Ghent University Academic Bibliography

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- Journal Article
- A1
- open access
Evaluating clinical mastitis in four dimensions : definition and correlation analysis of the production, somatic cell count, clinical and pathogen severity

Yifan Song, Lore D'Anvers, Martin Julius Gote, Katleen Geerinckx, Sofie Piepers (UGent) , Sarne De Vliegher (UGent) , Ines Adriaens and Ben Aernouts

(2026) PREVENTIVE VETERINARY MEDICINE. 246.
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- Journal Article
- A2
- open access
Consistent multi-animal pose estimation in cattle using dynamic Kalman filter based tracking

Maarten Perneel (UGent) , Ines Adriaens (UGent) , Ben Aernouts and Jan Verwaeren (UGent)

(2025) SMART AGRICULTURAL TECHNOLOGY. 11.
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- Journal Article
- A1
- open access
Dynamic multi-behaviour, orientation-invariant re-identification of Holstein-Friesian cattle

Maarten Perneel (UGent) , Ines Adriaens (UGent) , Jan Verwaeren (UGent) and Ben Aernouts

(2025) SENSORS. 25(10).
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- Journal Article
- A1
- open access
Periparturient oxidative and inflammatory status and their relation to energy metabolism and performance in transition dairy cows

Mingqi Zhang, Stijn Heirbaut (UGent) , Karolien Hertogs, Muluken Girma Mulat, Katleen Geerinckx, Els Stevens, Ben Aernouts, Nympha De Neve (UGent) and Veerle Fievez (UGent)

(2025) JOURNAL OF DAIRY SCIENCE. 108(12). p.13872-13889
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- Journal Article
- A1
- open access
Temporal and interanimal variation in bloodspot acylcarnitine and amino acid profiles in relation to conventional metabolites and hormones in Holstein dairy cows

Pius Lutakome (UGent) , Stijn Heirbaut (UGent) , Muluken Girma Mulat, Mingqi Zhang, Xiaoping Jing, Karolien Hertogs, Katleen Geerinckx (UGent) , Els Stevens, Ben Aernouts, Leen Vandaele, et al.

(2025) JOURNAL OF DAIRY SCIENCE. 108(5). p.5382-5404
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Key udder health parameters on dairy farms with an automated milking system

Lore D'Anvers, Ines Adriaens (UGent) , Igor Van Den Brulle, Dimitri Valckenier, Matthieu Salamone (UGent) , Sofie Piepers (UGent) , Sarne De Vliegher (UGent) and Ben Aernouts

(2024) LIVESTOCK SCIENCE. 287.
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Association between management practices and estimated mastitis incidence and milk losses on robotic dairy farms

Lore D’Anvers, Ines Adriaens (UGent) , Sofie Piepers (UGent) , Martin Julius Gote, Bart De Ketelaere and Ben Aernouts

(2023) PREVENTIVE VETERINARY MEDICINE. 220.
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Behaviour monitoring of dairy youngstock using pose estimation in video

Maarten Perneel (UGent) , Ines Adriaens, Jan Verwaeren (UGent) and Ben Aernouts

(2022) 4th Precision Livestock Farming PLF workshop seminar, Abstracts.
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- Conference Paper
- C3
Residual milk based on historic data, a new possibility to evaluate the transition succes

Matthieu Salamone (UGent) , Ines Adriaens, Geert Opsomer (UGent) , Stijn Heirbaut (UGent) , Veerle Fievez (UGent) , Miel Hostens (UGent) and Ben Aernouts

(2022) BuiatrIE-net congres 2022, Abstracts.
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Usage of video monitoring and machine learning to monitor dairy cow behaviour

Maarten Perneel (UGent) , Ben Aernouts, Ines Adriaens and Jan Verwaeren (UGent)

(2021) 3rd Precision Livestock Farming PLF workshop seminar, Abstracts.

Academic Bibliography

Evaluating clinical mastitis in four dimensions : definition and correlation analysis of the production, somatic cell count, clinical and pathogen severity

Consistent multi-animal pose estimation in cattle using dynamic Kalman filter based tracking

Dynamic multi-behaviour, orientation-invariant re-identification of Holstein-Friesian cattle

Periparturient oxidative and inflammatory status and their relation to energy metabolism and performance in transition dairy cows

Temporal and interanimal variation in bloodspot acylcarnitine and amino acid profiles in relation to conventional metabolites and hormones in Holstein dairy cows

Key udder health parameters on dairy farms with an automated milking system

Association between management practices and estimated mastitis incidence and milk losses on robotic dairy farms

Behaviour monitoring of dairy youngstock using pose estimation in video

Residual milk based on historic data, a new possibility to evaluate the transition succes

Usage of video monitoring and machine learning to monitor dairy cow behaviour

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