Infrared skin temperature measurements for monitoring health in pigs: a review
Soerensen and Pedersen Acta Veterinaria Scandinavica
Infrared skin temperature measurements for monitoring health in pigs: a review
Dennis Dam Soerensen 0
Lene Juul Pedersen 0
0 Department of Animal Science, Aarhus University , Blichers Alle 20, PO Box 50, DK-8830 Tjele , Denmark
Infrared temperature measurement equipment (IRTME) is gaining popularity as a diagnostic tool for evaluating human and animal health. It has the prospect of reducing subject stress and disease spread by being implemented as an automatic surveillance system and by a quick assessment of skin temperatures without need for restraint or contact. This review evaluates studies and applications where IRTME has been used on pigs. These include investigations of relationships between skin, ambient and body temperatures and applications for detecting fever, inflammation, lesions, ovulation, and stress as well as for meat quality assessment. The best skin locations for high correlation between skin temperature and rectal temperature are most likely thermal windows such as ear base, eye region and udder. However, this may change with age, stressors, and biological state changes, for example, farrowing. The studies performed on pigs using IRTME have presented somewhat discrepant results, which could be caused by inadequate equipment, varying knowledge about reliable equipment operation, and site-specific factors not included in the assessment. Future focus areas in the field of IRTME are suggested for further development of new application areas and increased diagnostic value in the porcine and animal setting in general.
Infrared thermography; Temperature; Fever; Thermoregulation; Pig
Infrared thermography (IRT) and infrared thermometry
(IRTM) are non-contact temperature measurement
methods, which offer several advantages over other
temperature measurement methods used in veterinary
medicine. Infrared (IR) temperature measurements
considerably reduce the risk of spreading infection, since
touching the subject is unnecessary. In animals, this is
advantageous since handling and restraint increases
stress, causing an effect on core and surface
temperatures [1-7]. Due to the non-obtrusive nature of IRTME,
it is an insignificant stressor, theoretically making it
well-suited for assessment of animal stress and welfare.
The potential of IRTME is reflected in the various
applications for which it has been used. IRT was used
successfully for detecting meat defects [8-12] and has been
attempted for predicting estrus from vulva surface
temperature [13-15]. Others have used IRTM  and
IRT [17,18] in feed and digestion studies to evaluate its
suitability for, aiding or replacing calorimetry. IRTME
does not affect the temperature of the object surface by
conduction or convection, which is the case with regular
temperature sensors. IRT acquires thermal images,
enabling measurement of surface temperature
distributions, suited for detecting localized anomalies. It is
possible to select regions of interest (ROIs) in the
thermal images, thereby only selecting specific areas of
interest for subsequent data analyses. These ROIs may
be analyzed by spots (e.g. single pixel), lines, or areas of
various shapes. While IRT produces thermal images
with many pixels, IRTM utilizes only one pixel, which
measures the average temperature of the area it covers.
IRT is fitting for measuring skin temperature in pigs,
since pelage of pigs is different than many other
mammals, which have more hair coverage. Even though pig
hair is much coarser than human hair, hair density is
comparable to that of humans , offering several bare
skinned surface areas.
Reviews covering the use of IRTME on animals [20-24]
have had very little focus on pigs. The aim of this review is
to assemble studies investigating use of IRTME on pigs
with focus on the temperature relationships between
environment, skin, and body as well as detection of fever
and other health issues.
Surface temperature in relation to ambient temperature
Thermoregulatory ability in pigs increases with age. As
opposed to a piglet having less than 2% body fat during
the first two weeks of life , an adult pig has a thicker
fat layer, a denser hair coat and a smaller surface to
volume ratio, enabling them to limit the heat flow from the
body core to the surroundings. From here on, body core
temperature is referred to as body temperature. Piglets
maintain their body temperature by reducing the
exposure to the colder environment, for example, by huddling
and by increasing their heat production by shivering
[26-28]. Due to their lack of insulation, newborn piglets
may be looked upon as one large thermal window,
where the skin temperature is almost uniform
throughout the body surface. A thermal window is a skin area,
which is always well perfused by blood and as such is a
window to the body temperature . This in
opposition to a non-thermal window, such as the ear flap or
shoulder, where blood perfusion to the outer skin
surface is controlled by thermoregulation. From here on,
when referring to measured skin temperatures, they
have been measured by IRT or IRTM, if not mentioned
IRTME measures the surface temperature of pigs. The
surface temperature of the skin (hairy or bare) is
influenced by environmental ambient factors and the
thermoregulatory response by the body that maintains a
stable body temperature. Therefore, if an elevated skin
temperature due to fever is to be detected correctly, it is
necessary to quantify the effect of ambient temperature
on skin temperature for non-febrile pigs. Ultimately,
this should be included in a correction formula, which
could be used for fever determination purposes. The
few studies that have investigated this relationship are
summarized in Table 1. These studies vary in their
approach regarding the area of skin, age, breed,
experimental setting and use of different IRTME and
methodology. This makes it impossible to combine the findings
into one correction formula. However, studies have
shown that skin areas with an increased fat layer
(nonthermal window), which may be breed dependent, have
a lower regression constant and higher coefficient .
This means that skin temperature is lower at low
ambient temperatures due to the fat insulation, while
increasing ambient temperature rapidly increases the skin
temperature, due to the vasocontrolled
thermoregulation, supplying more blood to the skin tissue. As
expected, of the studies included in Table 1, the thermal
windows exhibit higher regression constants and lower
regression coefficients than the non-thermal windows, as
they are less affected by the ambient room temperature.
Surface temperature in relation to core body temperature
Knowing the skin temperature for non-febrile pigs under
different ambient temperatures may not be enough for
measuring elevated body temperature, which is the
most important indicator of fever. A prerequisite for
detecting elevated body temperature by measurement of skin
temperature is a sufficient correlation between the two.
Table 2 summarizes the studies that have investigated the
correlation between skin surface temperatures measured
using IRTME and body temperature. Usually, the body
temperature remains relatively constant due to
thermoregulation, but in certain situations, body temperature is
regulated or altered: fever, hypothermia, digestion,
parturition, and diurnal rhythm. Body temperature is usually
determined by inserting a lubricated thermometer into the
rectum, with the probe touching the mucus lining.
Penetration depth depends on size of the pig, but in an adult
sow, the probe should be inserted approx. 10 cm into the
rectum. See Table 3 for normal rectal temperatures in
resting pigs of different age at ambient temperatures in the
Correlation between skin and body temperature
The limited amount of studies found in the literature
that investigated the correlation between skin and body
temperature include a range of ages from newborn
piglets to old sows. Furthermore, the biological status of
the investigated pigs was different, for example, with
sows being investigated around the time of farrowing
[31-33], slaughter pigs just killed with carbondioxide and
exsanguinated in a stressful abattoir , and growing
pigs being inoculated with Actinobacillus
pleuropneumoniae . This makes it difficult to compare the
correlation between skin and body temperature even between
the same skin areas. However, there are indications that
the skin measurement sites for highest correlation to
body temperature are the ears, eyes and udder. One
study  found that the skin areas with the highest
repeatability were the eyes and ears, even though the vulva
skin area (when lying down) exhibited the highest
correlation (r = 0.49) to body temperature. The standing
position reduced the correlation substantially (r = 0.32),
which is difficult to explain physiologically and may
emanate from differences in methodology. In contrast,
another study  did not find any correlation between
vulva surface temperatures and body temperature, but a
significant correlation between the vulva surface temperature
and ambient temperatures was observed. This may be
explained by the limited acclimatization period (30 min.) and
moisture in the vulva orifice, causing cooling by evaporation,
since within the ROI, the minimum temperature was 20.6C
and the maximum was 35.6C.
The correlation between the ear skin and body
temperature seems highly dependent on the exact location
Norwegian, Finnish and 26
Dutch Landrace and
Great Yorkshire Crossbred [Large White Landrace] Pitrain
Ear base, abdomen
(caudal) and upper
medial side of legs
Part of body with the
Snout Udder (caudal) X X
Thermal Window Tambient Regression Constant, Regression Correlation (r) and
(X: yes) [C] T0 [C] (A) coefficient, b (A) goodness of fit (R2) (A)
r = 0.830.91 (**)
r = 0.68 (***)
R2 = 0.97 (***)
R2 = 0.44 (***)
R2 = 0.57 (***)
Magnani et al. 
Chung et al. 
Yorkshire LR (Gnotobiotic)
Malmkvist et al. 
Danish LR Yorkshire
Sykes et al. 
Before after parturition.
Hairy sites were trimmed.
Tabuaciri et al. 
Large White (LW) LR, LW Duroc
AIf only the coefficient of determination (R2) was provided in the article, the magnitude of the correlation (r) between body and IR measured skin temperature was calculated by taking the square root of R2. *:P < 0.05,
**:P < 0.01, ***:P < 0.001.
BIndicates measurement sites that are both thermal windows and not thermal windows.
CTemperature was the mean of the 3 spots of the ear (base, middle, and tip). Body temperature was measured by aiming IR spotmeter on blood on concrete floor, lost from sticking neck vessels.
DNumbers provided from personal communication.
Back (crown to rump) X N/A 0.85
Table 3 Normal rectal temperatures in resting pigs in the
thermoneutral zone. Modified from 
Young sows, gilts
of which the skin temperature was measured. The ear flap
is an important thermoregulatory area, while other areas
such as the ear base and ear canal area may be considered
thermal windows. This may explain the discrepant results
reported [4,7,32,33,39] and is nicely highlighted in the
study by Tabuaciri et al. , who found a much higher
correlation between the body and skin temperature of the
ear base (r = 0.85) compared to the ear tip (r = 0.27). The
study by Warriss et al.  differed from the other studies
by the method used for measuring body temperature (see
Table 2). Their reported high correlation (r = 0.71) could
be due to the stunning damage to the pigs brains, altering
their vasocontrolled thermoregulation and the stressful
situation in which the measurements took place (a
commercial abattoir). Stress is known to have a significant
effect on the surface temperatures of the ear and eyes 
and the loin  in pigs. The initial vaso-constrictive
response decrease the skin temperature, while after some
time, this may subside, followed by an increase in skin
temperature, releasing heat built up in the core from the
initial vasoconstriction . Similar results were found in
rabbits  and cattle [41-43]. A low correlation coefficient
(r = 0.02) between the eye and body temperature was
observed in response to a stressor (a backtest) in pigs .
Other studies investigating the correlation between eye
and body temperature reported higher correlation
coefficients, which has also been reported in humans [44-46]
and ponies . Perhaps a pig study focusing specifically
on the inner canthus, with adequate equipment (high
spatial resolution and accuracy) and using the maximum
pixel temperature would reveal higher correlation, as seen
in humans [44-46]. The inner canthus of the eye was
chosen as the best site for fever screening in humans
[48,49] due to the relatively easy access and its high
correlation to body temperature. However, the high correlations
reported were often based on tympanic temperature as
the reference for body temperature and one study
questions the suitability of the inner canthus to estimate body
temperature , while another suggests the ear canal as a
potentially better site . Regardless, if the maximum
temperature is to be detected in such relatively small areas
or orifices as the inner canthus and the ear canal opening,
the demand for a high spatial resolution is essential. Use
of maximum or near maximum pixel temperatures for
body temperature estimation in pigs is further supported
by Traulsen et al. , who found that the maximum,
average of the top-10% or top-25% IRT pixel temperatures
in sows yielded higher body temperature correlation than
average or minimum pixel temperatures for all the
investigated surface areas (see Table 2).
A few studies performed a regression analysis of the
skin - body temperature relationship in pigs
(summarized in Table 4). Even at similar ambient temperatures,
the studies reveal notably different regression constants
and coefficients. This may be due to the limited
variation in body temperature, even when observed animals
were febrile. Furthermore, accuracy of the rectal
thermometer measurements may be influenced by the
experience of the operator and this may account for the
variability between measurements. The only study that
did not use rectal measurements for measuring the
body temperature was also one of the studies with the
highest regression coefficient . They measured body
temperature from blood lost from a sticking wound.
However, with the large range of the measured body
(blood) temperatures (35.642.6C), the results are
questionable. Another explanation for the discrepant
results in Table 4 (and Table 2) may be due to the skin
body temperature relationship not being linear, at least
for some skin areas. Malmkvist et al.  found an
increased correlation coefficient (r = 0.32) for the snout if
using a quadratic relationship vs. a linear (r = 0.21) and
Traulsen et al.  found a significant quadratic
relationship between the skin and body temperatures in all
investigated skin areas other than the vulva and eyes
(see Table 2).
Detection of fever in pigs
Fever, as determined by rectal temperature, has been
shown to elevate the skin temperature significantly in pigs,
although with an expected time delay . However, the
skin temperature does not increase equally over the entire
pig surface. Traulsen et al.  observed average skin
temperature increases in sows, ranging from 0.20C for
the vulva to 0.56C for the inner ear and up to 0.99C for
Johnson and Dunbar  reported a skin temperature
increase 6 days post inoculation (classical swine fever) of
5.8, 12 and 10C for the edge of ear, foot and entire body
surface, respectively. They also observed the maximum
temperature of the entire body surface was found inside
the hind legs and on the dorsum of the pig. Similar results
have been reported in pigs infected with the A. epizooticae
virus (foot and mouth disease) with maximum foot skin
temperature elevating by more than 10C three days after
Dewulf et al.  also investigated pigs with classical
swine fever and deemed skin temperature measured using
IRTM as insufficient for fever detection, since no reliable
Breed Size/Age Surface area(s) Thermal window
Dewulf et al. 
Warriss et al. 
Chung et al. 
Kammersgaard et al.  91
148 hours Entire piglet from dorsal view
and sagittal view
r = 0.71 , (C)
No significant relationship
Adj. R2 = 0.34
Adj. R2 = 0.09
Adj. R2 = 0.19
Avg. of max. IR pixel temp.
from dorsal view and sagittal view
Legs (carpus and tarsus)
Inner side of ear pinna
15, 20, and 25
rectal temperature could be predicted, even though a
significant correlation was observed (see Table 4). Wendt
et al.  also investigated the diagnostic power by
measuring ear base skin temperature, obtained by using regular
thermocouple sensor put against skin. The sensitivity and
specificity for sows were 79.0%, 69.3%, respectively, with
positive (healthy) and negative (febrile) predictive values
of 78.5% and 70.0%, respectively. Similarly for young pigs
the numbers were 55.8%, 93.6%, 84.0% and 77.7%,
respectively. Schmidt et al.  were able to detect 6 and 7 febrile
sows out of 10, from eye and ear base temperature,
respectively, where fever threshold values were based on
90% quantiles. Most of the diagnostic performance
numbers presented in the mentioned studies are on the low
side and may not be satisfactory in most settings. This
may pertain to the delay between increase of skin and
body temperature from febrile onset as observed in
One investigation used IRT for pen-level fever detection
in pigs . Instead of investigating the individual pigs for
fever, the maximum temperature measured in pens with
approx. 20 pigs was used for detection of pens with
Actinobacillus pleuropneumoniae infection. Pens with mortality
had significantly higher maximum pen temperature
compared to three control pens (with no mortality) on the day
that the mortality was observed, and the two days before.
With each increase by 1C in maximum pen temperature,
the odds of a pen having mortality increased 3.6 times. The
concept of using the group of pigs as its own control by
comparing to a priori temperature measurements, was
investigated further in another study , which found
thermal response to a vaccination using a surveillance system.
Detection of inflammation and lesions
Sabec and Lazar  showed that boars with palpable
symptoms of osteoarthrosis tarsi deformans had
significant increased average skin temperature (36.27C) of
the surrounding skin surface when compared to boars
without palpable symptoms (35.64C). Savary et al. 
showed that IRT enabled detection in 40% of leg joints
with proven acute inflammation, but only 9.5% of
leg joints with chronic inflammation. With their
diagnosis criteria, IRT indicated approx. 10% of leg joints
in healthy pigs to be inflamed. They observed large
temperature differences (>1C) between symmetrical
regions in more than one fourth of the leg joint
measurements in healthy pigs, questioning reliability of this
method for detecting inflammation based on asymmetry
alone. The measured asymmetries in healthy pigs of
>1C are high compared to the max of 0.5C found in
healthy humans [61,62]. This discrepancy could be
explained by the housing facilities in which pigs rest. One
could speculate that hard floors would cause elevated
temperatures on the surface areas bearing the weight of
the pig, causing major changes in the subdermal tissue,
as is seen in sows with decubital pressure ulcers .
Active dynamic thermography (ADT) is a method by
which IRT recordings following an external heat or cold
exposure may reveal differences in the underlying tissue of the
surface in question due to different recooling or reheating
patterns. Thermal properties of pig skin have been shown to
change when burned [64,65]. In these studies, pig skin was
used for modeling human skin and they showed that ADT
performed just as well as the histopathological method
(reference), in evaluating skin burn depth, whereas the clinical
method (using traditional observational criteria) and static
IRT performed worse. The ADT and hisopathological
methods performed equally, exhibiting 100% accuracy,
sensitivity, and specificity. For the clinical method, these 3
numbers were 60.9%, 50%, and 100%, respectively, while for the
static IRT method, the numbers were 91.3%, 94.4%, and
80.0%, respectively. ADT has also been found to be superior
compared with static IRT when characterizing wound types
and assessing pressure ulcers .
Improving infrared measurements and their applications
Obviously, we cannot claim that IRT should be the new
gold standard for detecting fever in pigs from the
diagnostic test results reported in the literature.
There is a great demand for a comprehensive study
using calibrated, accurate IRTME investigating pigs from
different age groups (with known fat layer), at different
skin areas, and at a varying range of ambient
temperatures. Findings from this could result in correction
formulae (linear or quadratic), which could be used in a
number of different settings, where variation in ambient
temperature, age, and skin location could be accounted
for. Ultimately, this would then be used as a rough
baseline value; from which discrepancies could be attributed,
e.g. fever. Furthermore, including ADT in future
diagnostic tests may reveal that this method is not only
suited for detecting localized skin damage or
inflammation [64,65], but also for elevated systemic temperatures.
Adopting techniques as proposed by Ng and Kee 
could further improve diagnosis. Ng and Kee  used a
combination of parabolic regression, learning algorithms
and receiver operating characteristics (ROC) analysis
instead of the conventional method consisting of linear
regression and ROC analysis. In doing so, they increased
the accuracy of diagnoses in fever screenings of humans.
Accuracy rate for the same measurements was increased
from 93% to 96%, while sensitivity and specificity
changed from 85.4% and 95% to 95% and 85.6%, respectively.
The diagnostic toolbox additions as mentioned above may
be insufficient for improving fever detection from IRT
measurements. If the skin measurements themselves are
inaccurate, fever diagnosis will inevitably be inaccurate.
However, todays advanced IR cameras provide fairly
accurate temperature measurements with good spatial and
thermal resolution. Furthermore, diagnoses based on skin
measurements using IRT could be improved considerably
by creation of standardization protocols as have been
made for fever screening in humans [48,49,68]. Operators
of IR cameras should be trained properly, knowing the
limitations of the equipment . This could reduce the
variability in temperature measurements due to operator
errors, e.g. wrong choice of skin emissivity or incorrect
measurement of reflection temperature . In addition
to this, introducing the Digital Imaging and
Communication in Medicine (DICOM) standard in the field of IRT in
general as suggested by some scientists [71,72] will be a
valuable addition. If used correctly, this will enable
researchers and scientists to compare IRT measurements
performed with different devices by different operators
knowing that factors like distance, reflections, angles,
emissivity, poorly calibrated devices, etc. have been taken
into consideration for best possible measurement results.
Obviously, thermal properties between animal species and
breeds are different due to several factors, such as
body temperature set points, thermoneutral zone
differences, thermal windows, and hair density. These factors
should be considered when comparing any temperature
Further research on use of IRT for pig health screening is
still needed before it can be used as a reliable diagnostic
tool. Studies performed to date are inconclusive due to
much variance in results. Most of which are likely to arise
from inaccurate measurements and methodology
differences. IRT shows great potential in some health
applications where it may become superior to other methods.
However, ground research incorporating metrological
approaches for accurate measurements is necessary to
make IRT a reliable standardized method for detection of
changes in body surface temperatures due to fever,
inflammation, stress, pain or other conditions.
Thorough investigations of surface temperature
distributions of healthy pigs of different age groups, breeds
and in different environments is the first step towards
improving detection of unhealthy pigs. Furthermore,
skin temperature progression at different stages in the
course of fever for various diseases should be made. This
could enable detection of sick animals prior to evidence
of clinical symptoms.
The authors declare that they have no competing interests.
DDS reviewed the literature and drafted the major parts of manuscript. LJP
made substantial contributions to the drafting of the manuscript. Both
authors read and approved the final manuscript.
The authors greatly appreciate the input from Katrine Kop Fogsgaard, Mette
S. Herskin and Trine Sund Kammersgaard from Department of Animal
Science at Aarhus University in shaping this review. The work was supported
by The Danish National Advanced Technology Foundation and Danish
Centre for Animal Welfare.
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