• Asian-Australasian Journal of Animal Sciences
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• 제13권5호
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• pp.681-685
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• 2000

A computer software was developed in our laboratory to automatically control the pigs environment by the image analysis system (IAS), which monitors and analyzes the pig's behavior and feeds the results back to the computer hardware. Three feeding trials were conducted with growing pigs ($L{\times}Y$) to test the effectiveness of the IAS under various seasons. In all three trials, the open-sided conventional pens with half-slatted floor were used as controls; for the IAS treatment, fully-slatted floors were used in the windowless pens. Experiment 1 was conducted in the winter for 30 d with 24 growing pigs. There were two treatments (Conventional vs. IAS), and three pens (replicates) per treatment. During the growing period, the feed efficiency was significantly (p<0.05) improved by the IAS. In addition, the pigs reared under the IAS during the growing period displayed better growth rate during the finishing period than did the pigs reared under the conventional conditions. Experiment 2 was conducted in the summer for 30 d with 24 growing pigs. The experimental design was the same as Experiment 1. During the finishing period, all the pigs were kept in conventional open-sided pens until their market weights to evaluate their carcass characteristics. During the growing period, the growth rate and feed efficiency of the pigs in the IAS was better than those of the control pigs. In addition, various carcass characteristics were significantly improved by the IAS rearing during the growing period. Experiment 3 was conducted with 30 growing pigs for 30 d in the spring. The experimental design was the same as Experiment 1. No difference was found in growing performance between the control and IAS pigs. It could be concluded that the IAS is effective in providing optimum conditions for the growing pigs in summer and winter seasons. In addition, providing an optimum environment during the growing period results in improved growth rate, feed efficiency, and carcass qualities for the finishing pigs.

• 지능정보연구
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• 제28권2호
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• pp.263-278
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• 2022

최근 IoT 기술의 발달로 외출 중에도 반려동물에 급여하도록 자동 사료급식기가 유통되고 있다. 그러나 자동급식에서 중요한 중량을 측정하는 저울 방식은 쉽게 고장이 나고, 3D카메라 방식은 비용이 든다는 단점이 있으며, 2D카메라 방식은 중량 측정의 정확도가 떨어진다. 특히 사료가 복합된 경우 중량 측정 문제는 더욱 어려워질 수 있다. 따라서 본 연구의 목적은 2D카메라를 사용하면서도 중량을 정확하게 추정할 수 있는 딥러닝 접근법을 제안하는 것이다. 이를 위해 다양한 합성곱 신경망을 이용하였으며, 그중 ResNet101 기반 모델이 3.06 gram의 평균 절대 오차와 3.40%의 평균 절대비 오차를 기록하며 가장 우수한 성능을 보였다. 본 연구의 결과로 사료와 같이 규격화된 물체의 중량을 확보가 용이한 2D 이미지를 통해서만 예측할 필요가 있을 경우 유용한 정보로 활용될 수 있다.

• 한국수정란이식학회지
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• 제30권3호
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• pp.257-260
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• 2015

Reproductive disorders in cows cause economic loss in livestock farms. Reproductive diseases, such as follicular cyst, luteal cyst, endometritis, pyometra, and repeat breeding cause infertility. Among these diseases, endometritis and pyometra are uterine infections that are leading causes of infertility. This study was performed to investigate the causative agents of uterine diseases using bacterial culture. Bacteria were obtained from the reproductive organs (vagina, uterine cervix, and uterine horn) of dairy cow diagnosed with endometritis or pyometra, and cultured on blood agar. The colonies obtained from cultivation for 24 hours were passaged. To identify the bacteria, the colonies grown in passaged culture Gram stained and applied to an automatic biochemical microbial identification system. Escherichia coli were commonly detected in vagina, uterine cervix, and uterine horn of dairy cows diagnosed to pyometra. The cows having endometritis showed not only Escherichia coli but also Pantoea spp. and Klebsiella spp. strains. Dairy cows that were infected with Escherichia coli in uterus caused mastitis or digestive disease. These results suggest that sanitary feeding and management beforehand are needed to prevent bacterial infections.

• Journal of Animal Science and Technology
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• 제65권3호
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• pp.588-595
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• 2023

The aim of this study was to investigate the effects of heat stress on milk traits in South Korea using comprehensive data (dairy production and climate). The dataset for this study comprised 1,498,232 test-day records for milk yield, fat- and protein-corrected milk, fat yield, protein yield, milk urea nitrogen (MUN), and somatic cell score (SCS) from 215,276 Holstein cows (primiparous: n = 122,087; multiparous: n = 93,189) in 2,419 South Korean dairy herds. Data were collected from July 2017 to April 2020 through the Dairy Cattle Improvement Program, and merged with meteorological data from 600 automatic weather stations through the Korea Meteorological Administration. The segmented regression model was used to estimate the effects of the temperature-humidity index (THI) on milk traits and elucidate the break point (BP) of the THI. To acquire the least-squares mean of milk traits, the generalized linear model was applied using fixed effects (region, calving year, calving month, parity, days in milk, and THI). For all parameters, the BP of THI was observed; in particular, milk production parameters dramatically decreased after a specific BP of THI (p < 0.05). In contrast, MUN and SCS drastically increased when THI exceeded BP in all cows (p < 0.05) and primiparous cows (p < 0.05), respectively. Dairy cows in South Korea exhibited negative effects on milk traits (decrease in milk performance, increase in MUN, and SCS) when the THI exceeded 70; therefore, detailed feeding management is required to prevent heat stress in dairy cows.

• 한국축산시설환경학회지
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• 제2권1호
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• pp.27-39
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• 1996

낙농 전업농의 최적 기계장치 모델을 설정하는데 필요한 자료를 수집하고자 경기도 낙농가 중 사육규모 별로 經産牛 30두 미만, 30~50두, 50두 이상 각 5농가씩 15농가를 현지 방문하였다. 작업공정별 작업방법, 노동투하시간, 작업 비용 분석자료를 조사, 분석하고 관련 자료들을 수집하여, 經産牛 30두 내외규모, 40두 내외규모, 50두 내외규모에서의 최소 작업비용 기계장치 사육체계를 설정하여 우리나라의 절반 이상 낙농가에서 이용하고 있는 繫留式 牛舍, 양동이식 착유기 중심의 관행 작업 체계와 비교 분석한 결과는 다음과 같다. 1. 관행작업체계에서는 가족 노동 1.5인 기준 년 2,700시간으로 經産牛 15두까지 사육 가능하며, 이 때 필요한 총작업비용은 734천원/년ㆍ두로 산출되었다. 2. 繫留式 牛舍에서 최소작업비용을 구한 결과 호퍼식 농후사료 급여, 워터컵 급수, 파이프 라인 착유, 반크리너 분뇨청소에서는 經産牛 28두까지 사육 가능한 것으로 나타났으며, 총작업 비용은 520천원/년ㆍ두로 산출되었다. 3. 放飼式 牛舍는 繫留式 牛舍 보다 30두 내외로 사육하는 경우에는 총작업 비용이 더 높았다. 放飼式 牛舍의 최소 작업비용체계는 1열$\times$5두식 헤링본 착유실 착유, 농후사료 자동급여, 무가온보온급수, 스키로더 분뇨청소의 체계로, 經産牛 30두까지 사육 가능한 것으로 나타났으며, 총 작업 비용은 582천원/년ㆍ두로 나타났다. 4. 放飼式 牛舍 40두 내외 규모에서의 최소 작업비용체계는 2열$\times$4두식 헤링본 착유실 착유, 농후사료자동급여, 무가온보온급수, 스크레퍼 분뇨청소 체계로, 經産牛 41두까지 사육 가능하고 작업 비용은 501천원/년ㆍ두로 나타났다. 5. 放飼式 牛舍 50두 내외 규모에서의 최소 작업비용체계는 2열$\times$3두식 탠덤 착유실, 농후사료 자동급여, 무가온 보온급수, 스크레퍼 분뇨청소체계로, 經産牛 52두까지 사육가능하고 작업 비용은 500천원/두로 나타났다.

• Asian-Australasian Journal of Animal Sciences
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• 제20권5호
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• pp.682-692
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• 2007

This study presents an automatic system to predict parturition time in the crated sows. The system relies on ultrasonic transducers mounted from above along the length of the crate. Using a 40 kHz time of flight (TOF) single envelope wave, the momentary distances between the sensors are measured. Therefore, the local momentary height of the sow and the momentary posture, i.e. standing posture (SDP), kneeling posture (KP), sitting posture (STP) and lateral lying posture (LLP) are determined. Crated sows change their postures from standing to lying and vice versa which follows a characteristic pattern. As parturition approaches, sows exhibit uneasiness, restlessness and the stand up sequence (SUS, the posture transition from LLP to SDP) rate increases because of labor pains. In time series, the SUS rate demonstrates a peak and it happens approximately 0-12 h before parturition. In this paper, the basic parturition threshold value method (BPTVM) and the same hour method (SHM) are proposed for predicting parturition, both of which are based on the SUS rate. The BPTVM mainly detects the peak of the SUS rate. As the SUS rate exceeds the threshold value, the parturition becomes predictable. Moreover, the SHM calculates the difference in the SUS rates between a particular time of day and the corresponding time of the preceding day. Compared to the BPTVM, the SHM can eliminate the circadian rhythm of the SUS rate influenced by feeding behavior. Using the SHM the parturition can be approximately predicted within hours. In an attempt to define the threshold parameters of predicting parturition, a data set with 32 sows of the SUS rate are used to estimate assumable predicting probability. The results show the assumable probability of the parturition prediction within 9 h is 96.9% for the SHM and 84.4% for the BPTVM. Moreover, the SHM can even reach a 75% probability of prediction within three hours of parturition. We conclude that the SHM is more accurate and is more useful for parturition time prediction. When parturition is detected, the proposed algorithm generates a warning signal which can inform human personnel to protect the mother and newborn piglets.