• Journal of Animal Science and Technology
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• v.57 no.3
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• pp.7.1-7.7
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• 2015

To meet the increasing demands of specific pathogen free (SPF) minipigs in biomedical researches, 8 pregnant Chinese Wuzhishan minipigs (WZSP) sows with clear background were chosen to obtain SPF WZSP by hysterectomy. At $111{\pm}days2$ of the pregnancy, piglets were aseptically taken out from the sows and artificially suckled for 40 to 45 days in the positive isolators. Then, the piglets defined as F0 were transferred to barrier environment and fed with standard feeds. The original SPF colony was formed for breeding by selected piglets from F0 group of 6-8 months old. Biological characteristics of SPF WZSP were collected and further compared to those of conventional (CV) WZSP, including growth performance, reproductive performance, hematology and blood biochemistry, and major pathogens detection. As a result, 61 F0 piglets were obtained from 8 candidate sows, and 55 out of them survived. After strictly selection, 35 F0 piglets were used to form the original SPF colony, which produced 14 litters of SPF piglets defined as F1. Piglet survival rates, growth performance, and reproductive performance of SPF WZSP were similar to CV WZSP. Some hematology and blood biochemistry parameters showed significant differences between SPF and CV WZSP. Eighteen kinds of pathogens were identified to be free in F0 and F1 SPF colony by repeated pathogen detections. In conclusion, we established a satisfied SPF WZSP colony maintaining original characteristics, free of controlled diseases, and being proved to be a suitable laboratory animal.

• Proceedings of the Korean Society of Veterinary Clinics Conference
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• 2007.10a
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• pp.602-602
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• 2007

• Journal of Animal Science and Technology
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• v.62 no.5
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• pp.682-691
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• 2020

Careful cleaning and disinfection of pigpens is essential to prevent disease spread and avoid the resultant economic losses. Hygiene in pigpens is generally evaluated by visual monitoring supplemented with bacteriological monitoring, which includes counting the total aerobic bacteria (TAB) and/or fecal indicator bacteria (FIB). However, these methods present drawbacks such as time and labor requirements. As adenosine triphosphate (ATP) is ubiquitous in all living organisms including microorganisms, this study aimed to directly compare the results of microbial assessment and ATP quantification, and to suggest possible detailed application methods of the ATP test for hygiene evaluation in pigpens of a farrowing unit. Before and after standard cleaning procedures, samples were collected from the floor corner, floor center, and feeding trough of four pigpens at different time points. No FIB were detected and both the TAB and ATP levels were significantly decreased in the floor center area after cleaning. FIB were continuously detected after cleaning and disinfection of the floor corners, and there was no significant ATP level reduction. The feeding trough did not show any significant difference in these values before and after cleaning, indicating insufficient cleaning of this area. The levels of TAB and ATP after cleaning were significantly correlated and the average ATP value was significantly lower in the absence of FIB than in their presence. In the absence of standard references, a more thorough hygiene management could be achieved evenly by supplementing cleaning or disinfection based on the lowest ATP results obtained at the cleanest test site, which in the present study was the floor center. Overall, these results indicate that the on-farm ATP test can be used to determine the cleanliness status, in addition to visual inspection, as an alternative to laboratory culture-based testing for the presence of microorganisms.

• Korean Journal of Soil Science and Fertilizer
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• v.47 no.2
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• pp.133-139
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• 2014

Veterinary antibiotics (VAs) in animal compost and organic fertilizer can have adverse effect on ecosystem and eventually human health. The main purpose of this research was to evaluate feasibility of Charm II system for monitoring residuals of VAs in animal compost and organic fertilizer. Four different VAs (Tetracyclines: TCs, Sulfonamides: SAs, Macrolides: MLs, and ${\beta}$-lactams: ${\beta}$-LTs) were analyzed and total of 100 samples were monitored. Results reveled that SAs in animal compost showed the highest detection frequency (64%) with exceeded concentration of criteria. However, very low detection frequency (0-12%) for ${\beta}$-LTs was observed in animal compost and organic fertilizer. Depending on physicochemical properties of each VAs, detection frequency of VAs was determined. In conclusion, charm II system can be utilized to screen if residual of VAs is in animal compost and organic fertilizer. Also, more research is necessary to establish standard method for analysis of VAs in complex matrix and to minimize adverse effect of VAs from source to environment.

• 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.

• Animal Bioscience
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• v.35 no.9
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• pp.1314-1326
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• 2022

Objective: Alongside the rise of animal-protection awareness in Taiwan, the public has been paying more attention to dog genetic deficiencies due to inbreeding in the pet market. The goal of this study was to isolate novel microsatellite markers for monitoring the genetic structure of domestic dog populations in Taiwan. Methods: A total of 113 DNA samples from three dog breeds-beagles (BEs), bichons (BIs), and schnauzers (SCs)-were used in subsequent polymorphic tests applying the 14 novel microsatellite markers that were isolated in this study. Results: The results showed that the high level of genetic diversity observed in these novel microsatellite markers provided strong discriminatory power. The estimated probability of identity (P_(ID)) and the probability of identity among sibs (P_(ID)sib) for the 14 novel microsatellite markers were 1.7×10^-12 and 1.6×10^-5, respectively. Furthermore, the power of exclusion for the 14 novel microsatellite markers was 99.98%. The neighbor-joining trees constructed among the three breeds indicated that the 14 sets of novel microsatellite markers were sufficient to correctly cluster the BEs, BIs, and SCs. The principal coordinate analysis plot showed that the dogs could be accurately separated by these 14 loci based on different breeds; moreover, the Beagles from different sources were also distinguished. The first, the second, and the third principal coordinates could be used to explain 44.15%, 26.35%, and 19.97% of the genetic variation. Conclusion: The results of this study could enable powerful monitoring of the genetic structure of domestic dog populations in Taiwan.

• Journal of Animal Science and Technology
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• v.64 no.6
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• pp.1259-1260
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• 2022

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3384-3398
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• 2020

In recent years, as the environment has become an important issue in dealing with food, energy, and urban development, diverse environment-related applications such as environmental monitoring and ecosystem management have emerged. In such applications, automatic classification of animals using video or sound is very useful in terms of cost and convenience. So far, many works have been done for animal sounds classification using artificial intelligence techniques such as a convolutional neural network. However, most of them have dealt only with the sound of a specific class of animals such as bird sounds or insect sounds. Due to this, they are not suitable for classifying various types of animal sounds. In this paper, we propose a sound classification scheme based on a multi-feature network for classifying sounds of multiple species of animals. To do that, we first collected multiple animal sound datasets and grouped them into classes. Then, we extracted their audio features by generating mixed records and used those features for training. To evaluate the effectiveness of our scheme, we constructed an animal sound classification model and performed various experiments. We report some of the results.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.6
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• pp.603-608
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• 1997

To improve animal production, a simple and accurate pregnancy diagnosis plays a very important role. Therefore, the purpose of this study was to develop an on-farm blood progesterone enzyme immunoassay (EIA) system for monitoring the early pregnancy in sows. Star tubes coated with mouse monoclonal anti-progesterone antibody were used for this proposed EIA system which was tested in field trials. The results could be obtained within 30 minutes either by spectrophotometry or the naked eye. Heparinized fresh blood samples collected from the ear vein of sows 17-22 days after breeding (day 0) were tested qualitatively to diagnose sows as pregnant or non-pregnant with high ( > 3 ng/ml) or low ($${{\leq_-}}3ng/ml$$) progesterone in the blood. To provided a double check data, plasma progesterone levels were also measured quantitatively by the same EIA system with some modification. Total agreement of diagnosis by the on-farm EIA kit and by farrowing or abortion from 128 tested sows was found to be 92.2% accuracy (93.1% on pregnant diagnosis and 83.3% on non-pregnant diagnosis). It was concluded that the on-farm EIA blood progesterone test is a very useful method for monitoring the early pregnancy status of sows.

• Proceedings of the Korean Society for Food Science of Animal Resources Conference
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• 1997.06a
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• pp.94-94
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• 1997