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This is to certify that the
thesis entitled

THE USE OF INFRARED THERMOGRAPHY TO
DETERMINE THE SURFACE TEMPERATURE OF THE
CORONARY BAND OF DAIRY COWS AS A TOOL FOR

LAMENESS DETECTION

presented by

BETH MUNSELL

has been accepted towards fulﬁllment
of the requirements for the

Master of degree in Animal Science

 

 

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THE USE OF INFRARED THERMOGRAPHY TO DETERMINE SURFACE
TEMPERATURES OF THE CORONARY BAND OF DAIRY COWS AS A TOOL
FOR LAMENESS DETECTION

By

Beth Munsell

A THESIS
Submitted to
Michigan State University
In partial fulﬁllment of the requirements
for the degree of

MASTER OF SCIENCE
Department of Animal Science

2006

ABSTRACT

THE USE OF INFRARED THERMOGRAPHY TO DETERMINE SURFACE
TEMPERATURES OF THE CORONARY BAND REGION OF DAIRY COWS AS A
TOOL FOR LAMENESS DETECTION

By

Beth Munsell

Lameness is a major concern in the dairy industry because of its implications on
animal welfare and economics. Currently, locomotion scoring is the most common
method to detect lameness. However, this method is subjective, causing variability in
detected rates of lameness. The objective was to expand our knowledge of the use of
inﬁ'ared thermography (IRT) in dairy cattle and to assess its usefulness as an on-farm tool
for lameness detection. We hypothesize that IRT may be able to detect inﬂammation in
the coronary bad region that is associated with lameness earlier than locomotion scoring.
In Study 1, the rear limbs of 10 sound Holstein cows were imaged at different times of
the day and from different views of the hoof. In Study 2, 15 lame and 15 sound cows
were selected based on locomotion score and their rear limbs were imaged for 5 days
prior to and 5 days following hoof trimming. Results from both Study 1 and Study 2
indicate that for cows without hoof lesions, there is no signiﬁcant difference in surface
temperature between the left and right rear limbs. Also, in Study 2, results showed a
signiﬁcant difference in temperature between the left and right rear limb when only one
of these limbs was affected by hoof lesions. These results indicate that IRT may be a

useful tool to assess lameness in dairy cattle.

I dedicate this achievement to my family, who have always encouraged me to be the best,

but who have loved and supported me regardless.

iii

ACKNOWLEDGEMENTS

Throughout my Master’s studies, I have had the opportunity to work with an
incredible group of people who have helped me to grow both as a scientist and as a
person. I would like to thank my major professor, Dr. Adroaldo Zanella, for allowing me
to pursue my passion and for pushing me to be creative. Thanks also to my committee
members, Dr. Dave Beede for accepting nothing but my best, Dr. Joe Domecq for his
support and for keeping me focused on the dairy industry, Dr. Bill Epperson for his
patience and willingness to help and to Dr. Neil Wright for re-opening my eyes to the
world of physics and for his eagerness to learn about dairy cattle.

I need to thank the Animal Behavior and Welfare Group for providing me with
guidance and support both in my studies and in life. I am also thankful to Ashok
Ragavendran and the Statistical Consulting Center for their assistance with the statistical
analysis of this project. Also, thanks to everyone at the Michigan State University Dairy
Teaching and Research Center and at Green Meadow Farms and the MSU Training
Center for Dairy Professionals for their assistance while conducting research at their
facilities. I owe a lot to the faculty and staff of the Animal Science Department for
making me feel at home ever since I started in this department as an undergraduate.

Thanks to the Michigan Agricultural Experiment Station, the MSU Animal
Industry Coalition, Dr. Ted Ferris, and the CE Meadows Endowment for Dairy
Management for providing funding for this research.

I must also thank my close friends and family who provided me with distractions
when I needed to relax and who pushed me when I needed to succeed. Finally, thanks to

my family, for always providing me with extreme love and support.

iv

TABLE OF CONTENTS

List of Tables ........................................................................................ vi
List of Figures ...................................................................................... vii
Keys to Symbols or Abbreviations ............................................................... viii
Chapter One — Introduction ...................................................................... 01

Chapter Two - Review of Literature ............................................................ 03

Chapter Three - Use of Infrared Thermography to Determine Surface Temperatures of the

Coronary Band Region of Sound Dairy Cows .................................................. 29
Chapter Four - Using Infrared Thermography of the Coronary Band to Detect Hoof
Lesions in Dairy Cows ............................................................................ 42
Chapter Five — Discussion and Future Research Directions ................................... 59
Compiled References .............................................................................. 64

LIST OF TABLES

Chapter 2; Table 1: Examples of previous studies that have used infrared thermography
with livestock ....................................................................................... 12

Chapter 3; Table l: Locomotion scoring system as described by Sprecher et al., 1997.. 33

Chapter 3; Table 2: Maximum surface temperatures (MST) °C for and P values for the
left and right limbs at each image view ......................................................... 39

Chapter 4; Table 1: Locomotion scoring system as described by Sprecher et al., 1997.. 46

Chapter 4; Table 2: The cows selected as sound based on locomotion score (LS), the
number of limbs affected by lesions and the limb and claw where the lesions were
discovered (RRL = right rear lateral; RRM = right rear medial; RRLM = right rear lateral
and medial; LRL = left rear lateral; LRM = left rear medial; LRLM = left rear lateral and
medial; RFL = right front lateral; LF L = left front lateral) .................................... 51

Chapter 4; Table 3: Maximum surface temperature (MST) values, standard error of the
mean (SEM) and P values based on the least squares means for left and right limbs from
dorsal, lateral and plantar views in cows with only one hind limb affected by lesions over
the S-d pre-trimming ............................................................................... 53

Chapter 4; Table 4: Maximum surface temperature (MST) values, standard error of the
means (SEM), and P values based on the least squares means for left and right limbs
from dorsal, lateral and plantar views in cows with only one hind limb affected by lesions
over the S-d post-trimming ........................................................................ 55

vi

LIST OF FIGURES

Chapter 3; Figure 1: Infrared images of the dorsal, lateral, and plantar image views with
area of interest around the coronary band region ............................................... 35

Chapter 3; Figure 2: On the left, an infrared image of a non—lame limb of a Holstein cow.
On the right, a digital image of the same limb ................................................... 36

Chapter 3; Figure 3: The variance of the three views (plantar, dorsal and lateral) over
time ................................................................................................... 38

Chapter 4; Figure 1: Infrared images of the dorsal, lateral, and plantar image views with
area of interest around the coronary band region ............................................... 49

vii

KEYS TO SYMBOLS OR ABBREVIATIONS

AT - Temperature difference

,um - Micrometer

xl - Wavelength

BIC - Bayes

BRD - Bovine respiratory disease

BVD - Bovine viral diarrhea

cl - Constant of the value 3.743 x108 W - yin/m2
c2 - Constant of the value 1.4387 x104 m- K
cm - Centimeter

d - Day

lDFD - Dark ﬁrm and dry

DIM - Days in milk

a - Emissivity

exp - Exponent

E ,1 - Emissive power

E M, - Emissive power of a blackbody

h - Hour

IRT - Infrared thermography

K - Degrees Kelvin

LRL - Left front lateral claw

viii

LS - Locomotion score

LRL - Left rear lateral claws

LRLM - Left rear lateral and medial claws
LRM - Left rear medial claws

m - Meter

MBST - Mean body surface temperature
MST - Maximum surface temperature
PSE - Pale soft and exudative

SARA - Sub acute ruminal acidosis

SEM - Standard error of the mean

RFL - Right ﬁ'ont lateral claw

RRL - Right rear lateral claw

RRLM - Right rear lateral and medial claws
RRM - Right rear medial claw

T - Temperature

ix

CHAPTER ONE

Introduction

Lameness is a multi-factorial disease associated with an abnormal gait caused by
a cow’s attempt to alleviate pain (Scott, 1989; Kelton et al., 1998; Galindo and Broom,
2000). Lameness is also a major animal welfare concern (Hemsworth et al., 1995).
Based on results from trained observers, Kopcha et al. (2003) reported that 52% of a
sample of Michigan dairy cows were mild to severely lame. Lameness rates across the
US and the UK have been reported between 5% and 68.9% (Eddy and Scott, 1980; Wells
et al., 1993; Hedges, 2001; Cook, 2003). Greenough and Weaver (1997) estimated that
each case of lameness costs the producer between $300 and $400 for various reasons that
will be discussed further in Chapter 2.

The early detection of lameness and the lesions that cause lameness in cattle is
important to facilitate the relief of suffering (Whay, 2002). Currently, locomotion
scoring is the most common method used to quantify lameness. However, scoring
systems are subjective resulting in variability of the perceived incidence of lameness.
Using a technology-based approach to quantify lameness will decrease this variability
(Tasch and Rajkondawar, 2004) and may facilitate lameness detection earlier than
locomotion scoring. To date, force plates (Tasch and Rajkondawar, 2004) and pressure
plates (Scott, 1988; van der Tol et al., 2002, 2003; Alrneida et al., in press) have been
used to detect lameness. Other methods to detect lameness should be investigated.
Researchers recently have begun to investigate the use of infrared thermography (IRT) to

detect lameness in cattle (Schmidt et al., 2003; Whay et al., 2004; Haley et al., 2005;

Nikkah et al., 2005). Previous studies have provided evidence that IRT may be a useful
tool for lameness detection in dairy cattle. However, these studies have provided limited
results and conclusions on lameness detection on-farm. In addition, none of these studies
have reported baseline data of sound animals.

The main objective of the research reported herein was to expand our knowledge
of the use of IRT in dairy cattle and to assess the usefulness of IRT as an on-farm tool for
lameness detection. To answer this question we performed two studies. In the ﬁrst study
(Chapter 3), 10 sound, lactating Holstein cows were imaged at multiple times over a 2-d
period to give us an understanding of the normal thermal characteristics of healthy
animals. In the second experiment (Chapter 4), 15 sound and 15 lame cows were imaged
in order to determine the ability of IRT to detect lameness. We hypothesize that by
focusing on the coronary band region, IRT will be able to detect inﬂammation associated
with lameness in the distal limb(s) in dairy cattle. We anticipate that this technology may
be used to identify lameness at an earlier stage than by currently used methods and

protocols.

CHAPTER TWO

Review of Literature

Section 1: Review of Dairy Cattle Lameness Literature
1.1 Deﬁnition and Incidence of Lameness

There are multiple deﬁnitions for lameness in cattle. Kelton et a1. (1998) deﬁned
clinical lameness in cattle as an episode of abnormal gait attributable to either the foot or
leg, regardless of etiology or duration. Lameness also has been deﬁned as the abnormal
gait caused by painful lesions of the limbs or back as the cow attempts to alleviate or
avoid pain in the affected area (Scott, 1989) by reducing propulsion, reducing her speed
of walking, arching her back and lowering her head (Alrneida et al., in press). The
deﬁnition of clinical lameness in cattle is variable and these imprecise deﬁnitions may
cause misclassiﬁcations of lameness (Green et al., 2002).

Lameness is a major animal health and welfare concern within the dairy industry
that also has signiﬁcant economic effects (Nordlund et al., 2004). The term welfare
refers to the state of an individual as regards to its attempts to cope with its environment
(Broom, 1991). On a dairy farm, different factors can affect cow welfare and the
practical use of the term welfare applies to the comfort of the cow in the environment and
husbandry that is provided by the farmer. This includes housing, nutrition and the
manner in which farm workers treat the animals. Lameness may be affected by all of
these factors and therefore can serve as a means to measure the overall welfare of a dairy

herd (Hemsworth et al., 1995).

In a survey of a sample of Michigan dairy farms, Kopcha et al. (2003) reported
that 52% of 13,144 cows (about 4% of the total adult population in M1) were at least
mildly lame and 42% were moderately or severely lame as scored by trained observers.
Cook and Nordlund (2003) reported lameness rates ranging from 7.9 to 51.9% in
Wisconsin dairy herds with mean lameness of 24.8% in the winter and 21.8% in the
spring/summer. Wells et a1. (1993) reported slightly lower lameness incidence rates of
13.7 % in the summer and 16.7 % in the spring in Minnesota dairy herds. Overall, Cook
and Nordlund (2003) reported that 23% of US dairy cows are lame at any given time.
Estimates of lameness incidence in the UK have been reported between 5% (Eddy and
Scott, 1980) and 68.9% (Hedges et al., 2001). The lack of a standard deﬁnition of
clinical lameness in cattle discussed earlier may partially explain the high variability in

the reported incidence of clinical lameness (Green et al., 2002).

1.2 Impacts of Lameness

According to Greenough and Weaver (1997) the average cost associated with
each case of lameness is between $300 and $400. These losses may result from more
than one source. The most signiﬁcant costs of lameness come not from the treatment of
the problem itself, but from the aftereffects of the incident such as decreased milk
production (W amick et al., 2001; Green et al., 2002), longer calving intervals,
reproductive disorders (Hernandez et al., 2005; Sprecher et al., 1997), premature culling,
and reduced carcass weight at culling (Enting et al., 1997).

Wamick et a1. (2001) found that lame cows had reduced milk production

following treatment of the lameness. This particularly was evident in multi-parous cows

and cows with more severe cases of lameness. Reproductive disorders associated with
lameness are another key concern to dairy producers. Hernandez et a1. (2005) found that
cows classiﬁed as lame were 3.5 times more likely to have delayed ovarian cyclicity,
which can have detrimental effects on a cow’s reproductive cycle. Cows with more
severe cases of lameness are predicted to have a longer period of time from calving to
ﬁrst service and pregnancy, spend more time in the breeding herd and require more
services to become pregnant (Sprecher et al., 1997). These reproductive disorders likely
contribute to the decline in total lactation milk production because longer calving
intervals result in lower milk production in later lactation (Oltenacu et al., 1981).

Other losses due to lameness may include premature culling and decreased
carcass weight of cull cows (Enting et al., 1997). Sprecher et a1. (1997) reported that
lame cows are 8.4 times more likely to be culled from the herd. When cows must be
culled from the herd, economic losses result from missing income from the milk and
offspring that were not produced. Lame cows are also likely to have a decreased carcass
weight which will result in lower returns to the farmer when the animal is sent to

slaughter (Enting et al., 1997).

1.3 Causes of Lameness

In dairy cattle, lameness most readily occurs due to diseases of the foot (Clarkson
et al., 1996; Warnick et al., 2001). Shearer and Van Amstel (2000) reported that 90% or
more of lameness is associated with the foot and most of these cases occur in the rear
feet, particularly in the lateral claw. Lameness is ultimately a result of the cow’s genetics

or environment (Fatehi et al., 2003), however, the numerous factors associated with both

of these parameters makes identifying the speciﬁc cause of lameness problematic for
producers.

Both direct and indirect consequences of feet and leg problems can be reduced by
genetic selection (Fatehi et al., 2003). van der Waaij et al. (2005) reported that there is
evidence that susceptibility to a number of claw disorders is heritable. Boelling and
Pollott (1998) also reported correlations between genetic parameters and lameness, but
concluded that changes in body conformation and locomotion over the years need to be
taken into consideration for genetic selection. F atehi et al. (2003) also reported that the
effects of different environments and management practices had a more pronounced
effect on lameness than genetic parameters.

Environmental factors that affect lameness include management procedures as
well as housing systems and conditions. Proper feeding management and nutrition plans
are imperative for maintaining the health and vitality of a dairy herd. Both subacute
ruminal acidosis (SARA) and acute acidosis appear to be associated with laminitis
(N ocek, 1997; Stone, 2004; Vermunt, 2000). Rumen acidosis in cattle is caused by large
increases in the amount of lactic acid in the rumen, attributable to high carbohydrate, low
ﬁber diets (N ocek, 1997) as well as meal size and frequency (Owens et al., 1998). The
link between acidosis and laminitis appears to be associated with the release of
vasoactive substances during the decline in rumen pH, which ultimately destroy the
microvasculature of the corium and lead to lesions of the hoof (Nocek, 1997).

The cow’s housing environment effects both the spread of infectious diseases
associated with lameness, as well as the physical integrity of the hoof. When assessing

the housing environment of a dairy cow, a variety of factors need to be considered, such

as the type of housing system, bedding, ﬂooring, the cleanliness of the environment, and
the stocking density. The type of housing system can have a signiﬁcant impact on
lameness (Cook and Nordlund, 2003). Housing systems include free-stalls, tie-stalls,
group housing on straw packs or compost, and pasture based systems or a combination of
any of these systems. F ree-stall housing is the most common system implemented on
large scale dairy farms in the US. Cook and Nordlund (2003) found signiﬁcantly lower
incidence of lameness in herds using sand bedding in free-stalls when compared to other
types of stall surfaces, including rubber mats and rubber crumb ﬁlled mattresses. Design
of free-stalls also may have an effect on lameness. Gaworski et al. (2003) reported that
cows with access to larger stalls spent 70% more time standing with all four feet in their
stalls than those housed in smaller stalls. This increased time standing in the stall is
thought to be favorable as it decreases the amount of time the cows spend standing on
concrete which is a contributing factor to hoof injuries (Gaworski et al., 2003).

Rubber ﬂooring provides an alternative flooring surface to the commonly used
concrete. In a study looking at time budgeting of cows housed in barns with rubber
flooring in front of the feed bunk, F regonesi et al. (2004) concluded that cows ﬁnd rubber
ﬂooring more comfortable to stand on than concrete. Wilkes (2005) found that cows
housed in a ﬁ'ee-stall facility with rubber mat in front of the feed bunk had lower
lameness scores than cows housed in pens with concrete floors. However, Vokey et al.
(2001) concluded that the use of rubber ﬂooring had no effect on reducing the number of
claw lesions or clinical lameness.

It also is important that cows are provided with a clean and well-maintained

environment. Cook and Nordlund (2003) reported that cattle housed in wet conditions

with manure contamination are more likely to contract infectious foot diseases such as
interdigital necrobacillosis (foot rot), heel horn erosion and digital dermatitis (heel warts).
Keeping a clean environment also helps to reduce the risk of physical injuries to the hoof
by keeping ﬂoors clear of stones or other items which may cause bruising or puncture the
sole.

Stocking density is another factor to consider when assessing at the environment
of dairy cattle. Overstocking will lead to more manure production which could
contribute to the spread of infectious foot diseases (Cook and Nordlund, 2003). Also,
Cook et al. (2004) reported that overstocking could limit access to feed, which may cause
cows to eat larger, less frequent meals which could lead to ruminal acidosis.
Overstocking also has been shown to reduce laying times which is believed to be linked

with lameness (Friend et al., 1977; Gaworski et al., 2003).

1.4 Lameness Detection Methods

Traditionally, the herdsperson has detected lameness in cattle through observation
of the cow’s behavior. However, the subjectivity of this approach led researchers to
devise more objective methods of detection through lameness scoring systems. Manson
and Leaver (1988) published a lameness scoring system using a 9—point scale with scores
1 through 5 pertaining to animals that are not clinically lame. While this system has the
advantage of stressing the importance of detecting lameness early, the large point spread
makes the system complicated to learn and implement (Nordlund et al., 2004). Simpler,
more accessible systems using 4 and 5-point scales were developed by Wells et al.

(1993), Sprecher et al. (1997), Vokey et al. (2001) and Nordlund et al. (2004). The

system devised by Wells et al. (1993) uses a scale range from 0 to 4 while the Nordlund
et al. (2004) and Vokey et al. (2001) systems use a range from 1 to 4 with a score of 4
indicating a severely lame animal in all of these systems. Sprecher et a1. (1997) proposed
a l to 5 point scoring system based upon both gait and posture that has become a widely
used system in dairy research and herd management.

The variety of lameness scoring systems allows researchers to choose a system to
suit them best. However, because there is no set standard for locomotion scoring,
perception of lameness is variable. As reported earlier, trained observers determined that
52% of dairy cows in a sample of Michigan herds are at least mildly lame, while results
of a survey in the same study indicated Michigan dairy producers perceived the incidence
of lameness to be an average rate of 4.5% (Kopcha et al., 2003). This perceived low
incidence of lameness also was found in a recent survey conducted by Edgecomb et al.
(2006), which indicated that 53% of Michigan dairy producers perceived lameness
incidence rates to be less than 10% in their herds. These differences between perceived
and actual incidence of lameness may be accounted for by the subjectivity of locomotion
scoring, which often results in high inter-observer variability (Engel et al., 2003).

The use of a technology-based approach to lameness detection will help the dairy
industry to assess the realistic level of lameness prevalence on-farm (Tasch and
Rajkondawar, 2004). Changes in ground reaction force measured using force plates were
used as indicators of lameness in horses (Clayton et al., 2000) and cattle (Scott, 1989;
Tasch and Rajkondawar, 2004). Tasch and Rajkondawar (2004) recently developed a
mechanical approach to lameness detection which analyzes the ground force reaction of

each limb to assess how a cow is distributing her weight to determine if a cow is lame.

This technology is now commercially marketed by Bou-Matic as the StepMetn'x system.
This automatic system may prove to be a valuable and more standardized alternative to
existing scoring systems which are based on observation alone (Tasch and Rajkondawar,
2004)

Other studies have used pressure plate technology to assess weight distributions
within each claw (Scott, 1988; van der Tol et al., 2002, 2003; Almeida et al., in press).
Scott (1988) measured the pressure distribution of a cow while walking and found that
the hoof wall carried the most pressure. This ﬁnding was contradicted by van der Tol et
al. (2002) who found that the maximum pressure was exerted almost always in the sole of
the claws. van der Tol et al. (2003) also found that pressure is not distributed evenly
between claws in both the fore and hind limbs, with more pressure was being exerted on
the medial claw in the fore limbs and on the lateral in the hind limbs. Almeida et al. (in
press) used similar pressure plate technology to detect lameness in heifers with hairy heel
warts. In this study, peak vertical force was measured as Holstein heifers walked across a
pressure plate after assessment of locomotion based on the Sprecher et al. (1997) system.
The researchers concluded that gait abnormalities that were undetectable in locomotion
scoring were evident using a pressure plate. This research indicates the potential of using
a pressure plate to enhance lameness detection in cattle (Almeida et al., in press).

Lesions associated with lameness also may be assessed through tactile inspection
of the hoof by checking for soft soles or inﬂammation. However, hoof inspections are
typically carried out only after cows are showing obvious signs of lameness or during
routine hoof trimmings. By using IRT to assess surface temperatures of limbs, it may be

possible to identify inﬂammation at an early stage. Infrared thermography has previously

10

been used in several animal studies and because IRT is the main focus of the current

research, an in-depth review of this technology is presented in the next section.

Section 2: The Use of Infrared Thermography as a Diagnostic Tool for Livestock
2.1 Introduction

A growing number of animal science studies use infrared thermography (IRT) to
assess the distributions of surface temperatures in livestock. Variations in surface
temperature of mammals often indicate the presence of an underlying pathology (Cena
and Clark, 1973; Barnes, 1968), although surface temperatures also are inﬂuenced by the
environment. Early instruments used to detect surface temperature included mercury
thermometers and thermocouples; however, these methods require surface contact, which
may alter the temperature of the surface itself (Barnes, 1968; Stoll, 1964). IRT provides
a non-invasive, non-tactile method for determining surface temperature by measuring the
infrared radiation emitted by the object and converting it into a pictorial representation of
the surface temperature (Barnes, 1968).

Early ventures into the use of IRT in livestock applications yielded variable
results. A major limitation of these early studies was the need for subjects to remain still
for periods of up to 6 min while the scan was completed (Delahanty and Georgi, 1965).
Advances in technology have reduced the time needed for the scan to fractions of a
second, making thermography more feasible for use with live animals. Nonetheless, it is
important to recognize that IRT is limited to measuring only the surface temperature of
the skin or hair coat. Thus, IRT may only be useful in situations where this surface

temperature provides an accurate model for the condition of the underlying tissue.

11

IRT has been used to explore diagnostic issues, ranging from identiﬁcation of

pain and inﬂammation to the conﬁrmation of pregnancy, in several studies involving

horses, cattle, and swine (Table 1). These studies used IRT to investigate variations in

surface temperature as signs of unease, to diagnose ailments and to assess treatment

methods.

Table 1. Examples of previous studies that have used infrared thermography with

 

livestock.

Subject References

Horses
Surface Temperature Smith, 1964; Delahanty and Georgi, 1965; Palmer, 1981
Pain von Scwienitz, 1999

Inflammatory Process

Lameness

Drug Effects

Exercise Effects

Cattle
Surface Temperature

Infection

Branding
Reproduction

Lameness

Stress

Environmental Effects

Swine
Infection

Environmental Effects

Meat Quality

Purohit and McCoy, 1980

Purohit and McCoy, 1980; Denoix, 1994; Turner, 2001; Eddy et al., 2001;
Head, 2001

Van Hoogmoed and Snyder, 2002; Deumer et al., 1991; Harkins et al., 1996;
Holmes et al., 2003

Marlin et al., 1998

Berry et al., 2003

Lepper et al., 1974; Merkal et al., 1977; Spire et al., 1999; Schaefer et al.,
2004; Schaefer et al., 2005

Schwartzkopf-Genswein and Stookey, 1997

Purohit et al., 1985; Gabor et al.; 1998, Jones et al., 2005a ; Jones et al.,
2005b

Cockroft et al., 2000; Momcilovic et al., 2000; Schmidt et al., 2003; Whay et
al., 2004; Haley etal., 2005; Nikkah et al., 2005

Stewart et al., 2005

Knizkova et al., 2002

Loughmiller et al., 2001
Loughmiller et al., 2001
Gariepy et al., 1989

 

12

The objectives of this review are to: 1) describe the science and technology
underlying IRT, 2) discuss results of previous studies, and 3) explore future possibilities

for the diagnostic use of IRT with livestock.

2.2 Technical Overview and Considerations

Thermal radiation encompasses the portion of the electromagnetic spectrum
ranging in wavelength, ,1, from approximately 0.1 to 100 pm. This includes the visible
part of the spectrum (0.35 S ,1 S 0.75 pm) and the infrared region (0.75 S A S 100 ,um)
(Incropera and DeWitt, 2002). Infrared thermography cameras operate similarly to
standard digital cameras, except that they capture images by assessing wavelengths from
the infrared portion of the electromagnetic spectrum, usually from 3 to 14 ,um, depending
on equipment. Typical IRT systems are termed mid-wave (3 to 7 pm) or long-wave (8 to
14 pm), the difference being based on the detector material of the inﬁared camera used
(Kastberger and Stachl, 2003). Mid-wave cameras tend to have greater temperature
sensitivity, but require internal mechanisms to cool the detector.

The physical basis for IRT relies on the concept that all matter emits
electromagnetic radiation at power that is a function of the temperature of the matter.
This power is called the emissive power, E A, and for a perfect emitter (i.e., a blackbody

emitter) is described by Planck’s distribution

EN = flexpﬁci/AT]- lj, (I)

 

l3

where E u, is the emissive power of a blackbody, T is the temperature of the matter, and

c1 and c2 are constants with values of 3.743x108 W- #m/mzand 1.4387><104 ,um-K,
respectively. The spectral emissive power calculated using Equation 1 at 300 K (27 °C
or 81 °F) is illustrated as a ﬁrnction of wavelength in Figure 1. Each pixel of an IRT
detector measures the power emitted from a portion of a surface and within the range of
wavelengths corresponding to the sensitivity of the detector (e.g., 3 to 7 pm for a mid-
wave camera). Software then calculates the corresponding temperature viewed by each
pixel.

Real materials emit less power than is predicted by Equation 1. The ratio of the

emissive power of real matter (i.e., an animal), E A , to that of a blackbody emitter, E Lb ,

is the emissivity, £,which is deﬁned as:

a: 5%,“) (2)

Emissivity has a value between 0 and 1. Most electrically non-conducting materials have
values of 0.8 or greater, with human skin having a = 0.95 at 300 K (Incropera and
DeWitt, 2002). Figure 1 illustrates the estimated emissive power of a bovine surface with

a: 0.96 compared to that of a blackbody emitter at the same temperature.

14

 

 

 

 

 

    

Blackbody
3n _ — — -£= 0.96
E 25 _
E
3
j: 20 _
<1)
3
o
“a; 15 .
.5 Surface Temperature of 300 K,
.m
E 10 -
u.)
S ..

 

() l 1 lllllll I

0.1 I 10 100

,1 (Mn)
Figure l. Emissive power for a surface at 300 K (27 °C, approximately the surface

temperature of a cow) for a blackbody emitter and a surface with an emissivity of

0.96 (the estimated emissivity of a bovine surface).

In addition to being emitted from a surface, infrared radiation may be absorbed,
reﬂected, or transmitted in a manner similar to light at other wavelengths. (Eddy et al.,
2001; Purohit and McCoy, 1980). Because of these four properties, the infrared radiation
leaving a surface may be affected by environmental conditions. For example, water
vapor is transparent to the visible spectrum, but readily absorbs infrared radiation at some
wavelengths. Also, dust particles suspended in air may absorb, reﬂect, or emit radiation.

For practical applications of IRT, care must be taken to limit dust and humidity in the

15

atmosphere of the collection environment. Substantial amounts of either could alter the
signal from the animal to the detector, which would result in erroneous temperature
readings. Similarly, reﬂective surfaces and extraneous sources of substantial infrared
radiation, such as sunlight and radiant heat sources, must be avoided to reduce
measurement errors. Ideally, IRT measurements should be collected in a closed room
that is free of drafts, changing temperatures, and external light sources (Barnes, 1968).
Turner ( 1991) also has suggested that a draft-free and low-light area with an ambient
temperature less than 30 °C should be used when collecting thermal images of horses.
Even recent changes in environmental conditions may produce anomalous results. Cena
and Clark (1973) measured the temperature of zebras that had been standing in the sun
and found that the black stripes of the animal displayed maximum temperatures of 39 °C,
which were 9 °C warmer than the white stripes of the same animal. Similar differences
between light and dark surface areas also were measured in giraffes and penguins
exposed to sunlight.

In addition to the collection environment, the state of the surface itself plays an
important role in the accuracy of temperature measurements. For example, hair can
block infrared radiation, so that the image of an animal reveals the temperature of the
surface of the hair, rather than the temperature of the skin. Because hair is a thermal
insulator, its surface temperature may be substantially different than that of the
underlying skin. Turner (2001) suggests, however, that an accurate thermal image can be
produced as long as the hair is short and uniform in length. Any differences in hair
length should be taken into consideration when analyzing data. We do not anticipate hair

length to be a contributing factor when assessing the coronary band region in cattle as

16

hair in this area is generally short (< 2 cm) and uniform in length. Nevertheless, the most

accurate measurement of the skin surface temperature requires imaging the skin directly.

2.3 Livestock Production Applications
2. 3.1 Lameness

Lameness is associated with injury of the distal limb and may be caused by an
array of factors (Galindo et al., 2000). Many of the pathologies that cause lameness also
create inﬂammatory responses. IRT was used to study lameness and these inﬂammatory
responses in both cattle and horses. Smith (1964) and Delahanty and Georgi (1965)
studied both lame and sound horses using early IRT technology, which required the horse
to stand still for up to 6 min. Both studies found that IRT made it possible to detect
differences in temperature between lame and sound legs when the animal was properly
restrained. Delahanty and Georgi (1965) concluded that there were possible applications
for IRT in veterinary medicine and speculated that with advances in technology, these
possibilities would increase.

Several years later, Purohit and McCoy (1980) used IRT to examine the
inﬂammatory process by studying three groups of equids: clinically normal horses, those
with some sort of inﬂammatory disease, and normal ponies that were treated with an
inﬂammatory agent in the distal limb. Clinically normal horses of various ages and
breeds were imaged following 30 min of exercise to determine the normal thermal pattern
of a horse. When examining these normal horses, Purohit and McCoy (1980) found that
the coronary band was the warmest area in thermograms taken from the frontal view of

both the thoracic and pelvic limbs. In thermograms taken from the palrnar and plantar

17

views, the warmest area was between the bulbs of the heel. Eddy et al. (2001) concured
with this ﬁnding and reported that the coronary band and laminar corium just proximal to
the hoof were the warmest regions of the distal limb. The second group in the study by
Purohit and McCoy (1980) consisted of nine horses, each expressing different clinical
cases involving acute or chronic inﬂammatory conditions of the distal limb. One horse
with laminitis showed no signs of excessive temperature when examined clinically,
however, the thermograms showed a distinct change to the normal temperature pattern of
the hoof, thus indicating laminitis. Twenty—four h after the thermograms were taken,
laminitis was evident in clinical examinations. In the third group of sound ponies, the
researchers investigated the effects of anti-inﬂammatory drugs on surface temperature.
Thirteen Shetland ponies were injected with 1.25 ml of 1.9% iodine solution to create an
inﬂammatory response. The ponies were then split into four groups. Three of these
groups received different anti-inﬂammatory treatments (topical benzydamine HCL
ointment; IV injections of benzydamine HCL twice a day; IV injections of
phenylbutazone and a Poltis leg wrap), while the remaining group served as an untreated
control for the inﬂammatory agent. A decrease in inﬂammation was evident in thermal
images taken of all three groups treated with anti-inﬂammatory agents while continued
inﬂammation in the untreated inﬂammatory control group was evident in thermal images
for 4 to 8 d after the cessation of all clinical signs. The authors concluded that IRT could
aid detecting sites of early inﬂammation.

Turner (2001) reported that in cases of laminitis, IRT images of horses show a
change in the thermal pattern of the hoof wall. The coronary band of a horse is generally

1 to 2 °C warmer than the rest of the hoof. In cases of laminitis, however, the hoof

l8

begins to approach the temperature of the coronary band due to inﬂammation of the
laminar structures within the hoof. Thermography detects inﬂammation associated with
laminitis well before lameness is evident through traditional detection methods, allowing
preventive therapies to be applied before the laminitis becomes irreversible. Turner
(2001) suggested that inﬂammation in the area of the coronary band, however, may be
hard to detect as this area is the warmest area of the leg and therefore comparisons
between all four hooves (from front to front, rear to rear and rear to front) should be
made. A difference of more than 1 °C between any two of the four hooves was suggested
to be signiﬁcant with need for further examination.

Studies using IRT also have been conducted in cattle to assess hoof and limb
health. Whay et al. (2004) used IRT to verify lame limbs in cattle. They imaged the
lateral aspects of each limb of 50 dairy cows. In addition, each cow was locomotion
scored following imaging. The results showed that the temperature in the lame limbs was
increased and that the difference in temperature between the lame and sound limb
extended beyond the horn capsule into the proximal region of the limb. Schmidt et al.
(2003) also suggested that IRT may be useful for diagnosing lameness in cattle. They
found an association between lameness score and variations in claw temperature in cases
where pathologies of the claw were found. Another recent study used IRT to assess
temperatures of the coronary band of dairy cows in two stages of lactation: early to mid-
lactation, S 200 d in milk (DIM), or in late lactation, > 200 DIM (Nikkah et al., 2005).
The temperature difference, AT, between the coronary band and a control area just above
the coronary band was analyzed. Temperatures of the coronary band were found to be

higher in cows S 200 DIM than in the late lactation cows. Increased temperatures of the

19

coronary band and AT corresponded with an increased incidence of sole ulcers, but not to
incidences of underrun heels in the early to mid-lactation group. Nikkah et al. (2005)
concluded that measurement of hoof temperatures in early lactation cows may be useful
for monitoring hoof health.

Momcilovic et al. (2000) attempted to induce acidosis by feeding a higher energy
diet in an effort to cause laminitis in dairy calves and then used a digital infrared scanner
to measure the surface temperature of the hoof. This device measures only the surface
temperature of a small area rather than the entire distal limb as is possible with IRT.
Temperature readings were taken eight times during the 48-h period after feeding the
acidosis-inducing diet. Overall, hoof temperatures varied signiﬁcantly, but were
generally lower in the high energy group. Hooves inspected 3 mo after the acidosis
experiment indicated hoof damage may have begun during administration of the high
energy diet. In this case, the infrared scanning may have been done too soon to show any

signs of inﬂammation.

2.3.2 Reproduction

Infrared thermography also was used in reproductive studies of cattle. Purohit et
al. (1985) established the thermographic patterns of the scrotum of 15 normal bulls and
10 bulls with scrotal or testicular disease. Therrnograms of the normal bulls showed a
symmetrical and constant thermal pattern of the scrotum with a temperature difference of
4 to 6 °C between the base and the apex of the scrotum. In bulls where one testicle was
inﬂamed, differences in scrotal surface temperature were evident between the two sides.

Furthermore, in bulls with inﬂammation of both testicles, there was an overall increase in

20

surface temperature. The authors concluded that when semen cannot easily be collected
for quality evaluation, IRT may be a useful tool for evaluating testicular damage. Lunstra
and Coulter (1997) employed IRT to investigate the relationship between scrotal infrared
temperature patterns and natural-mating fertility in beef bulls. Temperature patterns were
recorded on 73 yearling bulls using IRT. For each therrnogram, the average scrotal
temperature, temperature at the base and apex of the scrotum, scrotal temperature
gradient and thermal class (normal, questionable or abnormal scrotal surface temperature
as determined by a subjective interpretation of each bull’s scrotal surface temperature)
were recorded. Half of the 73 bulls showed a normal thermal pattern whereas 20 (27%)
had a questionable thermal pattern and 16 (22%) had an abnormal pattern. The 16 bulls
showing an abnormal pattern also had lower percentages of sperm exhibiting normal head
and tail morphology, and higher percentages of sperm with proximal droplets than bulls
exhibiting normal or marginal thermal patterns. Furthermore, the impregnation rate was
lower for bulls with abnormal thermal patterns compared to those with normal or
marginal patterns. The data from this study indicate that bulls with abnormal thermal
patterns of the scrotum, as determined by IRT, had a reduced ability to maintain an
effective thermal gradient from top to bottom of the scrotum and had reduced fertilization
rates when used for natural mating. The conclusions of both studies support the
hypothesis that IRT can be useful when evaluating the reproductive soundness of bulls.
In reproductive studies of females, IRT has not been as effective as a diagnostic
tool. Jones et al. (2005a) used IRT to assess the pregnancy status of Holstein heifers.
Both the left and right sides (from shoulder to ﬂank) of pregnant heifers were imaged and

the right side images were more accurate predictors of pregnancy than the left side

21

images. However, researchers concluded that the ability to discriminate between
pregnant and non-pregnant heifers is questionable and greatly affected by ambient
temperature. In another study, Jones et al. (2005b) investigated the ability of IRT to
detect differences in vulva surface temperature of cows in estrus versus those not in
estrus. When comparing vulva surface temperatures of cows in estrus and in early
diestrus at an ambient temperature of 2 1 .4 °C, the researchers found no difference in
minimum temperatures and standard deviations, whereas the maximum temperature of
the vulva of a cow in estrus was higher than that of a cow in diestrus. No differences in
temperature were found between cows in late diestrus and the second estrus period. At
an ambient temperature of 12.1 °C no temperature differences were found between
groups of cows in estrus and cows in diestrus. It was unclear whether this magnitude of
temperature change is physiologically relevant for the detection of estrus. Furthermore,
ambient temperature greatly inﬂuenced the ability to discriminate between estrus and

diestrus.

2.3.3 Infection and Pain

Schaefer et al. (2004) used IRT to detect the progression of infection with bovine
viral diarrhea (BVD) in 15 calves. Ten of the calves were inoculated with Type 2 BVD
and housed separately from healthy control calves. The animals were not restrained at the
time of imaging and the technician took images from dorsal, lateral, distal, and selected
facial views. Blood samples and rectal temperatures also were collected to help
determine the progress of the infection. All inoculated animals responded to the infection

and the results showed significant changes in temperature at approximately 4 to 5 days

22

post inoculation during the 10-d collection period for many of the areas imaged. Images
taken of the orbital area were notable especially in the BVD-inoculated calves as they
were the most consistent and most sensitive to increases in temperature and were also the
earliest images to display temperature differences during the 10-d trial. Increases in
orbital temperature were significant as early as d 1, allowing early detection of infection.
In the control animals, there were some differences from day to day in the orbital
temperature, but these changes were sporadic and inconsistent. Clinical symptoms
occurred later than changes in the IRT images and were not evident in the inoculated
animals until 8 to 9 d post inoculation, reaching a peak at d 11. This study proved to be a
breakthrough in the possibilities of IRT as a means to detect infection earlier than through
observation of clinical signs, making earlier treatment possible. Schaefer et a1. (2005)
also used IRT images of the orbital area for early detection of bovine respiratory disease
(BRD), a costly heath afﬂiction in the cattle industry. Of the 13 weaned calves used in
the experiment, 11 were exposed in a herd known to be infected with BRD and two were
used as controls. Thermal data were collected through an automatic system which took
IRT images of the orbital area and these data were then analyzed to determine which
calves were showing an inﬂammatory response. The results from this study showed that
IRT may assist in the earlier detection of BRD. Stewart et al. (2005) have suggested,
however, that orbital temperatures in cattle may be affected by stress, which could be a
confounding factor for the previous studies.

Schwartzkopf-Genswein and Stookey (1997) used IRT to assess inﬂammation
associated with both hot-iron and freeze branding in cattle. Currently, these are two of

the most common methods used to make permanent marks on cattle, even though

23

temperature associated injuries are linked with pain (Provost, 1992). Thirty beef heifers
were used in this study, with 15 heifers in the freeze branding group and 15 heifers in the
hot-iron branding group. Two patches were shaved on the right thigh of each heifer the
day prior to the start of the experiment. The patch located on the upper part of the thigh
was the treatment site while the lower patch was designated as the control site. Infrared
images of the branding sites were collected starting at 5 min prior to branding and
continued at various intervals until 7 d post branding. The results of this study indicate
that while both the hot-iron and ﬁ'eeze branding methods caused an inﬂammatory
response, hot-iron branding caused a longer lasting response, thus suggesting that hot-
iron branding may cause more intense and prolonged pain than freeze branding.

Another study of cattle by Spire et al. (1999) used IRT to detect inﬂammation
associated with contaminated growth-promoting ear implants. Growth promotants
commonly are used in the beef industry to improve average daily gain of feeder steers
and heifers. If the implants are administered improperly, partial or complete interference
with absorption may occur. Thirty-two crossbred beef steers were used as the
experimental group with 16 steers implanted with a clean needle after scrubbing the ear.
The remaining 16 steers were implanted after the ear and implantation needle had been
contaminated with a mixture of fecal material and water. In each animal, the non-
implanted ear was used as an internal control. Thermal images were collected on d 0, 2,
4, 7, l4 and 21. Significant differences were evident between the temperature of the ears
with contaminated implants and control ears. Spire et a1. (1999) concluded that the use of
IRT is a non-invasive diagnostic tool that may be useful in feedlots to identify cattle with

ear abscesses caused by contaminated growth-promoting implants.

24

2.3. 4 Animal Environment and Stress

Infrared thermography is not only useful for identifying inﬂammation associated
with disease, but also is useful for evaluating animal environments and habitats.
Knizkova et al. (2002) used IRT to assess the thermal comfort of dairy cattle based on
body surface temperature. They considered both barn air temperature and velocity, and
the effects these had on dairy cow comfort. The results showed no changes in body
surface temperature when barn air temperature dropped by 3.1 °C, while still within the
cow’s thermoneutral zone. Conversely, when barn air temperature dropped by 6.5 °C
from 22.7 to 16.2 °C, changes in body surface temperature were evident. Moreover,
signiﬁcant changes in air velocity within the thermal neutral zone also caused changes in
body surface temperature. The results of this study not only indicate the importance of
ambient temperature on cow comfort, but also the importance of maintaining constant
temperature and air velocity in any environment used for thermal data collection.

The relationship between mean body surface temperature (MBST) and ambient
temperature was analyzed in clinically normal pigs and pigs inoculated with
Actinobacillus pleuropneumoniae, a bacteria that causes the respiratory disease porcine
pleuropneumonia (Loughmiller et al., 2001). First, Loughmiller et al. used four castrated
male pigs housed in a controlled temperature environment to determine the relationship
of ambient temperatures to MBST in normal pigs. Ambient temperatures were adjusted
to 10, 13, 16, 18, 21, 24, 27, 29 and 32 °C and each temperature was maintained for a
period of 60 minutes. The left side of each pig was then imaged 30 min after each

temperature had been reached. The results of this part of the study showed a positive

25

linear relationship between MBST and ambient temperature with a 0.4 °C increase in
mean body surface temperature with every 1 °C increase in ambient temperature. In a
second part of the study, 24 pigs were divided into inoculated and non-inoculated groups.
In this part of the study, the researchers concluded that a treatment by time interaction
was evident as a result of increased combined MBST and rectal temperature in febrile
pigs inoculated with Actinobacillus pleuropneumoniae as compared to the non-inoculated
(P < 0.001) and inoculated non-febrile pigs from 4.25 to 18 h after inoculation. The
results of this study indicate that the use of IRT in imaging broad areas (2 10 cm) in pigs
can detect accurately changes in the MBST temperature in pigs and may serve as a
useﬁal, non-invasive tool in identifying febrile pigs.

Animal stress is a concern not only from an animal welfare standpoint, but it also
has a signiﬁcant impact on the meat packing industry. In the pork processing industry,
IRT can be a useful tool to predict meat quality. Dark, ﬁrm and dry meat (DFD) and
pale, soft and exudative meat (PSE) are important quality issues in the pork industry and
both result from stressful situations. DFD is caused by long-term stress prior to slaughter
while PSE is caused by high levels of acute stress immediately prior to slaughter.
Gariepy et al. (1989) obtained IRT images of hogs immediately prior to electrical
stunning to determine the skin temperature of the animals before slaughter. All images
were taken from the dorsal View to include the entire hog. After arbitrary partitioning of
IRT data, some form of decreased meat quality was found in 71% of hogs exhibiting skin
temperatures higher than 32.2 °C. Handling, behavior, and genetics of the animals prior

to the study may have affected meat quality, but these data were not included in this

26

study. These results illustrate that IRT may be a useful tool for detecting pigs with the

potential to yield lower quality meat.

2.4 Future Possibilities of IRT Use for Livestock

New opportunities for research and production applications come with
technological advances and reduced costs of IRT. Newer, more sensitive thermographic
cameras help researchers to distinguish minute temperature differences, and the
decreasing cost of cameras will make this technology more affordable. Thermography
already is being used as a diagnostic tool by some veterinarians and has the possibility of
becoming an on-farm tool to help herd managers identify illness in animals. Future
research on lameness in dairy cattle could lead to on-farm scanning systems that could
detect lameness earlier than through the use of locomotion scoring. In the horse industry,
IRT may become available to barn managers to regularly scan animals for signs of injury.
Automatic IRT systems in feedlots may be able to identify sick animals before they
spread disease to the larger group of cattle. Meat packing plants could use IRT to scan
for sick or stressed animals upon their arrival. While the possibilities for IRT use in
livestock applications seem numerous, more research is needed to set standards and
protocols for collection and interpretation of data from different animal species.
Additionally, it will be important for researchers and industry alike to consider that IRT
does not provide a cure for these various maladies, but only serves as a tool to help
veterinarians and managers detect these illnesses and therefore IRT also may be used to

supplement research and practice directed towards diagnosing and curing illnesses.

27

Subsequent chapters will illustrate the use of previous research to assess the

possibility of using IRT as an on—farm tool to detect lameness in dairy cattle.

28

CHAPTER THREE
Use of Infrared Thermography to Determine Surface Temperatures of the

Coronary Band Region of Sound Dairy Cows

Abstract

Infrared thermography (IRT) creates a pictorial representation of the surface temperature
of an object. It has potential as a method to detect inﬂammation associated with
lameness. In this study, IRT was used to assess surface temperature near and at the
coronary band of the hind limbs of non-lame dairy cows. Ten visibly sound 2-yr-old
Holsteins less than 150 DIM were clinically examined for soundness. IRT images were
obtained six times per day (before and after each of two milkings and again 3 h after
milking) for two consecutive days to determine differences in surface temperature among
cows, at different image views, different measurement times, and between hind limbs of
the same cow. Three different image views of the coronary band were analyzed for both
hind limbs: dorsal, lateral and plantar aspects. Images were analyzed using ThermaCAM
Reporter 7.0 (F LIR Systems, Inc., Boston, MA). Average and maximum temperatures
were determined for an area approximately 2 cm above and below the coronary band.
Maximum temperatures were correlated with average temperatures (r = 0.826, P < 0.01)
and were used for all subsequent statistical analyses. A mixed model procedure was used
for statistical analysis with cow and the interaction of cow by side (leﬁ or right) as
random effects and time, view and side as ﬁxed effects. Image view was a signiﬁcant

factor (P < 0.05) with average maximum temperatures of 33.5, 31.9, and 31.5 °C for

29

dorsal, lateral and plantar views, respectively. Time of IRT measurement affected
temperatures (P < 0.05) with average maximum temperatures ranging from 30.5 to 33.0
°C for the six measurement times. There was also no interaction of side by View and no
difference in temperature between left and right limbs in the plantar view. These results
suggest that IRT data should be collected using a standardized protocol with a consistent
image view and time of day. Also, differences in temperature measured by IRT between
left and right limbs may be useﬁrl for detecting inﬂammation associated with lameness in

one limb.

1. Introduction

Infrared thermography (IRT) measures the radiant energy emitted by an object
and provides a non—invasive means of determining surface temperature (Barnes, 1968;
Head, 2001). In mammals, variations in surface temperature often indicate the presence
of some underlying pathology (Cena and Clark, 1973; Barnes, 1968). Thus far, IRT has
been used to detect inﬂammation associated with lameness in horses (Purohit and
McCoy, 1980; Denoix, 1994; Turner, 2001; Eddy et al., 2001) differences in surface
temperature of limbs in cattle (Cockroft et al., 2000; Momcilovic et al., 2000; Schmidt et
al., 2003; Whay et al., 2004; Haley et al., 2005, Nikkah et al., 2005), presence of
infection in cattle (Lepper et al., 1974; Merkal et al., 1977; Spire et al., 1999; Schaefer et
al., 2004; Schaefer et al., 2005), and to assess inﬂammation associated with branding of
cattle (Schwartzkopf-Genswein and Stookey, 1997).

Lameness in dairy cows has been shown to decrease milk production (W amick et

al., 2001) and increase the incidence of reproductive disorders (Hernandez et al., 2005,

30

Sprecher et al., 1997) which have a direct impact on the productivity and economic
output of the herd. Lameness is also a major animal welfare concern for dairy cattle
(Hemsworth et al., 1995) as it is associated with pain (Whay et al., 1998). Currently,
locomotion scoring is a common method used in research to detect lameness and
numerous scoring systems have been proposed (Manson and Leaver, 1988; Nordlund et
al., 2004; Wells et al., 1993; and Vokey et al., 2001). Locomotion scoring quantiﬁes
lameness by using a numerical scale to assign a score to a cow based on posture and gait
symmetry. A commonly used locomotion scoring system is the 5 point scale described
by Sprecher et al. (1997) which uses both gait and posture to determine lameness.

Locomotion scoring is helpful in determining the overall lameness prevalence of a
herd, however, scoring systems are subjective and perception of lameness is variable.
Results of a recent survey in Michigan reported that 53% of a sub sample of dairy herd
owners perceived lameness rates to be <10% in their herd (Edgecomb et al., 2006).
These results were similar to those found by Kopcha et al., (2003) who reported that a
sample of Michigan dairy producers perceived lameness to be at an average rate of 4.5%
in their herds. However, trained observers determined that in a sub sample of Michigan
dairy cows (approximately 4% of the total adult population) 52% showed mild to severe
lameness, suggesting that producers may not perceive the full extent of lameness in their
herds (Kopcha et al., 2003). In addition to low rates of detection by untrained observers,
the subjectivity of locomotion scoring often results in high inter-observer variability
(Engel et al., 2003).

Researchers currently are working to determine more objective methods to help

the dairy industry assess the true prevalence of lameness on-farm (Tasch and

31

Rajkondawar, 2004). Recent studies have shown evidence that the use of force plates
(Tasch and Rajkondawar, 2004) and pressure plates (Ahneida et al., in press) may be
useful to aid in the early detection of lameness. IRT is another technology being used in
research to assess lameness. Whay et al. (2004) reported a difference in temperature
between lame and sound limbs while Schmidt et al. (2003) found an association between
lameness score and claw temperature in animals where pathologies of the claw were
found. Further, Nikkah et al. (2005) assessed coronary band temperatures of cows in
different stages of lactation and determined that monitoring hoof temperature in early
lactation may be useful in detecting lameness.

While previous research with IRT has expanded our understanding of the
potential to use IRT to detect lameness, there has been no report of baseline data from
sound dairy cows. The objectives of this study were to examine the coronary band region
of sound Holstein cattle in order to determine the normal surface temperature pattern,
particularly in the coronary band region; to determine the least variable view for
collecting IRT images of the rear limb; and, to determine within day variation in the

surface temperature of the distal limb.

2. Materials and Methods
2.1 Animals

This study was conducted in May, 2005 at the Michigan State University Dairy
Cattle Teaching and Research Center in East Lansing. The experimental protocol was
reviewed and approved by the All University Committee on Animal Use and Care. Ten

visibly sound 2-yr-old Holsteins, less than 150 (1 into their ﬁrst lactation, were selected

32

for study. Each cow had a locomotion score of 1 based on the Sprecher et al. (1997)

system (Table 1). On the day prior to the onset of the study, all four hooves of each cow

were examined for any signs of lesions by a qualiﬁed veterinarian. During the exam,

cows were restrained in a hoof trimming chute and each foot was lifted and checked for

soft soles and obvious signs of inﬂammation of the hoof and joints. Hoofs were not

trimmed. Herd health records also were examined and cows with signs of poor health

were excluded.

Table 1. Locomotion scoring system as described by Sprecher et al., (1997).

 

 

Lameness Clinical
score Disposition Assessment Criteria
1 Normal The cow stands and walks with a level-back posture.
Her gait is normal.
2 Mildly The cow stands with a level-back posture but develops
Lame an arched back posture while walking. Her gait
remains normal.
3 Moderately An arched-back posture is evident both while standing
Lame and walking. Her gait is affected and is best described
as short-striding with one or more limbs
4 Lame An arched-back posture is always evident and gait is
best described as one deliberate step at a time. The
cow favors one or more limbs
5 Severely The cow additionally demonstrates an inability or
Lame extreme reluctance to bear weight on one or more of

her limbs or feet.

 

33

2.2 Housing and Management

Cows were housed in a 70-cow tie-stall barn with stall dimensions of 1.82 m x
1.32 m. Stalls were bedded with rubber crumb ﬁlled mattresses lightly covered with lye
and sawdust. Manure was removed from stalls every day during the two milking times,
with fresh sawdust being added to each stall at this time and fresh lye added to stalls once
a day with the sawdust. The barn had a ventilation system with air inlets and fans
controlled by thermostats. The diet consisted of a totally mixed ration (TMR) balanced
to meet NRC (1989) requirements for lactating cows; it was fed daily at 0900 h. Cows
were milked twice daily at 0200 h and 1400 h in a double-7 herringbone parlor. All
cows were in the same milking group and were released daily into a concrete ﬂoored,

outdoor exercise pen for 1 h prior to the 1400 h milking period.

2.3 IRT Data Collection

IRT images were collected for two consecutive days, six times a day with
collection times at 0130, 0430, 0800, 1130, 1445 and 1900 h. The 0130 and 1130 h
collection times were pre-milking, 0430 and 1445 h were post-milking, and 0800 and
1900 h were 3 h post-milking. All IRT data collection occurred while cows were
standing in their tie-stalls. Images were taken in a random, order for the pre-milking and
3 h post-milking collections. For the post-milking collection period, cows were imaged
based on the order that they came from the milking parlor. Images of both rear limbs
were taken from three different views, dorsal, lateral and plantar, from a distance of

approximately 1 m (Figure 1) measured by a string attached to the camera, which was

34

held up to the area being imaged. Images of the fore udder also were taken from as

distance of l m as a possible control measure.

 

Figure l. Inﬁ'ared images of the dorsal (A), lateral (B), and plantar (C) image views

with area of interest around the coronary band region.

Prior to imaging, all cows were made to stand and any manure was removed from
the stall. The rear distal limbs and fore udders were then brushed lightly to remove any
wood shavings or manure. Images were taken at least 10 s after brushing.

Images were taken using a FLIR P-65 infrared camera (FLIR Systems Inc., New
Billerica, MA). The sensitivity of the camera is 50 mK at 30 °C with a spectral range of
7.5 to 13 um and the accuracy of the camera is :1: 2 °C. After all data were collected, IRT
images were analyzed using ThermaCAM Reporter 7.0 (FLIR Systems, Inc., New
Billerica, MA) and were corrected for average ambient temperature during each
collection time and distance within the software. In each udder image, average and
maximum temperatures were reported from within a pre-set rectangle encompassing an
area of approximately 14 cm2 of the fore udder above the front teat on each side. In each
hoof image, the average and maximum temperatures were determined from within an
area approximately 2 cm above and 2 cm below the coronary band (Figure 2). We

assumed that the horn capsule likely serves as more of a natural insulator to the internal

35

temperature of the hoof than the skin of the coronary band and therefore may not
accurately express any inﬂammation within the horn. As the coronary band is a highly
vascularized area located directly above the horn capsule (Greenough, 1997), we
assumed that any inﬂammation occurring within the horn capsule will be expressed in the

coronary band.

38.0 'C

30

20

   

10.0
Figure 2. On the left, an infrared image of a non-lame limb of a Holstein cow. On the

right, a digital image of the same limb.

2.4 Additional Temperature Measurements

Ambient air temperature was recorded every 10 min during each collection time
over the 2-d period with a thermometer (WS-9014 U Wireless 433 MHz Temperature
Station, La Crosse Technology) suspended from the ceiling at a height of 2 m in the
center of the area in the barn where data were collected. Ambient temperatures within
the barn ranged from 11.4 to 20.9 °C during the collection times. Rectal temperatures
were taken immediately following IRT imaging of each cow using a digital probe type

thermometer (GLA M525/550, GLA Agricultural Electronics, San Luis Obispo, CA).

36

2. 5 Statistical Analysis

Data were analyzed using a mixed model procedure (PROC MD(ED, SAS version
9.1.3). Side (left or right limb), view of the limb, and day were modeled as ﬁxed effects
and cow was modeled as a random effect. To account for variability between the two
sides, cow by side interaction was modeled as a random effect. In addition, repeated
measures across time were accounted for by modeling time as a random effect with each
cow as a subject. The residual variation was partitioned as follows to examine the
variability due to view. A log-linear variance model was adopted with view and time as
effects contributing to dispersion effects.

02 (VIEW. TIME) =02 (error) exp {5 (.,*VIEW (i) +5 0)*Time 0)}
Residual and inﬂuence diagnostics (Schabenberger, 2004) were performed and we

determined that no single cow had a signiﬁcant effect on the conclusions of this analysis.

3. Results

Among the ﬁxed effects, view was highly signiﬁcant (P < 0.001) and side was
marginally signiﬁcant (P = 0.05 8). The signiﬁcance of side changed based on whether or
not side by cow was included in the model indicating that there is some effect of the
variability due to side on the response. As a general trend, the left side had a slightly
higher maximum temperature than the right side. There was no signiﬁcant interaction of
side and view, however, when analyzed individually, there was a difference (P = 0.026)
in temperature between left and right limbs in the dorsal view, a trend for a temperature
difference (P = 0.072) in the lateral view and no difference (P = 0.242) in the plantar

view (Table 2). There was a subject-speciﬁc trend of the variability of maximum surface

37

temperature across time within each cow. The Wald test for the coefﬁcients for view in
the log-linear model for the residual variation was signiﬁcant indicating heterogeneity of
variances among views (Figure 3). Furthermore, the Wald test for coefﬁcients of time
was also signiﬁcant, indicating that there was an effect of time on the variability
associated with view. Therefore, view may need to be controlled for when assessing
temperature. The tests were not signiﬁcant for times 0130 and 1900 h suggesting that in
this study, there was no effect of time on the variance heterogeneity of view at these

collection periods.

 

 

2.5 s ~ ~— +- A ~ A
2 g A -o:Plantar
- -I- -Lateral
:rﬂﬁ'-

 

 

Temperature Variability (SD) °C

073030 0430:,0 0330. 7730.,o L745." 7900.
. r677”? . OS ‘07 [7,008 - r677)” -. 03"”): 3,7 8
[0’79 ”‘7' "mi/Ia); [0"9 [“759 I‘m/”who

Collection Times

Figure 2. The variance of the three views (plantar, dorsal, and lateral) over time.

38

Table 2. Maximum surface temperatures (MST) °C and P values for the left and right

limbs at each image view.

 

 

MST MST MST

View Left Right P value Bothb
Dorsal 33.7 33.4 0.026 33.5
Lateral 32.0 31.8 0.072 31.9
Plantar 31.6 31.4 0.242 31.5
Overall3 32.4 32.2 0.055 32.3

 

a MST for left and right pooled across dorsal, lateral and plantar were different at P = 0.058.

b MST for dorsal, lateral, and plantar pooled across left and right were different (P < 0.001)

4. Discussion

The results from this study showed that there is variability in surface temperature
amongst sound cows. This variability may be in part due to natural circadian rhythms
such as those previously reported in core (Lefcourt et al., 1989), vaginal (Wrenn et al.,
1961; Araki et al., 1984, 1987) and rectal temperatures (Lefcourt et al., 1999).
Variability amongst cows may also be associated with environmental effects such as
ambient temperature and exercise. Berry et al. (2003) reported that mechanical brushing
caused a momentary cooling of udder surface temperature (< 10 5) due to removal of the
warm air layer trapped in the hair, however, surface temperature rapidly returned to
normal. We waited > 10 s after brushing before imaging cattle and therefore would not
anticipate any variability due to brushing. There were also differences in variability of
temperatures in each view over time. A noticeable rise in variability can be seen
following the ﬁrst post-milking collection time, particularly in the plantar view. This rise

in variability may be due to water splash or other foreign material on the limb coupled

39

with the lower ambient temperatures found in the morning as moisture on the limb will
cause evaporative cooling (Knizkova et al., 1996). Overall, the lateral view showed the
least variability across time and therefore provides the most reliable source of IRT
surface temperature data of the distal limb. However, if a cow has a lesion on the medial
claw, inﬂammation may not be evident in IRT images taken from the lateral view.
Therefore, it also may be important to assess images of the dorsal view to investigate for
lesions in both claws.

In addition, we found no effect of day in this study, however, data were only
collected over a 2-d period. Measurement time within each day was a signiﬁcant factor.
Our results indicated that the 0130 and 1900 h collection periods showed no effect of
time in this study. The variability due to time is likely affected by management practices
and uncontrollable environmental factors that will vary on different farms. This
variability also may be accounted for by the natural circadian rhythms of cattle as
mentioned previously. Therefore, even considering the lower variability encountered in
our study, we cannot conclude that 0130 and 1900 h are the best times to collect IRT data
in other farms. Nonetheless, we did see a noticeable rise in variability in the post milking
collection times, particularly in the plantar view, and we do suggest this is not the most
ideal time to collect IRT data.

Images were taken only on the rear hooves because these were most accessible.
In addition, Shearer and van Amstel (2000) reported that 90% of all lameness occurs in
the rear limbs. Our results revealed no interaction of side and view, thus suggesting no
difference in MST of the coronary band region between the left and right rear limbs at

each image view. However, upon ﬁthher analysis we found a difference (P = 0.026)

40

between temperatures of the left and right limbs in the dorsal view, a trend towards
difference (P = 0.072) in temperature between limbs in the lateral view, and no difference
(P = 0.242) between limbs in the plantar view. As there was no interaction of side by
view we may be able to account for these limited differences we observed between limbs
by applying a correction factor to account for the left limb generally being warmer than
the right limb. Overall, these results indicate that a cow may serve as a self control when
comparing images of the same view between limbs.
5. Conclusions

In conclusion, we determined that IRT images taken from the lateral view had the
least variability. Also, we found no interaction of side by view indicating no difference
in surface temperature between coronary band temperatures of the left and right limbs of
the same cow. These results suggest that a cow may serve as its own control to compare
images between left and right limbs at each image view. Therefore, we may be able to
identify inﬂammation associated with lameness when comparison between limbs reveals

a difference in surface temperature within cow.

41

CHAPTER FOUR
Using Infrared Thermography of the Coronary Band to Detect Hoof Lesions in

Dairy Cows

Abstract

Infrared thermography (IRT) creates a pictorial representation of the surface temperature
of an object. It has potential to detect inﬂammation associated with lameness. In the dairy
industry, lameness is a costly problem. Currently few methods are available for early
lameness detection. In this study, IRT was used to assess the surface temperature of the
coronary band region of the hind limbs of sound and lame dairy cows. On day l of the
11-day collection period, 30 multiparous Holstein cows less than 40 DIM were selected
based on their locomotion score: 15 sound (score = l) cows and 15 moderately lame
(score = 3) cows. IRT images of the dorsal, lateral and plantar aspects of both distal
limbs were collected once daily after the second of 3 milkings for 11 consecutive days.
Using the IRT images, average and maximum temperatures were identiﬁed from within
an area approximately 2 cm above to 2 cm below the coronary band. Maximum
temperatures were correlated with average temperatures (r = 0.88, P < 0.01) and were
used in all statistical analyses. On (1 6, claws of all cows were trimmed to identify
lesions. Sixteen cows had 1 or more lesions; 7 of which had been selected as sound and 9
of which had been selected as lame on d 1. Data were analyzed using a mixed model
procedure with view, limb, lesion, pre and post trimming as ﬁxed effects. Cow was a

random effect. Variability due to cow, view, and limb were modeled using appropriate

42

covariance structures. Cows with lesions had a higher maximum temperature of the
coronary band in the dorsal View than cows without lesions over the 5 days prior to
trimming. There was no signiﬁcant difference in maximum temperature between lesion
and non-lesion cows over the 5 days post trimming. These results suggest that IRT may

be useful to distinguish cows that have claw lesions.

1. Introduction

Lameness is a major concern for the dairy industry due to its impact on
proﬁtability and animal welfare (Greenough et al., 1997, Hemsworth et al., 1995).
Lameness in dairy cattle decreases milk production (Warnick et al., 2001) and increases
the incidence of reproductive disorders (Hernandez et al., 2005, Sprecher et al., 1997)
which have a direct impact on the productivity of the herd. Lameness most frequently
occurs soon after calving (Offer et al., 2000; Leonard et al., 1996) and is caused by a
multitude of factors (Galindo and Broom, 2000). In dairy cattle, lameness is most often a
result of diseases of the foot (Clarkson et al., 1996; Warnick et al., 2001) which are
associated commonly with laminitis (Nocek, 1997). Laminitis appears to be associated
with the release of vasoactive substances during the decline in ruminal pH that occurs
during acidosis, which ultimately destroys the microvasculature of the corium leading to
sole hemorrhaging and the formation of claw lesions (Nocek, 1997). Lesions often
mature in a predictable manner with an initial increase in vascular supply and tissue
permeability during acute inﬂammation (Trent and Redic-Kill, 1997).

Locomotion scoring is a common method used to detect and quantify lameness by

using a numerical system assigned to a cow based on posture and gait symmetry. Several

43

locomotion scoring systems have been proposed (Manson and Leaver, 1988; Wells et al.,
1993; Sprecher et al., 1997; Vokey et al., 2001; Nordlund et al., 2004). While
locomotion scoring is helpful in determining the overall hoof health of a herd, the
systems are subjective (Engel et al., 2002). Researchers are currently working to develop
more objective methods to assess lameness using more advanced technologies including
force plates (Tasch and Rajkondawar, 2004), pressure plates (Scott, 1988; van der Tol et
al., 2002, 2003, 2004; Ahneida et al., in press) and IRT (Whay et al., 2004; Schmidt et
al., 2003; Nikkah et al., 2005).

Infrared thermography non-invasively measures the radiant energy emitted by an
object to determine its surface temperature (Barnes, 1968; Head, 2001). It has been used
to assess inﬂammatory conditions in livestock in several studies (Purohit and McCoy,
1980; Spire etal., 1999; Loughmiller et al., 2001; Turner, 2001). Previously, IRT was
used to detect differences between lame and sound limbs in cows (Whay et al., 2004) and
to determine associations between lameness score and claw temperatures where
pathologies of the claw were present (Schmidt et al., 2003). Nikkah et al. (2005) found
that early lactation cows have a higher coronary band temperature which corresponded to
a more ﬁ'equent occurrence of sole hemorrhaging in this group. Together these studies
indicate that IRT may be a useful tool for lameness detection in cattle. However, none of
these previous studies have reported baseline data of sound cattle and results of surface
temperature data in lame cattle are limited.

Therefore, the objective of this study was to determine the ability of IRT to detect
lameness in dairy cows by comparing surface temperatures of the coronary band region

between lame and sound cows and cows with and without claw lesions.

44

2. Materials and Methods
2.] Animals

This study was conducted in September 2005 on a large commercial dairy farm in
central Michigan. The experimental protocol was reviewed and approved by the All
University Committee on Animal Use and Care. Thirty second and third lactation cows
less than 40 DIM were selected based on their locomotion score on d 1 of this ll-d study.
Fifteen sound (locomotion score = l) and 15 lame (locomotion score = 3) cows, were
selected based on the Sprecher et al. (1997) locomotion scoring system (Table 1). All
cows were locomotion scored daily by one of four different observers. Three of the
observers scored the cows on only one day each, while the remainder of the scoring was
completed by one person. Each observer watched a training video and completed at least
one session of on farm scoring with a trained observer before collecting data. Videos of
locomotion also were collected daily for each cow and a subset of videos were reviewed
by a veterinarian to conﬁrm locomotion scores. The hooves of all cows were trimmed on
d 6 and lesions were recorded and treated at this time. Health records also were

monitored throughout the study.

45

Table l. Locomotion scoring system as described by Sprecher et al., 1997.

 

 

Lameness Clinical
score Disposition Assessment Criteria
1 Normal The cow stands and walks with a level-back posture.
Her gait is normal.
2 Mildly The cow stands with a level-back posture but develops
Lame an arched back posture while walking. Her gait
remains normal.
3 Moderately An arched-back posture is evident both while standing
Lame and walking. Her gait is affected and is best described
as short-striding with one or more limbs
4 Lame An arched-back posture is always evident and gait is
best described as one deliberate step at a time. The
cow favors one or more limbs
5 Severely The cow additionally demonstrates an inability or
Lame extreme reluctance to bear weight on one or more of

her limbs/ feet.

 

2.2 Housing and Management

Cows were housed in a four-row free-stall facility with a center drive through
feeding lane, natural ventilation with side curtains, and an open peak. Free-stalls were
1.2 m wide by 2.2 m long and were bedded with sand, which was replenished weekly.
All ﬂooring surfaces in the barn were concrete except for the holding area behind the
milking parlor, which was a rubber mat surface. Concrete alleys were cleaned during
each milking time. All cows used in this study were kept in a pen of 175 cows with a
97% stocking rate. Cows were fed a totally mixed ration, consisting of 52% grain mix,

23% corn silage, 21% haylage, and 4% dry hay on an as-fed basis, twice a day. Cows

46

were milked three times a day at 0700, 1700, and 2300 h and all IRT images were

collected following the 1700 h milking.

2.3 Hoof T rimming

All cows had all four hooves trimmed on d 6 of the ll-d collection period. Hoof
trimming was performed by a trained hoof trimmer who regularly trims hooves on the
farm where this study was conducted. During trimming, lesions were assessed by the
hoof trimmer and were recorded by both the hoof trimmer and the researcher.
Photographs of the lesions also were taken at this time. In claws where lesions were
identiﬁed, therapeutic hoof trimming was performed according to standard farm
procedures; the damaged portion of the claw was removed and when severe lesions were
discovered, wooden blocks were attached to the sound claw to relieve pressure on the
damaged claw. All cows remained in the study after hoof trimming regardless of lesions

and treatments.

2.4 IRT Data Collection

Infrared images were collected once a day for 11 consecutive (1. Image collection
began at 1700 h following the second of three milkings and concluded at approximately
2100 h daily. Cows were sorted automatically from their milking group upon exiting the
parlor and their hind limbs imaged based on the order that they exited the parlor. All
cows had full access to water and hay after exiting the parlor and before imaging

commenced.

47

For IRT imaging, cows were restrained in a headlock chute used for veterinary
procedures on the farm. Images were taken from the dorsal, lateral, and plantar views of
both rear distal limbs as well as the both sides of the fore udder above the front teat. The
rear limbs and the udder were not cleaned of any foreign material for IRT imaging. All
images were taken from a distance of 1 m measured by a string attached to the camera
which was held up to the area being imaged.

Images were taken using a FLIR P-65 infrared camera (FLIR Systems Inc., New
Billerica, MA). The sensitivity of the camera is 50 mK at 30 °C with a spectral range of
7.5 to 13 um and the accuracy of the camera is i 2 °C. IRT images were analyzed using
ThermaCAM Reporter 7.0 (F LIR Systems, Inc., New Billerica, MA) and were corrected
for average ambient temperature during each collection time and distance within the
software. In each udder image, average and maximum temperatures (MST) were
reported from within a pre-set rectangle within ThermaCAM Reporter 7.0 encompassing
an area approximately 14 cm2 of the fore udder above the front teat on each side. In each
hoof image, the average and MST were determined from within an area approximately 2
cm above and 2 cm below the coronary band (Figure 1). Average and MST from within
the speciﬁed area of the coronary band and the fore udder were correlated highly (r =

0.879, P < 0.001) and MST was used for statistical analysis.

48

 

Figure 1. Infrared images of the dorsal (A), lateral (B), and plantar (C) image views

with area of interest around the coronary band region.

2.5 Additional Temperature Measurements

Barn temperature and relative humidity were measured using a HOBO® H8 Data
Logger (Onset Computer Corp., Boume, MA) afﬁxed to the headlock chute used for data
collection at a height of approximately 2 111. Temperature and humidity were recorded
every 5 min and the daily ambient temperature and relative humidity was determined by
averaging data from within the collection time period. Ambient temperatures within the
collection area ranged ﬁom 21.4 to 29.2 °C with relative humidity ranging ﬁ'om 37.1 to
67.0 % during this study. Rectal temperatures were collected during IRT imaging using a
digital probe thermometer (GLA M525/550, GLA Agricultural Electronics, San Luis

Obispo, CA).

2.6 Statistical Analysis
A mixed model procedure (PROC MIXED, SAS ver 9.1.3) was used for data
analysis. Pre and post-trimming data were analyzed separately because of differences in

the data sets. Image angle, side (left or right side), cows with or without lesions and the

49

occurrence of lesions in only one rear hoof were treated as ﬁxed effects. The number of
lesions was also tested as a covariate. To test for the effect of lesion on MST, cows were
classiﬁed as lesion or non-lesion based on the presence or absence of a lesion in any
claw. In addition, repeated measures on individual cows across days were modeled as
subject-speciﬁc random effect proﬁles. Based on the Bayes Information Criterion (BIC)
value for model ﬁt, in conjunction with the residual analysis, day was ﬁt as a covariate in
the pre-trimming analysis and as a factor in the post-trimming analysis. The residual
variation was modeled as a log-linear variance model with view and day as the only
signiﬁcant factors. For all analyses, observations with MST < 29 °C were deleted as
these data were highly inﬂuential and were treated as outliers. Most of these
observations were from one cow on the ﬁrst day of data collection. Signiﬁcance was set

at P < 0.05 and a signiﬁcant trend was considered to be 0.05 < P < 0.1.

3. Results

Of the 15 cows selected as sound (locomotion score = 1 on d 1 of the study), eight
cows had no hoof lesions, ﬁve cows had one limb affected by hoof lesions (two of these
cows had lesion in both claws), one cow had two limbs affected by hoof lesions, and one
cow had three limbs affected by hoof lesions as determined by the hoof trimmer on d 6
(Table 2). Of the 15 cows selected as lame (locomotion score 3 on d l of the study), six
cows had no lesions, seven cows had one limb affected by hoof lesions (one cow had
lesions in both claws), and two cows had two limbs affected by hoof lesions (Table 2).
After conducting a Spearman’s correlation analysis, lesion number was not correlated

with daily locomotion scores in both the pre-trimming (r = 0.0574, P = 0.3254) and post-

50

trimming (r = 0.0869, P = 0.1332) data sets. The occurrence of lesions also was not
correlated with daily locomotion scores in both the pre-trimming (r = 0.0843, F = 0.1478)

and post-trimming (r = - 0.0809, P = 0.1621) data sets.

Table 2. The cows selected as sound based on locomotion score (LS), the number of
limbs affected by lesions, and the limb and claw where the lesions were discovered
(RRL = right rear lateral; RRM = right rear medial; RRLM = right rear lateral and
medial; LRL = left rear lateral; LRM = left rear medial; LRLM = left rear lateral and

medial; RFL = right front lateral; LFL = left front lateral).

 

 

 

 

Selected Sound Cows Selected Lame Cows
Number of Number of
Day limbs with Lesion Day limbs with Lesion
Cow 1 LS lgions lggtions Cow 1 LS lesions locations
1 l 0 -- 16 3 0 --
2 1 0 -- 17 3 0 --
3 l 0 -- 18 3 0 --
4 1 0 -- 19 3 0 --
5 1 0 -- 20 3 0 --
6 1 0 -- 21 3 0 --
7 l 0 -- 22 3 I RRM“
8 1 0 -- 23 3 1 RFL
9 l 1 RRL“ 24 3 1 LF L
10 1 1 LRL“ 25 3 l LRM“
11 l 1 RRLM“ 26 3 1 RRL“
12 1 1 LRL“ 27 3 I RRM“
13 l l LRLM“ 28 3 l LRLM"I
l4 1 2 LRL 29 3 2 LFL
RRL RF L
15 1 3 LF L 30 3 2 RFL
RF L LRL
RRM

 

* Indicates cows with one hind limb affected by lesions used in subsequent analysis.

51

3.1 Pre- Trimming IRT Data Analysis

Data were analyzed with lesion as a factor to check for differences between lesion
and non-lesion cows. MST data for both rear limbs of all non-lesion cows and all lesion
cows, regardless of the location or number of lesions were pooled for this analysis. There
was no difference in MST of the coronary band between lesion and non-lesion cows in
the dorsal (P = 0.28) and lateral (P = 0.14) views but there was a signiﬁcant trend in the
plantar (P = 0.06) view. While the values are not signiﬁcant there is a trend that the cows
with lesions have a somewhat higher MST across all views (Figure 2).

To set a standard within cows, we compared MST in both limbs of cows that were
not affected by any hoof lesions. There were no differences in MST between left and
right rear limbs among cows with no lesions (P = 0.8085) of the dorsal (34.7 °C; P =
0.4958), lateral (33.8 °C; P = 0.4183), and plantar (34.1 °C; P = 0.6005) views.

We also assessed differences in temperature between the lesion and non-lesion
limb in cows with lesions in only one rear limb (Table 3). In the dorsal view, when
lesions were found in the left limb, there was a trend for the right limb to have a lower
MST (P = 0.0526) and when lesions were found in the right limb the left limb had a
lower MST (P < 0.05). In the lateral view, when lesions were found in the left limb there
was a trend for the right limb to have a lower MST (P = 0.056) and when lesions were
found in the right limb there was a trend for the left limb to have a lower MST (P =
0.0669). In the plantar view, when lesions were found in the left limb there was no
difference in MST (P = 0.1384) and when lesions were found in the right limb there was

a trend for the left limb to have a lower MST (P = 0.0663).

52

Table 3. Maximum surface temperature (MST) values, standard error of the mean (SEM)
and P values based on the least squares means for left and right limbs from dorsal, lateral

and plantar views in cows with only one hind limb affected by lesions over the 5-d pre-

 

 

trimming.
Lesion MST MST
View Location Left °C SEM Right °C SEM P value1
Dorsal Left 35.4 0.359 34.7 0.368 0.053
Right 33.1 0.294 33.8 0.293 0.016
Lateral Left 34.4 0.357 33.8 0.362 0.056
Right 32.3 0.292 32.8 0.291 0.067
Plantar Left 35.2 0.403 34.6 0.415 0.138
Right 32.7 0.329 33.3 0.329 0.066

 

‘ Values based on n = 5 cows with lesions in the left limb and n = 5 cows with
lesions in the right limb over the 5 d pre-trimming.

Lesion also was tested as a covariate to check for trends associated with the
number of lesions among cows. MST of the coronary band increased as the number of
lesions on all hooves (both front and rear) increased (P < 0.05). Furthermore, there was a
signiﬁcant interaction of lesion number by side (P < 0.01) indicating that the increase in

MST depends on the side in which the lesions are occurring.

3. 2 Post— Trimming Data Analysis
In general, there was more variability in the post-trimming data than the pre—
trimming data. When testing lesion as a factor, no difference in MST between non-lesion

cows and lesion cows in the post-trimming analysis was detected. Among non-lesion

53

cows, there was no difference of MST between limbs in images of the plantar (P =
0.5656) view. However, there was a difference in MST between sides in images of the
lateral view (P < 0.05) and a trend for a difference in MST in the dorsal (P = 0.0622)
view. Additionally, there was no effect of number of lesions on MST (P = 0.9561) in the
post-trimming analysis.

For cows with only one rear limb affected by lesions, there was an effect of lesion
location by side interaction post-trimming (P < 0.005). Pair-wise comparison of the LS
means showed that lesions located in the left hoof caused no difference in maximum
temperature of the coronary band when compared to the right. In contrast, lesions located
in the right hoof caused the right coronary band to have a higher maximum temperature
than the left (Table 4). In the post trimming analysis, we found no signiﬁcant trends

associated with lesion when tested as a covariate.

54

Table 4. Maximum surface temperature (MST) values and P values based on the
least squares means for left and right limbs from dorsal, lateral and plantar views

in cows with only one hind limb affected by lesions over the 5-d post-trimming.

 

 

Lesion MST MST
View Location Left °C SEM Right °C SEM P value2
Dorsal Left 35.4 0.415 35.0 0.402 0.314
Right 33.6 0.332 35.0 0.332 P < 0.001
Lateral Left 34.4 0.431 34.1 0.417 0.625
Right 32.8 0.347 34.0 0.344 0.002
Plantar Left 34.8 0.446 34.3 0.432 0.271
Right 33.0 0.359 34.1 0.356 0.010

 

2 Values based on n = 5 animals with lesions in the left limb and n = 5 cows with

lesions in the right limb over the 5 d post-trimming.
4. Discussion

Cows were selected for this study based on their locomotion score at d 1, with the

assumption that at least some of the cows would have claw lesions upon inspection at
hoof trimming on d 5. After inspection at hoof trimming, we found no correlation
between the number of lesions and daily locomotion score. This ﬁnding is consistent
with previous research with no correlation between hoof lesions and lameness after
collecting data on 3,444 cattle on 77 Swedish dairy farms (Manske et al., 2002). A
downfall of the current study was that locomotion scoring was not collected using the
most ideal protocol, with only one person recording locomotion per day. In addition, we
had four different observers perform the scoring and although all were trained, some

observers had more experience than others. While the occurrence of claw lesions was

55

recorded in this study, scoring of lesion type and severity was not performed. This
information perhaps would have allowed us to test for temperature differences associated
with different types and severity of lesions, which could have complemented the study by
Schmidt et al. (2003), who reported in an abstract that IRT may be useful for assessing
claw abnormalities.

In this study, MST was derived from an area surrounding the coronary band, the
highly vascularized area located just proximal to the hoof wall (Greenough, 1997).
During preliminary analysis of data, we determined that differences existed between pre-
trimming and post-trimming data and therefore we carried out independent data analyses.
These differences may be due to the invasiveness of hoof trimming and further studies
should investigate the effects of hoof trimming on surface temperature values of the distal
limb. In the pre-trimming data analysis, we found no signiﬁcant difference in MST
between cows with lesions and cows without lesions, although there was a trend for cows
with lesions, regardless of lesion location, to have a higher MST in all three image views.
In the post-trimming analysis, we also found no differences between limbs of non-lesion
cows in images taken from the plantar view. However, there was a difference in MST
from the lateral view and a trend in the dorsal view. In a similar study, Haley et al.
(2005) also found no difference between lame and sound cows based on locomotion
score. Together, these results indicate that the cow should serve as its own control for
surface temperature determination.

Previous research has determined differences in surface temperatures between
lame and sound limbs (Whay et al., 2004). Therefore, in the pre-trimming analysis of

cows with a lesion in only one hind limb, we expected to ﬁnd differences in MST

56

between lesion and non-lesion limbs. However, signiﬁcance of results depended on the
location of the lesion and the image view. In the plantar view, we found a trend for
difference in temperature between limbs when lesions were found in the right limb;
however, there was no difference in MST when lesions were found in the left limb. In
the lateral view, we found a trend for difference in MST between limbs when lesions
occurred in both the left and right limbs. Differences in the MST of the dorsal view were
found when lesions occurred in the right limb and a trend for differences in MST when
the lesions occurred in the left limb. In Chapter 3, we concluded that images of the
lateral view showed the least variation in sound cows and should be used for IRT data
collection. In the current research, differences may be evident in the dorsal view but not
the lateral view because of the occurrence of lesions in the medial claw as well as the
lateral claw. Differences in signiﬁcance when lesions occurred on left and right limbs
may be associated with the severity of the lesions. In contrast, our post-trimming data
analysis did not show differences in MST of the coronary hand between lesion and non-
lesion limbs. This may be due to the invasiveness of hoof trimming or the effects of
treatment methods (i.e., wooden blocks).

When testing lesion as a covariate in the pre-trimming analysis, we determined
that as the number of limbs (including both front and rear) affected by lesions increased,
there was a trend for the MST of the coronary band to increase. As with other measures,
these results were not repeated in the post-trimming analysis where there was no effect of

the number of limbs affected by lesions on the MST.

57

5. Conclusion

In conclusion, we found that in non-lesion cows before hoof trimming there was
no signiﬁcant difference between MST of the left and right limbs in each image view,
which corresponds with results from Chapter 3. Furthermore, in cows with only one rear
limb affected by one or two hoof lesions (three cows had lesions in both claws of one
hind limb), a difference in MST was evident in images taken from the dorsal view
indicating that we may be able to use IRT images of the dorsal view to detect lesions.
The results of this study suggest that IRT may be a useful tool in detecting inﬂammation
associated with hoof lesions when comparing MST between limbs of the same cow. This
technology merits further research to determine differences in surface temperatures

between limbs affected by different hoof lesions and sound limbs.

58

CHAPTER FIVE

Discussion and Future Research Directions

5.1 Discussion

Lameness may be caused by an array of factors (Galindo et al., 2000). This
disease, which is often perceived by farmers at level lower than the actual occurrence
(Kopcha et al., 2003; Edgecomb et al., 2006), has a major impact on economics
(Nordlund et al., 2004) and animal welfare (Hemsworth et al., 1995; Whay et al., 1998).
More than 90% of lameness cases involve the foot (Shearer and VanAmstel, 2000) and
many of these pathologies also create an inﬂammatory response. Infrared thermography
(IRT) provides a non-invasive method to measure the surface temperature (e. g. Barnes,
1968; Head, 2001). It has been well documented that IRT is a useful tool to detect
lameness in horses (Denoix, 1994; Turner, 2001; Eddy et al., 2001). Some studies also
have been successful in detecting lameness in cattle using IRT (Cockroft et al., 2000;
Schmidt et al., 2003; Whay et al., 2004; Nikkah et al., 2005) while others have failed
(Momcilovic et al., 2000; Haley et al., 2005).

We concur with Whay (2002) who reported that the early detection of lameness in
dairy cattle is pivotal to all subsequent action to relieve suffering. Also, Clarkson et al.
(1996) reported evidence that early detection and subsequent treatment of lameness
resulted in a reduction in the duration and cases of lameness. Therefore, the main
objective of this project was to assess the usefulness of using IRT, on-farm, to detect

lameness in dairy cattle. We hypothesize that this technology may be used to detect

59

lameness at an earlier stage than the existing protocols. To answer this question we
performed two studies. In the ﬁrst study (Chapter 3), 10 sound, lactating Holstein cows
were imaged at multiple times over a 2 d period to give us an understanding of the
normal thermal characteristics in limbs of healthy animals. In the second experiment
(Chapter 4) 15 sound (locomotion score = l) and 15 lame (locomotion score = 3) cows
were imaged in order to determine the ability of IRT to detect lameness.

In Study 1 we determined that sound cows have no signiﬁcant interaction between
side and view and that there was no difference in temperature between the left and right
limbs in the plantar view, a trend towards difference in the lateral view, and a difference
in temperature between limbs in the dorsal view. As there was no signiﬁcant interaction,
these results indicate that a correction factor may be used to account for slight differences
between limbs. We also found a general trend that the left limb has a slightly higher
maximum surface temperature (MST). These differences may be due to a variety of
factors including which side the cow generally lays on, which limb was exposed to the
most moisture and possible interference from extraneous sources of radiation (i.e.,
windows). In Study 2, we found that cows without lesions show no signiﬁcant difference
in temperature between left and right hind limbs at each image view, which concurs with
the ﬁndings in the plantar view for Study 1, but differs from our ﬁndings in the dorsal
and lateral views . We also found differences of MST between lame and sound limbs in
images taken of the dorsal view and a trend for differences in images taken from the
lateral view in cows with only one rear limb affected by a hoof lesion, indicating that a

cow may serve as a self control measure of inﬂammation as suggested in Study 1.

60

In Study 2, we also determined that there was no correlation between locomotion
score and the occurrence of lesions indicating that lesions do not always cause lameness
which concurs with previous research (Manske et al., 2002). However, the locomotion
scoring protocol used in Study 2 (i.e., different observers, one observer per day) was not
ideal for a decisive locomotion scoring study. Also, although we recorded the occurrence
and type of lesion, severity and speciﬁc lesion etiologies were not recorded at the time of
hoof trimming.

It was interesting to see that when assessing the MST values of the two studies,
we observed noticeable differences in the MST of non-lesion cows between the two
facilities. MST values in Study 2 were approximately 1 OC higher in the dorsal view, 2
°C higher in the lateral view, and 3 °C higher in the plantar view. These differences may
be due to a number of factors including ambient temperature, the amount of foreign
material on the hoof, the amount of exercise the animals had before imaging, and the
overall hoof health of the animals. To reiterate, the animals used in Study 1 were housed
in a tie-stall facility at the MSU Teaching and Research Center and hooves of these
animals were generally cleaner and dryer than those of the cows used in Study 2, which
were housed in a large free-stall facility on a commercial dairy. Also, data for Study 1
was collected in May and ambient temperatures were lower than those during the data
collection for Study 2, which took place in early September.

Overall, the results from these studies in conjunction with previous research
indicate that IRT has the possibility to detect lameness earlier than through conventional
methods such as locomotion scoring. Results from both studies (Chapters 3 and 4)

indicate that a cow may be able to serve as a self control when one hind limb is sound,

61

 

which is important because of the numerous opportunities for variability in IRT data
between cows and at different facilities. This technology presents a more objective ‘
measure to detect temperature changes in the hoof which may be useful to detect

lameness early and ultimately increase productivity and decrease suffering in dairy cattle.

5.2 Future Research Directions
The use of IRT to measure surface temperature as an indicator of inﬂammation,

provides a unique and innovative way to assess lameness in cattle and further studies

 

should be performed to continue to explore the possibilities and limitations of this
technology. Longitudinal studies which follow cows throughout lactation and the dry
period should be encouraged. Purohit and McCoy (1980) reported that thermograms of a
horse with laminitis showed an increase in surface temperature 24 h before clinical signs
were evident. It is likely that in cattle we may ﬁnd similar increases in surface
temperature before clinical signs of lameness are evident. Future studies also will help to
further understand differences in temperature throughout a cow’s lactation. Nikkah et al.
(2005) reported a higher surface temperature in early lactation cows than in late lactation
cows. By following cows throughout multiple lactations, we may be able to better
understand why these temperature differences occur as well as exactly when they occur.
In addition, collecting data at different intervals throughout these studies will help us to
understand how often cows need to be imaged in order to detect lameness earlier than
through conventional methods.

Further research is also needed to help us better understand the normal thermal

patterns of dairy cows, not just the temperature values, as the patterns of temperature may

62

tell us more than just the temperature values. Turner (2001) reported that in a horse with
laminitis, the temperature of the hoof will begin to approach the temperature of the

coronary band. In cattle, it is likely that we could see similar changes in the thermal

 

patterns of the coronary band and the hoof. In addition, further studies need to be
conducted which include data from the front hooves. In the present study, we chose to
assess only the rear limbs because most lesions occur in the hind limbs (Shearer and

VanAmstel, 2000) and at both facilities used, the rear limbs were more accessible for

 

imaging. It will be interesting to see if the results found in this study would be consistent
in the front limbs and to see if front limbs also may serve as controls for rear limbs.

Moreover, large scale studies conducted on multiple commercial dairies in
different environmental conditions will help us better understand the amount of
variability due to cows, facilities, and environment. While we expect to see differences
in surface temperature due to a variety of factors including ambient temperatures and
circadian rhythms, we need to determine a range of normal temperatures for sound cows
in speciﬁc environmental conditions.

Further studies investigating the use of IRT to detect lameness may provide
researchers with an objective method to detect inﬂammation in the limbs of dairy cattle.
In summary, future studies should investigate the use of IRT to detect lameness early and

ultimately increase productivity and welfare of the animals.

63

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