{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T10:50:48Z","timestamp":1785408648484,"version":"3.56.0"},"reference-count":28,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T00:00:00Z","timestamp":1782950400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100017640","name":"Aalborg Zoo","doi-asserted-by":"publisher","award":["A2-2024"],"award-info":[{"award-number":["A2-2024"]}],"id":[{"id":"10.13039\/501100017640","id-type":"DOI","asserted-by":"publisher"}]},{"award":["A2-2024"],"award-info":[{"award-number":["A2-2024"]}],"id":[{"id":"https:\/\/ror.org\/01j3tkf69","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/100020032","name":"15. Juni Fonden","doi-asserted-by":"crossref","award":["2020-0667"],"award-info":[{"award-number":["2020-0667"]}],"id":[{"id":"10.13039\/100020032","id-type":"DOI","asserted-by":"crossref"}]},{"award":["2020-0667"],"award-info":[{"award-number":["2020-0667"]}],"id":[{"id":"https:\/\/ror.org\/00vp82b55","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Animals"],"abstract":"<jats:p>Virtual fencing is increasingly used in grazing systems as a flexible alternative to physical fencing, yet detailed assessments of cattle behavior within such systems remain limited. This study investigates the use of collar-mounted tri-axial accelerometers combined with supervised machine learning to characterize cattle behavior in a virtual fencing system. Seven free-ranging Angus cattle were monitored using accelerometers mounted on a virtual fencing system, GNSS positioning, and virtual fence warning logs. A random forest classifier was developed and trained to identify key behaviors (grazing\/feeding, ruminating, lying, standing and locomotion) using features derived from tri-axial accelerometer data. The model achieved high classification performance for grazing\/feeding, ruminating, and lying (mean accuracy = 0.87, range = 0.83\u20130.90), enabling estimation of individual behavioral time budgets. Daily activity patterns were generally stable over time and across individuals. Spatial analyses revealed significant differences in behavior between areas near the virtual fence boundary and interior pasture locations, with increased grazing and reduced ruminating near the boundary, potentially reflecting spatial variation in habitat type or forage availability. In the virtual fencing system, cattle are equipped with collars that emit an auditory warning when they approach a virtual boundary, followed by a low-energy electrical impulse when the warning is ignored over a directional distance of 5\u201310 m. Event-based analyses showed no consistent short-term changes in either movement intensity and direction nor locomotion following auditory warning events, indicating that cattle habituated to the system did not exhibit uniform behavioral disturbance in response to warnings. These results suggest that accelerometer-based behavior classification can provide fine-scale, non-invasive insights into spatio-temporal cattle behavior in virtual fencing systems. The finding indicates that, in a habituated herd, virtual fencing was not associated with pronounced disruption to the measured behavioral patterns, while highlighting the potential of embedded sensor data for animal-based behavioral monitoring.<\/jats:p>","DOI":"10.3390\/ani16132022","type":"journal-article","created":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T10:04:44Z","timestamp":1782986684000},"page":"2022","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Behavior Classification of Cattle in a Virtual Fencing System Using Tri-Axial Accelerometers and Machine Learning"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-7282-8298","authenticated-orcid":false,"given":"Silje Marquardsen","family":"Lund","sequence":"first","affiliation":[{"name":"Department of Chemistry and Bioscience, Aalborg University, Frederik Bajers Vej 7H, 9220 Aalborg, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4644-8981","authenticated-orcid":false,"given":"Cino","family":"Pertoldi","sequence":"additional","affiliation":[{"name":"Department of Chemistry and Bioscience, Aalborg University, Frederik Bajers Vej 7H, 9220 Aalborg, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Frikke","sequence":"additional","affiliation":[{"name":"Nationalpark Vadehavet, Havnebyvej 154, 6792 R\u00f8m\u00f8, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Sonne","sequence":"additional","affiliation":[{"name":"Department of Ecoscience, Arctic Research Cluster (ARC), Aarhus University, Frederiksborgvej 399, 4000 Roskilde, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0084-9122","authenticated-orcid":false,"given":"Aage Kristian Olsen","family":"Alstrup","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, 8200 Aarhus, Denmark"},{"name":"Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 11, 8200 Aarhus, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"100429","DOI":"10.1016\/j.animal.2021.100429","article-title":"Review: Precision Livestock Farming technologies in pasture-based livestock systems","volume":"16","author":"Aquilani","year":"2022","journal-title":"Animal"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"776","DOI":"10.3390\/dairy3040053","article-title":"Mapping Welfare: Location Determining Techniques and Their Potential for Managing Cattle Welfare\u2014A Review","volume":"3","author":"Hofstra","year":"2022","journal-title":"Dairy"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Lund, S.M., Jacobsen, J.H., Nielsen, M.G., Friis, M.R., Nielsen, N.H., Mortensen, N.\u00d8., Skibsted, R.C., Aaser, M.F., Staahltoft, S.K., and Bruhn, D. (2024). Spatial Distribution and Hierarchical Behaviour of Cattle Using a Virtual Fence System. Animals, 14.","DOI":"10.3390\/ani14142121"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"100646","DOI":"10.1016\/j.atech.2024.100646","article-title":"In search of an optimal bio-logger epoch and device combination for quantifying activity budgets in free-ranging cattle","volume":"9","author":"Cunningham","year":"2024","journal-title":"Smart Agric. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"565","DOI":"10.3390\/ruminants4040040","article-title":"A Review of Animal-Based Welfare Indicators for Calves and Cattle","volume":"4","author":"Harris","year":"2024","journal-title":"Ruminants"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"7084","DOI":"10.3168\/jds.2020-19797","article-title":"Virtual fencing technology to intensively graze lactating dairy cattle. II: Effects on cow welfare and behavior","volume":"104","author":"Verdon","year":"2021","journal-title":"J. Dairy Sci."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Aaser, M.F., Staahltoft, S.K., Korsgaard, A.H., Trige-Esbensen, A., Alstrup, A.K.O., Sonne, C., Pertoldi, C., Bruhn, D., Frikke, J., and Linder, A.C. (2022). Is Virtual Fencing an Effective Way of Enclosing Cattle? Personality, Herd Behaviour and Welfare. Animals, 12.","DOI":"10.3390\/ani12070842"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Staahltoft, S.K., Aaser, M.F., Jensen, J.N.S., Zadran, I., S\u00f8rensen, E.B., Nielsen, A.E., Alstrup, A.K.O., Bruhn, D., Linder, A.C., and Sonne, C. (2023). The Effectiveness of Virtual Fencing of Bull Calves in a Holistic Grazing System. Animals, 13.","DOI":"10.3390\/ani13050917"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Aaser, M.F., Staahltoft, S.K., Andersen, M., Alstrup, A.K.O., Sonne, C., Bruhn, D., Frikke, J., and Pertoldi, C. (2024). Using Activity Measures and GNSS Data from a Virtual Fencing System to Assess Habitat Preference and Habitat Utilisation Patterns in Cattle. Animals, 14.","DOI":"10.20944\/preprints202404.0189.v1"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Sonne, C., Alstrup, A.K.O., Pertoldi, C., Frikke, J., Linder, A.C., and Styrishave, B. (2022). Cortisol in Manure from Cattle Enclosed with Nofence Virtual Fencing. Animals, 12.","DOI":"10.3390\/ani12213017"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3265","DOI":"10.3168\/jds.2012-6003","article-title":"Technical note: Evaluation of data loggers for measuring lying behavior in dairy calves","volume":"96","author":"Bonk","year":"2013","journal-title":"J. Dairy Sci."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Smid, A.-M.C., Weary, D.M., and Von Keyserlingk, M.A.G. (2020). The Influence of Different Types of Outdoor Access on Dairy Cattle Behavior. Front. Vet. Sci., 7.","DOI":"10.3389\/fvets.2020.00257"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Cabezas, J., Yubero, R., Visitaci\u00f3n, B., Navarro-Garc\u00eda, J., Algar, M.J., Cano, E.L., and Ortega, F. (2022). Analysis of Accelerometer and GPS Data for Cattle Behaviour Identification and Anomalous Events Detection. Entropy, 24.","DOI":"10.3390\/e24030336"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"106610","DOI":"10.1016\/j.compag.2021.106610","article-title":"Predicting livestock behaviour using accelerometers: A systematic review of processing techniques for ruminant behaviour prediction from raw accelerometer data","volume":"192","author":"Riaboff","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"106045.","DOI":"10.1016\/j.compag.2021.106045","article-title":"In-situ classification of cattle behavior using accelerometry data","volume":"183","author":"Arablouei","year":"2021","journal-title":"Comput. Electron. Agric."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.compag.2009.03.002","article-title":"Evaluation of three-dimensional accelerometers to monitor and classify behavior patterns in cattle","volume":"67","author":"Robert","year":"2009","journal-title":"Comput. Electron. Agric."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Versluijs, E., Niccolai, L.J., Spedener, M., Zimmermann, B., Hessle, A., Tofastrud, M., Devineau, O., and Evans, A.L. (2023). Classification of behaviors of free-ranging cattle using accelerometry signatures collected by virtual fence collars. Front. Anim. Sci., 4.","DOI":"10.3389\/fanim.2023.1083272"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Pavlovic, D., Davison, C., Hamilton, A., Marko, O., Atkinson, R., Michie, C., Crnojevi\u0107, V., Andonovic, I., Bellekens, X., and Tachtatzis, C. (2021). Classification of cattle behaviours using neck-mounted accelerometer-equipped collars and convolutional neural networks. Sensors, 21.","DOI":"10.3390\/s21124050"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1325","DOI":"10.1111\/2041-210X.12584","article-title":"BORIS: A free, versatile open-source event-logging software for video\/audio coding and live observations","volume":"7","author":"Friard","year":"2016","journal-title":"Methods Ecol. Evol."},{"key":"ref_20","unstructured":"Python Software Foundation (2025, October 09). Python, Available online: https:\/\/www.python.org\/."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_22","unstructured":"R Core Team (2026, January 28). R: A Language and Environment for Statistical Computing, Available online: https:\/\/www.R-project.org\/."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1686","DOI":"10.21105\/joss.01686","article-title":"Welcome to the Tidyverse","volume":"4","author":"Wickham","year":"2019","journal-title":"J. Open Source Softw."},{"key":"ref_24","unstructured":"Arnold, J.B. (2026, January 28). ggthemes: Extra Themes, Scales and Geoms for \u201cggplot2\u201d (p. 5.2.0) [Dataset]. Available online: https:\/\/cran.r-project.org\/web\/packages\/ggthemes\/index.html."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Pebesma, E., and Bivand, R. (2023). Spatial Data Science: With Applications in R, Chapman and Hall\/CRC. [1st ed.].","DOI":"10.1201\/9780429459016"},{"key":"ref_26","unstructured":"Ooms, J. (2026, January 28). jsonlite: A Simple and Robust JSON Parser and Generator for R (p. 2.0.0) [Dataset]. Available online: https:\/\/cran.r-project.org\/web\/packages\/jsonlite\/index.html."},{"key":"ref_27","unstructured":"Barrett, T., Dowle, M., Srinivasan, A., Gorecki, J., Chirico, M., Hocking, T., Schwendinger, B., and Krylov, I. (2026, January 28). data.table: Extension of \u2018data.frame\u2019 (p. 1.18.2.1) [Dataset]. Available online: https:\/\/cran.r-project.org\/web\/packages\/data.table\/index.html."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"173","DOI":"10.2307\/3895642","article-title":"Activities of Hereford and Santa Gertrudis cattle on a southern New Mexico range","volume":"19","author":"Herbel","year":"1966","journal-title":"J. Range Manag."}],"container-title":["Animals"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-2615\/16\/13\/2022\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T04:21:10Z","timestamp":1783138870000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-2615\/16\/13\/2022"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,2]]},"references-count":28,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2026,7]]}},"alternative-id":["ani16132022"],"URL":"https:\/\/doi.org\/10.3390\/ani16132022","relation":{},"ISSN":["2076-2615"],"issn-type":[{"value":"2076-2615","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,2]]}}}