{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T19:01:02Z","timestamp":1792695662594,"version":"4.5.0"},"reference-count":61,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T00:00:00Z","timestamp":1731542400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003624","name":"Ministry of Agriculture, Food and Rural Affairs","doi-asserted-by":"publisher","award":["RS-2024-00402276"],"award-info":[{"award-number":["RS-2024-00402276"]}],"id":[{"id":"10.13039\/501100003624","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Animals"],"abstract":"<jats:p>The monitoring of pre-weaned calf behavior is crucial for ensuring health, welfare, and optimal growth. This study aimed to develop and validate a machine learning-based technique for the simultaneous monitoring of multiple behaviors in pre-weaned beef calves within a cow\u2013calf contact (CCC) system using collar-mounted sensors integrating accelerometers and gyroscopes. Three complementary models were developed to classify feeding-related behaviors (natural suckling, feeding, rumination, and others), postural states (lying and standing), and coughing events. Sensor data, including tri-axial acceleration and tri-axial angular velocity, along with video recordings, were collected from 78 beef calves across two farms. The LightGBM algorithm was employed for behavior classification, and model performance was evaluated using a confusion matrix, the area under the receiver operating characteristic curve (AUC-ROC), and Pearson\u2019s correlation coefficient (r). Model 1 achieved a high performance in recognizing natural suckling (accuracy: 99.10%; F1 score: 96.88%; AUC-ROC: 0.999; r: 0.997), rumination (accuracy: 97.36%; F1 score: 95.07%; AUC-ROC: 0.995; r: 0.990), and feeding (accuracy: 95.76%; F1 score: 91.89%; AUC-ROC: 0.990; r: 0.987). Model 2 exhibited an excellent classification of lying (accuracy: 97.98%; F1 score: 98.45%; AUC-ROC: 0.989; r: 0.982) and standing (accuracy: 97.98%; F1 score: 97.11%; AUC-ROC: 0.989; r: 0.983). Model 3 achieved a reasonable performance in recognizing coughing events (accuracy: 88.88%; F1 score: 78.61%; AUC-ROC: 0.942; r: 0.969). This study demonstrates the potential of machine learning and collar-mounted sensors for monitoring multiple behaviors in calves, providing a valuable tool for optimizing production management and early disease detection in the CCC system<\/jats:p>","DOI":"10.3390\/ani14223278","type":"journal-article","created":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T04:15:49Z","timestamp":1731557749000},"page":"3278","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Monitoring Multiple Behaviors in Beef Calves Raised in Cow\u2013Calf Contact Systems Using a Machine Learning Approach"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5490-6268","authenticated-orcid":false,"given":"Seong-Jin","family":"Kim","sequence":"first","affiliation":[{"name":"Asia Pacific Ruminant Institute, Icheon 17385, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2828-2359","authenticated-orcid":false,"given":"Xue-Cheng","family":"Jin","sequence":"additional","affiliation":[{"name":"Asia Pacific Ruminant Institute, Icheon 17385, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3751-6898","authenticated-orcid":false,"given":"Rajaraman","family":"Bharanidharan","sequence":"additional","affiliation":[{"name":"Department of Eco-Friendly Livestock Science, Institute of Green Bio Science and Technology, Seoul National University, Pyeongchang 25354, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2016-9714","authenticated-orcid":false,"given":"Na-Yeon","family":"Kim","sequence":"additional","affiliation":[{"name":"Asia Pacific Ruminant Institute, Icheon 17385, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7164","DOI":"10.3168\/jds.2022-22795","article-title":"Graduate Student Literature review: The problem of calf mortality on dairy farms","volume":"106","author":"Winder","year":"2023","journal-title":"J. Dairy Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"100150","DOI":"10.1016\/j.animal.2020.100150","article-title":"Feeding behaviour and activity as early indicators of disease in pre-weaned dairy calves","volume":"15","author":"Duthie","year":"2021","journal-title":"Animal"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.tvjl.2017.11.013","article-title":"Use of rumination and activity data as health status and performance indicators in beef cattle during the early fattening period","volume":"231","author":"Marchesini","year":"2018","journal-title":"Vet. J."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"100111","DOI":"10.1016\/j.vas.2020.100111","article-title":"Short Communication: Association between neonatal calf diarrhea and lying behaviors","volume":"9","author":"Swartz","year":"2020","journal-title":"Vet. Anim. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"8208","DOI":"10.3168\/jds.2017-14207","article-title":"Measurement of dairy calf behavior prior to onset of clinical disease and in response to disbudding using automated calf feeders and accelerometers","volume":"101","author":"Sutherland","year":"2018","journal-title":"J. Dairy Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1874","DOI":"10.3168\/jds.2019-16887","article-title":"Using behavior as an early predictor of sickness in veal calves","volume":"103","author":"Belaid","year":"2020","journal-title":"J. Dairy Sci."},{"key":"ref_7","unstructured":"Toaff-Rosenstein, R.L. (2016). The Sickness Response in Bovine Respiratory Disease, University of California."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"4014","DOI":"10.3168\/jds.S0022-0302(06)72445-6","article-title":"Calf Respiratory Disease and Pen Microenvironments in Naturally Ventilated Calf Barns in Winter","volume":"89","author":"Lago","year":"2006","journal-title":"J. Dairy Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"885","DOI":"10.3168\/jds.2015-9975","article-title":"Invited review: Transitioning from milk to solid feed in dairy heifers","volume":"99","author":"Khan","year":"2016","journal-title":"J. Dairy Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.applanim.2011.12.004","article-title":"Behaviour and welfare of veal calves fed different amounts of solid feed supplemented to a milk replacer ration adjusted for similar growth","volume":"136","author":"Webb","year":"2012","journal-title":"Appl. Anim. Behav. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Sun, D., Webb, L., van der Tol, P.P.J., and van Reenen, K. (2021). A Systematic Review of Automatic Health Monitoring in Calves: Glimpsing the Future From Current Practice. Front. Vet. Sci., 8.","DOI":"10.3389\/fvets.2021.761468"},{"key":"ref_12","first-page":"435","article-title":"Behavioral Fingerprinting: Acceleration Sensors for Identifying Changes in Livestock Health","volume":"5","author":"Fan","year":"2022","journal-title":"J"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3397","DOI":"10.3168\/jds.2009-2040","article-title":"Technical note: Quantifying and characterizing behavior in dairy calves using the IceTag automatic recording device","volume":"92","author":"Jensen","year":"2009","journal-title":"J. Dairy Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"743","DOI":"10.15232\/pas.2017-01623","article-title":"Evaluation of an ear-attached movement sensor to record rumination, eating, and activity behaviors in 1-month-old calves","volume":"33","author":"Hill","year":"2017","journal-title":"Prof. Anim. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"426","DOI":"10.3168\/jds.2010-3239","article-title":"Technical note: Evaluation of a system for monitoring rumination in heifers and calves","volume":"94","author":"Burfeind","year":"2011","journal-title":"J. Dairy Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.applanim.2018.01.012","article-title":"Validation of accelerometer use to measure suckling behaviour in Northern Australian beef calves","volume":"202","author":"Kour","year":"2018","journal-title":"Appl. Anim. Behav. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1203","DOI":"10.3168\/jds.2019-17885","article-title":"Symposium review: Precision technologies for dairy calves and management applications*","volume":"104","author":"Costa","year":"2021","journal-title":"J. Dairy Sci."},{"key":"ref_18","first-page":"177","article-title":"Brief Communication: The use of infrared thermography and feeding behaviour for early disease detection in New Zealand dairy calves","volume":"76","author":"Lowe","year":"2016","journal-title":"Proc. N. Z. Soc. Anim. Prod."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"9109","DOI":"10.3168\/jds.2016-11297","article-title":"Technical note: The use of an accelerometer for measuring step activity and lying behaviors in dairy calves","volume":"99","author":"Swartz","year":"2016","journal-title":"J. Dairy Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1017\/S0022029920000564","article-title":"Methodological terminology and definitions for research and discussion of cow-calf contact systems","volume":"87","author":"Sirovnik","year":"2020","journal-title":"J. Dairy Res."},{"key":"ref_21","unstructured":"Kack, M., Ziemerink, J., and Forster-Technik, G.N. (2010, January 2\u20135). Benefits, function and operation of computer-controlled calf feeders. Proceedings of the First North American Conference on Precision Dairy Management, Toronto, ON, Canada."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Whalin, L., Weary, D.M., and von Keyserlingk, M.A.G. (2021). Understanding Behavioural Development of Calves in Natural Settings to Inform Calf Management. Animals, 11.","DOI":"10.3390\/ani11082446"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"5765","DOI":"10.3168\/jds.2018-16021","article-title":"Invited review: A systematic review of the effects of prolonged cow\u2013calf contact on behavior, welfare, and productivity","volume":"102","author":"Meagher","year":"2019","journal-title":"J. Dairy Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.jrurstud.2022.11.013","article-title":"Animal welfare and cow-calf contact-farmers\u2019 attitudes, experiences and adoption barriers","volume":"97","author":"Hansen","year":"2023","journal-title":"J. Rural Stud."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"322","DOI":"10.5713\/ab.22.0135","article-title":"Dairy cow and calf behavior and productivity when maintained together on a pasture-based system","volume":"36","author":"Mac","year":"2023","journal-title":"Anim. Biosci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"100624","DOI":"10.1016\/j.animal.2022.100624","article-title":"Strategies for keeping dairy cows and calves together\u2014A cross-sectional survey study","volume":"16","author":"Eriksson","year":"2022","journal-title":"Animal"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"101","DOI":"10.3168\/jds.S0022-0302(97)75917-4","article-title":"Relationship between body condition scores and milk yield in a large dairy herd of high yielding Holstein cows","volume":"80","author":"Domecq","year":"1997","journal-title":"J. Dairy Sci."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Bailey, D.W., Trotter, M.G., Tobin, C., and Thomas, M.G. (2021). Opportunities to Apply Precision Livestock Management on Rangelands. Front. Sustain. Food Syst., 5.","DOI":"10.3389\/fsufs.2021.611915"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.applanim.2015.11.011","article-title":"Is rearing calves with the dam a feasible option for dairy farms?\u2014Current and future research","volume":"181","author":"Johnsen","year":"2016","journal-title":"Appl. Anim. Behav. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.anbehav.2016.12.005","article-title":"Applications of machine learning in animal behaviour studies","volume":"124","author":"Valletta","year":"2017","journal-title":"Anim. Behav."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1016\/j.rvsc.2017.10.005","article-title":"On the use of on-cow accelerometers for the classification of behaviours in dairy barns","volume":"125","author":"Benaissa","year":"2019","journal-title":"Res. Vet. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Balasso, P., Marchesini, G., Ughelini, N., Serva, L., and Andrighetto, I. (2021). Machine Learning to Detect Posture and Behavior in Dairy Cows: Information from an Accelerometer on the Animal\u2019s Left Flank. Animals, 11.","DOI":"10.3390\/ani11102972"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"5664","DOI":"10.3168\/jds.2016-11526","article-title":"Machine-learning-based calving prediction from activity, lying, and ruminating behaviors in dairy cattle","volume":"100","author":"Borchers","year":"2017","journal-title":"J. Dairy Sci."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Carslake, C., V\u00e1zquez-Diosdado, J.A., and Kaler, J. (2021). Machine Learning Algorithms to Classify and Quantify Multiple Behaviours in Dairy Calves Using a Sensor: Moving beyond Classification in Precision Livestock. Sensors, 21.","DOI":"10.3390\/s21010088"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1093\/ptj\/85.3.257","article-title":"The Kappa Statistic in Reliability Studies: Use, Interpretation, and Sample Size Requirements","volume":"85","author":"Sim","year":"2005","journal-title":"Phys. Ther."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"171442","DOI":"10.1098\/rsos.171442","article-title":"Evaluation of sampling frequency, window size and sensor position for classification of sheep behaviour","volume":"5","author":"Walton","year":"2018","journal-title":"R. Soc. Open Sci."},{"key":"ref_37","unstructured":"Palshikar, G. (2009, January 6\u20137). Simple algorithms for peak detection in time-series. Proceedings of the 1st International Conference on Advanced Data Analysis, Business Analytics and Intelligence, Ahmedabad, India."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1007\/s00779-010-0293-9","article-title":"Preprocessing techniques for context recognition from accelerometer data","volume":"14","author":"Figo","year":"2010","journal-title":"Pers. Ubiquitous Comput."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1090\/S0025-5718-1965-0178586-1","article-title":"An Algorithm for the Machine Calculation of Complex Fourier Series","volume":"19","author":"Cooley","year":"1965","journal-title":"Math. Comput."},{"key":"ref_40","unstructured":"Ke, G., Meng, Q., Finley, T., Wang, T., Chen, W., Ma, W., Ye, Q., and Liu, T.-Y. (2017, January 4\u20139). LightGBM: A Highly Efficient Gradient Boosting Decision Tree. Proceedings of the Neural Information Processing Systems, Long Beach, CA, USA."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","article-title":"SMOTE: Synthetic minority over-sampling technique","volume":"16","author":"Chawla","year":"2002","journal-title":"J. Artif. Intell. Res."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Akiba, T., Sano, S., Yanase, T., Ohta, T., and Koyama, M. (2019, January 4\u20138). Optuna: A Next-generation Hyperparameter Optimization Framework. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Anchorage, AK, USA.","DOI":"10.1145\/3292500.3330701"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1016\/S0031-3203(96)00142-2","article-title":"The use of the area under the ROC curve in the evaluation of machine learning algorithms","volume":"30","author":"Bradley","year":"1997","journal-title":"Pattern Recognit."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Schneidewind, S.J., Al Merestani, M.R., Schmidt, S., Schmidt, T., Th\u00f6ne-Reineke, C., and Wiegard, M. (2023). Rumination Detection in Sheep: A Systematic Review of Sensor-Based Approaches. Animals, 13.","DOI":"10.3390\/ani13243756"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"105630","DOI":"10.1016\/j.applanim.2022.105630","article-title":"Classifying the posture and activity of ewes and lambs using accelerometers and machine learning on a commercial flock","volume":"251","author":"Price","year":"2022","journal-title":"Appl. Anim. Behav. Sci."},{"key":"ref_46","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_47","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.compag.2017.04.009","article-title":"Automatic detection of suckling events in lamb through accelerometer data classification","volume":"138","year":"2017","journal-title":"Comput. Electron. Agric."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.cvfa.2007.01.002","article-title":"Early Weaning Beef Calves","volume":"23","author":"Rasby","year":"2007","journal-title":"Vet. Clin. N. Am.-Food Anim. Pract."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"4483","DOI":"10.1093\/jas\/sky337","article-title":"Technical Note: Development of a pressure sensor-based system for measuring rumination time in pre-weaned dairy calves1","volume":"96","author":"Eslamizad","year":"2018","journal-title":"J. Anim. Sci."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"6555","DOI":"10.3168\/jds.2018-15635","article-title":"Technical note: An evaluation of technology-recorded rumination and feeding behaviors in dairy heifers","volume":"102","author":"Reynolds","year":"2019","journal-title":"J. Dairy Sci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"10421","DOI":"10.3168\/jds.2018-14720","article-title":"Technical note: Evaluation of a triaxial accelerometer for monitoring selected behaviors in dairy calves","volume":"101","author":"Roland","year":"2018","journal-title":"J. Dairy Sci."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"106445","DOI":"10.1016\/j.smallrumres.2021.106445","article-title":"Evaluation of proper sensor position for classification of sheep behaviour through accelerometers","volume":"201","author":"Decandia","year":"2021","journal-title":"Small Rumin. Res."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Mansbridge, N., Mitsch, J., Bollard, N., Ellis, K., Miguel-Pacheco, G.G., Dottorini, T., and Kaler, J. (2018). Feature Selection and Comparison of Machine Learning Algorithms in Classification of Grazing and Rumination Behaviour in Sheep. Sensors, 18.","DOI":"10.3390\/s18103532"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"105027","DOI":"10.1016\/j.compag.2019.105027","article-title":"Behavior classification of goats using 9-axis multi sensors: The effect of imbalanced datasets on classification performance","volume":"166","author":"Sakai","year":"2019","journal-title":"Comput. Electron. Agric."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/S0749-0720(02)00004-X","article-title":"Biosecurity and bovine respiratory disease","volume":"18","author":"Callan","year":"2002","journal-title":"Vet. Clin. Food Anim. Pract."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"9273","DOI":"10.3168\/jds.2016-12280","article-title":"Short communication: Automated detection of behavioral changes from respiratory disease in pre-weaned calves","volume":"100","author":"Swartz","year":"2017","journal-title":"J. Dairy Sci."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Cantor, M.C., Casella, E., Silvestri, S., Renaud, D.L., and Costa, J.H.C. (2022). Using Machine Learning and Behavioral Patterns Observed by Automated Feeders and Accelerometers for the Early Indication of Clinical Bovine Respiratory Disease Status in Preweaned Dairy Calves. Front. Anim. Sci., 3.","DOI":"10.3389\/fanim.2022.852359"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.biosystemseng.2018.06.018","article-title":"Automatic cough detection for bovine respiratory disease in a calf house","volume":"173","author":"Carpentier","year":"2018","journal-title":"Biosyst. Eng."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.compag.2016.07.014","article-title":"Early recognition of bovine respiratory disease in calves using automated continuous monitoring of cough sounds","volume":"129","author":"Vandermeulen","year":"2016","journal-title":"Comput. Electron. Agric."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.ins.2013.07.007","article-title":"An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics","volume":"250","author":"Palade","year":"2013","journal-title":"Inf. Sci."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"9366","DOI":"10.3168\/jds.2023-23380","article-title":"Activity behaviors and relative changes in activity patterns recorded by precision technology were associated with diarrhea status in individually housed calves","volume":"106","author":"Renaud","year":"2023","journal-title":"J. Dairy Sci."}],"container-title":["Animals"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-2615\/14\/22\/3278\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:32:05Z","timestamp":1760113925000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-2615\/14\/22\/3278"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,14]]},"references-count":61,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2024,11]]}},"alternative-id":["ani14223278"],"URL":"https:\/\/doi.org\/10.3390\/ani14223278","relation":{},"ISSN":["2076-2615"],"issn-type":[{"value":"2076-2615","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,14]]}}}