• Asian-Australasian Journal of Animal Sciences
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• 제24권4호
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• pp.449-456
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• 2011

Eighteen different biometric traits in 407 Kankrej cows from their breeding zone, i.e. Palanpur district of Gujarat, India, were recorded and analyzed by factor analysis to explain body conformation. The averages of body length, height at withers, height at shoulder, height at knee, heart girth, paunch girth, face length, face width, horn length, horn diameter, distance between horns, ear length, ear width, neck length, neck diameter, tail length with switch, tail length without switch and distance between hip bones were $123.44{\pm}0.37$, $124.49{\pm}0.28$, $94.68{\pm}0.30$, $38.2{\pm}0.14$, $162.56{\pm}0.56$, $178.95{\pm}0.70$, $44.09{\pm}0.10$, $15.91{\pm}0.05$, $42.47{\pm}0.53$, $26.07{\pm}0.19$, $13.34{\pm}0.08$, $31.24{\pm}0.12$, $16.10{\pm}0.05$, $50.63{\pm}0.18$, $73.21{\pm}0.32$, $111.62{\pm}0.53$, $89.34{\pm}0.34$ and $17.28{\pm}0.10\;cm$, respectively. The correlation coefficients between different traits ranged from -0.806 (horn diameter and distance between horns) to 0.815 (heart girth and paunch girth). Most of the correlations were positive and significant. Factor analysis with promax rotation with power 3 revealed three factors which explained about 66.02% of the total variation. Factor 1 described the cow body and explained 38.89% of total variation. The second factor described the front view/face of the cow and explained 19.68% of total variation. The third factor described the back of the cow and explained 7.44% of total variation. It was necessary to include some more variables for factor 3 to obtain a reliable estimate of the back view of the cow. The lower communities shown for distance between horns, horn diameter, ear width and neck diameter indicated that these traits did not contribute effectively to explaining body conformation and can be dropped from recording, whereas all other traits are important and needed to explain body conformation in Kankrej cows. The result suggests that principal component analysis (PCA) could be used in breeding programs with a drastic reduction in the number of biometric traits to be recorded to explain body conformation.

• Asian-Australasian Journal of Animal Sciences
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• 제18권6호
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• pp.868-872
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• 2005

Individual management of the animal is the first step towards reaching the goal of precision livestock farming that aids animal welfare. Accurate recognition of each individual animal is important for precise management. Electronic identification of cattle, usually referred to as RFID (Radio Frequency Identification), has many advantages for farm management. In practice, however, RFID implementations can cause several problems. Reading speed and distance must be optimized for specific applications. Image processing is more effective than RFID for the development of precision farming system in livestock. Therefore, the aim of this paper is to attempt the identification of cattle by using image processing. The majority of the research on the identification of cattle by using image processing has been for the black-and-white patterns of the Holstein. But, native Japanese and Korean cattle do not have a consistent pattern on the body, so that identification by pattern is impossible. This research aims to identify to Japanese black cattle, which does not have a black-white pattern on the body, by using image processing and a neural network algorithm. 12 Japanese black cattle were tested. Values of input parameter were calculated by using the face image values of 12 cows. The face was identified by the associate neural memory algorithm, and the algorithm was verified by the transformed face image, for example, of brightness, distortion, noise and angle. As a result, there was difference due to a transformation ratio of the brightness, distortion, noise, and angle. The algorithm could identify 100% in the range from -30 to +30 degrees of brightness, -20 to +40 degrees of distortion, 0 to 60% of noise and -20 to +30 degree of angle transformed images.

• Asian-Australasian Journal of Animal Sciences
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• 제31권7호
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• pp.992-1006
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• 2018

Beef production extends over almost half of Australia, with about 47,000 cattle producers that contribute about 20% ($A12.7 billion gross value of production) of the total value of farm production in Australia. Australia is one of the world's most efficient producers of cattle and was the world's third largest beef exporter in 2016. The Australian beef industry had 25 million head of cattle in 2016-17, with a national beef breeding herd of 11.5 million head. Australian beef production includes pasture-based cow-calf systems, a backgrounding or grow-out period on pasture, and feedlot or pasture finishing. Feedlot finishing has assumed more importance in recent years to assure the eating quality of beef entering the relatively small Australian domestic market, and to enhance the supply of higher value beef for export markets. Maintenance of Australia's preferred status as a quality assured supplier of high value beef produced under environmentally sustainable systems from 'disease-free' cattle is of highest importance. Stringent livestock and meat quality regulations and quality assurance systems, and productivity growth and efficiency across the supply chain to ensure price competiveness, are crucial for continued export market growth in the face of increasing competition. Major industry issues, that also represent research, development and adoption priorities and opportunities for the Australian beef industry have been captured within exhaustive strategic planning processes by the red meat and beef industries. At the broadest level, these issues include consumer and industry support, market growth and diversification, supply chain efficiency, productivity and profitability, environmental sustainability, and animal health and welfare. This review provides an overview of the Australian beef industry including current market trends and future prospects, and major issues and opportunities for the continued growth, development and profitability of the industry.

• 한국수정란이식학회지
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• 제20권3호
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• pp.303-309
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• 2005

본 연구는 한우 난구 복합체의 체외성숙에서 OA가 미치는 영향에 대하여 조사하였다. 도축 한우암소의 난소로부터 난구 복합체를 채취하여 $0.1\%$ PVA-TCM199로 3회 이상 세정 후 $0.1\%$ PVA-TCM 199, 0.2 uM, 2 uM, 20 uM OA를 각각 첨가하여 $5\%\;CO_2,\;95\%$ 공기, $39^{\circ}C$에서 6, 12, 24시간 동안 체외성숙을 실시하였다. 또한 체외성숙시 cycloheximide(CX)와 OA와 체외성숙 효과를 확인하기 위하여 0.1M-PVA TCM199, CX 25 ug/mL, 동량의 CX를 6시간 처리한 후 2uM의 OA로 체외성숙을 실시하거나, 0.2 uM OA 단독으로 체외 성숙시켰다. 체외 성숙된 한우 난구 복합체의 핵형을 조사하기 위하여 $0.5\%$ hyaluronidase 용액으로 난구세포를 용해하고, 난자는 1:3 acetic acid, ethanol 용액에 30초간 고정하였으며, $3\%$ basic Fuchsin을 염색하여 핵형을 관찰하였다. 체외 성숙된 난자의 핵형 및 체외 발달율에 대한 통계분석은 3반복을 하여 얻어진 결과를 ANOVA test로 분석하였다. 한우 난구 복합체의 체외성숙율은 $0.1\%$ PVA-TCM199, 0.2 uM, 2 uM, 20 uM OA를 첨가시, 각각 72.0, 50.0, 70.9, $68.8\%$를 나타내어 유의적인 차이를 보였으며(p<0.05), CX와 OA가 한우 난구복합체에 미치는 영향을 조사한 결과, 0.1M-PVA, CX 25 ug/mL, 동량의 CX를 6시간 처리한 후 2uM의 OA로 체외성숙을 실시, 0.2 uM OA 단독처리시의 체외 성숙율은 각각 73.8, 7.2, 45.5, $73.7\%$를 나타냈어 극도의 유의적인 차이를 보였다(p<0.01). 미토콘드리아의 활성은 0.1M-PVA, CX 25 ug/mL, 동량의 CX를 6시간 처리한 후 2uM의 OA로 체외성숙을 실시, 0.2 uM OA 단독 처리시, 핵성숙기간 동안 증가하는 경 향을 보였고, CX 처리시 다른 처리와 비교하였을 때, 성숙 6시간에 1/3의 FI를 나타내었다. 이상의 결과를 미루어 OA는 한우 난구 복합체의 체외성숙에 중요한 조절물질이며, 핵성숙과정 중 미토콘드리아의 활성에도 중요한 역할을 하는 것으로 나타났다.