Validation of the Ability of a 3D Pedometer to Accurately Determine the Number of Steps Taken by Dairy Cows When Housed in Tie-Stalls

Elise Shepley,Elsa Vasseur,Marianne Berthelot

doi:10.3390/agriculture7070053

Elise Shepley, Elsa Vasseur + Show 1 more

Open Access

https://doi.org/10.3390/agriculture7070053

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Journal: Agriculture	Publication Date: Jun 30, 2017
Citations: 13	License type: CC BY 4.0

Affiliation: McGill University, Institut Agro Rennes-Angers

Abstract

The automation of farm tasks in dairy production has been on the rise, with an increasing focus on technologies that measure aspects of animal welfare; however, such technologies are not often validated for use in tie-stall farms. The objectives of the current study were to (1) determine the ability of the IceTag 3D pedometer to accurately measure step data for cows in tie-stalls, and (2) determine whether the leg on which the pedometer is mounted impacts step data. Twenty randomly selected Holstein dairy cows were equipped with pedometers on each rear leg and recorded for 6 h over three 2-h periods. Two observers were trained to measure step activity and the total number of steps per minute were measured. Hourly averages for right and left leg data were analyzed separately using a multivariate mixed model to determine the correlation between pedometer and video step data as well as the correlation between left and right leg step data. The analysis of the video versus pedometer data yielded a high overall correlation for both the left (r = 0.93) and right (r = 0.95) legs. Additionally, there was good correlation between the left and right leg step data (r = 0.80). These results indicate that the IceTag 3D pedometers were accurate for calculating step activity in tie-stall housed dairy cows and can be mounted on either leg of a cow. This study confirms that these pedometers could be a useful automated tool in both a research and commercial setting to better address welfare issues in dairy cows housed in tie-stalls.

Highlights

IntroductionThe adoption of automation within the dairy industry has increased, changing how cows are milked (e.g., robotic milkers), fed (e.g., automatic feeding systems), and monitored (e.g., ear-, collar- or leg-mounted activity monitors)
In recent years, the adoption of automation within the dairy industry has increased, changing how cows are milked, fed, and monitored
This is true in the implementation of activity monitoring through pedometers

Summary

Introduction

The adoption of automation within the dairy industry has increased, changing how cows are milked (e.g., robotic milkers), fed (e.g., automatic feeding systems), and monitored (e.g., ear-, collar- or leg-mounted activity monitors). Lying time, assessed by activity monitors such as pedometers, is one of the most commonly used outcome measure of dairy cow welfare [1]. Measured by these devices, may have its own application in welfare monitoring, with regard to lameness detection [2]. Tie-stall housing, as a primary example, inhibits movement ability in dairy cows, restricting the physical and behavioral indicators that can be used by farmers to detect early signs of illness or monitor heat. This is true in the implementation of activity monitoring through pedometers. Step activity for various types of pedometer technologies have been previously validated, primarily targeting use in loose-housing [3]

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