An evaluation of a novel device for measuring eating, rumination, and inactive behaviors in lactating Holstein dairy cattle
Copyright © 2020. Published by Elsevier B.V..
Validation of precision dairy-monitoring technologies establishes technology behavioral-monitoring efficacy for research and commercial application. Technology metrics should be associated with behaviors of known physiological importance. The objective of this research project was to evaluate the Nedap SmartTag Neck (Nedap Livestock Management, Groenlo, the Netherlands) for dairy cow behavior measuring accuracy. The behaviors measured were eating, ruminating, and inactivity. Thirty-six lactating Holstein dairy cows were randomly selected from the University of Kentucky's Coldstream Dairy Research Herd and fitted with a Nedap SmartTag Neck. Cows were observed by a single observer for a total of 4 h per cow, including 2 h after the morning milking (0800 h) and 2 h after the evening milking (2000 h), from May to December 2017. The observer recorded the time behaviors occurred using a synchronized watch (CASIO, CASIO America, Inc., Dover, NJ, USA). The hour, minute, and second of the day each behavior occurred were compared with corresponding technology measurements. Pearson correlation coefficients (r; CORR procedure; SAS Institute Inc., Cary, NC, USA), concordance correlation coefficients (CCC; epiR package; R Foundation for Statistical Computing, Vienna, Austria), and Bland-Altman plots (epiR package; R Foundation for Statistical Computing) were used to determine association between visual observations and technology-recorded behaviors. Visually recorded eating, ruminating, and inactive time were moderately to strongly correlated with technology data (CCC ≥ 0.88) and Bland-Altman plots showed no bias, indicating a high level of agreement. In conclusion, the Nedap SmartTag Neck accurately monitored eating, ruminating, and inactivity behaviors and is expected to be effective in monitoring these behaviors in lactating dairy cattle in research or commercial farm settings.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2021 |
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Erschienen: |
2021 |
Enthalten in: |
Zur Gesamtaufnahme - volume:15 |
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Enthalten in: |
Animal : an international journal of animal bioscience - 15(2021), 1 vom: 02. Jan., Seite 100008 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Borchers, M R [VerfasserIn] |
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Links: |
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Themen: |
Accuracy |
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Anmerkungen: |
Date Completed 24.03.2021 Date Revised 24.03.2021 published: Print-Electronic Citation Status MEDLINE |
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doi: |
10.1016/j.animal.2020.100008 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM321339975 |
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520 | |a Copyright © 2020. Published by Elsevier B.V. | ||
520 | |a Validation of precision dairy-monitoring technologies establishes technology behavioral-monitoring efficacy for research and commercial application. Technology metrics should be associated with behaviors of known physiological importance. The objective of this research project was to evaluate the Nedap SmartTag Neck (Nedap Livestock Management, Groenlo, the Netherlands) for dairy cow behavior measuring accuracy. The behaviors measured were eating, ruminating, and inactivity. Thirty-six lactating Holstein dairy cows were randomly selected from the University of Kentucky's Coldstream Dairy Research Herd and fitted with a Nedap SmartTag Neck. Cows were observed by a single observer for a total of 4 h per cow, including 2 h after the morning milking (0800 h) and 2 h after the evening milking (2000 h), from May to December 2017. The observer recorded the time behaviors occurred using a synchronized watch (CASIO, CASIO America, Inc., Dover, NJ, USA). The hour, minute, and second of the day each behavior occurred were compared with corresponding technology measurements. Pearson correlation coefficients (r; CORR procedure; SAS Institute Inc., Cary, NC, USA), concordance correlation coefficients (CCC; epiR package; R Foundation for Statistical Computing, Vienna, Austria), and Bland-Altman plots (epiR package; R Foundation for Statistical Computing) were used to determine association between visual observations and technology-recorded behaviors. Visually recorded eating, ruminating, and inactive time were moderately to strongly correlated with technology data (CCC ≥ 0.88) and Bland-Altman plots showed no bias, indicating a high level of agreement. In conclusion, the Nedap SmartTag Neck accurately monitored eating, ruminating, and inactivity behaviors and is expected to be effective in monitoring these behaviors in lactating dairy cattle in research or commercial farm settings | ||
650 | 4 | |a Journal Article | |
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650 | 4 | |a Validation | |
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