Online warning systems for individual fattening pigs based on their feeding pattern
| Autor: | Sam Millet, Jürgen Vangeyte, Jarissa Maselyne, Dominiek Maes, Janne Van den Hof, Bart De Ketelaere, Annelies Van Nuffel, Petra Briene, Wouter Saeys |
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| Rok vydání: | 2018 |
| Předmět: |
Feeding pattern
Computer science Soil Science Agriculture Multidisciplinary Operations management HF RFID SYSTEM RFID Science & Technology Warning system GROWING-FINISHING PIGS ANIMALS 0402 animal and dairy science Agriculture Synergistic control 04 agricultural and veterinary sciences 040201 dairy & animal science Decision support INTELLIGENT CONTROL CHART Control and Systems Engineering 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Pigs WEIGHT Agricultural Engineering Life Sciences & Biomedicine Agronomy and Crop Science BEHAVIOR Control methods Barn (unit) Food Science |
| Zdroj: | Biosystems Engineering. 173:143-156 |
| ISSN: | 1537-5110 |
| DOI: | 10.1016/j.biosystemseng.2017.08.006 |
| Popis: | For sustainable pork production and maximum pig welfare, all health, welfare and productivity problems in the barn should be detected as early as possible. In this paper, an automated monitoring and warning system is proposed. Based on measurements of the feeding pattern, it is able to generate daily alerts for individual fattening pigs. Using historical data, the following types of warning systems were developed: (1) fixed limits that treat all pigs and all days equally; and (2) time-varying individual limits using the concept of Synergistic Control. These types of limits were constructed either for the number of registrations per pig or the average interval between feeding visits of a pig, leading to four warning systems in total. These warning systems were used to generate alerts during an online validation period. During an entire fattening period, all pigs were individually monitored to establish true alerts, false alerts and missed problems. The best performance was achieved for the Synergistic Control method on the number of registrations, with a sensitivity of 58.0%, specificity of 98.7%, accuracy of 96.7% and precision of 71.1%. Severe problems were detected on average within 1.3 days from the start of the problem. These are promising results that provide a solid basis for the development of a system for individual pigs but further improvements are warranted to make the system more practical. ispartof: BIOSYSTEMS ENGINEERING vol:173 pages:143-156 status: published |
| Databáze: | OpenAIRE |
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