• Title, Summary, Keyword: Pig Productivity

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Investigation on changes in pig farm productivity after ban of antibiotics growth promoter in commercial mixed feed (배합사료 내 항생제 사용금지 이후 양돈농가 생산성적 변화 조사)

  • Kim, Ki-Hyun;Cho, Eun-Seok;Kim, Kwang-Sik;Kim, Jo-Eun;Seol, Kuk-Hwan;Park, Jun-Cheol;Kim, Young-Hwa
    • Korean Journal of Agricultural Science
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    • v.42 no.3
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    • pp.223-229
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    • 2015
  • This study was conducted to investigate the changes in the pig productivity after ban of antibiotics growth promoter in commercial pig farms. A total 74 pig farms that herd size is from less than 100 sows to more than 500 sows were selected for survey. Changes of pig productivity before/after ban of antibiotics were analyzed by comparing with our survey results and report of KPPA (Korean Pork Producers Association, 2013). In the results, no difference on pig productivity was observed by herd size among our survey farms. Live born piglets have been raised as time passes since 2003, and then it reach to 10.6 head per sow in 2012. The numbers of weaning piglet tended to increase, but sow turnover ratio was found to be a tendency to decrease after ban of antibiotics in our survey results. There was no effect of using antibiotics on mortality of pre- and post- weaning. Marketing per sow per year (MSY) does not be improved because the post-weaning mortality was maintained at a high level, despite live pig born and weaning piglet have increased after 2003. In conclusion, a ban of antibiotics growth promoter does not directly affect to pig productivity, but it needs the efforts to reduce the mortality of post-weaning for improvement of pig productivity. We suggest that this data will be useful to swine industry as the fundamental information.

Effects of Humic Acid and Blueberry Leaf Powder Supplementation in Feeds on the Productivity, Blood and Meat Quality of Finishing Pigs

  • Kim, Kwonjung;Bae, Inkyu;Cho, Jinho;Choi, Yangil;Ha, Jungheun;Choi, Jungseok
    • Food Science of Animal Resources
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    • v.39 no.2
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    • pp.276-285
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    • 2019
  • The objective of this study was to determine effects of humic acid (HA) and blueberry leaf powder (BLP) supplementation in pig feed on productivity, blood profiles, and meat quality characteristics of longissimus muscle. The experimental design included six treatments: 1) CON, no addition; 2) T1, BLP 0.1%; 3) T2, BLP 0.2%; 4) T3, humic acid 2%; 5) T4: humic acid 2%+BLP 0.1%; and 6) T5: humic acid 2%+BLP 0.2%. HA and BLP supplementation in pig feed significantly increased average daily feed intake (ADFI) values (p<0.05). HA supplementation in pig feed had beneficial effects in lipid profiles without altering feed efficiency rate (FER). HA and BLP co-supplementation in pig feed decreased pH in longissimus thoracis (p<0.05). In addition, sensory characteristics were enhanced when pig feed was supplemented with HA and BLP without causing adverse effects in meat quality. Taken together, addition of HA and BLP in pig feed may produce functional meat products.

TRADITIONAL PIG FARMING IN THE SOUTH PACIFIC: PROBLEMS AND OPPORTUNITIES FOR INCREASING PRODUCTIVITY

  • Ochetim, S.
    • Asian-Australasian Journal of Animal Sciences
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    • v.6 no.3
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    • pp.347-360
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    • 1993
  • The project was undertaken to provide information on the present system of traditional pig farming in the South Pacific region, to identify the problems currently limiting productivity of such pigs and to offer practical strategies which could be used for increasing productivity of the animals. The problems were identified by surveying some 220 subsistence pig farms in eleven island countries in the South Pacific region using a prepared questionnaire. The units were found to be generally small, consisting of about 2-4 sows per herd. The productivity of the units as assessed in terms of sow reproductive efficiency was rather low, being only about 7.5. Feed, housing, breeding, disease, marketing, lack of capital, technical know-how and existing social traditions were identified as current constraints. Based on three of the most limiting factors identified namely feed, housing and breeding, strategies for improvement were developed on the basis of better and more effective use of locally available feed resources, better housing and genetic improvement through crossbreeding programmes. These improvement strategies were tested as a package model on some ten farms in two of the island countries. The results of these on-farm trials indicated that using the improvement strategies increased sow reproductive efficiency by approximately 60 percent, to nearly 12. The significance of these findings in the overall management of traditionally raised pigs in the South Pacific region is discussed.

Effect of Floor Space Allowance on Pig Productivity across Stages of Growth: A Field-scale Analysis

  • Lee, Joon H.;Choi, Hong L.;Heo, Yong J.;Chung, Yoon P.
    • Asian-Australasian Journal of Animal Sciences
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    • v.29 no.5
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    • pp.739-746
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    • 2016
  • A total of 152 pig farms were randomly selected from the five provinces in South Korea. During the experiment, the average temperature and relative humidity was $24.7^{\circ}C$ and 74% in summer and $2.4^{\circ}C$ and 53% in winter, respectively. The correlation between floor space allowance (FSA) and productivity index was analyzed, including non-productive sow days (NPD), number of weaners (NOW), survival rate (SR), appearance rate of A-grade pork (ARA), and days at a slaughter weight of 110 kg (d-SW) at different growth stages. The objectives of the present study were i) to determine the effect of FSA on the pig productivity index and ii) to suggest the minimum FSA for pigs based on scientific baseline data. For the pregnant sow, NPD could be decreased if pregnant sows were raised with a medium level (M) of FSA (3.10 to $3.67m^2/head$) while also keeping the pig house clean which improves hygiene, and operating the ventilation system properly. For the farrowing sows, the NOW tended to decrease as the FSA increased. Similarly, a high level of FSA (H) is significantly negative with weaner SR of farrowing sows (p-value = 0.017), indicating this FSA tends to depress SR. Therefore, a FSA of 2.30 to $6.40m^2/head$ (very low) could be appropriate for weaners because a limited space can provide a sense of security and protection from external interruptions. The opposite trend was observed that an increase in floor space (> $1.12m^2/head$ leads to increase the SR of growing pigs. For the fattening pigs, H level of FSA was negatively correlated with SR, but M level of FSA was positively correlated with SR, indicating that SR tended to increase with the FSA of 1.10 to $1.27m^2/head$. In contrast, ARA of male fattening pigs showed opposite results. H level of FSA (1.27 to $1.47m^2/head$) was suggested to increase productivity because ARA was most affected by H level of space allowance with positive correlation ($R^2=0.523$). The relationship between the FSA and d-SW of fattening pigs was hard to identify because of the low $R^2$ value. However, the farms that provided a relatively large floor space (1.27 to $1.54m^2/head$) during the winter period showed d-SW was significantly and negatively affected by FSA.

Analysis of Working Environment and Ventilation Efficiency in Pig House using Computational Fluid Dynamics (전산유체역학을 사용한 양돈장 내 작업환경 환기효율성 분석)

  • Oh, Byung-Wook;Lee, Seong-Won;Kim, Hyo-Cher;Seo, Il-Hwan
    • Journal of The Korean Society of Agricultural Engineers
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    • v.61 no.2
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    • pp.85-95
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    • 2019
  • The internal environment in pig house is closely related to the animal productivity. In addition, it is important to consider a working environment inside the pig house due to high gas and dust concentrations. The poor working environment inside the pig house can cause health problems including respiratory diseases. To analyze the working environment, it is important to evaluate the ventilation efficiency to effectively remove harmful gases and dust. The purpose of this study is to develop a 3D CFD model to analyze the working environment in the pig house. CFD model was validated by comparing air temperature distributions between CFD computed and field measured data. The average air flow rate at the pig height was 40.1 % lower than the working height when incoming air was concentrated on upper layer by the installed ventilation system on the experimental pig house. Using the validated CFD model, the regional ventilation efficiency was computed by the TGD(tracer gas decay) method at the pig and working heights. There was a difference of ventilation efficiency on 14 % between the air stagnated section and the rest sections. Stagnated gas concentration can be effected by animal and human health.

SELECTION OF THE SENSORS FOR THE ENVIRONMENTAL CONTROL SYSTEMS OF PIG-HOUSING IN TEMPERATE ZONE

  • Chang, Dong-Il;Chang, Hong-Hee
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • pp.1126-1135
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    • 1996
  • This study was conducted to select the sensors for measuring temperature, relative humidity, and air velocity among the major environmental factors affecting the pig productivity as a part of the study for the optimum production system model development of pig-housing. The study results are summarized as the follows : Two sensors , HMP233L and HANI, were tested for measuring temperature and relative humidity , Test results were analyzed by the statistical methods. And the sensor, HMP233L was selected as a proper sensor for temperature sand relative humidity measurement . An air velocity sensor was tested. Test results showed that its accuracy was low and incongruent for the air velocity measurement when it was lower than 4m/s.

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Development of a CFD Model to Study Ventilation Efficiency of Mechanically Ventilated Pig House (강제환기식 돈사의 환기 효율성 분석을 위한 CFD 모델 개발)

  • Seo, Il-Hwan;Lee, In-Bok;Hong, Se-Woon;Hwang, Hyun-Seob;Bitog, Jessie Pascul;Yoo, Jae-In;Kwon, Kyung-Suk;Ha, Tae-Hwan;Kim, Hyeon-Tae
    • Journal of The Korean Society of Agricultural Engineers
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    • v.50 no.1
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    • pp.25-37
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    • 2008
  • When livestock facilities in Korea have been changed larger and denser, rearing conditions have been getting worse and the productivity of animal production have been decreased. Especially in the cold season, the minimized ventilation has generally been operated to save energy cost in Korea resulting in very poor environmental condition and high mortality. While the stability, suitability, and uniformity of the rearing condition are the most important for high productivity, the ventilation configuration is the most important to improve the rearing condition seasonally. But, it is so difficult to analyze the internal air flow and the environmental factors by conducting only field experiment because the weather condition is very unpredictable and unstable as well as the structural specification can not be easily changed by the researchers considering cost and labor. Accordingly, an aerodynamic computer simulation was adopted to this study to overcome the weakness of conducting field experiment and study the aerodynamic itself. It has been supposed that the airflow is the main mechanism of heat, mass, and momentum transfers. To make the simulation model accurately and actually, simplified pig models were also developed. The accuracy of the CFD simulation model was enhanced by 4.4 % of errors compared with the data collected from field experiments. In this paper, using the verified CFD model, the CFD computed internal rearing condition of the mechanically ventilated pig house were analyzed quantitatively as well as qualitatively. Later, this developed model will be computed time-dependently to effectively analyze the seasonal ventilation efficiency more practically and extensively with tracer gas decay theory.

Prediction of Water Usage in Pig Farm based on Machine Learning (기계학습을 이용한 돈사 급수량 예측방안 개발)

  • Lee, Woongsup;Ryu, Jongyeol;Ban, Tae-Won;Kim, Seong Hwan;Choi, Heechul
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.8
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    • pp.1560-1566
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    • 2017
  • Recently, accumulation of data on pig farm is enabled through the wide spread of smart pig farm equipped with Internet-of-Things based sensors, and various machine learning algorithms are applied on the data in order to improve the productivity of pig farm. Herein, multiple machine learning schemes are used to predict the water usage in pig farm which is known to be one of the most important element in pig farm management. Especially, regression algorithms, which are linear regression, regression tree and AdaBoost regression, and classification algorithms which are logistic classification, decision tree and support vector machine, are applied to derive a prediction scheme which forecast the water usage based on the temperature and humidity of pig farm. Through performance evaluation, we find that the water usage can be predicted with high accuracy. The proposed scheme can be used to detect the malfunction of water system which prevents the death of pigs and reduces the loss of pig farm.

FEED RESOURCE AVAILABILITY AND UTILIZATION IN SMALLHOLDER PIG FARMS IN SRI LANKA

  • Ravindran, V.;Cyril, H.W.;Nadesalingam, P.;Gunawardene, D.D.
    • Asian-Australasian Journal of Animal Sciences
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    • v.8 no.4
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    • pp.311-316
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    • 1995
  • Data on available feed resources, feeding practices and nutrient adequacy of rations under small farm conditions in Sri Lanka were obtained in a baseline survey involving 104 pig farms. The results showed that a wide range of non-conventional feedstuffs are used for pig feeding under typical small farm conditions and that dietary protein quality is a major factor limiting productivity. Following the survey, two on-farm trials were conducted to evaluate cheaper, alternative feeding strategies. In trial 1, a test diet was formulated using several non-conventional feedstuffs and compared with a commercial feed that is normally fed in the farms. In trial 2, the possibility of improving growth rates by amino acid supplementation was evaluated. The results demonstrated that feed costs can be considerably lowered through these packages. Some problems inherent to on-farm livestock trials are highlighted.

Image Processing and Deep Learning Techniques for Fast Pig's Posture Determining and Head Removal (돼지의 빠른 자세 결정과 머리 제거를 위한 영상처리 및 딥러닝 기법)

  • Ahn, Hanse;Choi, Wonseok;Park, Sunhwa;Chung, Yongwha;Park, Daihee
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.11
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    • pp.457-464
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    • 2019
  • The weight of pig is one of the main factors in determining the health and growth state of pigs, their shipment, the breeding environment, and the ration of feed, and thus measuring the pig's weight is an important issue in productivity perspective. In order to estimate the pig's weight by using the number of pig's pixels from images, acquired from a Top-view camera, the posture determining and the head removal from images are necessary to measure the accurate number of pixels. In this research, we propose the fast and accurate method to determine the pig's posture by using a fast image processing technique, find the head location by using a fast deep learning technique, and remove pig's head by using light weighted image processing technique. First, we determine the pig's posture by comparing the length from the center of the pig's body to the outline of the pig in the binary image. Then, we train the location of pig's head, body, and hip in images using YOLO(one of the fast deep learning based object detector), and then we obtain the location of pig's head and remove an outside area of head by using head location. Finally, we find the boundary of head and body by using Convex-hull, and we remove pig's head. In the Experiment result, we confirmed that the pig's posture was determined with an accuracy of 0.98 and a processing speed of 250.00fps, and the pig's head was removed with an accuracy of 0.96 and a processing speed of 48.97fps.