Abstract
The main objective of this paper is the monitoring of daily activity patterns of fattening pigs at different locations in the housing environment using UHF-RFID. Four hundred fattening pigs were equipped with UHF-RFID ear tags and monitored during the fattening period for about four months. The RFID antennas were installed at the feeding troughs, playing devices and drinkers. A validation phase for each of these locations was carried out prior to the first data collection. The sensitivity (true positive rate) of the UHF-RFID system was about 80% at the feeding trough and the playing device and about 60% at the drinkers. The mean of the daily visiting time of all pigs at the trough was about 55 min. The mean visiting duration at the playing device was about 38 min and at the drinkers about 9 min. The visiting times of the pigs showed a high intra- and inter-variability. It was observed that the average visit duration at the feeding trough decreases over the course of a fattening period but increases at the playing device. A documentation of visiting times of animals is possible utilizing RFID systems, allowing a higher data density than video or direct observations.
Highlights
The monitoring of individual animals has been growing in importance due to the rising level of interest in animal welfare
The combination of visit criteria selected for aggregation of the radio-frequency identification (RFID) raw data was a minimum duration of 1 s and a bout criterion of 60 s at the feeding trough, 0 s and 50 s at the drinkers and a minimum duration of 3 s with a 40 s bout criterion at the playing device
The sensitivity was over 80% at the trough and the playing device, and about 60% at the drinkers
Summary
The monitoring of individual animals has been growing in importance due to the rising level of interest in animal welfare. The transparency of production methods and product traceability has become more relevant on the consumer side. Research on the individual behavior of animals is very time-consuming and laborious in the conventional way of direct or video observation. An automatic system monitoring the relevant behavior of pigs at an individual level can lead to a higher data output in a shorter time and is interesting for many different topics. According to Ahmed et al [1], farm animals express a broad spectrum of behaviors, many of which may be impacted by their health and welfare conditions directly or indirectly. Berckmans [2] stated that continuous direct monitoring of animals can help farmers to control health and welfare issues, but only a few precision livestock farming tools have focused on the animals themselves
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