High-performance simulation of disease outbreaks in growing-finishing pig herds raised by the precision feeding method
•An advanced simulation model of the precision feeding system for pigs is presented.•A state machine behavior model is combined with a resilience and resistance model.•A disease outbreak model is integrated into the advanced precision feeding model.•A high-performance simulation program is created t...
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| Vydáno v: | Computers and electronics in agriculture Ročník 225; s. 109335 |
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| Jazyk: | angličtina |
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Elsevier B.V
01.10.2024
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| ISSN: | 0168-1699 |
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| Abstract | •An advanced simulation model of the precision feeding system for pigs is presented.•A state machine behavior model is combined with a resilience and resistance model.•A disease outbreak model is integrated into the advanced precision feeding model.•A high-performance simulation program is created to run disease control scenarios.
Perturbations always affect livestock during the breeding process, including harmful diseases. Researching the impact of disease outbreaks on pig herds is extremely important so that disease control measures can be applied early. However, conducting practical experiments on disease outbreaks is extremely expensive. Precision feeding systems (PFS) for pigs use data on the animal’s own feed intake to calculate the appropriate amount of feed for each individual. This helps increase productivity and product quality while contributing to reducing waste generation in the environment. Daily feed intake (DFI) and cumulative feed intake (CFI) data can be automatically collected and estimated from the PFS, which can help detect or predict disease outbreaks. In this article, we introduce an advanced simulation model of the PFS for pigs and the integration of disease outbreak models into this system. A disease outbreak simulation application within the pig herd raised by the precision feeding method is also developed for running high-performance experimental simulations. The results of the simulation scenarios are analyzed and compared with data from a real-world experiment to assess the accuracy of the application. The correlation coefficient values of DFI in all scenarios fall within the range of 0.25 to 0.5, suggesting almost no correlation between simulated DFI and actual DFI. The overall average correlation coefficient of CFI for all scenarios is 0.764, falling within the strong correlation range. It can be concluded that the simulation accurately represents CFI values compared to reality. |
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| AbstractList | Perturbations always affect livestock during the breeding process, including harmful diseases. Researching the impact of disease outbreaks on pig herds is extremely important so that disease control measures can be applied early. However, conducting practical experiments on disease outbreaks is extremely expensive. Precision feeding systems (PFS) for pigs use data on the animal’s own feed intake to calculate the appropriate amount of feed for each individual. This helps increase productivity and product quality while contributing to reducing waste generation in the environment. Daily feed intake (DFI) and cumulative feed intake (CFI) data can be automatically collected and estimated from the PFS, which can help detect or predict disease outbreaks. In this article, we introduce an advanced simulation model of the PFS for pigs and the integration of disease outbreak models into this system. A disease outbreak simulation application within the pig herd raised by the precision feeding method is also developed for running high-performance experimental simulations. The results of the simulation scenarios are analyzed and compared with data from a real-world experiment to assess the accuracy of the application. The correlation coefficient values of DFI in all scenarios fall within the range of 0.25 to 0.5, suggesting almost no correlation between simulated DFI and actual DFI. The overall average correlation coefficient of CFI for all scenarios is 0.764, falling within the strong correlation range. It can be concluded that the simulation accurately represents CFI values compared to reality. •An advanced simulation model of the precision feeding system for pigs is presented.•A state machine behavior model is combined with a resilience and resistance model.•A disease outbreak model is integrated into the advanced precision feeding model.•A high-performance simulation program is created to run disease control scenarios. Perturbations always affect livestock during the breeding process, including harmful diseases. Researching the impact of disease outbreaks on pig herds is extremely important so that disease control measures can be applied early. However, conducting practical experiments on disease outbreaks is extremely expensive. Precision feeding systems (PFS) for pigs use data on the animal’s own feed intake to calculate the appropriate amount of feed for each individual. This helps increase productivity and product quality while contributing to reducing waste generation in the environment. Daily feed intake (DFI) and cumulative feed intake (CFI) data can be automatically collected and estimated from the PFS, which can help detect or predict disease outbreaks. In this article, we introduce an advanced simulation model of the PFS for pigs and the integration of disease outbreak models into this system. A disease outbreak simulation application within the pig herd raised by the precision feeding method is also developed for running high-performance experimental simulations. The results of the simulation scenarios are analyzed and compared with data from a real-world experiment to assess the accuracy of the application. The correlation coefficient values of DFI in all scenarios fall within the range of 0.25 to 0.5, suggesting almost no correlation between simulated DFI and actual DFI. The overall average correlation coefficient of CFI for all scenarios is 0.764, falling within the strong correlation range. It can be concluded that the simulation accurately represents CFI values compared to reality. |
| ArticleNumber | 109335 |
| Author | Pham, Linh Manh Le, Duc-Toan |
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| Cites_doi | 10.1016/j.physbeh.2014.09.012 10.3920/978-90-8686-712-7_36 10.1016/j.livsci.2021.104530 10.1109/ACCESS.2019.2955761 10.2527/1994.7261455x 10.1016/j.compag.2020.105826 10.3390/ani11092743 10.1007/978-3-030-89123-7_27-1 10.2527/jas.2014-7643 10.1109/KSE53942.2021.9648760 10.1017/S1751731108001766 10.1016/j.compag.2007.09.002 10.1590/S1516-35982009001300023 10.3390/ijerph192416440 10.3390/ani13040571 10.1017/S175173112000083X 10.1017/S1751731119001976 10.1016/j.animal.2021.100251 10.1016/j.livsci.2009.12.006 10.1016/j.iot.2023.100724 10.1007/s10707-018-00339-6 10.1017/S1751731117003159 10.1071/AN14521 10.1093/jas/skz167 10.1016/S0168-1591(98)00221-4 10.1787/19991142 10.3390/agronomy12030750 10.1073/pnas.082080899 10.2527/jas.2011-4252 10.3390/s22176541 10.2527/af.2017.0102 10.3109/03602530903125807 |
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| Keywords | Disease outbreak Precision feeding system Simulation Swine Agent-based model |
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| SubjectTerms | Agent-based model agriculture disease control Disease outbreak disease outbreaks electronics feed intake herds Precision feeding system product quality Simulation simulation models Swine |
| Title | High-performance simulation of disease outbreaks in growing-finishing pig herds raised by the precision feeding method |
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