• Title/Summary/Keyword: chicken performance

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Intestinal segment and vitamin D3 concentration affect gene expression levels of calcium and phosphorus transporters in broiler chickens

  • Jincheng Han;Lihua Wu;Xianliang Lv;Mengyuan Liu;Yan Zhang;Lei He;Junfang Hao;Li Xi;Hongxia Qu;Chuanxin Shi;Zhiqiang Li;Zhixiang Wang;Fei Tang;Yingying Qiao
    • Journal of Animal Science and Technology
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    • v.65 no.2
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    • pp.336-350
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    • 2023
  • Two experiments were conducted in this research. Experiment 1 investigated the spatial expression characteristics of calcium (Ca) and phosphorus (P) transporters in the duodenum, jejunum, and ileum of 21-day-old broilers provided with adequate nutrient feed. Experiment 2 evaluated the effects of dietary vitamin D3 (VD3) concentration (0, 125, 250, 500, 1,000, and 2,000 IU/kg) on growth performance, bone development, and gene expression levels of intestinal Ca and P transporters in 1-21-day-old broilers provided with the negative control diet without supplemental VD3. Results in experiment 1 showed that the mRNA levels of calcium-binding protein 28-kDa (CaBP-D28k), sodium-calcium exchanger 1 (NCX1), plasma membrane calcium ATPase 1b (PMCA1b), and IIb sodium-phosphate cotransporter (NaPi-IIb) were the highest in the broiler duodenum. By contrast, the mRNA levels of inorganic phosphate transporter 1 (PiT-1) and 2 (PiT-2) were the highest in the ileum. Results in experiment 2 showed that adding 125 IU/kg VD3 increased body weight gain (BWG), feed intake (FI), bone weight, and percentage and weight of Ca and P in the tibia and femur of 1-21-day-old broilers compared with the negative control diet (p < 0.05). The rise in dietary VD3 levels from 125 to 1,000 IU/kg further increased the BWG, FI, and weights of the bone, ash, Ca, and P (p < 0.05). No difference in growth rate and leg bone quality was noted in the broilers provided with 1,000 and 2,000 IU/kg VD3 (p > 0.05). Supplementation with 125-2,000 IU/kg VD3 increased the mRNA abundances of intestinal Ca and P transporters to varying degrees. The mRNA level of CaBP-D28k increased by 536, 1,161, and 28 folds in the duodenum, jejunum, and ileum, respectively, after adding 1,000 IU/kg VD3. The mRNA levels of other Ca and P transporters (PMCA1b, NCX1, NaPi-IIb, PiT-1, and PiT-2) increased by 0.57-1.74 folds by adding 1,000-2,000 IU/kg VD3. These data suggest that intestinal Ca and P transporters are mainly expressed in the duodenum of broilers. Moreover, the addition of VD3 stimulates the two mineral transporter transcription in broiler intestines.

Estimation of Genetic Variations and Selection of Superior Lines from Diallel Crosses in Layer Chicken (산란계종의 잡종강세 이용을 위한 유전학적 기초연구와 우량교배조합 선발에 관한 연구)

  • 오봉국;한재용;손시환;박태진
    • Korean Journal of Poultry Science
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    • v.13 no.1
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    • pp.1-14
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    • 1986
  • The subject of this study was to obtain some genetic information for developing superior layer chickens. Heterosis and combining ability effects were estimated with 5,759 progenies of full diallel crosses of 6 strains in White Leghorn. Fertility, hatchability, brooder-house viability, rearing- house viability, laying-house viability, age at 1st egg laying, body weight at 1st egg laying, average egg weight, hen-day egg production, hen-housed egg production, and feed conversion were investigated and analyzed into heterosis effect, general combining ability, specific combining ability and reciprocal effect by Grilling's model I. The results obtained were summarized as follows; 1. The general performance of each traits was 94.76% in fertility, 74.05% in hatchability, 97.47% in brooder-house viability, 99.72% in rearing-house viability, 93.81% in laying-house viability, 150 day in the age at 1st egg laying, 1,505g in the body weight at 1st egg laying, 60.08g in average egg weight, 77.11% in hen-day egg production, 269.8 eggs in hen-housed egg Production, and 2.44 in feed conversion. 2. The heterosis effects were estimated to -0.66%, 9.58%, 0.26%, 1.83%, -3.87%, 3.63%, 0.96%, 4.23%, 6.4%, and -0.8%, in fertility, hatchability, brooder-house viability, laying-house viability, the age at 1st egg laying, the body weight at 1st egg laying, average egg weight, hen-day egg Production, hen-housed egg production and feed conversion, respectively. 3. The results obtained from analysis of combining ability were as follows ; 1) Estimates of general combining ability, specific combining ability and reciprocal effects were not high in fertility. It was considered that fertility was mainly affected by environmental factors. In the hatchability, the general combining ability was more important than specific combining ability and reciprocal effects, and the superior strains were K and V which the additive genetic effects were very high. 2) In the brooder-house viability and laying-house viability, specific combining ability and reciprocal effects appeared to be important and the combinations of K${\times}$A and A${\times}$K were very superior. 3) In the feed conversion and average egg weight, general combining ability was more important compared with specific combining ability and reciprocal effects. On the basis of combining ability the superior strains were F, K and B in feed conversion, F and B in the average egg weight. 4) General combining ability, specific combining ability and reciprocal effects were important in the age at 1st egg laying and the combination of V ${\times}$F, F${\times}$K and B${\times}$F were very useful on the basis of these effects. In the body weight at 1st egg laying, general combining ability was more important than specific combining ability and reciprocal effects, relatively. The K, F and E strains were recommended to develop the light strain in the body weight at 1st egg laying. 5) General combining ability, specific combining ability and reciprocal effects were important in the hen-day egg production and hen-housed egg production. The combinations of F${\times}$K, A${\times}$K, and K${\times}$A were proper for developing these traits. 4. In general, high general combining ability effects were estimated for hatchability, body weight at 1st egg laying, average egg weight, hen-day egg production, hen-housed egg production, and feed conversion and high specific combining ability effects for brooder-house viability, laying house viability, age at 1st egg laying, hen-day egg production and hen-housed egg production, and high reciprocal effects for the age at 1st egg laying.

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Animal Infectious Diseases Prevention through Big Data and Deep Learning (빅데이터와 딥러닝을 활용한 동물 감염병 확산 차단)

  • Kim, Sung Hyun;Choi, Joon Ki;Kim, Jae Seok;Jang, Ah Reum;Lee, Jae Ho;Cha, Kyung Jin;Lee, Sang Won
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.137-154
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    • 2018
  • Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.