• 한국유기농업학회지
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• 제19권spc호
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• pp.186-189
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• 2011

By surveying the 70 composting plants in Gyeonggi Province, the total commercial production of livestock faeces composts (LFCs) in 2008 was estimated to be about 480,000 Mg year-1 and they were manufactured mainly by using both mechanical mixer and bottom air blower. LFCs were composed mainly of chicken faeces 29.2%, pig+chicken faeces 23.1%, pig faeces 20.0%, livestock faeces+oil cake 12.3%, pig+chicken+cattle faeces 10.8% and pig+cattle faeces 4.6%. On the basis of the current official standard which was revised on March 2010, 11 composts out of surveyed 76 ones did not meet the LFCs quality standard (LQS) due to inadequate content of water (5), OM/N (1), NaCl (2) and Zn (3). The OM/N declined by adding chicken faeces and oil cake, while Ca content increased by the addition of chicken faeces and NaCl increased by adding cattle faeces.

• 한국유기농업학회지
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• 제19권spc호
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• pp.182-185
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• 2011

Soil $NH_4$-N content became higher in proportion to the increase in the urea application rate, while in livestock faeces compost (LFC) plots, it became lower than in urea plots and had no significant difference statistically among LFC plots. There was a close relationship between phosphate fertilization rate and the increment of soil available phosphate content after experiment resulting y=0.1788x-6.169 ($R^2=0.9425$) when applied fused superphosphate fertilizer, and y=0.0662x-2.689 ($R^2=0.9315$) when applied LFCs by the same amounts of phosphate (x: phosphate application, kg $ha^{-1}$, y: increment in soil available phosphate content, mg $kg^{-1}$. Plant height, number of stems, nutrients uptake by rice and rice yield showed higher levels in N 100, 150% application plots of chemical fertilizers, while every LFC plots exhibited lower values and no significant difference among them. Relative nitrogen fertilization efficiencies of LFCs compared to urea was 12.3% for cattle faeces compost (CaFC), 8.8 for swine faeces compost (SwFC) and 24.6 for chicken faeces compost (ChFC), respectively.

• Journal of Biosystems Engineering
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• 제29권4호
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• pp.341-346
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• 2004

Recent livestock people concern not only increase of production, but also superior quality of animal-breeding environment. So far, the optimization of the breeding and air environment has been focused on the production increase. In the very near future, the optimization will be emphasized on the environment for the animal welfare and health. Especially, cattle farming demands the precision livestock farming and special attention has to be given to the management of feeding, animal health and fertility. The management of individual animal is the first step for precision livestock farming and animal welfare, and recognizing each individual is important for that. Though electronic identification of a cattle such as RFID(Radio Frequency Identification) has many advantages, RFID implementations practically involve several problems such as the reading speed and distance. In that sense, computer vision might be more effective than RFID for the identification of an individual animal. The researches on the identification of cattle via image processing were mostly performed with the cows having black-white patterns of the Holstein. But, the native Korean and Japanese cattle do not have any definite pattern on the body. The purpose of this research is to identify the Japanese black cattle that does not have a body pattern using computer vision technology and neural network algorithm. Twelve heads of Japanese black cattle have been tested to verify the proposed scheme. The values of input parameters were specified and then computed using the face images of cattle. The images of cattle faces were trained using associate neural network algorithm, and the algorithm was verified by the face images that were transformed using brightness, distortion, and noise factors. As a result, there was difference due to transform ratio of the brightness, distortion, and noise. And, the proposed algorithm could identify 100% in the range from -3 to +3 degrees of the brightness, from -2 to +4 degrees of the distortion, and from 0% to 60% of the noise transformed images. It is concluded that our system can not be applied in real time recognition of the moving cows, but can be used for the cattle being at a standstill.

• 한국수정란이식학회지
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• 제28권4호
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• pp.337-342
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• 2013

Salmonellosis is one of the life-threating diseases of goat in Bangladesh. Therefore, the present study was designed to study the prevalence of Salmonellosis, and isolation and characterizations of the Salmonella spp. from apparently healthy and diarrheic goat. A total of 47 faces samples were collected from selected place and cultured onto different prescribed medium to isolate it. In this study, 12.76% (6/47) samples were found to be positive for Salmonella spp. During culture on SS agar medium, all of the Salmonella isolates produced round, smooth, opaque, translucent and black color colonies on SS agar media. All of the isolated Salmonella spp. fermented dextrose, maltose and mannitol with production of acid and gas but did not ferment sucrose and lactose. However, these isolates had showed Indole and Voges-Proskauer test negative, Methyl-Red test positive. All of these isolates were subjected to rapid plate agglutination test with polyvalent "O" (Poly 'O') and polyvalent "H" (poly 'H') antisera where positive agglutination were observed. They were highly sensitive to ciprofloxacin, spiramycin and gentamycin; moderately sensitive to oxytetracyline, streptomycin and amoxicillin; less sensitive to sulphamethoxazole and resistant to penicillin-G. Based on the present findings, it may be concluded that the investigated Salmonella spp. from goats might be S. typhimurium, S. enteritidis, S. brandenburg, S. salford, S. newbrunswick, S. newport or S. dublin. Further study will be needed, therefore it requires further characterization using other serological and molecular techniques.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 추계학술발표대회
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• pp.493-494
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• 2022

The development of livestock faces intensive farming results in a rising need for recognition of individual animals such as cows and pigs is related to high traceability. In this paper, we present a non-invasive biometrics systematic approach based on the deep-learning classification model to pig face identification. Firstly, in our systematic method, we build a ROS data collection system block to collect 10 pig face data images. Secondly, we proposed a preprocessing block in that we utilize the SSIM method to filter some images of collected images that have high similarity. Thirdly, we employ the improved image classification model of CNN (ViT), which uses the finetuning and pretraining technique to recognize the individual pig face. Finally, our proposed method achieves the accuracy about 98.66%.

• 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.

• 한국축산시설환경학회지
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• 제13권1호
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• pp.35-44
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• 2007

본 시험은 육성돈 사료에 미생물제제를 사료에 미생물제제 A 및 B 0.1 미생물제제 C를 0.2% 혼합 급여할 경우 사료섭취량 및 돈분의 오염물질 배설농도에 미치는 영향을 분석하기 위하여 4처리$\times$반복당 5두로서 총 20두를 공시하여 실시하였는데 그 결과를 요약하면 다음과 같다. 1. 육성비육돈의 일일 평균사료섭취량은 대조구 2.06kg/일.두였고 미생물 A, B, C 구는 각각 2.13kg/일.두, 2.17, 2.34로 미생물제제 C구에서 일일 사료섭취량이 가장 높게 조사되었으며(p<0.05), 2. 일일평균 음수량은 사료섭취량이 높았던 미생물 C구에서 2.89kg/일/두로 가장 높게 조사되었다(p<0.05). 3. 미생물제제 처리구별로 분뇨 배설량은 사료섭취량이 높았던 미생물제제 C 구에서 가장 많이 배설되는 것으로 조사되었으며 (0<0.05), 돈뇨의 배설량도 미생물제제 C구에서 2.31kg/일/두에서 높았다(p<0.05). 4. 육성돈의 성장단계별 돈분뇨의 수분 함량은 및 비료성분인 T-N, $P_2O_5,\;K_2O$ 성분도 처리간에 큰 차이를 보이지 않았다(p<0.05). 5. 육성돈 분뇨의 평균 BOD 농도는 돈분의 경우 미생물제제 A, B제제 급여구가 유의적으로 높게 조사되었다(p<0.05). 그리고 돈뇨의 BOD의 경우에도 미생물제제 A급 여구에서 $6,537mg/\ell$로 가장 높은 것으로 조사되었다(p<0.05). 6. COD의 경우에도 미생물 C급여구에서 가장 높게 조사되었으며(p<0.05). 돈뇨의 경우에는 미생물제제 A급여구에서 평균 $8,566mg\ell$로 가장 높았다(p<0.05). 7. SS 농도는 대조구에서 가장 높게 조사 되었으며(p<0.05), 그 다음이 미생물 B> 미생물 C> 대조구 순으로 조사되었다. 8. 돈분뇨중의 T-N 농도는 처리구간에 유의적인 차이가 나타나지 않았다(p<0.05). 9. 돈분중의 T-P 농도는 미생물제제 처리 구간별로 미생물제제 A, C 급여구에서 유의적인 차이가 나는 것으로 조사되었다(p<0.05). 이상의 결과를 요약해보면 육성돈에 미생물제제 혼합급여는 사료섭취량을 증가시키는데 효과가 있으나 비료성분 배설량에는 큰 차이를 보이지 않는 것으로 조사되었으며, 오염물질 배설량의 경우에는 사료섭취량이 높은 미생물제제 C 급여구에서 높은 것으로 조사되었다.