Using the Herd Status Index to remotely assess the welfare status of dairy herds based on prerecorded data

The use of prerecorded data to remotely assess the herd welfare status is a promising approach to reduce the need for costly and time-consuming on-farm welfare assessments. Therefore, the objective of this study was to validate the Herd Status Index, an index developed based on Dairy Herd Improvemen...

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Main Authors: G.M. Dallago, N. Mauyenova, D. Warner, R.I. Cue, E. Vasseur
Format: Article
Language:English
Published: Elsevier 2022-10-01
Series:Animal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1751731122001987
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author G.M. Dallago
N. Mauyenova
D. Warner
R.I. Cue
E. Vasseur
author_facet G.M. Dallago
N. Mauyenova
D. Warner
R.I. Cue
E. Vasseur
author_sort G.M. Dallago
collection DOAJ
description The use of prerecorded data to remotely assess the herd welfare status is a promising approach to reduce the need for costly and time-consuming on-farm welfare assessments. Therefore, the objective of this study was to validate the Herd Status Index, an index developed based on Dairy Herd Improvement data from Canada, to remotely evaluate the welfare status of dairy herds. Herd-level prevalence of five animal-based welfare outcomes, measured once on 2 986 Quebec – Canada dairy herds between 2016 and 2019, were used to generate clusters with different welfare status using the algorithm partitioning around medoids. Dairy Herd Improvement data from 12 months prior to the welfare assessment were extracted and used to calculate the Herd Status Index. A linear model was used to carry out comparisons between clusters. Three stable clusters were found to best describe the data. Cluster two had the best overall welfare status since it had the lowest prevalence of all welfare issues while cluster three had the highest prevalence of most welfare issues, with the exception for the prevalence of neck lesions that was not different than cluster one. Cluster one had an overall intermediate welfare status. The Herd Status Index was higher (i.e., indicating a good welfare status) on cluster two compared to cluster three, but neither cluster three nor two differed to cluster one. In its current format, the Herd Status Index has a weak potential to identify herds with varying prevalence of welfare issues and it requires further improvements before it could be used to accurately assess the welfare status of the herds.
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spelling doaj.art-88ae91add29549fcadc90df64d38a3da2022-12-22T02:34:02ZengElsevierAnimal1751-73112022-10-011610100641Using the Herd Status Index to remotely assess the welfare status of dairy herds based on prerecorded dataG.M. Dallago0N. Mauyenova1D. Warner2R.I. Cue3E. Vasseur4Animal Science Department, McGill University, 21111 Lakeshore, Sainte-Anne-de-Bellevue, Quebec H9X 3V9, CanadaAnimal Science Department, McGill University, 21111 Lakeshore, Sainte-Anne-de-Bellevue, Quebec H9X 3V9, CanadaLactanet, 555 Boul. des Anciens-Combattants, Sainte-Anne-de-Bellevue, Quebec H9X 3R4, CanadaAnimal Science Department, McGill University, 21111 Lakeshore, Sainte-Anne-de-Bellevue, Quebec H9X 3V9, CanadaAnimal Science Department, McGill University, 21111 Lakeshore, Sainte-Anne-de-Bellevue, Quebec H9X 3V9, Canada; Corresponding author.The use of prerecorded data to remotely assess the herd welfare status is a promising approach to reduce the need for costly and time-consuming on-farm welfare assessments. Therefore, the objective of this study was to validate the Herd Status Index, an index developed based on Dairy Herd Improvement data from Canada, to remotely evaluate the welfare status of dairy herds. Herd-level prevalence of five animal-based welfare outcomes, measured once on 2 986 Quebec – Canada dairy herds between 2016 and 2019, were used to generate clusters with different welfare status using the algorithm partitioning around medoids. Dairy Herd Improvement data from 12 months prior to the welfare assessment were extracted and used to calculate the Herd Status Index. A linear model was used to carry out comparisons between clusters. Three stable clusters were found to best describe the data. Cluster two had the best overall welfare status since it had the lowest prevalence of all welfare issues while cluster three had the highest prevalence of most welfare issues, with the exception for the prevalence of neck lesions that was not different than cluster one. Cluster one had an overall intermediate welfare status. The Herd Status Index was higher (i.e., indicating a good welfare status) on cluster two compared to cluster three, but neither cluster three nor two differed to cluster one. In its current format, the Herd Status Index has a weak potential to identify herds with varying prevalence of welfare issues and it requires further improvements before it could be used to accurately assess the welfare status of the herds.http://www.sciencedirect.com/science/article/pii/S1751731122001987Cluster analysisDairy cowDairy herd improvement dataHerd managementPrecision dairy farming
spellingShingle G.M. Dallago
N. Mauyenova
D. Warner
R.I. Cue
E. Vasseur
Using the Herd Status Index to remotely assess the welfare status of dairy herds based on prerecorded data
Animal
Cluster analysis
Dairy cow
Dairy herd improvement data
Herd management
Precision dairy farming
title Using the Herd Status Index to remotely assess the welfare status of dairy herds based on prerecorded data
title_full Using the Herd Status Index to remotely assess the welfare status of dairy herds based on prerecorded data
title_fullStr Using the Herd Status Index to remotely assess the welfare status of dairy herds based on prerecorded data
title_full_unstemmed Using the Herd Status Index to remotely assess the welfare status of dairy herds based on prerecorded data
title_short Using the Herd Status Index to remotely assess the welfare status of dairy herds based on prerecorded data
title_sort using the herd status index to remotely assess the welfare status of dairy herds based on prerecorded data
topic Cluster analysis
Dairy cow
Dairy herd improvement data
Herd management
Precision dairy farming
url http://www.sciencedirect.com/science/article/pii/S1751731122001987
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