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Evaluating swine disease occurrence on farms using the state-space model based on meat inspection data: a time-series analysis
http://hdl.handle.net/10458/0002000737
http://hdl.handle.net/10458/00020007378b7e89fd-0758-4b8e-8e33-3f4e6f3c2d43
| 名前 / ファイル | ライセンス | アクション |
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article (1.2 MB)
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||||||
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| 公開日 | 2024-09-06 | |||||||||
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| タイトル | Evaluating swine disease occurrence on farms using the state-space model based on meat inspection data: a time-series analysis | |||||||||
| 言語 | en | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| キーワード | ||||||||||
| 言語 | en | |||||||||
| 主題Scheme | Other | |||||||||
| キーワード | Swine | |||||||||
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| 言語 | en | |||||||||
| 主題Scheme | Other | |||||||||
| キーワード | Slaughterhouse | |||||||||
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| 言語 | en | |||||||||
| 主題Scheme | Other | |||||||||
| キーワード | Inspection data | |||||||||
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| 言語 | en | |||||||||
| 主題Scheme | Other | |||||||||
| キーワード | State-space model | |||||||||
| 資源タイプ | ||||||||||
| 資源タイプ | journal article | |||||||||
| アクセス権 | ||||||||||
| 著者 |
Narita, Tsubasa
× Narita, Tsubasa
× Kubo, Meiko× Nagakura, Yuichi
× 関口, 敏 |
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| 抄録 | ||||||||||
| 内容記述タイプ | Abstract | |||||||||
| 内容記述 | BACKGROUND Data on abnormal health conditions in animals obtained from slaughter inspection are important for identifying problems in fattening management. However, methods to objectively evaluate diseases on farms using inspection data has not yet been well established. It is important to assess fattening management on farms using data obtained from slaughter inspection. In this study, we developed the state-space model to evaluate swine morbidity using slaughter inspection data. RESULTS The most appropriate model for each disease was constructed using the state-space model. Data on 11 diseases in slaughterhouses over the past 4 years were used to build the model. The model was validated using data from 14 farms. The local-level model (the simplest model) was the best model for all diseases. We found that the analysis of slaughter data using the state-space model could construct a model with greater accuracy and flexibility than the ARIMA model. In this study, no seasonality or trend model was selected for any disease. It is thought that models with seasonality were not selected because diseases in swine shipped to slaughterhouses were the result of illness at some point during the 6-month fattening period between birth and shipment. CONCLUSION Evaluation of previous diseases helps with the objective understanding of problems in fattening management. We believe that clarifying how farms manage fattening of their pigs will lead to improved farm profits. In that respect, it is important to use slaughterhouse data for fattening evaluation, and it is extremely useful to use mathematical models for slaughterhouse data. However, in this research, the model was constructed on the assumption of normality and linearity. In the future, we believe that we can build a more accurate model by considering models that assume non-normality and non-linearity. |
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| 言語 | en | |||||||||
| 内容記述 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | Citation: Narita, T., Kubo, M., Nagakura, Y. et al. Evaluating swine disease occurrence on farms using the state-space model based on meat inspection data: a time-series analysis. Porc Health Manag 10, 6 (2024). https://doi.org/10.1186/s40813-024-00355-z |
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| 言語 | en | |||||||||
| 書誌情報 |
en : Porcine Health Management 巻 10, 号 1, p. Article number: 6, 発行日 2024-01-23 |
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| 出版者 | ||||||||||
| 出版者 | Springer Science and Business Media LLC | |||||||||
| 言語 | en | |||||||||
| ISSN | ||||||||||
| 収録物識別子タイプ | EISSN | |||||||||
| 収録物識別子 | 2055-5660 | |||||||||
| DOI | ||||||||||
| 関連タイプ | isVersionOf | |||||||||
| 識別子タイプ | DOI | |||||||||
| 関連識別子 | https://doi.org/10.1186/s40813-024-00355-z | |||||||||
| 権利 | ||||||||||
| 言語 | en | |||||||||
| 権利情報 | © The Author(s) 2024. | |||||||||
| 著者版フラグ | ||||||||||
| 出版タイプ | VoR | |||||||||
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Narita, Tsubasa, Kubo, Meiko, Nagakura, Yuichi, 関口, 敏, 2024, Evaluating swine disease occurrence on farms using the state-space model based on meat inspection data: a time-series analysis: Springer Science and Business Media LLC, Article number: 6– p.
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