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Cannas A, Cabrera VE, Dougherty HC, Ellis JL, Gallo A, Huhtanen P, Kyriazakis I, McPhee M, Reed KF, Sakomura NK, van Milgen J. Editorial: The 10th international Workshop on Modelling Nutrient Digestion and Utilization in Farm Animals (MODNUT). Animal 2023; 17 Suppl 5:101067. [PMID: 38286524 DOI: 10.1016/j.animal.2023.101067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 12/18/2023] [Indexed: 01/31/2024] Open
Affiliation(s)
- A Cannas
- Department of Agricultural Sciences, University of Sassari, Italy.
| | - V E Cabrera
- Department of Animal and Dairy Sciences, University of Wisconsin, Madison, Madison, WI, United States
| | - H C Dougherty
- Department of Animal Science, University of New England, Armidale, NSW, Australia
| | - J L Ellis
- Centre for Nutrition Modelling, Department of Animal Biosciences, University of Guelph, Ontario, Canada
| | - A Gallo
- Dipartimento di Scienze animali, della nutrizione e degli alimenti (DIANA), Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - P Huhtanen
- Natural Resources Institute Finland (LUKE), Production Systems, Jokioinen, Finland
| | - I Kyriazakis
- Institute for Global Food Security, Queen's University, Belfast, United Kingdom
| | - M McPhee
- NSW Department of Primary Industries, Armidale Livestock Industries Centre, University of New England, Armidale, Australia
| | - K F Reed
- Department of Animal Science, Cornell University, Ithaca, NY, United States
| | - N K Sakomura
- Department of Animal Science, School of Agricultural and Veterinary Sciences, São Paulo State University (UNESP), Jaboticabal, São Paulo, Brazil
| | - J van Milgen
- Pegase, INRAE, Institut Agro, Le Clos, Saint Gilles 35590, France
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Küçüktopçu E, Cemek B, Simsek H. Application of Mamdani Fuzzy Inference System in Poultry Weight Estimation. Animals (Basel) 2023; 13:2471. [PMID: 37570279 PMCID: PMC10417342 DOI: 10.3390/ani13152471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 07/19/2023] [Accepted: 07/28/2023] [Indexed: 08/13/2023] Open
Abstract
Traditional manual weighing systems for birds on poultry farms are time-consuming and may compromise animal welfare. Although automatic weighing systems have been introduced as an alternative, they face limitations in accurately estimating the weight of heavy birds. Therefore, exploring alternative methods that offer improved efficiency and precision is necessary. One promising solution lies in the application of AI, which has the potential to revolutionize various aspects of poultry production and management, making it an indispensable tool for the modern poultry industry. This study aimed to develop an AI approach based on the FL model as a viable solution for estimating poultry weight. By incorporating expert knowledge and considering key input variables such as indoor temperature, indoor humidity, and feed consumption, FL-based models were developed with different configurations using Mamdani inferences and evaluated across eight different rearing periods in Samsun, Türkiye. This study's results demonstrated the effectiveness of FL-based models in estimating poultry weight. The models achieved varying average absolute error values across different age groups of broilers, ranging from 0.02% to 5.81%. These findings suggest that FL-based methods hold promise for accurate and efficient poultry weight estimation. This study opens up avenues for further research in the field, encouraging the exploration of FL-based approaches for improved poultry weight estimation in poultry farming operations.
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Affiliation(s)
- Erdem Küçüktopçu
- Department of Agricultural Structures and Irrigation, Ondokuz Mayıs University, Samsun 55139, Türkiye;
| | - Bilal Cemek
- Department of Agricultural Structures and Irrigation, Ondokuz Mayıs University, Samsun 55139, Türkiye;
| | - Halis Simsek
- Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN 47907, USA;
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