Predicting Risk of Ammonia Exposure in Broiler Housing: Correlation with Incidence of Health Issues
This study assesses the risk of ammonia exposure in broiler chicken production and correlates these risks with health issues, utilizing machine learning techniques. Two broiler breeds, fast-growing (Ross®, 42 days) and slow growing (Hubbard®, 63 days), were studied at different densities. Slow-growi...
| Autores principales: | , , , , , , , |
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| Formato: | article |
| Lenguaje: | Inglés |
| Publicado: |
MDPI
2024
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/20.500.11939/8846 https://www.mdpi.com/2076-2615/14/4/615 |
| _version_ | 1855032864412794880 |
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| author | Barbosa, Leonardo V. S. da-Silva-Lima, Nilsa D. Granja-Barrios, Juliana-de-Souza de-Moura, Daniella J. Estellés, Fernando Ramón-Moragues, Adrián Calvet-Sanz, Salvador Villagrá, Arantxa |
| author_browse | Barbosa, Leonardo V. S. Calvet-Sanz, Salvador Estellés, Fernando Granja-Barrios, Juliana-de-Souza Ramón-Moragues, Adrián Villagrá, Arantxa da-Silva-Lima, Nilsa D. de-Moura, Daniella J. |
| author_facet | Barbosa, Leonardo V. S. da-Silva-Lima, Nilsa D. Granja-Barrios, Juliana-de-Souza de-Moura, Daniella J. Estellés, Fernando Ramón-Moragues, Adrián Calvet-Sanz, Salvador Villagrá, Arantxa |
| author_sort | Barbosa, Leonardo V. S. |
| collection | ReDivia |
| description | This study assesses the risk of ammonia exposure in broiler chicken production and correlates these risks with health issues, utilizing machine learning techniques. Two broiler breeds, fast-growing (Ross®, 42 days) and slow growing (Hubbard®, 63 days), were studied at different densities. Slow-growing birds had a fixed density of 32 kg/m2, while fast-growing ones were housed at low (16 kg/m2) and high (32 kg/m2) densities. The high concentration of atmospheric ammonia has been associated with a greater occurrence of bird health problems, such as pododermatitis, visual impairment and mucosal lesions compared to birds stocked in controlled environments with low concentrations of atmospheric ammonia. A total of 1250 birds were used, and classification algorithms (decision tree, SMO, Naive Bayes, and Multilayer Perceptron) were applied to predict ammonia risk levels. The analysis involved data selection, pre-processing, transformation, mining, and interpretation of results. The Multilayer Perceptron proved the most effective in predicting exposure risk. The Spearman’s correlation coefficient indicated a strong correlation between high ammonia concentrations and higher incidences of injuries in the birds that were evaluated. This research highlights the importance of managing ammonia levels in broiler production to mitigate health risks for both fast- and slow-growing breeds. |
| format | article |
| id | ReDivia8846 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | MDPI |
| publisherStr | MDPI |
| record_format | dspace |
| spelling | ReDivia88462025-04-25T14:49:33Z Predicting Risk of Ammonia Exposure in Broiler Housing: Correlation with Incidence of Health Issues Barbosa, Leonardo V. S. da-Silva-Lima, Nilsa D. Granja-Barrios, Juliana-de-Souza de-Moura, Daniella J. Estellés, Fernando Ramón-Moragues, Adrián Calvet-Sanz, Salvador Villagrá, Arantxa U10 Mathematical and statistical methods L01 Animal husbandry L70 Veterinary science and hygiene L73 Animal diseases Broiler chickens Ammonia Pododermatitis Prediction machine learning This study assesses the risk of ammonia exposure in broiler chicken production and correlates these risks with health issues, utilizing machine learning techniques. Two broiler breeds, fast-growing (Ross®, 42 days) and slow growing (Hubbard®, 63 days), were studied at different densities. Slow-growing birds had a fixed density of 32 kg/m2, while fast-growing ones were housed at low (16 kg/m2) and high (32 kg/m2) densities. The high concentration of atmospheric ammonia has been associated with a greater occurrence of bird health problems, such as pododermatitis, visual impairment and mucosal lesions compared to birds stocked in controlled environments with low concentrations of atmospheric ammonia. A total of 1250 birds were used, and classification algorithms (decision tree, SMO, Naive Bayes, and Multilayer Perceptron) were applied to predict ammonia risk levels. The analysis involved data selection, pre-processing, transformation, mining, and interpretation of results. The Multilayer Perceptron proved the most effective in predicting exposure risk. The Spearman’s correlation coefficient indicated a strong correlation between high ammonia concentrations and higher incidences of injuries in the birds that were evaluated. This research highlights the importance of managing ammonia levels in broiler production to mitigate health risks for both fast- and slow-growing breeds. 2024-04-26T10:50:18Z 2024-04-26T10:50:18Z 2024 article publishedVersion Barbosa, L. V., Silva-Lima, N. D., Granja-Barros, J. S., Estellés, F., Ramón-Moragues, A., Calvet-Sanz, S. et al. (2024). Predicting Risk of Ammonia Exposure in Broiler Housing: Correlation with Incidence of Health Issues. Animals, 14(4), 615. 2076-2615 https://hdl.handle.net/20.500.11939/8846 10.3390/ani14040615 https://www.mdpi.com/2076-2615/14/4/615 en Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ openAccess MDPI electronico |
| spellingShingle | U10 Mathematical and statistical methods L01 Animal husbandry L70 Veterinary science and hygiene L73 Animal diseases Broiler chickens Ammonia Pododermatitis Prediction machine learning Barbosa, Leonardo V. S. da-Silva-Lima, Nilsa D. Granja-Barrios, Juliana-de-Souza de-Moura, Daniella J. Estellés, Fernando Ramón-Moragues, Adrián Calvet-Sanz, Salvador Villagrá, Arantxa Predicting Risk of Ammonia Exposure in Broiler Housing: Correlation with Incidence of Health Issues |
| title | Predicting Risk of Ammonia Exposure in Broiler Housing: Correlation with Incidence of Health Issues |
| title_full | Predicting Risk of Ammonia Exposure in Broiler Housing: Correlation with Incidence of Health Issues |
| title_fullStr | Predicting Risk of Ammonia Exposure in Broiler Housing: Correlation with Incidence of Health Issues |
| title_full_unstemmed | Predicting Risk of Ammonia Exposure in Broiler Housing: Correlation with Incidence of Health Issues |
| title_short | Predicting Risk of Ammonia Exposure in Broiler Housing: Correlation with Incidence of Health Issues |
| title_sort | predicting risk of ammonia exposure in broiler housing correlation with incidence of health issues |
| topic | U10 Mathematical and statistical methods L01 Animal husbandry L70 Veterinary science and hygiene L73 Animal diseases Broiler chickens Ammonia Pododermatitis Prediction machine learning |
| url | https://hdl.handle.net/20.500.11939/8846 https://www.mdpi.com/2076-2615/14/4/615 |
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