Next Article in Journal
HSAW: A Half-Face Self-Attention Weighted Approach for Facial Expression Recognition
Previous Article in Journal
Optimization of Green Sample Preparation for the Determination of Hydroxycinnamic Acids in Multi-Floral Honey Using Response Surface Methodology
Previous Article in Special Issue
Thermal–RGB Imagery and Computer Vision for Water Stress Identification of Okra (Abelmoschus esculentus L.)
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

A Precision Livestock Farming Technique from Breeding to Slaughter: Infrared Thermography in Pig Farming

1
Department of Human Science and Quality of Life Promotion, Università Telematica San Raffaele Roma, Via di Val Cannuta 247, 00166 Rome, Italy
2
Department of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, Via della Commenda 10, 20122 Milan, Italy
3
Department of Agricultural and Food Sciences, Alma Mater Studiorum Università di Bologna, Viale Fanin 46, 40127 Bologna, Italy
*
Author to whom correspondence should be addressed.
Appl. Sci. 2024, 14(13), 5780; https://doi.org/10.3390/app14135780
Submission received: 22 May 2024 / Revised: 21 June 2024 / Accepted: 27 June 2024 / Published: 2 July 2024
(This article belongs to the Special Issue Recent Progress in Infrared Thermography)

Abstract

:
Infrared thermography is a contactless imaging technique, useful for measuring surface temperature at distance, which has been widely applied in animal production. The possible applications within the pig husbandry include sow heat detection, the reduction in the incidence of neonatal mortality, the recognition of the febrile state caused by pathogens, the study of metabolic efficiency, the evaluation of stress caused by heat, by constraints, or by aggressive interaction, and meat quality prediction. Even if this technique could be easily influenced by environmental factors, the continuous improvement in the procedures and the decrease in the cost of the equipment will allow for new and more applications in swine farming in the future.

1. Introduction

Thanks to its characteristics, thermography is a very well-suited technique to operate in extremely diverse contexts, such as building, plant engineering, human medicine, and, likewise, precision animal husbandry [1]. Within animal husbandry, its applications are innumerable, and they encompass silage control, udder health, oestrus detection, stress assessment, and early diagnosis of certain diseases, to name a few [2].
Swine husbandry has good prospects because of its high feed conversion efficiency, quick body weight gain, high fecundity, and prolificacy and economic aspects of a swine breeding depends on maintaining good herd health. The animals’ exposure to stressful conditions has been increased together with the intensity of pig production and could be harmful to their welfare and productivity [3].
In the field of pig farming, thermography is highly suitable to operate by remotely sensing the skin temperature, being able to measure temperatures without coming into contact with or interacting with the individual, thus not altering their behavior, and in a completely noninvasive manner insofar as it does not require any restraint.
Such a range of applications makes infrared thermography a widely usable technique for obtaining some important information about the thermal status of animals, through which the management of production stages and operations on individuals can be faster and more effective [4]. The proper use of the thermal imaging camera is not uncomplicated, and thermographic techniques at the farm should be carried out with care. Indeed, the thermal imaging cameras don’t directly measure the surface temperature like the contact probes, but they capture the electromagnetic radiation emitted from any object at a temperature above absolute zero (−273.15 °C). This radiation, which is not harmful to living organisms, and not detectable by the human eye, is closely connected to the object temperature through specific physical formulas, called Planck, Wien, and Stefan–Boltzmann laws, that are part of the camera software [5]. It follows that the IRT camera is a device capable of measuring the surface temperature of a body by detecting the infrared radiation emitted by it.
The two-dimensional thermal map of the captured body is then presented as a false-color image (Figure 1), in which each pixel represents the surface temperature of the object at that point. The colors chosen are based on a chromatic scale, which can be adjusted using various dedicated software on the market and chosen based on requirements. Multiple confounding factors, both environmental and animal-specific, can affect this process, as will be examined in Section 3.

2. Application of Thermography in Pig Breeding

Below, the most relevant applications of this technique in the field of swine will be briefly explained, in order to provide an overview of its potential (Table 1).

2.1. Oestrus Detection

Thermography is highly suitable for detecting changes in the surface temperature of the vulvar area (Figure 1) in gilts and sows during the heat period, because it is not covered in bristles. In addition, the changes can be easily measured by the operator, when the individual is placed inside an insemination cage and has its backside facing the passageway. A few studies on oestrus detection [6,7,8] have shown that the peak vulvar temperature reaches values just above 36 °C in the pre-ovulatory phase, while in gilts, it is lower by about half a degree. Subsequently, 12 h before ovulation, these values decrease to 34.6 °C and 33.9 °C, respectively. Like previous authors, they have confirmed the changes in vulvar temperature associated with oestrus, having found values slightly higher than those indicated above and having noticed the absence of any relationship between vulvar temperature and rectal or buttock surface temperature [9]. Recently, Lee et al. have shown that the simultaneous application of thermographic measurement and ultrasonic sensors, used to quantify the time sows remain standing, tends to improve the success of artificial insemination interventions [10].
Altogether, it seems clear that thermography is suitable for detecting changes in vulvar temperature at different stages of the ovarian cycle and may be an applicable technique, not only in detecting oestrus, but also in monitoring its lowering toward the ovulation phase. At present, the cost of thermographic sensors is still high, but it is expected to drop over the coming years, thus making their permanent placement possible inside sow farms, in order to identify the best moment to carry out inseminations.

2.2. Neonatal Mortality Reduction

Neonatal hypothermia is known as a frequent cause of mortality in pre-weaning piglets, particularly affecting those individuals who have lower temperatures during the first few hours after their birth [11]. As a rule, those individuals who weigh less at birth have a hard time recovering from the initial drop in body temperature, which occurs during the first hour after birth, and they subsequently struggle to maintain it within an adequate level [12]. The use of a digital thermometer for measuring rectal temperature (RT) is considered the gold standard, so it has been widely used in piglet viability research. Thermography allows faster and continuous identification of those piglets requiring supportive interventions in the immediate postpartum, thus enabling the aforementioned interventions (Figure 2).
The thermoregulatory capacity of newborn piglets is related to their body energy and metabolism, which can be influenced by genetic differences among different existing breeds, such as average weight and metabolic efficiency. We also need to consider external factors, such as air temperature or the state of piglets’ skin (wet or dry). Drying piglets at birth, placing them near a heat source, and providing them with some energetic supplementation improves their thermal status and prevents hypothermia, but it is necessary to pay attention before shooting with the thermal camera, because emissivity of the wet skin is different from that of dry skin and the presence of heat sources can affect data [12,13]. Llamas Moya found out that the skin temperature was not related to birth weight but was influenced by the huddling behavior of piglets and their location (near or far) from a heat source [13], and Tabuarici found out that the IRT data were not predictive of mortality risk, however, they could be used to predict shivering [14]. Note that although not all piglets suffering from hypothermia would shiver [15], IRT could be used to identify and help piglets in need in order to limit mortality.
Schmitt has carried out a study regarding the possibility of applying thermography to the assessment of thermoregulation differences among piglets belonging to two genetic lines, whose growth efficiency is lower or higher. Piglets belonging to a genetic line with higher efficiency showed a higher temperature at both the 15th and 30th minute postpartum, particularly the ear temperature, suggesting an effect of the genetic selection for feeding efficiency on neonatal thermoregulation abilities [16].

2.3. Fever or Diseases Early Detection

The increase in body temperature in pigs caused by some bacterial or viral infection can be detected using the thermographic technique. After induced infection using pathogens, several examples of surface temperature measurement can be found for different parts of the body. In comparison with the rectal temperature, response times are more delayed yet still present. A total of 6 days after classical swine fever virus inoculation, Johnson and Dunbar reported an increase in skin temperatures by 5.8°, 12.0°, and 10.0 °C on the edge of the ear, foot, and on the entire body surface, respectively [26]. The same Authors have also observed that the maximum body temperature was detected on the inside of the hind legs and on the back of affected individuals. Similar results have been reported on pigs infected with the foot-and-mouth disease virus, showing increases in the maximum temperature on foot skin by more than 10 °C, three days after the infection [27].
The evaluation of the temperature increase of the skin surface on pathogen-infected pigs has been carried out in several studies and has included Escherichia coli [28], Actinusbacillus pleuropneumoniae [29,30], and foot-and-mouth disease [27].

2.4. Growing Pig Efficiency

In the context of evaluating temperature changes related to food intake and its energy content, Loughmiller examined the effects of four diets that were characterized by increasing levels of metabolizable energy and equal to 0.75, 1.5, 2.5, and 4.7 (ad libitum) times compared to the maintenance energy diet (MEm) [17]. The thermographic images have been taken three times a day for three consecutive days, starting from the fifth day after the onset of the trial, because the first four days were used for the adaptation to such diets. The pigs have been photographed at a 2 m distance, perpendicularly to the flank, while standing free in their stalls. This study has confirmed that weight gain and feed ingestion increase the body surface temperature, and, for the first time, it has shown the applicability of thermographic tracking to the study of temperature changes associated with feed ingestion. Moreover, it has highlighted the need to consider the timing of the thermographic shooting of the pig and the distance from the last feeding since the associated temperature variation can affect the detected value.
Cook evaluated the application of thermography to the measurement of radiant heat loss in relation to the metabolic activity, in order to identify the most growth-efficient pigs [18]. The thermographic camera was placed above an automatic feed station capable of weighing the amount of supplied and remaining food, as well as recording the individual’s actual weight. The part of the body detected by the camera was, therefore, the back. The data surveys involved 141 pigs that had been checked as actually weighing around 35, 65, and 105 kilos. The performance of a 24 h fasting period revealed a decrease in the maximum dorsal surface temperature by 0.28 °C. Moreover, this temperature presented a negative relationship with ingestion and growth. This suggested the possibility of identifying, through thermography, individuals with more efficient metabolic processes associated with lower energy losses in the form of radiant energy.
Lengling has recently evaluated whether, during the growth of animals, the use of thermography could identify fatter and leaner individuals [19]. Their initial hypothesis was that the increase in the back fat layer, due to its insulating power, could reduce the surface temperature detected on the back. However, the obtained results showed that we cannot discriminate this way since the changes in the fat layer associated with the growth, measured by ultrasound, are not as remarkable as to cause a decrease in the surface temperature of pig backs. Furthermore, the methods employed to evaluate this possible application of thermography have shown how the effects of the environmental conditions in which measurements are recorded can significantly interfere when working on the detection of limited thermal variations.

2.5. Environmental Stress Assessment

Loughmiller compared environmental temperature changes measured inside a climate chamber with the surface skin temperature of pathogen-inoculated pigs and healthy pigs. In particular, it has been observed that the surface temperature of the latter linearly increased the moment the environmental temperature changed [29].
Thermography has been employed by Nanni Costa to continuously detect the skin temperature of some piglets during long-duration transports (Figure 3), precisely lasting 14 h, in order to evaluate the relationships with the environmental temperature inside the vehicle [31]. This study has made it possible not only to quantify the increase in surface temperature as a response to a rise in environmental temperature but also to show a linear relationship between skin temperature and environment temperature inside a vehicle. In fact, a 1° C rise inside the vehicle produced a 0.2 °C rise in the maximum skin temperature. Such a linear relationship was found to be similar to the one measured by Loughmiller in the above-mentioned study [29].

2.6. Interaction or Restraint Stress Assessment

2.6.1. Assessment of Restraint-Related Stress

Through thermography, Magnani et al. have assessed temperature changes on the eye, back, belly, and flank of piglets that had previously undergone the so-called “Backtest” [32]. This test is carried out on piglets aged between 10 and 17 days, holding an individual supine for one minute and observing its behavioral response, which can range from immobility (low-resisters or LR) to extreme struggle (high-resisters or HR). HR individuals show higher aggressiveness and reluctance to adapt to environmental changes, while LR individuals explore the environment and show flexibility in their response to environmental stimuli. Regardless of whether the piglets belonged to the LR or HR group, the backtest resulted in a remarkable, yet small, decrease in skin temperature on the right ear and the right eye. The decrease in temperature after the test indicates that the restraint causes some peripheral vasoconstriction due to the immobilization stress. With the sole exception of the dorsal part (which pigs were held supine over), the skin temperature values of the examined areas tended to be higher in HR individuals than in LR individuals, probably due to the stronger movement of the former in response to immobilization.

2.6.2. Assessment of Stress Related to Aggressive Interaction

Boileau et al. have employed thermography in order to assess changes in skin temperatures in response to a highly stressful event, such as an aggressive interaction between two individuals [36]. The problem of aggression among pigs is a common occurrence in all farms, and it is important to acquire some information to understand their physical and emotional responses, which can be achieved with noninvasive techniques such as thermography. Forty-six pigs aged 13 weeks were examined, entire males and females, who had undergone no tail cut and no teeth trimming. The test that has been carried out consisted of placing pairs of individuals unrelated to each other into an 11 m2 arena, then comparing male–male, female–female, and male–female combinations in 69 encounters. The confrontation began with the entry of the two individuals into the arena and ended when any of the following three situations occurred: when there was an obvious winner, after 20 min of no interaction, and when a fear or mounting behavior occurred, even in a single individual. In this study, the back, particularly the area between the shoulder blades and the rump, was selected as thermal frame to analyze the exchanges in blood-irradiated areas.
In the case of an aggressive confrontation, at the time of termination due to the loser’s withdrawal, a decrease in back surface temperature was observed, although there were no differences between the winning and losing pigs. Conversely, duration of the confrontation, body weight, and sex of participants were found to be of little influence. Since the drop in temperature at the end of the confrontation was independent from the physical effort required to win or defend, the vasoconstriction observed by thermography may be the result of psychological stress rather than that of physiological adaptation. This outcome, highlighted through the thermographic application, provides us with new evidence to evaluate aggressive behavior more thoroughly in terms of animal well-being and physiological response to such behaviors.

2.7. Assessing the Stress Related to Pre-Slaughter Procedures

To identify those pigs showing stress signs before slaughter, Warris measured ear temperature at three different locations through thermography, and then compared it with blood temperature recorded using an infrared thermometer [33]. Also, the blood levels of cortisol and creatine kinase, used as indicators of stress level in the animals, were determined. The correlation between ear and blood temperatures was statistically significant, but low (r = +0.11). The coefficients of correlation between ear temperature and creatine kinase levels (r = +0.55) were higher, while cortisol was found to have a correlation with the average blood temperature. This confirmed that pigs having a higher stress level were showing the highest temperatures.
Through thermography, Weschenfelder et al. measured the eye temperature of pigs placed into a restrainer within an automatic system of electrical stunning before shock. The study determined that the eye temperature measured just before the stunning is partially correlated with both the blood lactate level and the measurements carried out for the quality assessment of meat. It is likely that the uncomfortable measurement conditions affected the ocular temperature data collected during the experiment, which was not suitable for providing sufficient prediction of those parameters detectable postmortem [34].
Thermography can be employed in the identification of the pigs that show an abnormally high temperature upon arrival at the resting stalls [35] (Figure 4). Obviously, this condition can be recognized without the aid of a thermal imaging camera, but we can envision the use of such a device on large groups of pigs that are stunned and sent to the rest areas, which are rooms with uncomfortable environmental conditions, such as high levels of temperature and relative humidity.

2.8. Meat Quality Prediction

Several studies have been conducted on the use of infrared thermography to predict the final quality of pork meat. Postmortem, Gariepy [20] assessed the quality of pork meat in pigs having high temperature values collected by thermography before stunning. Based on color and water retention, the assessed pork meat was classified as PSE (pale, soft, and exuding), normal, or DFD (dark, firm, and dry). The thermographic values collected in vivo did not allow the prediction of PSE or DFD meat, but as the surface temperature of the back of the examined pigs increased, so did the frequency of flaws related to meat quality.
Lawrence et al. [21] carried out the following experiment: They classified animals as “warm” or “normal” based on the temperature of their lumbar region, measured with a thermographic camera, after having kept pigs at the slaughterhouse for some variable time span. The group of pigs kept in the rest area for a time span of 1 to 4 h, the “warm” ones, had a lighter muscle color, while no difference in pH and water retention rates had been detected. In the group of pigs kept in the rest area for one night (12 to 16 h), any difference in meat quality, both for “warm” and “normal” pigs, had disappeared. The pigs’ recovery from previous stress, before stunning, had reduced any difference among the animals, and consequently, the effectiveness of thermography in predicting meat quality.
Schaefer [22] studied the use of thermography in measuring the surface temperature of those pigs that were exempt, heterozygous and homozygous for the recessive allele of the halothane gene. Images have framed the back and side surfaces of pigs kept in the rest area and on the outer and inner median of the midsection, 45 min after their deaths. Although the thermographic analysis showed no differences between genotypes, small, localized areas with higher temperatures were observed on the dorsal surface of homozygous pigs for the recessive allele of the halothane gene. Regardless of the genotype, pigs that had lower average temperatures on the side tended to have meats with worse retention and a lighter color. From this test, a need emerged for the identification of the most important anatomical parts of the animal’s body, the most useful temperature ranges for thermal imaging, and the most appropriate environment and handling conditions suitable for a more effective use of infrared thermography in predicting pork meat quality.
Due to the complexity of conditions where a thermographic shooting can be carried out, its definition is still undergoing some evaluations. Lately, Rocha et al. [23] have tried to single out the best spots on a pig body for the thermographic shootings that aim at identifying the widest temperature variations on the skin surface, as a result of two different handling ways from stable to ramp (calm or rude), and consequent upon a 40 min transportation. During this test, besides the use of the thermal camera, some stress indicators, such as salivary cortisol rate, heart rate and rectal temperature, had been used. The temperature measured in the orbital region is more sensitive to physical activity than the rectal one because of the different dissipation rate between internal and surface temperatures. The parasympathetic system reduces the gastrointestinal activity by decreasing the blood flow toward the intestinal tract, probably because of the vasoconstriction of the rectal wall in contrast to the orbital region.
The orbital regions, and the one located at the posterior base of the ear, have shown the best correlation coefficients with the salivary cortisol (r = +0.49 e r = +0.50, respectively), proving to be the most reliable spots to measure body surface temperature. However, because of the low or moderate correlations with other physiological indicators, the authors have concluded that thermography cannot be used as the sole tool for assessing the physiological conditions of pigs in response to stress and it needs to be complemented by other indicators in order to have a reliable assessment of the status of pigs after pre-slaughter handlings.
Similarly to the study by Lawrence, Dikeman et al. [24] used thermography to identify pigs having a warmer- or cooler-than-normal surface skin temperature during the pre-slaughter rest. Over 500 pigs in various environmental conditions, ranging from −2° to + 26° C, have been tested. When the environment temperature ranged between + 6° and +14 °C, the “warm” pigs, having their temperature 1.3 standard deviations above average, had a kind of meat with lower water retention rates, while “cold” pigs, having their temperature 1.3 standard deviations below average, had the same fault, yet at a range of environmental temperature between +21° and +26 °C. Within the lowest temperature ranges, between −2°and−1 °C, no differences have been detected in the meat quality belonging to the two groups of animals. The outcome of this study suggest that thermography may indeed play a role in predicting final meat quality, but its effectiveness is highly dependent on the environment conditions under which it operates.
Nanni Costa et al. [25] have considered the possibility of using thermography on the slaughter line to assess the quality of hams intended for their transformation into PDO hams. Images have been recorded 20 min after stunning, and a square area located in the center of the caudal surface of the thigh has been scanned. Beside the measurements to assess the quality of the semimembranosus muscle, such as pH and color, another assessment was made on the thighs being trimmed for fat layer and for the identification of vein defects and reddened skin. The temperature of both hams was found to be very similar and unrelated to changes in pH and color of the muscle examined. Vein defects and reddened skin too have not shown any connection to thighs temperature. Conversely, the surface temperatures of thighs were different according to their fat layer. Those with a lighter fat layer showed higher temperatures, while those with a heavier fat layer showed the lowest temperatures because of the insulating effect of the fat layer around the thigh. The relationship between the fat layer and surface temperature suggests that thermography could be a valuable, fast, and noninvasive method to estimate the degree of adiposity.

3. Discussion

Within pig farming, thermography is used in many stages of production because it is noninvasive, it does not require contact with the surface to be measured, it can be applied to hard-to-approach or moving individuals, and its application can be advantageous along some industrial processing chains, such as slaughter lines [37].
The application versatility of the thermal imaging camera, an instrument that can detect the amount of heat produced by a body or surface, should not overshadow the knowledge of factors that might influence thermometric measurement, as discussed below (Table 2). Thus, it is essential to use appropriate procedures when working with livestock, in order to reduce the impact of these confounding variables. It is good practice to always compare the body area where a thermal anomaly has been detected with the symmetric or contralateral ones and carry out the same surveys at different times [38].

3.1. Individual Variables

Emissivity is a peculiar characteristic of any heat-emitting surface, therefore we need to calibrate the thermal imaging camera considering this parameter, which may be considered to be 0.98 for those parts of the skin that can be measured on pigs [39]. Of course, if skin changes occur due to dermatitis or pathologies, the temperatures of the affected areas will also change.
Subject variability cannot be underestimated, both due to the individual traits of living subjects and to the sudden environmental stimuli present when operating in the field, often not fully controllable, that can stress each animal differently.
The presence of fear and pain, or excitement and positive emotional status, can generate peripherical vasoconstriction or vasodilatation phenomena, respectively, altering the subject’s skin thermal distribution [40].
Even an increase in cardiac work can cause a temperature increase, not only in muscles, and should be prevented before and throughout the thermographic measurements. Instead, it is important to remember that in areas where the skin fat is greater, the temperatures will be lower because of its insulating effect on the conduction of heat from inside to outside the body [40].

3.2. Outer Variables

The environmental parameters of the place where the measurement is taken, i.e., relative temperature and humidity, are to be considered when setting up the thermal imaging camera because this instrument may record different values in the presence of appreciable changes in such parameters. Moreover, water or dirt on the coat or skin, proximity to reflective planes, direct solar radiation (or other heat sources nearby), and the wind can also interfere with thermometric measurements [1,41]. Thus, the presence of these factors should be avoided and it is recommended to operate inside or in weather-protected facilities.
When dealing with living subjects, for a correct interpretation of the obtained reliefs, it is also necessary to consider the physiological phenomena regarding the animals in observation. For example, two of them may be in the digestive process and the body temperature circadian trend. To obtain comparable temperature values, it is therefore advisable to make measurements in the same time slot of the day and at the same time distance from the feeding.

3.3. Technical Variables

Thermographic images need to be taken at the same distance and viewing angle from the subject, since the variation of these parameters affects the temperatures recorded [42]. If things become complicated, as pigs are living, moving subjects, it could be useful take infrared videos instead of single images.
The proper use of a professional infrared camera is necessary and only a routinely calibrated device can be used. Currently, a largely range of commercial models are available, but a microbolemetric sensor with no less than 320 × 240 pixels is recommended [38]; both spatial and thermal resolutions suitable for applications on livestock can be guaranteed by this kind of tool.
As seen in the previous paragraphs, many variables can impact temperature relief, with the creation of low-quality infrared images. As a consequence, a great number of thermal images are usually collected beforehand in experiments and need to be processed and categorized before the temperature analysis [43].
Furthermore, the thermocamera records the skin temperature in various parts of the animal’s body in the same frame, so the specific region of interest, ROI, needs to be determined and selected. Finally, we have to decide which temperature is better to analyze within the observed ROI. When using infrared thermography in animal husbandry, special attention is often paid to the maximum temperature value detected and not to the average value [38]. That’s because the lower and average values could be affected by the presence of dirt and liquid, instead the maximum temperature should more accurately describe the actual skin temperature.
As a result, recent works are mainly focusing on the development of procedures for managing a great number of infrared images, using up-to-date tools, such as computer vision technologies [38], convolutional neural networks [44], and deep learning techniques [45], in order to enhance spatial resolution, reduce noise, average images over time, detect ROI, and identify the needed temperature changes in a completely automated way [41,46].

4. Perspectives

Thermographic applications in pig farming include all stages of animal husbandry and management, from the insemination of sows to the slaughter of fattening pigs. The versatility typical of this technique is a great plus in finding useful applications in animal husbandry, but its use requires knowledge of the principles on which it is based, the variables that affect the right temperature measurement, and the physiological phenomena it is meant to detect. Although it is not suitable for all situations and conditions, this kind of camera can greatly assist in the early identification of diseases and stress conditions. In the near future, other applications will surely be developed, aided by the decrease in infrared device costs and the integration with other sensors in situ, creating a precision farming system that can improve both the daily welfare of swine and farm productivity. Finally, the development of the latest techniques related to computer vision and artificial intelligence in this field will make even those procedures that today still require human intervention, such as cataloging, selection, and analysis of images and ROI, more automatic and faster.

Author Contributions

V.R. and L.N.C. visualized the concept and drafted the article. M.Z., P.M., and F.L. revised the content according to their expertise. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Zheng, S.; Zhou, C.; Jiang, X.; Huang, J.; Xu, D. Progress on Infrared Imaging Technology in Animal Production: A Review. Sensors 2022, 22, 705. [Google Scholar] [CrossRef]
  2. McManus, C.; Tanure, C.B.; Peripolli, V.; Seixas, L.; Fischer, V.; Gabbi, A.M.; Menegassi, S.R.O.; Stumpf, M.T.; Dias, G.J.; Costa, J.B.G. Infrared thermography in animal production: An overview. Comput. Electron. Agric. 2016, 123, 10–16. [Google Scholar] [CrossRef]
  3. Guevara, R.D.; Pastor, J.J.; Manteca, X.; Tedo, G.; Llonch, P. Systematic review of animal-based indicators to measure thermal, social, and immune-related stress in pigs. PLoS ONE 2022, 17, e0266524. [Google Scholar] [CrossRef]
  4. Yin, M.; Ma, R.; Hailing, L.; Jun, L.; Zhao, Q.; Zhang, M. Non-contact sensing technology enables precision livestock farming in smart farms. Comput. Electron. Agric. 2023, 212, 108171. [Google Scholar] [CrossRef]
  5. Maldagues, X.P.V.; Moore, P.O. Nondestructive Testing Handbook: Infrared and Thermal Testing, 3rd ed.; The American Society for Nondestructive Testing: Columbus, OH, USA, 2001. [Google Scholar]
  6. Scolari, S.; Evans, R.; Knox, R.; Tamassia, M.; Clark, S. Determination of the relationship between vulvar skin temperatures and time of ovulation in swine using digital infrared thermography. Reprod. Fertil. Dev. 2009, 22, 178. [Google Scholar] [CrossRef]
  7. Scolari, S.; Clark, S.; Knox, R.; Tamassia, M. Vulvar skin temperature changes significantly during estrus in swine as determined by digital infrared thermography. J. Swine Health Prod. 2011, 19, 151–155. [Google Scholar]
  8. Simões, V.; Lyazrhi, F.; Picard-Hagen, N.; Gayrard, V.; Martineau, G.; Waret-Szkuta, A. Variations in the vulvar temperature of sows during proestrus and estrus as determined by infrared thermography and its relation to ovulation. Theriogenology 2014, 82, 1080–1085. [Google Scholar] [CrossRef]
  9. Sykes, D.J.; Couvillion, J.S.; Cromiak, A.; Bowers, S.; Schenck, E.; Crenshaw, M.; Ryan, P.L. The use of digital infrared thermal imaging to detect estrus in gilts. Theriogenology 2012, 78, 147–152. [Google Scholar] [CrossRef]
  10. Lee, J.H.; Lee, D.H.; Yun, W.; Oh, H.J.; An, J.S.; Kim, Y.G.; Kim, G.M.; Cho, J.H. Quantifiable and feasible estrus detection using the ultrasonic sensor array and digital infrared thermography. J. Anim. Sci. Technol. 2019, 61, 163–169. [Google Scholar] [CrossRef]
  11. Schmitt, O.; Reigner, S.; Bailly, J.; Ravon, L.; Billon, Y.; Gress, L.; Bluy, L.; Canario, L.; Gilbert, H.; Bonnet, A.; et al. Thermoregulation at birth differs between piglets from two genetic lines divergent for residual feed intake. Animal 2021, 15, 100069. [Google Scholar] [CrossRef]
  12. Muns, R.; Nuntapaitoon, M.; Tummaruk, P. Non-infectious causes of pre-weaning mortality in piglets. Livest. Sci. 2016, 184, 46–57. [Google Scholar] [CrossRef]
  13. Llamas Moya, S.; Boyle, L.A.; Lynch, P.B.; Arkins, S. Influence of teeth resection on the skin temperature and acute phase response in newborn piglet. Anim. Welf. 2006, 15, 291–297. [Google Scholar] [CrossRef]
  14. Tabuarici, P.; Bunter, K.L.; Graser, H.-U. Thermal imaging as a potential tool for identifying piglets at risk. In Proceedings of the AGBU Pig Genetics Workshop, Armidale, Australia, 24–25 October 2012; pp. 23–30. [Google Scholar]
  15. Herpin, P.; Damon, M.; Le Dividich, J. Development of thermoregulation and neonatal survival in pigs. Livest. Prod. Sci. 2002, 78, 25–45. [Google Scholar] [CrossRef]
  16. Schmitt, O.; O’Driscoll, K. Use of infrared thermography to noninvasively assess neonatal piglet temperature. Transl. Anim. Sci. 2021, 5, txaa208. [Google Scholar] [CrossRef] [PubMed]
  17. Loughmiller, J.A.; Spire, M.F.; Tokach, M.D.; Dritz, S.S.; Nelssen, J.L.; Goodband, R.D.; Hogge, S.B. An Evaluation of Differences in Mean Body Surface Temperature with Infrared Thermography in Growing Pigs Fed Different Dietary Energy Intake and Concentration. J. Appl. Anim. Res. 2005, 28, 73–80. [Google Scholar] [CrossRef]
  18. Cook, N.; Chabot, B.; Liu, T.; Froehlich, D.; Basarab, J.; Juarez, M. Radiated temperature from thermal imaging is related to feed consumption, growth rate and feed efficiency in grower pigs. J. Therm. Biol. 2020, 94, 102747. [Google Scholar] [CrossRef]
  19. Lengling, A.; Alfert, A.; Reckels, B.; Steinhoff-Wagner, J.; Büscher, W. Feasibility Study on the Use of Infrared Thermography to Classify Fattening Pigs into Feeding Groups According Their Body Composition. Sensors 2020, 20, 5221. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  20. Gariepy, C.; Amiot, J.; Nadai, S. Ante-mortem detection of PSE and DFD by Infrared Thermography of pigs before stunning. Meat Sci. 1989, 25, 37–41. [Google Scholar] [CrossRef]
  21. Lawrence, T.E.; Spire, M.F.; Dikeman, M.E.; Hunt, M.C.; Hogge, S.B.; James, B.W. Utilizing Infrared Thermography to Predict Pork Quality. Swine Day 2001, 2001, 131–134. [Google Scholar]
  22. Schaefer, A.L.; Jones, S.D.M.; Murray, A.C.; Sather, A.P.; Tong, A.K.W. Infrared thermography of pigs with known genotypes for stress susceptibility in relation to pork quality. Can. J. Anim. Sci. 1989, 69, 491–495. [Google Scholar] [CrossRef]
  23. Rocha, L.M.; Devillers, N.; Maldague, X.; Kabemba, F.Z.; Fleuret, J.; Guay, F.; Faucitano, L. Validation of anatomical sites for the measurement of infrared body surface temperature variation in response to handling and transport. Animals 2019, 9, 425. [Google Scholar] [CrossRef]
  24. Dikeman, M.; Spire, M.; Hunt, M.; Lowak, S. Infrared Thermography of Market Hogs as a Predictor of Pork Quality; Research Report NP B #02-025; National Pork Board: Des Moines, IA, USA, 2003; pp. 1–9. [Google Scholar]
  25. Nanni Costa, L.; Stelletta, C.; Cannizzo, C.; Gianesella, M.; Lo Fiego, D.P.; Morgante, M. The use of thermography on the slaughter-line for the assessment of pork and raw ham quality. Ital. J. Anim. Sci. 2007, 6 (Suppl. S1), 704–706. [Google Scholar] [CrossRef]
  26. Johnson, S.R.; Dunbar, M.R. Infrared thermography: Its use and application for detecting infectious diseases in wildlife and domestic animals. In Proceedings of the InfraMation 2010, Las Vegas, NV, USA, 8–12 November 2010. [Google Scholar]
  27. Bashiruddin, J.B.; Mann, J.; Finch, R.; Zhang, Z.; Paton, D. Preliminary study of the use of thermal imaging to assess surface temperatures during foot-and-mouth disease virus infection in cattle, sheep and pigs. In Proceedings of the 2006 Session of the Research Group of the Standing Technical Committee of the European Commission for the Control of Foot-and-Mouth Disease (Appendix 46), Paphos, Cyprus, 17–20 October 2006; Food and Agriculture Organization: Rome, Italy, 2006; pp. 304–308. [Google Scholar]
  28. Wendt, M.; Eickhoff, K.; Koch, R. Die Messung der Hauttemperatur als Methode zur Erkennung fieberhaft erkrankter Schweine. Deut. Tierarztl. Woch. 1997, 104, 29–33. [Google Scholar]
  29. Loughmiller, J.A.; Spire, M.F.; Dritz, S.S.; Fenwick, B.W.; Hosni, M.H.; Hogge, S.B. Relationship between mean body surface temperature measured by use of infrared thermography and ambient temperature in clinically normal pigs and pigs inoculated with Actinobacillus pleuropneumoniae. Am. J. Vet. Res. 2001, 62, 676–681. [Google Scholar] [CrossRef]
  30. Friendship, R.; Poljak, Z.; McIntosh, K. Use of infrared thermography for early detection of disease causing sudden death in a swine finishing barn. In Proceedings of the 28th Annual Centralia Swine Research Update, Guelph, ON, Canada, 28 January 2009; pp. I27–I28. [Google Scholar]
  31. Nanni Costa, L.; Redaelli, V.; Magnani, D.; Cafazzo, S.; Amadori, M.; Razzuoli, E.; Verga, M.; Luzi, F. Preliminary study on the relationship between skin temperature of piglet measured by infrared thermography and environmental temperature in a vehicle in transit. In Veterinary Science. Current Aspects in Biology, Animal Pathology, Clinic and Food Hygiene; Springer-Verlag: Berlin/Heidelberg, Germany, 2012; pp. 193–198. [Google Scholar]
  32. Magnani, D.; Gatto, M.; Cafazzo, S.; Stelletta, C.; Morgante, M.; Costa, L. Difference of surface body temperature in piglets due to the backtest and environmental condition. In Animal Hygiene and Sustainable Livestock Production. In Proceedings of the XVth International Congress of the International Society for Animal Hygiene, Vienna, Austria, 3–7 July 2011; pp. 1029–1032. [Google Scholar]
  33. Warriss, P.; Pope, S.; Brown, S.; Wilkins, L.; Knowles, T. Estimating the body temperature of groups of pigs by thermal imaging. Vet. Rec. 2006, 158, 331–334. [Google Scholar] [CrossRef]
  34. Weschenfelder, A.V.; Saucier, L.; Maldague, X.; Rocha, L.M.; Schaefer, A.L.; Faucitano, L. Use of infrared ocular thermography to assess physiological conditions of pigs prior to slaughter and predict pork quality variation. Meat Sci. 2013, 95, 616–620. [Google Scholar] [CrossRef]
  35. Flores-Peinado, S.; Mota-Rojas, D.; Guerrero-Legarreta, I.; Mora-Medina, P.; Cruz-Monterrosa, R.; Gómez-Prado, J.; Hernández, M.G.; Cruz-Playas, J.; Martínez-Burnes, J. Physiological responses of pigs to preslaughter handling: Infrared and thermal imaging applications. Int. J. Vet. Sci. Med. 2020, 8, 71–84. [Google Scholar] [CrossRef]
  36. Boileau, A.; Farish, M.; Turner, S.P.; Camerlink, I. Infrared thermography of agonistic behaviour in pigs. Physiol. Behav. 2019, 210, 112637. [Google Scholar] [CrossRef]
  37. Zhang, Z.; Zhang, H.; Liu, T. Study on body temperature detection of pig based on infrared technology: A review. Artif. Intell. Agric. 2019, 1, 14–26. [Google Scholar] [CrossRef]
  38. Reza, M.N.; Ali, M.R.; Kabir, M.S.N.; Karim, M.R.; Ahmed, S.; Kyoung, H.; Kim, G.; Chung, S.O. Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. J. Anim. Sci. Technol. 2024, 66, 31–56. [Google Scholar] [CrossRef]
  39. Soerensen, D.D.; Clausen, S.; Mercer, J.B.; Pedersen, L.J. Determining the emissivity of pig skin for accurate infrared thermography. Comput. Electron. Agric. 2014, 109, 52–58. [Google Scholar] [CrossRef]
  40. De Santis, M.; Contalbrigo, L.; Borgi, M.; Cirulli, F.; Luzi, F.; Redaelli, V.; Stefani, A.; Toson, M.; Odore, R.; Vercelli, C.; et al. Equine Assisted Interventions (EAIs): Methodological Considerations for Stress Assessment in Horses. Vet. Sci. 2017, 4, 44. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  41. Perić, D.; Livada, B.; Perić, M.; Vujić, S. Thermal imager range: Predictions, expectations, and reality. Sensors 2019, 19, 3313. [Google Scholar] [CrossRef] [PubMed]
  42. Wang, X.; Hu, F.; Yang, R.; Wang, K. An Infrared Temperature Correction Method for the Skin Temperature of Pigs in Infrared Images. Agriculture 2023, 13, 520. [Google Scholar] [CrossRef]
  43. Cai, Z.; Cui, J.; Yuan, H.; Cheng, M. Application and research progress of infrared thermography in temperature measurement of livestock and poultry animals: A review. Comput. Electron. Agric. 2023, 205, 107586. [Google Scholar] [CrossRef]
  44. Küster, S.; Haverkamp, L.; Schlather, M.; Traulsen, I. An Approach towards a Practicable Assessment of Neonatal Piglet Body Core Temperature Using Automatic Object Detection Based on Thermal Images. Agriculture 2023, 13, 812. [Google Scholar] [CrossRef]
  45. Garrido, I.; Erazo-Aux, J.; Lagüela, S.; Sfarra, S.; Ibarra-Castanedo, C.; Pivarčiová, E.; Gargiulo, G.; Maldague, X.; Arias, P. Introduction of deep learning in thermographic monitoring of cultural heritage and improvement by automatic thermogram pre-processing algorithms. Sensors 2021, 21, 750. [Google Scholar] [CrossRef]
  46. Vardasca, R.; Bento, F.; Tereso, M.; Martinho, D. Infrared thermal imaging: A dataset definition towards decision making and intelligence. In Proceedings of the 16th Quantitative InfraRed Thermography Conference (QITC), Paris, France, 4–8 July 2022. [Google Scholar]
Figure 1. Infrared image of a sow’s vulvar area shows a temperature of 39.07 °C at point A.
Figure 1. Infrared image of a sow’s vulvar area shows a temperature of 39.07 °C at point A.
Applsci 14 05780 g001
Figure 2. Control of skin and environmental temperatures during farrowing with an infrared camera.
Figure 2. Control of skin and environmental temperatures during farrowing with an infrared camera.
Applsci 14 05780 g002
Figure 3. The infrared image shows the skin temperature of some piglets and the environment during a long transport.
Figure 3. The infrared image shows the skin temperature of some piglets and the environment during a long transport.
Applsci 14 05780 g003
Figure 4. Monitoring the skin temperatures of pigs as they arrive at the slaughterhouse.
Figure 4. Monitoring the skin temperatures of pigs as they arrive at the slaughterhouse.
Applsci 14 05780 g004
Table 1. An overview of the thermography technique applications in pig farming.
Table 1. An overview of the thermography technique applications in pig farming.
Application Area of InterestReferences
Enhance productionOestrus DetectionVulvar, Body, Eye[6,7,8,9,10]
Neonatal mortality reductionDorsal, Body, Eye[11,12,13,14,15,16]
Growing pig efficiencyDorsal, Eye, Body[17,18,19]
Meat quality predictionDorsal, Body, Eye[20,21,22,23,24,25]
Enhance animal welfareFever or diseases early detectionEye, Ear, Body[26,27,28,29,30]
Environmental stress assessmentDorsal, Eye, Ear[29,31]
Interaction or restraint stress assessmentDorsal, Eye, Ear[32]
Assessing the stress related to pre-slaughter proceduresEye, Ear, Body[33,34,35]
Table 2. Factors to pay attention to that may alter the correct measurement of skin temperature on animals.
Table 2. Factors to pay attention to that may alter the correct measurement of skin temperature on animals.
Individual variablesSkin emissivity
Body condition score
Coat alterations
Stress or disease
Individual physiological variability
Outer variablesPhysical efforts
Kind and time of feeding
Timetable of the surveys
Dirt, sweat, or moisture on the skin
Solar radiation or other heating sources nearby
Wind
Environmental temperature and humidity
Technical variablesDistance
Viewing angle
Type of device (microbolometric or not)
Thermic and spatial resolution
ROI
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Redaelli, V.; Zaninelli, M.; Martino, P.; Luzi, F.; Costa, L.N. A Precision Livestock Farming Technique from Breeding to Slaughter: Infrared Thermography in Pig Farming. Appl. Sci. 2024, 14, 5780. https://doi.org/10.3390/app14135780

AMA Style

Redaelli V, Zaninelli M, Martino P, Luzi F, Costa LN. A Precision Livestock Farming Technique from Breeding to Slaughter: Infrared Thermography in Pig Farming. Applied Sciences. 2024; 14(13):5780. https://doi.org/10.3390/app14135780

Chicago/Turabian Style

Redaelli, Veronica, Mauro Zaninelli, Pieranna Martino, Fabio Luzi, and Leonardo Nanni Costa. 2024. "A Precision Livestock Farming Technique from Breeding to Slaughter: Infrared Thermography in Pig Farming" Applied Sciences 14, no. 13: 5780. https://doi.org/10.3390/app14135780

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop