Instrumentation & Measurement Magazine 23-6 - 32

Fig. 1. Hoof infected with white line disease.

world-wide incidence rates of lameness indicate that as many
as 60% of cows in a given herd may become lame at least once
in a year [4]. Estimated instances of lameness diagnosed in
New Zealand dairy farms are between 10% and 15% depending on the herd size and districts at any one time during the
year. Surveys based on cases treated by veterinarians show
that only around 25% of total cases of lameness are dealt with
by professionals directly. Farmers and stockpersons generally
deal with lameness incidences, so the rate of lameness is expected to be a lot greater than reported [4].

Current Identification Method, Accuracy and
Consistency
Traditionally, the identification of lame cattle has involved
passive observation, with the farmer noticing a cow walking slower and with irregular steps. This identification
method is very time consuming and labor intensive and is not

particularly efficient as it often results in a significant delay between the onset and detection of lameness. This problem has
been exacerbated by the introduction of milk shed automation
as the contact time between the farmer and the animal (during
which detection can occur) has become significantly reduced,
thus in large-sized herds it is difficult to identify lameness
using this traditional method. As the cost and frequency of
lameness will continue to increase into the future, this problem
will become worse, unless a more effective and efficient solution is found to detect cattle lameness.
Presently lameness is categorized using the Locomotion
Scoring (LS) System which is based on observing cattle walking, with the emphasis on head bob and stride length. The
scoring system in New Zealand ranges from 0 to 3 (shown in
Table 1), with 0 being normal and 3 being severely lame. This
method of visual scoring is very subjective and environmental conditions such as a sloped or muddy raceway can alter
the natural walking rhythm of the cattle, which leads to an incorrect score. Generally, trained large animal veterinarians
are employed to score an entire herd of cows, although many
farmers also know how to identify lame animals.
LS between trained individuals scoring the same cows displays a degree of variation. An experiment involving seven
experienced European observers viewing 58 video recordings
of cows was conducted. The distribution of healthy and lame
cows was approximately equal to represent the five-level European LS system. A cow with score 1 walks normally whereas
a cow with score 5 is an extremely lame cow. The observers
were asked to score all 58 cows on two different occasions, separated by four days or more. Within and between observer
agreement was investigated. Within observer agreement is the
percentage of all the cows that were given an identical score by
an individual observer on both occasions. Between observer
agreement is the percentage of cows given the same LS by all
seven observers [7]. It can be seen from Table 2 that both categories of observer agreement are less than conclusive. Within
observer agreement averaged 69.3% across the five levels and
between observer agreement averaged 55.3%. This makes
designing an automated system even more important, considering that each observer has a different perspective on separate
days. There is currently no clear and accurate numerical information that can be given to compare a healthy and abnormal
cow gait, which is less than ideal.

Table 1 - Locomotion Scoring Criteria [6]
Score

Description

0

Cow walks with a level back and long strides. Walks rapidly, confidently and shows no apparent signs of
lameness. The hind hoof lands in a similar location to the front hoof.

1

Cow shows no apparent signs of limping; however, the cow will take shorter strides and have a slightly arched
back.

2

Cow's head carried low or bobbing up and down; shows signs of obvious arched back and an obvious limp
which favors the affected limb(s).

3

Cow has a very noticeable arched back, difficulty turning; moves slowly and applies little or no weight to the
affected limb(s).

32	

IEEE Instrumentation & Measurement Magazine	

September 2020



Instrumentation & Measurement Magazine 23-6

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