses between 2015 and 2023. This study aimed to understand SFTSV infection in horses and its transmission to wildlife. A total of 707 samples from 180 feral horses were used to determine the seroprevalence of SFTSV using enzyme-linked immunosorbent assay (ELISA). Neutralization testing was performed on 118 samples. In addition, SFTS viral RNA was detected in ticks from Cape Toi and feral horses. The overall seroprevalence between 2015 and 2023 was 78.5% (555/707). The lowest seroprevalence was 55% (44/80) in 2016 and the highest was 92% (76/83) in 2018. Seroprevalence was significantly affected by age, with 11% (8/71) in those less than one year of age and 96.7% (435/450) in those four years of age and older (p < 0.0001). The concordance between ELISA and neutralization test results was 88.9% (105/118). SFTS viral RNA was not detected in ticks (n = 516) or feral horses. This study demonstrated that horses can be infected with SFTSV and that age is a significant factor in seroprevalence in wildlife. This study provides insights into SFTSV infection not only in horses but also in wildlife in SFTS-endemic areas.
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Kusumastuti, T., A., Kobayashi, I., Juwari, A., Antari, L., D.
Advances in Animal and Veterinary Sciences 12 ( 5 ) 862 - 872 2024年3月
記述言語：英語 掲載種別：研究論文（学術雑誌） 出版者・発行元：Advances in Animal and Veterinary Sciences
Foot and Mouth Disease (FMD) is a strategic disease in cloven-hoofed animals according to the World Organisation for Animal Health or Office International Des Epizooties (OIE). The last case of the spread of FMD in Indonesia occurred in 2022 and Japan in 2010. This research aims to determine the value of economic losses based on the conditions of beef and dairy cattle farms in two regions, namely East Java Province and Miyazaki Prefecture based on the consideration that they are cattle production centers. SWOT analysis is used to support a description of the condition of internal factors (strengths and weaknesses) and external factors (opportunities and threats) of animal husbandry in two countries. Data analysis was carried out descriptively and quantitatively. Primary and secondary data were collected from July to September 2023. The results showed that economic losses due to FMD in cattle in Miyazaki Prefecture amounted to USD 775,184.77/farmer (beef cattle and dairy cattle), higher than losses in East Java province with USD 2,508.27/farmer for dairy cattle and USD 2,747.26/farmer for beef cattle. The high economic losses per farmer in Miyazaki are related to the characteristics of the number of livestock ownership and price of each animal. The results of the SWOT analysis show that the main weaknesses in East Java are limited facilities, budget, and livestock mobility conditions but the support of the central government and human resources supports the success of the FMD handling policy. In Miyazaki, policy support is dominated by facilities, human resources, and a strong budget even though there were problems with time accuracy in the initial case of FMD.
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San Chain, T., Onizuka, T., Pyke, T., Aikawa, M., Kobayashi, I., Thi Thi, Z.
Journal of Imaging 10 ( 3 ) 67 2024年3月
記述言語：英語 掲載種別：研究論文（学術雑誌） 出版者・発行元：Journal of Imaging
This study innovates livestock health management, utilizing a top-view depth camera for accurate cow lameness detection, classification, and precise segmentation through integration with a 3D depth camera and deep learning, distinguishing it from 2D systems. It underscores the importance of early lameness detection in cattle and focuses on extracting depth data from the cow’s body, with a specific emphasis on the back region’s maximum value. Precise cow detection and tracking are achieved through the Detectron2 framework and Intersection Over Union (IOU) techniques. Across a three-day testing period, with observations conducted twice daily with varying cow populations (ranging from 56 to 64 cows per day), the study consistently achieves an impressive average detection accuracy of 99.94%. Tracking accuracy remains at 99.92% over the same observation period. Subsequently, the research extracts the cow’s depth region using binary mask images derived from detection results and original depth images. Feature extraction generates a feature vector based on maximum height measurements from the cow’s backbone area. This feature vector is utilized for classification, evaluating three classifiers: Random Forest (RF), K-Nearest Neighbor (KNN), and Decision Tree (DT). The study highlights the potential of top-view depth video cameras for accurate cow lameness detection and classification, with significant implications for livestock health management.
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Hemmi, K., Uenishi, K., Tsuzuki, Y., Kobayashi, I.
日本暖地畜産学会報 67 ( 1 ) 29 - 33 2024年3月
記述言語：英語 掲載種別：研究論文（学術雑誌）
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Customized tracking algorithm for robust cattle detection and tracking in occlusion environments 査読あり
Wai Hnin, E., M., Pyke, T., Aikawa, M., Kobayashi, I., Horii, Y., Honkawa, K., Thi Thi, Z.
Sensors 24 ( 4 ) 1181 2024年2月
記述言語：英語 掲載種別：研究論文（学術雑誌） 出版者・発行元：Sensors
Ensuring precise calving time prediction necessitates the adoption of an automatic and precisely accurate cattle tracking system. Nowadays, cattle tracking can be challenging due to the complexity of their environment and the potential for missed or false detections. Most existing deep-learning tracking algorithms face challenges when dealing with track-ID switch cases caused by cattle occlusion. To address these concerns, the proposed research endeavors to create an automatic cattle detection and tracking system by leveraging the remarkable capabilities of Detectron2 while embedding tailored modifications to make it even more effective and efficient for a variety of applications. Additionally, the study conducts a comprehensive comparison of eight distinct deep-learning tracking algorithms, with the objective of identifying the most optimal algorithm for achieving precise and efficient individual cattle tracking. This research focuses on tackling occlusion conditions and track-ID increment cases for miss detection. Through a comparison of various tracking algorithms, we discovered that Detectron2, coupled with our customized tracking algorithm (CTA), achieves 99% in detecting and tracking individual cows for handling occlusion challenges. Our algorithm stands out by successfully overcoming the challenges of miss detection and occlusion problems, making it highly reliable even during extended periods in a crowded calving pen.
DOI： 10.3390/s24041181
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Determinants and control strategies of FMD in Japan and Indonesia 査読あり
Kusumastuti, T., A., Kobayashi, I., Juwari, A., Antari, L., D.
American Journal of Animal and Veterinary Sciences 19 ( 1 ) 86 - 100 2024年2月
記述言語：英語 掲載種別：研究論文（学術雑誌）
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AI driven movement rate variability analysis around the time of calving events in cattle 査読あり
Wai Hnin, E., M., Pyke, T., Aikawa, M., Kobayashi, I., Horii, Y., Honkawa, K., Thi Thi, Z.
Lecture Notes in Electrical Engineering 1114 LNEE 227 - 237 2024年1月
記述言語：英語 掲載種別：研究論文（国際会議プロシーディングス） 出版者・発行元：Lecture Notes in Electrical Engineering
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Cow detection and tracking system utilizing multi-feature tracking algorithm 査読あり
Cho Cho, M., Thi Thi, Z., Pyke, T., Honkawa, K., Kobayashi, I., Horii, Y.
Scientific Reports 13 ( 1 ) 2023年12月
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Mekata, H., Kobayashi, I., Okabayashi, T.
Ticks and Tick-borne Diseases 14 ( 6 ) 2023年11月
記述言語：英語 掲載種別：研究論文（学術雑誌） 出版者・発行元：Ticks and Tick-borne Diseases
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Changes in population structure and genetic diversity of Misaki horses between 2015 and 2020 査読あり
Kobayashi, I., Nakamura, K., Saito, I., Akita, M., Tozaki, T., Miyazaki, M., Hano, K., Takasu, M.
The Journal of Veterinary Medical Science 85 ( 12 ) 1327 - 1329 2023年11月
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A non-invasive method for lameness detection in dairy cows using RGB cameras 査読あり
Onizuka, T., Thi Thi, Z., Kobayashi, I.
ICIC Express Letters, Part B: Applications 14 ( 10 ) 1107 - 1114 2023年10月
記述言語：英語 掲載種別：研究論文（学術雑誌） 出版者・発行元：ICIC Express Letters, Part B: Applications
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Tone, M., Ukyo, R., Sakamoto, S., H., Hemmi, K., Kobayashi, I., Tsuzuki, Y.
CryoLetters 44 ( 5 ) 307 - 313 2023年10月
記述言語：英語 掲載種別：研究論文（学術雑誌） 出版者・発行元：Cryo-Letters
BACKGROUND: Cryopreservation of porcine oocytes is difficult compared with other species and immature oocytes particularly so compared to the meiotic stage. OBJECTIVE: To evaluate the efficacy of a pretreatment with 1 μM paclitaxel (PTX, 30 min exposure) before vitrification to promote the maturation of porcine immature oocytes. MATERIALS AND METHODS: Cumulus cell-enclosed oocytes (COs) aspirated from porcine ovaries were divided into three groups: i) non-pretreated with PTX and non-vitrified group (control group); ii) pretreated with PTX and vitrified group (PTX-V group); and iii) non-pretreated with PTX and vitrified group (nPTX-V group). RESULTS: The nuclear maturation rate up to the preovulatory stage was significantly lower (P<0.05) in the nPTX-V group than in the control group, but was similar in the PTX-V and control groups. No significant differences were observed in viability assessed by a normal CO morphology and the embryonic development of oocytes activated by the parthenogenetic stimulation between the PTX-V and control groups, but not the non-PTX-V group. CONCLUSION: PTX may promote the maturation of vitrified porcine immature oocytes.
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Cho Cho, M., Thi Thi, Z., Pyke, T., Honkawa, K., Kobayashi, I., Horii, Y.
ICIC Express Letters, Part B: Applications 14 ( 9 ) 993 - 1000 2023年9月
記述言語：英語 掲載種別：研究論文（学術雑誌） 出版者・発行元：ICIC Express Letters, Part B: Applications
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分娩後早期の黒毛和種に対する腟内挿入型プロジェステロン徐放剤（PRID）を用いた定時人工授精プログラムにおけるEBおよびGnRHの投与の影響 査読あり
邉見広一郎，續木靖浩，小林郁雄
肉用牛研究会報 115 6 - 14 2023年6月
記述言語：日本語 掲載種別：研究論文（学術雑誌）
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Facial region analysis for individual identification of cows and feeding time estimation 査読あり
Kawagoe, Y., Kobayashi, I., Thi Thi, Z.
Agriculture 13 ( 5 ) 2023年5月
記述言語：英語 掲載種別：研究論文（学術雑誌） 出版者・発行元：Agriculture (Switzerland)
With the increasing number of cows per farmer in Japan, an automatic cow monitoring system is being introduced. One important aspect of such a system is the ability to identify individual cows and estimate their feeding time. In this study, we propose a method for achieving this goal through facial region analysis. We used a YOLO detector to extract the cow head region from video images captured during feeding with the head region cropped as a face region image. The face region image was used for cow identification and transfer learning was employed for identification. In the context of cow identification, transfer learning can be used to train a pre-existing deep neural network to recognize individual cows based on their unique physical characteristics, such as their head shape, markings, or ear tags. To estimate the time of feeding, we divided the feeding area into vertical strips for each cow and established a horizontal line just above the feeding materials to determine whether a cow was feeding or not by using Hough transform techniques. We tested our method using real-life data from a large farm, and the experimental results showed promise in achieving our objectives. This approach has the potential to diagnose diseases and movement disorders in cows and could provide valuable insights for farmers.