A correlated-variables model for monitoring individual growing-finishing pig's behavior by RFID registrations

Bruijn, B.G.C. de; Mol, R.M. de; Hogewerf, P.H.; Fels, Joachim

doi:10.1016/j.atech.2023.100189

Cited by 8 publications

(3 citation statements)

References 32 publications

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“…In this study, an IoT system was developed to monitor growth characteristics and physiological changes in individual geese in a non-invasive manner. The key element of the IoT system was the use of RFID technology, which is often aimed at large livestock, especially cows [28,29] and pigs [5,23,25,30]. However, research has already been conducted that focused on small livestock.…”

Section: Discussionmentioning

confidence: 99%

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Validation of an IoT System Using UHF RFID Technology for Goose Growth Monitoring

Černilová,

Linda,

Kuře

et al. 2023

Preprint

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Regular weight measurement is important in fattening geese to assess their health status. Failure to gain weight may indicate a potential illness. Standard weight gain analysis involves direct contact with the animal, which can cause stress to the animal, resulting in overall negative impacts on animal welfare. The focus of this study was to design a smart solution for monitoring weight changes in the breeding of farm animals. The proposed IoT system with a weighing device equipped with RFID technology for animal registration aimed to minimise the negative aspects associated with measuring in contact with humans. The designed system aims to incorporate modern approaches in animal husbandry and utilise the acquired data for the potential development of breeding approaches for various animal breeds. The system consisted of three main components: a data acquisition system, a weighing system with RFID, and an environmental monitoring system. In this study, the RFID system accuracy for detecting geese in the weighing system environment was assessed. The entire system evaluation yielded a sensitivity of 93.87%, specificity of 99.94%, accuracy of 99.85%, and precision of 95.09%. Regression analysis revealed a good correlation between observed feeding and RFID registrations with a determination coefficient of R2 = 0.9813.

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Section: Discussionmentioning

confidence: 99%

“…Using RFID technology, it is possible to monitor animal behaviour during feeding [23]. Brown-Brandl et al in 2018 and Maselyne et al in 2016 [5,24] found that the HF RFID system developed in their study could be used to measure the feeding patterns of growing pigs in a commercial or simulated commercial setting.…”

Section: Introductionmentioning

confidence: 99%

Validation of an IoT System Using UHF RFID Technology for Goose Growth Monitoring

Černilová,

Linda,

Kuře

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Using RFID technology, it is possible to monitor animal behavior during feeding [24]. Brown-Brandl et al in 2018 and Maselyne et al in 2016 [5,25] found that the HF RFID system developed in their study could be used to measure the feeding patterns of growing pigs in a commercial or simulated commercial setting.…”

Section: Introductionmentioning

confidence: 99%

Validation of an IoT System Using UHF RFID Technology for Goose Growth Monitoring

Černilová,

Linda,

Kuře

et al. 2023

Agriculture

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Regular weight measurement is important in fattening geese to assess their health status. Failure to gain weight may indicate a potential illness. Standard weight gain analysis involves direct contact with the animal, which can cause stress to the animal, resulting in overall negative impacts on animal welfare. The focus of this study was to design a smart solution for monitoring weight changes in the breeding of farm animals. The proposed IoT system with a weighing device equipped with RFID technology for animal registration aimed to minimize the negative aspects associated with measuring in contact with humans. The proposed system aims to incorporate modern approaches in animal husbandry and use these obtained data for the potential development of husbandry approaches for different breeds of animals and enhanced managerial decision-making within husbandry. The system consisted of three main components: a data acquisition system, a weighing system with RFID, and an environmental monitoring system. In this study, the RFID system accuracy for detecting geese in the weighing system environment was assessed. The entire system evaluation yielded a sensitivity of 95.13%, specificity of 99.89%, accuracy of 99.78%, and precision of 95.01%. Regression analysis revealed a good correlation between observed feeding and RFID registrations with a determination coefficient of R2 = 0.9813.

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Exploring individual responses to welfare issues in growing-finishing pig feeding behaviour

Bus,

Boumans,

te Beest

et al. 2024

animal

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A correlated-variables model for monitoring individual growing-finishing pig's behavior by RFID registrations

Cited by 8 publications

References 32 publications

Validation of an IoT System Using UHF RFID Technology for Goose Growth Monitoring

Validation of an IoT System Using UHF RFID Technology for Goose Growth Monitoring

Validation of an IoT System Using UHF RFID Technology for Goose Growth Monitoring

Exploring individual responses to welfare issues in growing-finishing pig feeding behaviour

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