{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T10:58:55Z","timestamp":1775473135972,"version":"3.50.1"},"reference-count":42,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers and Electronics in Agriculture"],"published-print":{"date-parts":[[2021,4]]},"DOI":"10.1016\/j.compag.2021.106080","type":"journal-article","created":{"date-parts":[[2021,3,5]],"date-time":"2021-03-05T15:54:02Z","timestamp":1614959642000},"page":"106080","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":27,"special_numbering":"C","title":["Horse foraging behavior detection using sound recognition techniques and artificial intelligence"],"prefix":"10.1016","volume":"183","author":[{"given":"Leon","family":"Nunes","sequence":"first","affiliation":[]},{"given":"Yiannis","family":"Ampatzidis","sequence":"additional","affiliation":[]},{"given":"Lucas","family":"Costa","sequence":"additional","affiliation":[]},{"given":"Marcelo","family":"Wallau","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.compag.2021.106080_b0005","doi-asserted-by":"crossref","first-page":"658","DOI":"10.2307\/3809192","article-title":"Towards an acoustic biotelemetry system for animal behavior studies","author":"Alkon","year":"1989","journal-title":"J. Wildl. Manage."},{"issue":"6","key":"10.1016\/j.compag.2021.106080_b0010","doi-asserted-by":"crossref","first-page":"1010","DOI":"10.3390\/su9061010","article-title":"iPathology: robotic applications and management of plants and plant diseases","volume":"9","author":"Ampatzidis","year":"2017","journal-title":"Sustainability"},{"issue":"July","key":"10.1016\/j.compag.2021.106080_b0015","article-title":"Agroview: cloud-based application to process, analyze and visualize UAV-collected data for precision agriculture applications utilizing artificial intelligence","volume":"174","author":"Ampatzidis","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2021.106080_b0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2019.104900","article-title":"Citrus rootstock evaluation utilizing UAV-based remote sensing and artificial intelligence","volume":"164","author":"Ampatzidis","year":"2019","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2021.106080_b0025","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.compag.2017.05.020","article-title":"Development of an open-source algorithm based on inertial measurement units (IMU) of a smartphone to detect cattle grass intake and ruminating behaviors","volume":"139","author":"Andriamandroso","year":"2017","journal-title":"Comput. Electron. Agric."},{"issue":"3","key":"10.1016\/j.compag.2021.106080_b9000","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1071\/AN14540","article-title":"Continuous bite monitoring: a method to assess the foraging dynamics of herbivores in natural grazing conditions","volume":"55","author":"Bonnet","year":"2015","journal-title":"Animal Prod. Sci."},{"key":"10.1016\/j.compag.2021.106080_b0035","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.compag.2014.06.010","article-title":"Evaluation of a new system for measuring feeding behavior of dairy cows","volume":"108","author":"B\u00fcchel","year":"2014","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2021.106080_b9005","doi-asserted-by":"crossref","first-page":"137","DOI":"10.17138\/TGFT(1)137-155","article-title":"Harry Stobbs Memorial Lecture : Can grazing behavior support innovations in grassland management?","volume":"1","author":"Carvalho","year":"2013","journal-title":"Trop. Grasslands"},{"key":"10.1016\/j.compag.2021.106080_b0040","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.compag.2017.12.013","article-title":"A pattern recognition approach for detecting and classifying jaw movements in grazing cattle","volume":"145","author":"Chelotti","year":"2018","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2021.106080_b0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105443","article-title":"An online method for estimating grazing and rumination bouts using acoustic signals in grazing cattle","volume":"173","author":"Chelotti","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2021.106080_b0050","unstructured":"Clapham, W.M., Abaye, A.O., Fedders, J.M., Yarber, E., 2006. Sound spectral analysis of grazing steers. In: Proceedings of the American Forage Grassland Conference, Vol. 15, pp. 139\u2013143."},{"issue":"1\u20132","key":"10.1016\/j.compag.2021.106080_b0055","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1007\/BF00317137","article-title":"Foraging in a landscape mosaic: selection for energy and minerals in free-ranging cattle","volume":"100","author":"de Vries","year":"1994","journal-title":"Oecologia"},{"issue":"2","key":"10.1016\/j.compag.2021.106080_b0060","doi-asserted-by":"crossref","first-page":"119","DOI":"10.2111\/1551-5028(2005)58<119:MSFSBC>2.0.CO;2","article-title":"Management strategies for sustainable beef cattle grazing on forested rangelands in the Pacific Northwest","volume":"58","author":"DelCurto","year":"2005","journal-title":"Rangeland Ecol. Manage."},{"key":"10.1016\/j.compag.2021.106080_b0065","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.compag.2017.04.024","article-title":"Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals","volume":"138","author":"Deniz","year":"2017","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2021.106080_b0075","doi-asserted-by":"crossref","unstructured":"Dutta, R., Smith, D., Rawnsley, R., Bishop-Hurley, G., Hills, J., 2014, November. Cattle behaviour classification using 3-axis collar sensor and multi-classifier pattern recognition. In: SENSORS, 2014 IEEE. IEEE, pp. 1272\u20131275.","DOI":"10.1109\/ICSENS.2014.6985242"},{"issue":"2","key":"10.1016\/j.compag.2021.106080_b0080","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1049\/ip-smt:19990100","article-title":"Prediction of health of dairy cattle from breath samples using neural network with parametric model of dynamic response of array of semiconducting gas sensors","volume":"146","author":"Gardner","year":"1999","journal-title":"IEE Proc.-Sci. Measur. Technol."},{"issue":"4","key":"10.1016\/j.compag.2021.106080_b9010","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1016\/S0168-1591(99)00014-3","article-title":"The effect of physiological state (lactating or dry) and sward surface height on grazing behaviour and intake by dairy cows","volume":"63","author":"Gibb","year":"1999","journal-title":"Appl. Animal Behav. Sci."},{"key":"10.1016\/j.compag.2021.106080_b0090","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.compind.2018.02.016","article-title":"Towards on-farm pig face recognition using convolutional neural networks","volume":"98","author":"Hansen","year":"2018","journal-title":"Comput. Ind."},{"issue":"8","key":"10.1016\/j.compag.2021.106080_b0095","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput."},{"key":"10.1016\/j.compag.2021.106080_b0100","unstructured":"Hochreiter, S., Bengio, Y., Frasconi, P., Schmidhuber, J., 2001. Gradient flow in recurrent nets: the difficulty of learning long-term dependencies."},{"issue":"5","key":"10.1016\/j.compag.2021.106080_b0105","article-title":"Recognition of individual dairy cattle based on convolutional neural networks","volume":"31","author":"Kaixuan","year":"2015","journal-title":"Trans. Chinese Soc. Agric. Eng."},{"issue":"5","key":"10.1016\/j.compag.2021.106080_b0110","doi-asserted-by":"crossref","first-page":"778","DOI":"10.1109\/LGRS.2017.2681128","article-title":"Deep learning classification of land cover and crop types using remote sensing data","volume":"14","author":"Kussul","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"1","key":"10.1016\/j.compag.2021.106080_b0115","doi-asserted-by":"crossref","first-page":"31","DOI":"10.2529\/PIERS081001110156","article-title":"Wireless sensor networks in agriculture: Cattle monitoring for farming industries","volume":"5","author":"Kwong","year":"2009","journal-title":"Piers Online"},{"key":"10.1016\/j.compag.2021.106080_b0120","unstructured":"Laca, E.A., Ortega, I.M., 1995, July. Integrating foraging mechanisms across spatial and temporal scales. In: International rangeland congress, Vol. 5, pp. 129\u2013132."},{"issue":"2","key":"10.1016\/j.compag.2021.106080_b0125","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1046\/j.1365-2494.2000.00203.x","article-title":"Acoustic measurement of intake and grazing behaviour of cattle","volume":"55","author":"Laca","year":"2000","journal-title":"Grass Forage Sci."},{"issue":"1","key":"10.1016\/j.compag.2021.106080_b0130","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/0168-1591(94)90011-6","article-title":"Mechanisms of handling time and intake rate of a large mammalian grazer","volume":"39","author":"Laca","year":"1994","journal-title":"Appl. Animal Behav. Sci."},{"issue":"7553","key":"10.1016\/j.compag.2021.106080_b0135","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"key":"10.1016\/j.compag.2021.106080_b0155","doi-asserted-by":"crossref","unstructured":"Nahid, M.M.H., Purkaystha, B., Islam, M.S., 2017, December. Bengali speech recognition: a double layered LSTM-RNN approach. In: 2017 20th International Conference of Computer and Information Technology (ICCIT). IEEE, pp. 1\u20136.","DOI":"10.1109\/ICCITECHN.2017.8281848"},{"key":"10.1016\/j.compag.2021.106080_b0160","unstructured":"Nunes, L., Ampatzidis, Y., Costa, L., Wallau, M., 2019. Horse foraging behavior detection using Recurrent Neural Networks. In: International Symposium on Artificial Intelligence and Mathematics, Fort Lauderdale, FL, January 6\u20138, 2020."},{"key":"10.1016\/j.compag.2021.106080_b9015","first-page":"60","article-title":"Automatic measurement of jaw movements in ruminants by means of a pressure sensor","volume":"2","author":"Nydegger","year":"2011","journal-title":"Recherche Agronomique Suisse"},{"key":"10.1016\/j.compag.2021.106080_b0165","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/j.compag.2018.12.048","article-title":"Development and evaluation of a low-cost and smart technology for precision weed management utilizing artificial intelligence","volume":"157","author":"Partel","year":"2019","journal-title":"Comput. Electron. Agric."},{"issue":"3\u20134","key":"10.1016\/j.compag.2021.106080_b0170","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/0168-1591(91)90008-L","article-title":"Patterns of ingestive behaviour of sheep continuously stocked on monocultures of ryegrass or white clover","volume":"31","author":"Penning","year":"1991","journal-title":"Appl. Animal Behav. Sci."},{"issue":"2","key":"10.1016\/j.compag.2021.106080_b0175","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1111\/j.1365-2494.1983.tb01626.x","article-title":"A technique to record automatically some aspects of grazing and ruminating behaviour in sheep","volume":"38","author":"Penning","year":"1983","journal-title":"Grass Forage Sci."},{"issue":"1","key":"10.1016\/j.compag.2021.106080_b0180","doi-asserted-by":"crossref","first-page":"86","DOI":"10.3758\/BF03200791","article-title":"Graze: a program to analyze recordings of the jaw movements of ruminants","volume":"32","author":"Rutter","year":"2000","journal-title":"Behav. Res. Methods, Instrum., Comput."},{"issue":"2\u20133","key":"10.1016\/j.compag.2021.106080_b0185","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/S0168-1591(96)01191-4","article-title":"An automatic system to record foraging behaviour in free-ranging ruminants","volume":"54","author":"Rutter","year":"1997","journal-title":"Appl. Animal Behav. Sci."},{"key":"10.1016\/j.compag.2021.106080_b0190","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.applanim.2015.11.005","article-title":"Validation of a pressure sensor-based system for measuring eating, rumination and drinking behaviour of dairy cattle","volume":"174","author":"Ruuska","year":"2016","journal-title":"Appl. Animal Behav. Sci."},{"key":"10.1016\/j.compag.2021.106080_b0195","doi-asserted-by":"crossref","DOI":"10.1016\/j.physd.2019.132306","article-title":"Fundamentals of recurrent neural network (RNN) and long short-term memory (LSTM) network","volume":"404","author":"Sherstinsky","year":"2020","journal-title":"Physica D: Nonlinear Phenomena"},{"issue":"3","key":"10.1016\/j.compag.2021.106080_b0210","doi-asserted-by":"crossref","first-page":"405","DOI":"10.4141\/A99-093","article-title":"Monitoring cattle behavior and pasture use with GPS and GIS","volume":"80","author":"Turner","year":"2000","journal-title":"Can. J. Anim. Sci."},{"key":"10.1016\/j.compag.2021.106080_b0215","unstructured":"Ungar, E.D., 1996. Ingestive behavior. In: Hodgson, J., Illius, A.W. (Eds.) The ecology and management of grassland systems. CAB International, Wallingford, UK, pp. 185\u2013218."},{"issue":"1\u20132","key":"10.1016\/j.compag.2021.106080_b0220","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.applanim.2005.08.011","article-title":"Classifying cattle jaw movements: comparing IGER behaviour recorder and acoustic techniques","volume":"98","author":"Ungar","year":"2006","journal-title":"Appl. Animal Behav. Sci."},{"issue":"3\u20134","key":"10.1016\/j.compag.2021.106080_b0225","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.applanim.2005.09.001","article-title":"The implications of compound chew\u2013bite jaw movements for bite rate in grazing cattle","volume":"98","author":"Ungar","year":"2006","journal-title":"Appl. Animal Behav. Sci."},{"key":"10.1016\/j.compag.2021.106080_b0235","series-title":"Proceedings of international conference of agricultural engineering CIGR-Ageng","first-page":"C0438","article-title":"July. Validation of a new health monitoring system (RumiWatch) for combined automatic measurement of rumination, feed intake, water intake and locomotion in dairy cows","author":"Zehner","year":"2012"}],"container-title":["Computers and Electronics in Agriculture"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0168169921000983?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0168169921000983?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T13:21:55Z","timestamp":1759152115000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0168169921000983"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4]]},"references-count":42,"alternative-id":["S0168169921000983"],"URL":"https:\/\/doi.org\/10.1016\/j.compag.2021.106080","relation":{},"ISSN":["0168-1699"],"issn-type":[{"value":"0168-1699","type":"print"}],"subject":[],"published":{"date-parts":[[2021,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Horse foraging behavior detection using sound recognition techniques and artificial intelligence","name":"articletitle","label":"Article Title"},{"value":"Computers and Electronics in Agriculture","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compag.2021.106080","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2021 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"106080"}}