Best Practice Guide: Youngstock Management and Early Rearing
/in Best Practice Guide, Cattle, Colostrum and Early Feeding, Pigs, Poultry, Sheep /by Laura PalczynskiBest Practice Guide: Water Quality
/in Best Practice Guide, Cattle, Pigs, Poultry, Sheep, Water /by Laura PalczynskiBest Practice Guide: Potential of Breeding and Genetics for Robust and Resilient animals
/in Best Practice Guide, Breeding for Resilience, Cattle, Pigs, Poultry, Sheep /by Laura PalczynskiBest Practice Guide: Precision Livestock Technologies
/in (Data) Monitoring & surveillance, Best Practice Guide, Cattle, Pigs, Poultry, Precision Livestock Farming, Sensor Technology, Sheep /by Laura PalczynskiBest Practice Guide: Optimal Housing
/in Best Practice Guide, Cattle, Environment, Group Management, Housing and Welfare, Housing Systems, Pigs, Poultry, Sheep /by Laura PalczynskiBest Practice Guide: External biosecurity
/in Best Practice Guide, Biosecurity, Cattle, Pigs, Poultry, Sheep /by Laura PalczynskiBest Practice Guide: Internal Biosecurity
/in Best Practice Guide, Biosecurity, Cattle, Pigs, Poultry, Sheep /by Laura Palczynski398 -Technological tools for infection detection Case studies with the SOMO respiratory distress monitor in Belgian pig farms (Research paper – Cui – 2019)
/in Belgium, Database record, Pigs, Precision Livestock Farming, Research report/paper, Sensor Technology /by GeorgetaANGST
In Significant Impact Groups: Precision Livestock Farming & Early detection \ Sensor technology
Species targeted: Pigs;
Age: Not stated;
Summary:
In a demonstration project in Flanders (Belgium), the SOMO Respiratory Distress Monitor of SoundTalks, was installed in 10 commercial fattening pig houses showing an automatic alarm when respiratory problems occurred. The warnings of the SOMO-system were analysed against the observations of the farmer. In most cases (74%) the alert situation was confirmed by the farmers inspection, and in 17% of the cases farmers started a medical treatment based on the alerts. At the time of the alert the number of sick animals was still low and the behaviour (activity, feed intake) of the animals still normal in most cases (86%). It was confirmed by the farmers that the use of the SOMO system helped to reduce the amount of medication, because treatments were done in an early stage of infection.
Where to find the original material: http://www.eaplf.eu/wp-content/uploads/ECPLF_19_book.pdf; ISBN 978-1-84170-654-2
Country: BE
396 – Precision livestock farming for pigs (Research report – Vranken – 2017)
/in Belgium, Database record, Netherlands, Pigs, Precision Livestock Farming, Research report/paper, Sensor Technology /by GeorgetaANGST
396 Research report – Vranken – 2017 – Precision livestock farming for pigs
In Significant Impact Groups: Precision Livestock Farming & Early detection \ Sensor technology
Species targeted: Pigs;
Age: Not stated;
Summary:
In the precision livestock farming (PLF) concept, sensors and algorithms translate the measured animal responses into key indicators for optimal performance, improved animal welfare, and farm sustainability. The output of the sensors (e.g., activity measures with a camera or sound measures with a microphone) is related to animal-based welfare and health indicators such as aggression or respiratory diseases. When sensor signals start to deviate from their expected values, alerts are given to the farmer. In this way the farmer can take an immediate action before the detected change in animal response negatively affects the production performance. These actions range from solving technical problems such as a blocked feeding line, adjusting control settings in the climate and feed controller, etc. In most cases, a preventive medical treatment prevents the further spreading of respiratory diseases in the pen, and the use of antibiotics can be reduced or even precluded.
Where to find the original material: https://academic.oup.com/af/article/7/1/32/4638771; https://doi.org/10.2527/af.2017.0106
Country: BE; NL
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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 817591
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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 817591
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