3237
The Journal of Experimental Biology 216, 3237-3248
© 2013. Published by The Company of Biologists Ltd
doi:10.1242/jeb.080309
RESEARCH ARTICLE
The gait dynamics of the modern broiler chicken: a cautionary tale of selective
breeding
Heather Paxton1,*, Monica A. Daley1, Sandra A. Corr1,2 and John R. Hutchinson1
1
Structure & Motion Laboratory, Department of Comparative Biomedical Sciences, The Royal Veterinary College,
University of London, Hatfield, Hertfordshire, UK and 2Division of Surgery, School of Veterinary Medicine and Science,
University of Nottingham, Sutton Bonington, Leicestershire, UK
*Author for correspondence (hpaxton@rvc.ac.uk)
SUMMARY
One of the most extraordinary results of selective breeding is the modern broiler chicken, whose phenotypic attributes reflect its
genetic success. Unfortunately, leg health issues and poor walking ability are prevalent in the broiler population, with the exact
aetiopathogenesis unknown. Here we present a biomechanical analysis of the gait dynamics of the modern broiler and its two
pureline commercial broiler breeder lines (A and B) in order to clarify how changes in basic morphology are associated with the
way these chickens walk. We collected force plate and kinematic data from 25 chickens (market age), over a range of walking
speeds, to quantify the three-dimensional dynamics of the centre of mass (CoM) and determine how these birds modulate the
force and mechanical work of locomotion. Common features of their gait include extremely slow walking speeds, a wide base of
support and large lateral motions of the CoM, which primarily reflect changes to cope with their apparent instability and large
body mass. These features allowed the chickens to keep their peak vertical forces low, but resulted in high mediolateral forces,
which exceeded fore–aft forces. Gait differences directly related to morphological characteristics also exist. This was particularly
evident in Pureline B birds, which have a more crouched limb posture. Mechanical costs of transport were still similar across all
lines and were not exceptional when compared with more wild-type ground-running birds. Broiler chickens seem to have an
awkward gait, but some aspects of their dynamics show rather surprising similarities to other avian bipeds.
Key words: broiler chicken, gait, locomotion, leg weakness, morphology, selective breeding.
Received 17 September 2012; Accepted 1 May 2013
INTRODUCTION
Although Darwin detailed how organisms evolve through natural
selection (Darwin, 1859), he built his case partly on the knowledge
that humans have used an analogous principle in the domestication
of plants and animals for thousands of years. This has allowed
livestock breeders to fully exploit desired phenotypic traits, resulting
in dramatic and rapid changes in appearance and behaviour from
their wild ancestors. A prime example of these dramatic changes
can be seen in the modern broiler (a type of chicken raised
specifically for meat), which has extremely rapid growth rates [18
standard deviations from its original rate across ~50years of
breeding (Whitehead et al., 2003)], a significantly larger pectoral
muscle mass and increased meat yield (Barton, 1994; Lilburn, 1994;
Webster, 1995; Nicholson, 1998; Corr et al., 2003a; Havenstein et
al., 2003a; Havenstein et al., 2003b). However, this seeming success
in the production efficiency of the modern broiler has come with
unwanted consequences. In particular, musculoskeletal
abnormalities and poor walking ability (commonly referred to
together as ‘leg weakness’) are the most prevalent causes of culling
and late mortality in the modern broiler (Pattison, 1992; Knowles
et al., 2008).
Typically, leg weakness is characterised using a subjective gait
scoring method, which assesses the walking ability of birds based
on an abstract ideal of a ‘normal’ gait. Normal birds are considered
more agile than those with an ‘abnormal’ gait, and in the worst
cases, extremely abnormal birds may be incapable of sustained
walking (Kestin et al., 1992). These gait scoring methods have been
used extensively within the scientific community to understand the
health and welfare implications in poultry (e.g. McGeown et al.,
1999; Danbury et al., 2000; Weeks et al., 2000; Sandilands et al.,
2011), but the actual relationship between this impaired walking
ability and specific leg problems remains unclear (for a review, see
Bradshaw et al., 2002). The difficulties are apparent; potential links
of gait mechanics to pathology and walking ability remain merely
inferential, the chance of detecting a subtle gait change correlated
to pathology appears low and hence requires large sample sizes
(Sandilands et al., 2011), and part of the difficulty in associating
gait changes with certain pathologies is that chickens often have
multiple pathologies. The way a chicken walks can therefore be a
product of the underlying pathology and/or stresses, plus the bird’s
attempt to compensate for it.
Our first aim is therefore to quantify the locomotor dynamics of
the modern broiler as an exploratory analysis of how selection has
actually altered the way these birds walk and perhaps contributed
to lameness. Because few studies have actually detailed objective
measures of the modern broiler’s gait (Reiter and Bessei, 1997; Corr
et al., 1998; Corr et al., 2003b; Corr et al., 2007), here we establish
the ‘normal’ gait characteristics of the modern broiler. We do this
as an essential first step toward the longer-term goal of quantitatively
characterising, identifying and understanding abnormal gaits in
different lineages of wild and domestic poultry, including broilers.
We also clarify possible misconceptions associated with what may
THEJOURNALOFEXPERIMENTALBIOLOGY
3238 The Journal of Experimental Biology 216 (17)
have partly evolved to be an awkward gait for effective locomotion
versus the individual perception of a ‘good’ versus ‘bad’ gait or
‘leg weakness’ in broilers. This is important to examine, because
future considerations for the welfare of the modern broiler are likely
to be based heavily on visual aspects of their gait.
Ironically, broiler chickens, like other galliform birds, may be
considered as specialist walkers [based on their dominant locomotor
mode (Tickle et al., 2007; Nudds et al., 2011)]. Yet their exaggerated
lateral motions (Corr et al., 2003b) suggest that they may share more
in common with other waddling, more aquatic species such as
penguins, geese or ducks (Griffin and Kram, 2000; Abourachid,
2001; Usherwood et al., 2008; Nudds et al., 2011). Such waddling
birds are often described as ‘awkward’ or ‘ungainly’ walkers, yet
the mechanics of waddling birds still conform with the classical
pendulum model of walking bipeds, associated with the conservation
of mechanical energy (Cavagna, 1975; Cavagna et al., 1976;
Cavagna et al., 1977). As much as 70% of the external work required
to lift and accelerate the centre of mass (CoM) can be recovered as
a result of this energy saving mechanism (Cavagna et al., 1977; but
see Donelan et al., 2002). The second aim of our study quantifies
the three-dimensional dynamics of the CoM in order to determine
how broiler chickens modulate the force and mechanical energy of
locomotion. Altered behavioural patterns and reduced activity levels
have been reported in these birds (Weeks et al., 1994; Estevez et
al., 1997; Bizeray et al., 2001; Weeks et al., 2000), which are thought
to be attributable to conformation-related gait alterations causing
fatigue (Abourachid, 1993; Corr et al., 2003b). We can test whether
broilers require excessive work (using the metric of the mechanical
cost of transport), requiring more mechanical energy from the limb
muscles.
Finally, we evaluate the effects of conformation on locomotor
dynamics, by investigating two pureline commercial broiler breeder
lines with high performance (in terms of meat production)
characteristics. These lines are typically crossbred by commercial
poultry production systems in order to produce the modern broiler
with desired characteristics (Anthony, 1998; Yang and Jiang, 2005).
Differences in the pelvic limb musculature of these study groups
have already been shown quantitatively, suggesting that differences
in the gait characteristics of these lineages may exist (Paxton et al.,
2010). Additionally, when the two purelines are compared at the
farm level, Pureline A birds generally yield greater breast muscle
mass per unit body mass and have lower average gait scores (poorer
walking ability), whereas Pureline B chickens tend to have a larger
body mass (~30% difference in some cases) with generally higher
gait scores (H.P., unpublished data). We aim to determine whether
these three lineages have adopted different locomotor strategies as
a result of their altered morphology.
In addition, studies have suggested an apparent instability in
broiler chickens, which – in line with the waddling gait of penguins
(Kurz et al., 2008) – has been considered, somewhat speculatively,
as more susceptible to falls. Specifically, broiler chickens appear
to have more excessive lateral motions than more ancestrally
typical ground-running birds (Cavagna et al., 1977; Gatesy and
Biewener, 1991; Rubenson et al., 2004). We present the first study
to investigate, albeit with an admittedly simple metric, the dynamic
stability of the modern broiler. We do this by considering their gait
variability and its potential role in locomotor stability (Winter, 1989;
Holt et al., 1995; Dingwell and Cavanagh, 2001; Dingwell and
Marin, 2006). By doing this, we aim to further highlight how
morphological changes may have led to difficulties with locomotor
stability in broiler chickens.
MATERIALS AND METHODS
Male commercial line birds (~42days old) were used in this study,
including two pureline commercial broiler breeder lines, referred
to as Pureline A and B, and a commercial broiler strain (Table1).
The main morphological characteristics for these groups (collected
from multiple cadaveric specimens) are also detailed in Table2.
These included breast muscle mass (±0.1g; pectoralis; i.e. pectoralis
major, and supracoracoideus; i.e. pectoralis minor; combined), girth
(±0.1cm), hip width (±0.1mm), keel length (±0.1mm) and total leg
length (±0.1mm). Hip width was taken as the distance between the
trochanteric crests of the femora (birds were similarly positioned
in each case), girth was measured around the circumference of the
thorax of the bird (tucked under the wings), and total leg length
was taken as the sum of the individual pelvic limb bones (femur,
tibiotarsus and tarsometatarsus), measured from the most proximal
point to the most distal point on the medial or lateral side of the
bone. The bird populations were all raised under the same
management conditions to ensure that any differences found were
not attributed to husbandry factors, which are well known to
influence the growth and leg health of broilers (Sørensen et al., 1999;
Su et al., 1999; Vestergaard and Sanotra, 1999; Kestin et al., 2001;
Scott, 2002; Dawkins et al., 2004; Mench, 2004; Brickett et al.,
2007; Buijs et al., 2009). Those birds that were visibly lame or
incapable of sustained walking were excluded from this study.
Motion capture was used to study individual birds using eight
Qualisys MCH 500 cameras (Gothenberg, Sweden) that were
synchronised to a Kistler 9287B force plate (Kistler Instruments,
Alton, UK). The trochanteric crest of the hip and the distal phalanx
of the middle toe of each limb were marked with infrared-reflective
motion capture markers, thereby simplifying each limb as a linear
segment. The birds were encouraged to walk over the force plate
(500Hz) parallel to the view of the cameras (167Hz), and the marker
position and the ground reaction forces in the vertical, fore–aft and
mediolateral directions were recorded. All the birds had known body
masses (±0.1kg), which were taken immediately after the trials for
each individual were finished.
The kinematic and force plate data were then analysed using two
computer programs, Qualisys Track Manager (QTM) and MATLAB
(The MathWorks, Natick, MA, USA). QTM formed a threedimensional image of the markers’ coordinates and these data were
then further processed with the force plate data using custom
MATLAB software. All trials were processed, but those trials where
there were large gap ranges between the coordinates or where the
bird was distracted were removed before further analysis. The
Table1. Mean subject data for chicken breeds used in this study
Bird group
Pureline A
Pureline B
Broiler
No. of individuals
8
8
9
No. of steps
118
90
130
Mass (kg)
a
2.8±0.3
2.7±0.4a
3.5±0.3b
CoM height (m)
Mean velocity (ms–1)
Velocity range (ms–1)
0.25±0.07
0.26±0.08
0.34±0.17
0.10–0.43
0.10–0.45
0.11–1.10
b
0.21±0.008
0.20±0.008a
0.22±0.007c
Data are means ± s.d. CoM, centre of mass. Means in a column (mass and CoM height only) with no common superscript differ significantly at the 0.05 level
between bird groups, emphasised in bold.
THEJOURNALOFEXPERIMENTALBIOLOGY
Gait dynamics of the broiler chicken
3239
Table2. General morphological characteristics of the chicken breeds used in this study
Bird group
Pureline A
Pureline B
Broiler
K–S test
Levene’s test
Girth (×10–2)
a
25.3±0.6
24.4±1.2a
24.7±1.3a
0.852
0.141
Hip width (×10–2)
a
6.34±0.16
6.90±0.28b
6.60±0.17a
0.493
0.106
Keel length (×10–2)
a
9.38±0.45
8.92±0.79a
8.27±1.21a
0.000
0.003
Total leg length (×10–2)
a
17.8±0.59
18.4±0.97a
18.6±0.58a
0.489
0.715
Breast muscle mass (% body mass)
22.1±1.6c (N=128)
20.1±1.4a (N=202)
20.6±1.0b (N=18)
0.000
0.000
Data originate from birds used in a previous muscle architecture study (Paxton et al., 2010), as well as from data collected on farms to provide a general
overview of how morphology differs between the bird groups. The data therefore do not necessarily correspond directly to the subjects used in this study, but
were all selected using the same criteria as set out here. To make valid comparisons across bird populations, the data (body measurements only) were
normalised to negate the effect of body mass (length ⬀ body mass1/3). Values reported here are means ± s.d. (N=10, unless otherwise stated). Means in a
column with no common superscript differ significantly at the 0.05 level and are highlighted in bold. P-values for the Kolmogorov–Smirnov and Levene’s test
are also presented.
kinematic data were filtered (Winter et al., 1974) using a low-pass,
zero-lag fourth-order Butterworth digital filter with a cut-off
frequency of 10Hz. The same filter type was used for the ground
reaction force data, with a cut-off frequency of 75Hz. The kinematic
data (foot markers only) were used to identify foot-down and footoff events and these identified steps were subsequently analysed.
This also allowed us to investigate any possible asymmetries (i.e.
left–right limb differences) that may exist in the broiler.
Ergonomic analysis was conducted in each step to quantify
mechanical energy fluctuations and to calculate the mechanical work
required to move the CoM. Because the chickens walked slowly,
and did not necessarily start walking ‘on cue’, there may have been
some baseline drift from the force plates (an unavoidable limitation
of the sensors recording over longer periods of time). To check and
correct for this possibility, we assumed that the birds supported their
own body mass through consecutive strides and the vertical forces
were corrected accordingly. In order to reduce the error in position
over time, the initial velocity conditions were calculated following
methods adapted from Daley et al. (Daley et al., 2007). A pathmatching technique was used where the initial velocity calculated
from the kinematic data was used as an initial guess, which was
then corrected to provide a base match between the CoM position
calculated using the kinematics over time and the CoM position
calculated through integration of the force plate data. The initial
velocity selected was the value that minimised the divergence (sum
of the squared differences) between the two paths and these
conditions were used to calculate CoM velocity and position by the
double integration of the accelerations from the force plate data.
Observation of the broilers through the length of the trial showed
that they rarely walked in a straight line. The fore–aft and
mediolateral forces and the CoM velocity in these two directions
could therefore be under-/over-estimated depending on the direction
the bird was walking in relation to the plate. The forces were thus
corrected based on the angle between the CoM velocity and the
force plate coordinate system. Peak forces were recorded along with
step width and step length, which were defined from the lateral
position of the CoM and the fore–aft position of the CoM,
respectively. CoM height was defined as the average CoM position
across a step. The leg length (in metres) and the leg angle (in degrees)
were calculated using the CoM position and the toe marker position
data. Based on basic trigonometry, if dX refers to the horizontal
distance between the CoM position and the toe marker and dZ refers
to the vertical distance between the CoM position and the toe marker,
leg length=√(dZ2+dX2) and leg angle=180–[tan−1(dZ/dX)]. The
trackway width (measured separate to step width, in order to consider
the outward splay of the lower leg) was also calculated, measured
as the lateral separation between the markers on the feet during the
double support phase and expressed as a fraction of CoM height.
The vertical and lateral displacement of the foot during swing was
also considered – i.e. the peak displacement of the foot during swing
relative to its position during stance – as a measure of limb
circumduction and to investigate foot path variability.
The average horizontal velocity, duty factor (the fraction of the
total stride cycle during which the foot is in contact with ground)
(Biewener, 1983; Alexander, 1985; McMahon, 1985; Taylor, 1985)
and the Froude number for each step were also recorded. The Froude
number (Fr) was calculated as Fr=v2g−1l−1, where g=9.81ms−2, l is
mean hip height and v is mean velocity. The mechanical cost of
transport (MCoT; Jkg−1m−1) was also considered: MCoT=Wm−1L−1,
where W is absolute work performed (J), m is body mass (kg) and
L is step length (m).
Only data that were considered steady state were used to draw
results and conclusions in this study, as it was important to establish
typical cyclical movements in these birds without halting or other
perturbations. Steady state was defined based on the ground reaction
force impulse and the change in CoM velocity over a step. A fore–aft
impulse of 0±2N s and a CoM velocity change of less than 35%
during a step were used. The data were then sorted into eight speed
categories for statistical analysis. A minimum of five data points
per speed category per bird group was set in order to consider their
contribution to the relationships observed as valid. Data were omitted
where this condition could not be met. Whilst our statistical tests
could manage a limited number of data points, because of the
unsteady nature of these birds and our objective to establish normal
gait characteristics, we wanted to ensure that the results were not
influenced by potentially more spurious values. The computer
package SPSS (IBM, Armonk, NY, USA) was used for statistical
analysis to check for differences between the relationships of bird
group, speed and the right or left foot with step width, step length,
step frequency, leg length and angle, displacement of the foot,
trackway width, peak forces, CoM energies, work performed and
MCoT between bird groups. The data were analyzed using a linear
mixed model, with speed, the foot used in each step (right/left) and
bird group (Pureline A, Pureline B and the commercial broiler) as
the fixed effects, the individual bird as the random effect and each
factor previously mentioned (MCoT, step frequency, etc.) as the
dependent variable. This procedure allowed the data to exhibit
correlated and non-constant variability. It estimated the effects of
speed, foot used and bird group on the dependent variables while
adjusting for correlation due to repeated trials on each bird. P-values
(≤0.05 deemed significant) were taken into consideration when
analyzing the data and drawing conclusions.
Additionally, as a measure of kinematic variability, the coefficient
of variation (ratio of the standard deviation to the mean) for a number
THEJOURNALOFEXPERIMENTALBIOLOGY
3240 The Journal of Experimental Biology 216 (17)
Duty factor
1
0.9
0.8
0.7
0.6
0.5
0
1
0.9
0.8
0.7
0.6
0.5
0
1
0.9
0.8
0.7
0.6
0.5
0
Pureline A
0.2
0.4
0.6
0.8
1
1.2
Pureline B
0.2
0.4
0.6
0.8
1
Fig.1. Duty factor versus centre of mass (CoM)
velocity for individual steps from walking chickens.
Each symbol represents an individual bird, with the
same symbol indicating multiple steps per bird
used for this analysis. The regression lines
represent a strong relationship (r2>0.4) between
duty factor and CoM velocity for Pureline A and
the broiler population, with a more moderate
relationship (r2 between 0.2 and 0.4) for Pureline B
chickens. The slopes of all three lines are
statistically different from 0 (P<0.001).
1.2
Broiler
0.2
0.4
0.6
0.8
1
1.2
CoM velocity (m s–1)
of variables was used in order to have a comparable measure of
dispersion among the three groups. To test for differences in
morphology, a one-way ANOVA was used to test the differences
among group means for significance. To validate the use of this
parametric test, assumptions of normal distribution and equal
variances were tested using Kolmogorov–Smirnov and Levene’s
tests, respectively (results displayed in Table2). Where these
assumptions were not met, an independent Kruskal–Wallis test was
used. If significant differences were found (P≤0.05), a Bonferroni
post hoc test was used to determine which groups were significantly
different from each other. Regression analyses were also used to
determine the relationship between CoM velocity and duty factor
(Fig.1), as well as any significant slope differences between step
variables (Fig.2).
We report the locomotor attributes of the modern broiler at their
‘preferred’ walking speed (mean velocity=0.25±0.02ms−1) – i.e. the
speed category used most commonly by the three groups (~40% of
the data in each group) – as well as any significant relationships
with speed. Although work performed is a scalar quantity, we
consider the absolute values for work performed as separate
components for each direction of motion in order to fully evaluate
the mechanical work based on the magnitude and direction of each
force vector.
All birds were examined post mortem to identify any pathological
condition that may have affected the observed gait, in particular,
femoral head necrosis, severe valgus deformities [greater than 45deg
is associated with lameness (Leterrier and Nys, 1992)], tibial
dyschondroplasia or gross swelling of the joints.
RESULTS
Gross abnormalities were not found during post-mortem examination.
We therefore considered these birds to have normal limb function
based on the absence of any gross pathology. It must be noted that
satisfying the conditions of steady state led to differing amounts of
data being excluded from this study. The largest number of steps was
discounted from Pureline A (47%; 308 out of 661 ‘unsteady’ steps),
with 33% (221 out of 661 ‘unsteady’ steps) and 20% (132 out of 661
‘unsteady’ steps) being discounted from Pureline B and the broiler
data sets, respectively. Collectively this accounted for 66% of the
total number of steps (999) originally collected.
Very subtle morphological differences existed between the
populations of our study birds (Table2), with only significant
differences in hip width (F2,27=16.5, P=<0.001) and breast muscle
mass (P=<0.001). Pureline B birds had wider hips than both the
broiler and Pureline A populations. Breast muscle mass varied
significantly between the three groups. Pureline A had an additional
2% body mass of breast muscle mass compared with Pureline B
and the broiler population, but total leg length was not statistically
different between groups. Across all chicken populations, girth was
~30% larger than leg length across all bird populations. CoM height
also varied between groups (F2,319.4=85.3, P=<0.001; Table1).
Pureline B chickens had the smallest CoM height, which was ~5%
smaller than Pureline A birds and ~10% smaller than the broiler
population.
Initial analysis of the CoM velocity and duty factor (Fig.1) shows
that the general trend among all populations was for CoM velocity
to increase with a decrease in duty factor, as expected. The broiler
population, which had the largest body mass (Table1), seemed able
to achieve a much broader speed range than the pureline populations,
with a few broiler individuals reaching speeds between 0.6 and
1.1ms−1. The largest fluctuations in CoM velocity can be seen in
the lateral component (Table3), with the highest fluctuations
reported in Pureline A chickens. This component also differed
depending on the foot used (larger for right steps; F1,311=6.49,
P=0.011), and was generally smaller (~16%) in Pureline A birds
(F2,311=5.59, P=0.004).
An increase in forward velocity was achieved by increasing step
length and step frequency (Fig.2), with a preference to increase step
frequency at a rate slightly faster than that of step length (based on
significant differences between the slope values of the two lines,
P<0.001). Stance duration also decreased, whereas swing duration
was kept almost constant (Fig.3). Step width decreased with an
increase in speed, with the magnitude of this effect varying
significantly between bird groups. Step width decreased at a faster
rate in Pureline B chickens and to a lesser degree in Pureline A
chickens and the broiler population. Step width changes were more
variable than changes in step length across all chicken populations.
This is seen more clearly if we consider these values at the birds’
preferred walking speed (Table4). Variability in step width is shown
to be approximately two times higher (~30%) than the variability
THEJOURNALOFEXPERIMENTALBIOLOGY
Gait dynamics of the broiler chicken
3241
Table3. Trackway width, lateral velocity and foot displacement (lateral and vertical) at preferred walking speed in chickens
Lateral velocity (ms–1)
Lateral displacement (m)
Bird group
Relative
trackway width
Right
Left
Right
Left
Vertical
displacement (m)
Pureline A
Pureline B
Broiler
0.52±0.16
0.53±0.17
0.48±0.10
0.13±0.05b (55%)
0.12±0.05a (42%)
0.12±0.03a (33%)
0.09±0.05b (56%)
0.12±0.05a (42%)
0.14±0.04a (29%)
0.037±0.023a
0.055±0.024b
0.039±0.020a
0.026±0.023a
0.039±0.033b
0.020±0.029a
0.082±0.032b
0.056±0.018a
0.091±0.024c
Data are means ± s.d. Relative trackway width was calculated by dividing trackway width by mean hip height.
Means in a column with no common superscript differ significantly at the 0.05 level and are highlighted in bold. The coefficient of variation for lateral velocity is
shown in parentheses.
Relative step frequency
Relative step width
Relative step length
in step length (~15%). Pureline B birds took longer steps than both
the Pureline A and the broiler populations (F2,85.2=7.58, P=0.001),
and this corresponded with a significantly lower step frequency
(F2,58.0=5.89, P=0.005). Trackway width was not significantly
different between groups (F2,140.0=2.66, P=0.073), remaining ~51%
of mean hip height across all bird populations (Table3).
Analysis of the chickens’ general limb motions across a step cycle
(Fig.4) shows that leg angle did not change by more than ~10deg
through the stance phase of locomotion and was relatively consistent
across steps (given the small standard deviations), in contrast to the
swing phase of locomotion, where leg angle was much more variable.
Changes in overall leg length were small between stance and swing
phases, with the more noticeable differences between these events
seen in the broiler population. This relates to the pathway of the feet
during swing (Table3), with the broiler population lifting their feet
roughly a third higher than Pureline B birds with each step. In all
bird populations, circumduction of both limbs was evident
(F2,303=5.49, P=0.005), with a significantly larger lateral displacement
of the right foot (F1,303=1.97, P=<0.001). This did not correlate with
lateral velocity. The largest lateral displacement of both limbs was
seen in Pureline B birds, which also had a significantly larger sweep
angle (F2,318=11.49, P=<0.001; Table4). Thus Pureline B birds took
longer steps while drawing their feet further away from the body but
at a lower elevation than broilers did.
1.5
The resulting ground reaction forces (Fig.5) show that our study
birds all tended to support forces equal to or slightly more than their
body weight during a step, with peak vertical forces (Table4) not
exceeding 1.4 times body weight. These peak vertical forces were
significantly larger in the broiler population (~15%) compared with
the Pureline A population (F2,67.9=6.31, P=0.003). Mediolateral
forces generally exceeded fore–aft forces, with both representing
10–15% of the peak vertical force. The subsequent direction of the
mediolateral force corresponded to which foot was placed on the
ground, with a general trend for birds to roll laterally over their
supporting leg with each step. These forces were also larger in the
right limb in all bird populations (F1,296.0=73.2, P=<0.001), which
was more evident in the Pureline B and broiler populations, where
the mediolateral forces were generally two times larger in the right
limb (Table4). Overall, the broiler population experienced
significantly larger (~30%) mediolateral forces than the pureline
groups (F2,84.3=10.3, P=<0.001).
The limb motions used by the birds led to a minimal change in
CoM displacement (Fig.5), which was generally less than 5% of
hip height, corresponding to very small changes in gravitational
potential energy. Fluctuations in kinetic energy were negligible and
changes in CoM energies across all bird populations were small
(fluctuating around zero) but extremely variable, with standard
deviations much larger than value means (Table4).
Slope=0.82±0.09
1
0.5
0
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.4
Slope=–1.83±0.20
0.3
Slope=–2.13±0.40
0.2
0.1
0
0
Fig.2. Step variables change with speed in walking
chickens. Data are means ± s.d. The different
coloured data points refer to Pureline A (red),
Pureline B (blue) and the broiler population (black).
Relative values were calculated by dividing step
length and step width by mean hip height. Relative
step frequency was calculated using the following
equation, f=(hg−1)0.5, where g=9.81ms−2 and h is
mean hip height (Alexander, 1977; Alexander and
Jayes, 1983). The slope values were tested for
significant differences between bird populations, i.e.
the coefficient for the interaction between the
dependent variable and the bird group is 0. Mean
slope values are displayed if no significant
differences exist.
Slope=−2.56±0.73
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.8
0.4
0.45
0.5
Slope=1.05±0.09
0.6
0.4
0.2
0
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
Dimensionless speed
THEJOURNALOFEXPERIMENTALBIOLOGY
3242 The Journal of Experimental Biology 216 (17)
Fig.3. Stance (squares) and swing phase (circles)
durations in walking chickens across their speed
range. The different coloured data points refer to
Pureline A (red), Pureline B (blue) and the broiler
population (black). Individuals are not distinguished,
thus data points may represent multiple steps from
one bird.
3
Swing/stance duration (s)
2.5
2
1.5
1
0.5
0
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
Dimensionless speed
The subsequent work performed in the vertical and mediolateral
directions was significantly smaller in Pureline A (F2,48.4=9.32,
P=<0.001 and F2,194.0=14.2, P=<0.001, respectively). Across all
birds, the work performed in the mediolateral direction was of
similar magnitude to the work performed in the fore–aft direction.
Despite the subtle differences in locomotor dynamics observed
between lines, the MCoT (work performed per kilogram body
mass over a step) was not significantly different between groups
(F2,68.5=1.43, P=0.247; Fig.6). Remarkably, when compared with
other ground-running birds (ostrich and guineafowl) for which
adequate data exist, the MCoT appears to follow simple bodysize scaling patterns (i.e. larger species toward the bottom of the
plot) rather than showing a sharp divergence between specialised
running birds and the more sedate, artificially selected domestic
chickens.
DISCUSSION
Leg weakness (encompassing lameness and poor walking ability)
is a topical issue concerning the health and welfare of the modern
broiler chicken. Unfortunately, there are many difficulties
associated with establishing the cause of leg weakness in poultry
and very little is understood about their gait. Our study therefore
had three major purposes: (1) to determine how selection has
actually altered the way that production-line chickens walk; (2)
to determine whether any changes in locomotor dynamics require
excessive work, requiring more mechanical energy from the limb
muscles; and (3) to establish whether a change in morphology in
these chickens leads to different locomotor mechanisms. Hence,
our study helps to illuminate how morphological changes may have
contributed to lameness or other difficulties with locomotion in
the broiler chicken.
Table4. Dynamic gait variables for the study chickens at their preferred walking speed
Step variables
Number of steps
Relative step length
Relative step width
Relative step frequency
Sweep angle (deg)
Peak forces (BW)
Vertical
Fore–aft
Mediolateral (right foot)
Mediolateral (left foot)
CoM energies
∆Gravitational potential energy (J)
∆Kinetic energy (J)
∆Total energy (J)
Work performed (absolute values)
Vertical (J)
Fore–aft (J)
Mediolateral (J)
Pureline A
Pureline B
Broiler
46
0.54±0.09
0.20±0.09
0.30±0.04
36.8±7.4
39
0.58±0.09*
0.25±0.09
0.28±0.03*
40.0±8.0*
56
0.53±0.01
0.24±0.07
0.31±0.04
34.8±5.3
1.18±0.12
0.10±0.04
0.12±0.09
0.11±0.06
1.27±0.30
0.11±0.04
0.18±0.06
0.09±0.04
1.38±0.10a
0.12±0.03
0.24±0.04*
0.11±0.04*
0.06±0.16
–0.02±0.14
0.04±0.14
0.04±0.45
–0.04±0.16
–0.02±0.43
0.01±0.29
0.05±0.09
0.05±0.23
0.60±0.20*
0.20±0.08
0.19±0.14
0.83±0.64
0.21±0.05
0.20±0.11
0.94±0.30
0.22±0.06
0.26±0.11*
Data are means ± s.d. *Significant differences at the 0.05 level between bird groups. Only significant asymmetries are reported; superscript ‘a’ indicates a
significant difference from Pureline A birds. BW, body weight; CoM, centre of mass.
THEJOURNALOFEXPERIMENTALBIOLOGY
Gait dynamics of the broiler chicken
Pureline A
At 50% of step cycle:
Stance – 115±2
Swing – 96±11
Leg angle (deg)
160
140
Broiler
Stance – 113±2
Swing – 89±8
Stance – 114±2
Swing – 95±4
120
100
80
0
100
0
At 50% of step cycle:
Stance – 0.25±0.01
Swing – 0.23±0.02
0.35
Leg length (m)
Pureline B
3243
0.30
100
0
Stance – 0.24±0.01
Swing – 0.23±0.01
100
Stance – 0.27±0.01
Swing – 0.25±0.02
0.25
0.20
0
100
0
100
0
100
Step cycle (%)
Fig.4. Leg length and angle at preferred walking speed in chickens. Data are means ± s.d. (shaded areas). Stance (solid lines) and swing (dashed lines)
phase are shown for the right (red) and left foot (blue).
CoM displacement (m)
0.02
Pureline A
1961; Tobalske and Dial, 2000). Broiler chickens are essentially
flightless at any stage of ontogeny (authors’ personal observations),
and previous literature has suggested that the influence of this alone
may put greater demands on the pelvic limb muscles, affecting the
birds’ walking ability (Abourachid, 1993; Corr et al., 2003b). The
logic underlying this presumed relationship between pectoral mass
and pelvic limb mechanics is that a more cranially positioned CoM
requires more limb muscle effort for support. This is not uncommon
among other bipeds, where the potential displacement of the CoM
(greatly influenced by body size and shape) has been found to have
a strong influence on aspects of locomotion [e.g. postural stability
in humans (Fregly et al., 1968; Corbeil et al., 2001)], such as a
Pureline B
0.10
0.05
0.01
0
0
–0.01
Ground reaction force (BW)
Broiler
CoM displacement
Mean hip height
It is well known that distinct selection pressures are applied on
a line-by-line basis, so we would expect morphological differences
to exist amongst our three study groups. Consequently, we found
subtle differences including a large pectoral muscle mass, accounting
for ~20% of total body mass (~2% larger in Pureline A chickens
compared with Pureline B and the broiler population), and
differences in hip width between the study populations (larger in
Pureline B). This disproportionate increase in pectoral muscle mass
to body mass is well documented (e.g. Havenstein et al., 1994a;
Havenstein et al., 1994b; Lilburn, 1994), but under natural conditions
is usually only seen in other Galliformes that require this large
muscle to power a rapid take-off; e.g. grouse or partridges (Hartman,
–0.05
1.50
1.00
0.50
0
–0.50
Step cycle
Fig.5. The ground reaction forces and CoM displacements at the preferred walking speed of three chicken populations. Data represented are means ± s.d.
(shaded areas). Vertical forces (black), fore–aft forces (yellow) and mediolateral forces (red, right foot; blue, left foot) are shown.
THEJOURNALOFEXPERIMENTALBIOLOGY
3244 The Journal of Experimental Biology 216 (17)
1.5
Pureline A
Pureline B
Broiler
1
0.5
Mechanical cost of transport
(J kg–1 m–1)
0
0
0.1
0.2
0.3
0.4
0.5
1.4
Guineafowl
1.2
Chicken
Ostrich
1
0.8
0.6
0.4
0
0.1
0.2
0.3
0.4
0.5
Dimensionless speed
0.6
0.7
0.8
Fig.6. The mechanical cost of transport of domestic chickens at their preferred walking speed. Data for the commercial line birds are means ± s.d. All other
data are means only. Note that data for the three chicken populations are shown together in purple at the bottom left for comparison to the guineafowl and
ostrich data, and separately in the inset at the top right to illustrate differences among them.
wider pelvis (Pureline B birds), in combination with the large
pectoral muscle mass (Hutchinson, 2004). Yet it remains unclear
how other morphological changes may affect gait.
Initial evaluation of the gait of our three study populations of
chickens reveals common features with other avian bipeds [guineafowl
(Gatesy, 1999); quail (Reilly, 2000); other avian taxa (Gatesy and
Biewener, 1991; Abourachid, 2000; Abourachid, 2001; Rubenson et
al., 2004; Nudds et al., 2011)], including typical associations seen
with increased speed, such as a preference to increase step frequency
at a slightly faster rate than step length, a decrease in step width and
a decrease in stance duration. This also coincides with a relatively
constant swing phase duration. However, our study birds were still
walking at substantially slower speeds than other ground-running birds
and even slower than waddling birds, such as ducks (Usherwood et
al., 2008) and penguins (Griffin and Kram, 2000), which also have
relatively short legs and exhibit a comparatively narrower range of
speeds than ground-running birds. The average duty factor of the
commercial lines studied (0.79±0.05) is still representative of other
slow-walking animals including humans (Alexander, 1989; Reilly,
2000; Aerts et al., 2000; Zani et al., 2005).
Typically in human gait studies, individuals who walk more
slowly than healthy controls are deemed to have some form of gait
disability, but slowing down can simply reflect a ‘safer’ and more
‘tentative’ strategy for moving around (Winter, 1989; Powers et al.,
1999; Dingwell and Cavanagh, 2001). This assessment of disability
is a common subjective view of locomotion in human obesity
studies, because obese humans have a similar problem of carrying
extra body mass (Messier, 1994; Messier et al., 1996; Browning
and Kram, 2009; Spyropoulos et al., 1991). Recent studies have
shown that slower walking velocities serve to increase dynamic
stability (Dingwell and Marin, 2006; England and Granata, 2007)
and consequently domestic chickens may benefit from reduced
falling risks at the cost of increased variability in their locomotor
movements. However, it has been shown that individuals can still
display decreased stability despite this compensatory mechanism
(Kang and Dingwell, 2008). Approximately 65% of the total data
were excluded from this study (did not meet criteria for steady state)
because birds were walking at even slower speeds than reported
here, and halting significantly between steps. These halting
movements were often sporadic in nature, with no association with
step number or trial number, and therefore the reasons for this
random unsteadiness were difficult to ascertain. It could be related
to physical constraints, such as decreased strength (DeVita and
Hortobagyi, 2000) or flexibility (Kerrigan et al., 2001), or even
exercise fatigue, which is known to affect gait in humans with
evidence of poorer dynamic stability (Wojtys et al., 1996; Yoshino
et al., 2004; Granata and Gottipati, 2008). From personal
observations, the chickens often became breathless with the mild
exertion of walking, and thus needed frequent rest between trials.
The percentage to live weight of hearts and lungs of broilers is much
smaller as a result of selection (Havenstein et al., 1994a; Havenstein
et al., 1994b; Havenstein et al., 2003b; Schmidt et al., 2009), and
so the influences of their cardiovascular system and perhaps a
reduced ‘cardiovascular fitness’ on their locomotor ability are
important to consider in future studies.
Irrespective of this, a few individuals of the broiler population
were able to achieve a much broader speed range, which is perhaps
surprising, considering that a larger body mass is typically associated
with poorer walking ability (Kestin et al., 1999; Kestin et al., 2001;
Bokkers et al., 2007; Naas et al., 2009). The question then remains
as to whether this broad speed range is indicative of a ‘good’ walking
bird and/or whether it simply reflects differences in the gait
characteristics of these commercial lines. Firstly, the variation in
the lateral velocity of the CoM was substantially smaller in the
broiler population compared with the pureline birds. If we use this
reduced variation as an indicator of improved lateral balance in
walking broilers (Winter, 1989; Holt et al., 1995), this supports our
initial suggestion that the broiler is perhaps a ‘better’ walking bird.
THEJOURNALOFEXPERIMENTALBIOLOGY
Gait dynamics of the broiler chicken
The differences in gait parameters seen (Table4) were generally
quite subtle, with the main changes seen in Pureline B birds, which
have a more crouched limb posture (lower CoM height for same
total leg length). Their longer step length, lower step frequency and
larger sweep angle are typical of this postural change (Gatesy and
Biewener, 1991). This is also associated with significantly greater
circumduction and less vertical displacement of the foot during
swing. Two plausible explanations for this crouched limb posture
may be their wider pelvis and a more cranially positioned CoM,
although more detailed biomechanical analyses are needed to test
this speculation. However, difficulty in walking was perhaps more
evident in Pureline A birds (48% of data not meeting requirements
for steady state), which carry more breast muscle mass compared
with the other populations (Table2). Pureline A birds are ‘front
heavy’, with the breast muscle mass concentrated at the cranial end
of the keel. We therefore suggest that not just the breast muscle
mass, but also the way it is distributed along the length of the keel,
potentially has a major effect on the way that domestic chickens
walk. To test this speculation, future studies could test whether
alterations in CoM caused by such changes in morphology cause
alterations in joint moments or tissue forces.
Across all bird populations, we found that our study chickens
generally took shorter steps than other ground-running birds, related
to their much slower velocities, and had an extremely wide trackway
width, substantially (~18%) larger than hip width. As a result, these
birds held their feet in a position more lateral to the hip, which
allows them to increase their lateral base of support and also provides
a larger potential for mediolateral motions of the CoM (Donelan et
al., 2001). This lateral motion was seen across all commercial lines
and is a common feature of waddling birds, usually attributed to
their short legs and wide base of support (Pinshow et al., 1977;
Griffin and Kram, 2000; Abourachid, 2001; Usherwood et al., 2008;
Nudds et al., 2011). Our study’s commercial line birds moved their
CoM ~23% of hip height with each step and subsequently rolled
their body laterally over the planted foot whilst the contralateral
limb was in swing phase. Adjusting step width and step length are
also key to redirecting the CoM to remain within the base of support
and prevent falling (Winter, 1991), and, similar to humans, the
chickens studied have a more variable step width than step length.
These chickens may rely on more precise foot placement to control
their lateral stability (Kuo, 1999; Bauby and Kuo, 2000) in contrast
to penguins, which have been shown to have a more consistent step
width and rely more on modulation of their trunk instead (Kurz et
al., 2008). Further perturbation studies are needed to test whether
this variance is associated with precise placement of the foot and
is not simply the result of a lack of control or instability, which is
commonly observed in these broiler populations. If waddling clearly
provides some benefits for penguins (Griffin and Kram, 2000; Kurz
et al., 2008), what does waddling mean for the modern broiler and
its generation lines?
The observed lateral motions resulted in high mediolateral
forces, which generally exceeded fore–aft forces across all bird
populations and were also substantially larger in the right limb.
The reason for this asymmetry is not clear, but may be linked to
limb dominance and a subsequent preference to use the right limb
for balance control, because our study birds also showed greater
lateral displacement of the right foot. Similar to elderly individuals
with imbalance, domestic chickens may swing the contralateral
limb more laterally to counterbalance the evident lateral roll over
the supporting leg (Chou et al., 2003). This would explain why
the subsequent mediolateral forces experienced by the left limb
were substantially reduced. The mediolateral forces were
3245
significantly larger in the broiler population, which is likely
attributable to their evidently greater limb motions, with the
broiler population lifting their limbs significantly higher during
swing and consequently exhibiting the largest changes in leg
length. A gradual decline in leg length and leg angle is still evident
through the stance phase of all three bird groups, which probably
is associated with slight flexion–extension of the knee (Jacobson
and Hollyday, 1982; Johnston and Bekoff, 1992) and toes (Reilly,
2000), supported by our personal observations during these
experiments. The angle of the limb was highly variable during
the swing phase, which likely corresponds to the high variation
in the vertical and lateral displacement of the foot during swing
before being placed on the ground to establish a new base of
support for gait progression. The significantly greater vertical
forces reported in the broilers compared with Pureline A birds
are presumably the direct result of this group of birds tending to
lift their feet much higher off the ground with each step. Pureline
B birds still experienced similar peak forces, despite their more
crouched limb posture, which would usually be considered as a
strategy to reduce the peak vertical forces experienced by the limb,
in a manner similar to bent-knee running in humans (McMahon
et al., 1987). This group may have a more plodding gait, involving
greater impacts of the feet with the ground early in stance phase.
If the chicken populations studied were indeed walking steadily
over ground, the kinetic energy and potential energy changes would
be the same at the beginning and the end of each step and would
fluctuate around zero (Alexander and Jayes, 1978; Griffin et al.,
2004). The changes in CoM energies did indeed fluctuate around
zero, but were extremely variable, highlighting the apparent
instability of walking in purelines and broilers. It is therefore difficult
to determine whether these birds perform similar quantities of
positive and negative work, and thus how much their muscles may
be actively contributing to each step. The broiler population
appeared to have significantly different kinetic energy changes to
the Pureline B population, but we hesitate to make inferences from
these data. In all three commercial lines, the fluctuations in kinetic
energy were small and the CoM displacement across a step was
also minimal, reflecting small changes in gravitational potential
energy. Passive pendular mechanics are well used among other
cursorial birds and other terrestrial animals (Cavagna et al., 1977;
Heglund et al., 1982; Blickhan and Full, 1992; Muir et al., 1996;
Griffin and Kram, 2000; Ahn et al., 2004; Rubenson et al., 2004;
Biewener, 2006; Biknevicius and Reilly, 2006), but this is usually
achieved at intermediate walking speeds in birds (Cavagna et al.,
1977; Rubenson et al., 2004). The capacity for these commercial
line birds to therefore recover mechanical energy through pendular
mechanics is likely to be low as a direct result of their slow walking
speeds. This has also been reported in other slow-walking animals
[geckos (Farley and Ko, 1997); alligators (Willey et al., 2004);
tortoises (Zani et al., 2005); elephants (Ren and Hutchinson, 2008)].
The subtle gait differences among this study’s three groups led
to varying amounts of work performed on the CoM in different
directions. For example, the largest amount of mediolateral work
was performed by the broiler population, whereas the shorter steps
and lower peak vertical forces of the Pureline A birds allowed this
group to perform less work in the vertical direction. Despite the
subtle differences in gait reported here, these commercial line birds
not only have similar mechanical costs of transport, but when
compared with the ostrich and guineafowl, appear to perform no
greater mechanical work. The mechanical cost of transport of these
commercial lines is substantially lower than that of guineafowl at
the same walking speed, and our results are consistent with the
THEJOURNALOFEXPERIMENTALBIOLOGY
3246 The Journal of Experimental Biology 216 (17)
widely accepted evidence that the cost of transport decreases with
increasing body size (Langman et al., 1995). The large lateral
motions of our study chickens result in similar amounts of work
performed in the lateral and fore–aft directions, but it is possible
that the relatively small limb movements we report here compensate
for the mechanical work of moving the body CoM in the lateral
direction. Constraining step length also has the additional advantage
of reducing mechanical work, because step length increases
mechanical work to a greater extent than step width (Donelan et
al., 2001; Donelan et al., 2002). The observed waddling movements
therefore do not, as sometimes thought, require excessive work.
However, slight caution should be taken when interpreting these
values. It must be noted that the MCoT was calculated using the
combined limbs method, which is known to underestimate the
external mechanical work performed in walking (Donelan et al.,
2002). As a result, these values are likely to be an underestimation
of the true magnitude in broilers, guineafowl and ostrich, especially
when the mechanical work performed by each individual pelvic limb
is unknown.
Unfortunately, a low MCoT does not necessarily correlate with
low metabolic costs. Contradictory patterns exist in the literature,
with mechanical energy recovery associated with low and high
metabolic costs. These metabolic costs can be associated with a
number of factors, including step-to-step transitions or step width
(Donelan et al., 2002), the cost of muscular force generation (Kram
and Taylor, 1990; Kram et al., 1997; Hoyt et al., 2000; Griffin et
al., 2003), the swing phase of locomotion (Marsh et al., 2004) or
even slow walking speeds (Langman et al., 1995). Indeed, the
absence or poor use of pendulum-like energy exchange that we report
here, as well as the active, lateral limb movement of their limbs that
we suggest chickens use for stability, may also exact a metabolic
cost (Donelan et al., 2001; Shipman et al., 2002). Hence, the
relationship between the mechanical work and the metabolic cost
of locomotion is difficult to assess and has not been measured in
the modern broiler chicken. Testing this issue is particularly difficult
because the commercial chicken lines used in this study are unable
to walk steadily and consistently long enough to obtain reliable direct
measurements of metabolic cost; hence either validated indirect
measurements on other birds or else novel ways of measuring
metabolic cost directly are needed to determine how costly walking
is for these chickens.
Our study has shown how subtle changes in the morphological
characteristics of the broiler chicken and its generation lines can
lead to changes in locomotor dynamics. We have highlighted the
potential mechanical benefits of slow walking speeds, a wide base
of support and large lateral, essentially ‘waddling’ motions for the
broiler, as well as showing that the seemingly awkward gait of the
broiler may not be as ‘inefficient’ as previously thought. Actually,
the gait of the modern broiler shows rather surprising similarities
to other avian bipeds. However, the influence of broilers’ unusual
three-dimensional movements on the occurrence of skeletal
pathologies is unknown. These large lateral motions, which appear
to be essential for the forward progression of the broiler, could play
a role in the development of skeletal pathologies; a speculation that
deserves testing in the future.
ACKNOWLEDGEMENTS
Other members of the Structure and Motion Laboratory at the Royal Veterinary
College are thanked for their assistance during experiments and data analysis,
including, but not limited to, Sharon Warner and Rebecca Fisher. We also thank
undergraduate student Will Parker for assistance in experiments and dissections.
Two anonymous reviewers gave helpful constructive criticisms that improved this
manuscript.
AUTHOR CONTRIBUTIONS
All authors contributed equally to this work. H.P. collected the experimental data,
and H.P. and M.A.D. were involved in the main analysis. H.P. wrote the paper and
all authors discussed the results and implications and commented on the
manuscript.
COMPETING INTERESTS
No competing interests declared.
FUNDING
We thank Cobb-Vantress Inc., especially Roy Mutimer and Kate Barger, for their
support on this project, which was part of a CASE Industrial Partnership PhD
studentship to H.P., funded by the Biotechnology and Biological Sciences
Research Council (BBSRC) of the UK. Additional support from BBSRC grant
number BB/I02204X/1 to J.R.H. and M.A.D. is acknowledged.
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