Lameness detection and scoring

TY - CHAP

T1 - Lameness detection and scoring

AU - Mesgaran, Sadjad Danesh

AU - Haladjian, Juan

AU - Nüske, Stefan

AU - Ledoux, Dorothée

AU - Humphries, David

AU - Munksgaard, Lene

AU - Veissier, Isabelle

PY - 2020

Y1 - 2020

N2 - Enting [1] concluded lameness, from an economic perspective, as the third most costly health disease, following mastitis and reproductive failure issues, in cattle units. Archer [2] estimated the incidence rate of lameness in the United Kingdom cattle herds roughly 50 cases/100 cows in a year; nevertheless, due to poor correlation between incidence rates and records of treatments in farms [3], the actual number seems to be higher. Surprisingly, the significance of lameness associated with cattle welfare, health and profitability of the unit has been greatly underestimated [4]. Recent works have shown a clear link between BCS and hook condition of cows with the development of lameness in these animals [5]. Lameness is a multifactorial and progressive issue where different detriments contribute to its development via complex interactions. Detection of lame cattle can be facilitated through description of the animals' gait characteristics in a numerical scaling system known as locomotion scoring [6]. The total number of visual (manual) locomotion scoring systems can reach up to 25, where differences lie mostly in the used scales, characterization of cows' gait, and posture [7]. Automated locomotion scoring tools would be a big advantage for regular monitoring of lameness in the herd. Three methods that are commonly engaged with automated systems are: kinetic, kinematic and indirect. The kinetic and kinematic approaches measure the forces, involved in locomotion, and time and distance of variables, associated to limb movement, respectively [8]. The indirect method simply exploits behavioral or production data as indicators for impaired locomotion. The automated tools/instruments that will be developed, based upon either of the aforementioned approaches, need to be validated with a ‘reference’ method. This usually is done by comparing with manual scoring; however, it is noteworthy that manual scoring systems have their own set of limitations [9].

AB - Enting [1] concluded lameness, from an economic perspective, as the third most costly health disease, following mastitis and reproductive failure issues, in cattle units. Archer [2] estimated the incidence rate of lameness in the United Kingdom cattle herds roughly 50 cases/100 cows in a year; nevertheless, due to poor correlation between incidence rates and records of treatments in farms [3], the actual number seems to be higher. Surprisingly, the significance of lameness associated with cattle welfare, health and profitability of the unit has been greatly underestimated [4]. Recent works have shown a clear link between BCS and hook condition of cows with the development of lameness in these animals [5]. Lameness is a multifactorial and progressive issue where different detriments contribute to its development via complex interactions. Detection of lame cattle can be facilitated through description of the animals' gait characteristics in a numerical scaling system known as locomotion scoring [6]. The total number of visual (manual) locomotion scoring systems can reach up to 25, where differences lie mostly in the used scales, characterization of cows' gait, and posture [7]. Automated locomotion scoring tools would be a big advantage for regular monitoring of lameness in the herd. Three methods that are commonly engaged with automated systems are: kinetic, kinematic and indirect. The kinetic and kinematic approaches measure the forces, involved in locomotion, and time and distance of variables, associated to limb movement, respectively [8]. The indirect method simply exploits behavioral or production data as indicators for impaired locomotion. The automated tools/instruments that will be developed, based upon either of the aforementioned approaches, need to be validated with a ‘reference’ method. This usually is done by comparing with manual scoring; however, it is noteworthy that manual scoring systems have their own set of limitations [9].

KW - gait and locomotion assessment

KW - motion sensors

U2 - 10.5680/mcpb018

DO - 10.5680/mcpb018

M3 - Book chapter

BT - Methods in cattle physiology and behaviour research

A2 - Mesgaran, Sadjad Danesh

A2 - Baumont, René

A2 - Munksgaard, Lene

A2 - Humphries, David

A2 - Kennedy, Emer

A2 - Dijkstra, Jan

A2 - Dewherst, Richard

A2 - Ferguson, Holly

A2 - Terré, Marta

A2 - Kuhla, Björn

PB - Publisso

CY - Dummerstorf

ER -