Infrared Thermal Image for Assessing Animal Health and Welfare

When Everything Becomes Bigger: Big Data for Big Poultry Production

In future decades, the demand for poultry meat and eggs is predicted to considerably increase in pace with human population growth. Although this expansion clearly represents a remarkable opportunity for the sector, it conceals a multitude of challenges. Pollution and land erosion, competition for limited resources between animal and human nutrition, animal welfare concerns, limitations on the use of growth promoters and antimicrobial agents, and increasing risks and effects of animal infectious diseases and zoonoses are several topics that have received attention from authorities and the public. The increase in poultry production must be achieved mainly through optimization and increased efficiency. The increasing ability to generate large amounts of data ("big data") is pervasive in both modern society and the farming industry. Information accessibility-coupled with the availability of tools and computational power to store, share, integrate, and analyze data with automatic and flexible algorithms-offers an unprecedented opportunity to develop tools to maximize farm profitability, reduce socio-environmental impacts, and increase animal and human health and welfare. A detailed description of all topics and applications of big data analysis in poultry farming would be infeasible. Therefore, the present work briefly reviews the application of sensor technologies, such as optical, acoustic, and wearable sensors, as well as infrared thermal imaging and optical flow, to poultry farming. The principles and benefits of advanced statistical techniques, such as machine learning and deep learning, and their use in developing effective and reliable classification and prediction models to benefit the farming system, are also discussed. Finally, recent progress in pathogen genome sequencing and analysis is discussed, highlighting practical applications in epidemiological tracking, and reconstruction of microorganisms' population dynamics, evolution, and spread. The benefits of the objective evaluation of the effectiveness of applied control strategies are also considered. Although human-artificial intelligence collaborations in the livestock sector can be frightening because they require farmers and employees in the sector to adapt to new roles, challenges, and competencies-and because several unknowns, limitations, and open-ended questions are inevitable-their overall benefits appear to be far greater than their drawbacks. As more farms and companies connect to technology, artificial intelligence (AI) and sensing technologies will begin to play a greater role in identifying patterns and solutions to pressing problems in modern animal farming, thus providing remarkable production-based and commercial advantages. Moreover, the combination of diverse sources and types of data will also become fundamental for the development of predictive models able to anticipate, rather than merely detect, disease occurrence. The increasing availability of sensors, infrastructures, and tools for big data collection, storage, sharing, and analysis-together with the use of open standards and integration with pathogen molecular epidemiology-have the potential to address the major challenge of producing higher-quality, more healthful food on a larger scale in a more sustainable manner, thereby protecting ecosystems, preserving natural resources, and improving animal and human welfare and health.

Non-invasive measurements of respiration and heart rate across wildlife species using Eulerian Video Magnification of infrared thermal imagery

BACKGROUND

An animal's metabolic rate, or energetic expenditure, both impacts and is impacted by interactions with its environment. However, techniques for obtaining measurements of metabolic rate are invasive, logistically difficult, and costly. Red-green-blue (RGB) imaging tools have been used in humans and select domestic mammals to accurately measure heart and respiration rate, as proxies of metabolic rate. The purpose of this study was to investigate if infrared thermography (IRT) coupled with Eulerian video magnification (EVM) would extend the applicability of imaging tools towards measuring vital rates in exotic wildlife species with different physical attributes.

RESULTS

We collected IRT and RGB video of 52 total species (39 mammalian, 7 avian, 6 reptilian) from 36 taxonomic families at zoological institutions and used EVM to amplify subtle changes in temperature associated with blood flow for respiration and heart rate measurements. IRT-derived respiration and heart rates were compared to 'true' measurements determined simultaneously by expansion of the ribcage/nostrils and stethoscope readings, respectively. Sufficient temporal signals were extracted for measures of respiration rate in 36 species (85% success in mammals; 50% success in birds; 100% success in reptiles) and heart rate in 24 species (67% success in mammals; 33% success in birds; 0% success in reptiles) using IRT-EVM. Infrared-derived measurements were obtained with high accuracy (respiration rate, mean absolute error: 1.9 breaths per minute, average percent error: 4.4%; heart rate, mean absolute error: 2.6 beats per minute, average percent error: 1.3%). Thick integument and animal movement most significantly hindered successful validation.

CONCLUSION

The combination of IRT with EVM analysis provides a non-invasive method to assess individual animal health in zoos, with great potential to monitor wildlife metabolic indices in situ.

Energy Assessment from Broiler Chicks' Vocalization Might Help Improve Welfare and Production

Vocalization seems to be a viable source of signal for assessing broiler welfare. However, it may require an understanding of the birds' signals, both quantitatively and qualitatively. The delivery of calls with a specific set of acoustic features must be understood to assess the broiler's well-being. The present study aimed to analyze broiler chick vocalization through the sounds emitted during social isolation and understand what would be the flock size where the chicks present the smallest energy loss in vocalizing. The experiments were carried out during the first 3 days of growth, and during the trial, chicks received feed and water ad libitum. A total of 30 1-day-old chicks Cobb^® breed were acquired at a commercial hatching unit. The birds were tested from 1 to 3 days old. A semi-anechoic chamber was used to record the vocalization with a unidirectional microphone connected to a digital recorder. We placed a group of 15 randomly chosen chicks inside the chamber and recorded the peeping sound, and the assessment was conducted four times with randomly chosen birds. We recorded the vocalization for 2 min and removed the birds sequentially stepwise until only one bird was left inside the semi-anechoic chamber. Each audio signal recorded during the 40 s was chosen randomly for signal extraction and analysis. Fast Fourier transform (FFT) was used to extract the acoustic features and the energy emitted during the vocalization. Using data mining, we compared three classification models to predict the rearing condition (classes distress and normal). The results show that birds' vocalization differed when isolated and in a group. Results also indicate that the energy spent in vocalizing varies depending on the size of the flock. When isolated, the chicks emit a high-intensity sound, "alarm call", which uses high energy. In contrast, they spent less energy when flocked in a group, indicating good well-being when the flock was 15 chicks. The weight of birds influenced the amount of signal energy. We also found that the most effective classifier model was the Random Forest, with an accuracy of 85.71%, kappa of 0.73, and cross-entropy of 0.2.

Prediction of rectal temperature in Holstein heifers using infrared thermography, respiration frequency, and climatic variables

The objective of this study was to develop an equation to predict rectal temperature (RT) using body surface temperatures (BSTs), physiological and climatic variables in pubertal Holstein heifers in an arid region. Two hundred Holstein heifers were used from July to September during two consecutive summers (2019 and 2020). Respiratory frequency (RF) was used as a physiological variable and ambient temperature, relative humidity and temperature-humidity index as climatic variables. For the body surface temperatures, infrared thermography was used considering the following anatomical regions: shoulder, belly, rump, leg, neck, head, forehead, nose, loin, leg, vulva, eye, flank, and lateral area (right side). Initially, a Pearson correlation analysis examined the relationship among variables, and then multiple linear regression analysis was used to develop the prediction equation. Physiological parameters RT and RF were highly correlated with each other (r = 0.73; P˂0.0001), while all BST presented from low to moderate correlations with RT and RF. BST forehead temperature (FH) showed the highest (r = 0.58) correlation with RT. The equation RT = 35.55 + 0.033 (RF) + 0.030 (FH) + e_i is considered the best regression equation model to predict RT in Holstein heifers in arid zones. This decision was made on the indicators R² = 60%, RMSE = 0.25, and AIC = 0.25, which were considered adequate variability indicators.

Thermoregulation mechanisms and perspectives for validating thermal windows in pigs with hypothermia and hyperthermia: An overview

Specific anatomical characteristics make the porcine species especially sensitive to extreme temperature changes, predisposing them to pathologies and even death due to thermal stress. Interest in improving animal welfare and porcine productivity has led to the development of various lines of research that seek to understand the effect of certain environmental conditions on productivity and the impact of implementing strategies designed to mitigate adverse effects. The non-invasive infrared thermography technique is one of the tools most widely used to carry out these studies, based on detecting changes in microcirculation. However, evaluations using this tool require reliable thermal windows; this can be challenging because several factors can affect the sensitivity and specificity of the regions selected. This review discusses the thermal windows used with domestic pigs and the association of thermal changes in these regions with the thermoregulatory capacity of piglets and hogs.

Thermal and Circulatory Changes in Diverse Body Regions in Dogs and Cats Evaluated by Infrared Thermography

Infrared thermography (IRT) has been proposed as a method for clinical research to detect local inflammatory processes, wounds, neoplasms, pain, and neuropathies. However, evidence of the effectiveness of the thermal windows used in dogs and cats is discrepant. This review aims to analyze and discuss the usefulness of IRT in diverse body regions in household animals (pets) related to recent scientific evidence on the use of the facial, body, and appendicular thermal windows. IRT is a diagnostic method that evaluates thermal and circulatory changes under different clinical conditions. For the face, structures such as the lacrimal caruncle, ocular area, and pinna are sensitive to assessments of stress degrees, but only the ocular window has been validated in felines. The usefulness of body and appendicular thermal windows has not been conclusively demonstrated because evidence indicates that biological and environmental factors may strongly influence thermal responses in those body regions. The above has led to proposals to evaluate specific muscles that receive high circulation, such as the bicepsfemoris and gracilis. The neck area, perivulvar, and perianal regions may also prove to be useful thermal windows, but their degree of statistical reliability must be established. In conclusion, IRT is a non-invasive technique that can be used to diagnose inflammatory and neoplastic conditions early. However, additional research is required to establish the sensitivity and specificity of these thermal windows and validate their clinical use in dogs and cats.

An Automatic Procedure for Overheated Idler Detection in Belt Conveyors Using Fusion of Infrared and RGB Images Acquired during UGV Robot Inspection

Complex mechanical systems used in the mining industry for efficient raw materials extraction require proper maintenance. Especially in a deep underground mine, the regular inspection of machines operating in extremely harsh conditions is challenging, thus, monitoring systems and autonomous inspection robots are becoming more and more popular. In the paper, it is proposed to use a mobile unmanned ground vehicle (UGV) platform equipped with various data acquisition systems for supporting inspection procedures. Although maintenance staff with appropriate experience are able to identify problems almost immediately, due to mentioned harsh conditions such as temperature, humidity, poisonous gas risk, etc., their presence in dangerous areas is limited. Thus, it is recommended to use inspection robots collecting data and appropriate algorithms for their processing. In this paper, the authors propose red-green-blue (RGB) and infrared (IR) image fusion to detect overheated idlers. An original procedure for image processing is proposed, that exploits some characteristic features of conveyors to pre-process the RGB image to minimize non-informative components in the pictures collected by the robot. Then, the authors use this result for IR image processing to improve SNR and finally detect hot spots in IR image. The experiments have been performed on real conveyors operating in industrial conditions.

Infrared Thermography Evaluation of Feet Temperature and Its Association with Claw Lengths and Anisodactylia in Purebred Sows of Three Greek Herds

The aim of the study was to investigate the associations of lower feet temperature with claw lengths measurements in purebred sows. In total 22, 19 and 45 multiparous sows in three herds A, B and C of PIC, DANBRED and TOPIGS genetic lines respectively participated in the study. Mean parity was 2.5, 2.3 and 3.0 for sows from herds A, B and C respectively. Measurements were made during the periparturient period. Infrared temperature distribution was measured in carpus/tarsus, upper-lower metacarpi/metatarsi and phalanges (IRT1, IRT2, IRT3 and IRT4 respectively). In addition, dorsal, diagonal, heel-sole and dew claw lengths of medial and lateral claw were measured and the difference in dorsal claw length between medial and lateral claw (anisodactylia) was calculated in all four feet. Differences between herds regarding IRT and claw length measurements were analyzed with one-way ANOVA with herds as a fixed factor. Correlations between IRT and claw length measurements in each foot including data from all herds were evaluated using the Pearson's correlation test. Maximum IRT1 to 4 in almost all rear feet, differed significantly between herds, being lower in sows of herd C than A and B (p < 0.05). Claw lengths of all feet were lower in herd C than those of A and B (p < 0.05). Anisodactylia, differed significantly only in rear feet between herds been higher in herd A than C and B (p < 0.05). In all sows, claw lengths and rear feet anisodactylia were positively correlated with maximum IRT1 to IRT4 (p < 0.05). According to the results, IRT temperature distribution of lower feet of purebred sows of different genetic lines were positive correlated with claw lengths measurements and anisodactylia. Collectively, measuring IRT temperature of lower feet of sows with mobile IRT device could be used as an additional tool towards monitoring feet and claw health.

Effects of Reduced Space Allowance and Heat Stress on Behavior and Eye Temperature in Unweaned Lambs: A Pilot Study

Simple Summary

In Europe, young lambs can be transported long distances for slaughter. While transport is regulated by E.U. law, there is a lack of research investigating the optimal transport conditions specifically for young lambs. For example, while the regulations set a minimum space allowance for lambs above 26 kg, no minimum is specified for young lambs meaning they can be transported in overcrowded conditions. Further, while the temperature within the vehicle must be maintained between 5–30 °C, this is well above the 21 °C said to be the upper end of the comfortable range for lambs. This study aimed to investigate how variation in space allowance and temperature can affect the welfare of young lambs. Three groups of lambs were created where either the density of individuals (0.27 vs. 0.20 m² per head) or the temperature range (12–18 °C vs. 19–30 °C) varied. Lambs housed in the higher density and heat stress groups showed more discomfort and higher body temperatures. In addition, lambs kept in the heat stress group lost weight over the course of the study, and showed signs of heat stress when the temperature exceeded 25 °C. These results indicate that the regulations for the transport of young lambs need to be refined.

Abstract

Current European animal transportation law contains only a few and vague indications concerning how to move lambs of less than 26 kg. Moreover, little information is available in the literature about factors affecting these lambs’ welfare. We investigated the effect of space allowance and ambient temperature on the welfare of unweaned Lacaune lambs during a simulation of long-distance transportation (19 h). Three groups of lambs (N = 130) were housed in equally sized pens for 19 h, Control (C; n = 39; 0.27 m² per head), Low Space Allowance (LSA; n = 52; 0.20 m² per head), and Heat Stress (HS; n = 39; 0.27 m² per head) groups. LSA lambs had lower space allowance than C but were tested at the same temperature, within their Thermoneutral zone (range = 12–18 °C). The HS lambs were, instead, subjected to higher temperatures (range = 19–30 °C). Scan sampling of behavior was conducted, eye temperature and body weight were also recorded. LSA and HS lambs showed more discomfort behaviors (p < 0.05) and higher eye temperatures (p < 0.001) compared to C lambs, while HS lambs additionally showed a decrease in body weight over the experimental period (p < 0.001). This study indicates that lower space allowances and higher temperatures impact negatively the welfare of lambs transported for slaughter suggesting that the regulation should be implemented taking these factors into account.

Experimental Applications and Factors Involved in Validating Thermal Windows Using Infrared Thermography to Assess the Health and Thermostability of Laboratory Animals

Evaluating laboratory animals' health and thermostability are fundamental components of all experimental designs. Alterations in either one of these parameters have been shown to trigger physiological changes that can compromise the welfare of the species and the replicability and robustness of the results obtained. Due to the nature and complexity of evaluating and managing the species involved in research protocols, non-invasive tools such as infrared thermography (IRT) have been adopted to quantify these parameters without altering them or inducing stress responses in the animals. IRT technology makes it possible to quantify changes in surface temperatures that are derived from alterations in blood flow that can result from inflammatory, stressful, or pathological processes; changes can be measured in diverse regions, called thermal windows, according to their specific characteristics. The principal body regions that were employed for this purpose in laboratory animals were the orbital zone (regio orbitalis), auricular pavilion (regio auricularis), tail (cauda), and the interscapular area (regio scapularis). However, depending on the species and certain external factors, the sensitivity and specificity of these windows are still subject to controversy due to contradictory results published in the available literature. For these reasons, the objectives of the present review are to discuss the neurophysiological mechanisms involved in vasomotor responses and thermogenesis via BAT in laboratory animals and to evaluate the scientific usefulness of IRT and the thermal windows that are currently used in research involving laboratory animals.

An evaluation of thermal imaging as a welfare monitoring tool for captive chimpanzees

Among the growing list of novel tools with which to assess animal welfare is the use of thermal (infrared) imaging. The technology has already been utilized to identify emotional arousal in several nonhuman primate species, though most of these approaches have necessitated the use of relatively controlled settings. Here, we were interested to determine the feasibility of such techniques in a sanctuary setting in which chimpanzees were unrestrained and able to move freely around their enclosures. Furthermore, we sought to evaluate how such thermal images could be paired with corresponding long-term behavioral data and contribute to a multifactorial welfare monitoring system. Over a 6-month period, we simultaneously collected both behavioral and thermographic data on 29 chimpanzees living in four social groups. While we took a thermal image with every behavioral data point, we found that only a small proportion (6.38%) of the thermal images we captured were of sufficient quality to analyze. Most of these usable thermal images (55%) corresponded with a behavioral observation scored as "inactive," and thus other, less frequent behaviors are not so well represented in our final data set. From our data set, we were able to determine that nasal temperatures were relatively lower when chimpanzees were categorized in active behaviors compared to inactive behaviors, providing some validity measures to our approach. While there are other potential applications for thermal imaging in the behavioral management of chimpanzees, managers should consider the practical limitations of developing long-term welfare monitoring programs that rely on thermographic data.

Clinical Applications and Factors Involved in Validating Thermal Windows Used in Infrared Thermography in Cattle and River Buffalo to Assess Health and Productivity

Infrared thermography (IRT) is a non-ionizing, non-invasive technique that permits evaluating the comfort levels of animals, a topic of concern due to the growing interest in determining the state of health and welfare of production animals. The operating principle of IRT is detecting the heat irradiated in anatomical regions characterized by a high density of near-surface blood vessels that can regulate temperature gain or loss from/to the environment by modifying blood flow. This is essential for understanding the various vascular thermoregulation mechanisms of different species, such as rodents and ruminants' tails. The usefulness of ocular, nasal, and vulvar thermal windows in the orbital (regio orbitalis), nasal (regio nasalis), and urogenital (regio urogenitalis) regions, respectively, has been demonstrated in cattle. However, recent evidence for the river buffalo has detected discrepancies in the data gathered from distinct thermal regions in these large ruminants, suggesting a limited sensitivity and specificity when used with this species due to various factors: the presence of hair, ambient temperature, and anatomical features, such as skin thickness and variations in blood supplies to different regions. In this review, a literature search was conducted in Scopus, Web of Science, ScienceDirect, and PubMed, using keyword combinations that included "infrared thermography", "water buffalo", "river buffalo" "thermoregulation", "microvascular changes", "lacrimal caruncle", "udder", "mastitis", and "nostril". We discuss recent findings on four thermal windows-the orbital and nasal regions, mammary gland in the udder region (regio uberis), and vulvar in the urogenital region (regio urogenitalis)-to elucidate the factors that modulate and intervene in validating thermal windows and interpreting the information they provide, as it relates to the clinical usefulness of IRT for cattle (Bos) and the river buffalo (Bubalus bubalis).

Precision Technologies to Address Dairy Cattle Welfare: Focus on Lameness, Mastitis and Body Condition

Simple Summary

The welfare of farm animals is a growing concern in the EU and across the world. In milk production, there is a strong need to assess the welfare of dairy cows. One of the most sound assessment initiatives has been practiced using protocols developed by the Welfare Quality project. These protocols mainly support the assessment of cow welfare with animal-based indicators. However, evaluating these indicators is time-consuming and expensive, so using precision livestock farming (PLF) solutions is a way forward and is becoming a reality in the dairy industry. This review presents advances in PLF solutions, particularly in the last five years, and for assessing the animal-based indicators of lameness, mastitis, and body condition in dairy cattle farming.

Abstract

Specific animal-based indicators that can be used to predict animal welfare have been the core of protocols for assessing the welfare of farm animals, such as those produced by the Welfare Quality project. At the same time, the contribution of technological tools for the accurate and real-time assessment of farm animal welfare is also evident. The solutions based on technological tools fit into the precision livestock farming (PLF) concept, which has improved productivity, economic sustainability, and animal welfare in dairy farms. PLF has been adopted recently; nevertheless, the need for technological support on farms is getting more and more attention and has translated into significant scientific contributions in various fields of the dairy industry, but with an emphasis on the health and welfare of the cows. This review aims to present the recent advances of PLF in dairy cow welfare, particularly in the assessment of lameness, mastitis, and body condition, which are among the most relevant animal-based indications for the welfare of cows. Finally, a discussion is presented on the possibility of integrating the information obtained by PLF into a welfare assessment framework.

A Machine Vision-Based Method Optimized for Restoring Broiler Chicken Images Occluded by Feeding and Drinking Equipment

Simple Summary

The equipment in the poultry house can occlude top view images of broiler chickens and limit the efficiency of vision-based target detection. In this study, we sought to improve the efficiency of a previously developed method to detect and restore broiler chicken areas blocked by feeders and drinkers. To do this, we developed and tested linear and elliptical fitting restoration methods under different occlusion scenarios to restore occluded broiler chicken areas. The restoration method correctly restored the occluded broiler chicken area >80% of the time. This study provides a practical approach to enhancing the image quality in applying a machine vision-based method for monitoring poultry health and welfare.

Abstract

The presence equipment (e.g., water pipes, feed buckets, and other presence equipment, etc.) in the poultry house can occlude the areas of broiler chickens taken via top view. This can affect the analysis of chicken behaviors through a vision-based machine learning imaging method. In our previous study, we developed a machine vision-based method for monitoring the broiler chicken floor distribution, and here we processed and restored the areas of broiler chickens which were occluded by presence equipment. To verify the performance of the developed restoration method, a top-view video of broiler chickens was recorded in two research broiler houses (240 birds equally raised in 12 pens per house). First, a target detection algorithm was used to initially detect the target areas in each image, and then Hough transform and color features were used to remove the occlusion equipment in the detection result further. In poultry images, the broiler chicken occluded by equipment has either two areas (TA) or one area (OA). To reconstruct the occluded area of broiler chickens, the linear restoration method and the elliptical fitting restoration method were developed and tested. Three evaluation indices of the overlap rate (OR), false-positive rate (FPR), and false-negative rate (FNR) were used to evaluate the restoration method. From images collected on d2, d9, d16, and d23, about 100-sample images were selected for testing the proposed method. And then, around 80 high-quality broiler areas detected were further evaluated for occlusion restoration. According to the results, the average value of OR, FPR, and FNR for TA was 0.8150, 0.0032, and 0.1850, respectively. For OA, the average values of OR, FPR, and FNR were 0.8788, 0.2227, and 0.1212, respectively. The study provides a new method for restoring occluded chicken areas that can hamper the success of vision-based machine predictions.

Refinement and validation of infrared thermal imaging (IRT): a non-invasive technique to measure disease activity in a mouse model of rheumatoid arthritis

Background

The discovery and development of new medicines requires high-throughput screening of possible therapeutics in a specific model of the disease. Infrared thermal imaging (IRT) is a modern assessment method with extensive clinical and preclinical applications. Employing IRT in longitudinal preclinical setting to monitor arthritis onset, disease activity and therapeutic efficacies requires a standardized framework to provide reproducible quantitative data as a precondition for clinical studies.

Methods

Here, we established the accuracy and reliability of an inexpensive smartphone connected infrared (IR) camera against known temperature objects as well as certified blackbody calibration equipment. An easy to use protocol incorporating contactless image acquisition and computer-assisted data analysis was developed to detect disease-related temperature changes in a collagen-induced arthritis (CIA) mouse model and validated by comparison with two conventional methods, clinical arthritis scoring and paw thickness measurement. We implemented IRT to demonstrate the beneficial therapeutic effect of nanoparticle drug delivery versus free methotrexate (MTX) in vivo.

Results

The calibrations revealed high accuracy and reliability of the IR camera for detecting temperature changes in the rheumatoid arthritis animal model. Significant positive correlation was found between temperature changes and paw thickness measurements as the disease progressed. IRT was found to be superior over the conventional techniques specially at early arthritis onset, when it is difficult to observe subclinical signs and measure structural changes.

Conclusion

IRT proved to be a valid and unbiased method to detect temperature changes and quantify the degree of inflammation in a rapid and reproducible manner in longitudinal preclinical drug efficacy studies.

Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding

Genomic breeding programs have been paramount in improving the rates of genetic progress of productive efficiency traits in livestock. Such improvement has been accompanied by the intensification of production systems, use of a wider range of precision technologies in routine management practices, and high-throughput phenotyping. Simultaneously, a greater public awareness of animal welfare has influenced livestock producers to place more emphasis on welfare relative to production traits. Therefore, management practices and breeding technologies in livestock have been developed in recent years to enhance animal welfare. In particular, genomic selection can be used to improve livestock social behavior, resilience to disease and other stress factors, and ease habituation to production system changes. The main requirements for including novel behavioral and welfare traits in genomic breeding schemes are: (1) to identify traits that represent the biological mechanisms of the industry breeding goals; (2) the availability of individual phenotypic records measured on a large number of animals (ideally with genomic information); (3) the derived traits are heritable, biologically meaningful, repeatable, and (ideally) not highly correlated with other traits already included in the selection indexes; and (4) genomic information is available for a large number of individuals (or genetically close individuals) with phenotypic records. In this review, we (1) describe a potential route for development of novel welfare indicator traits (using ideal phenotypes) for both genetic and genomic selection schemes; (2) summarize key indicator variables of livestock behavior and welfare, including a detailed assessment of thermal stress in livestock; (3) describe the primary statistical and bioinformatic methods available for large-scale data analyses of animal welfare; and (4) identify major advancements, challenges, and opportunities to generate high-throughput and large-scale datasets to enable genetic and genomic selection for improved welfare in livestock. A wide variety of novel welfare indicator traits can be derived from information captured by modern technology such as sensors, automatic feeding systems, milking robots, activity monitors, video cameras, and indirect biomarkers at the cellular and physiological levels. The development of novel traits coupled with genomic selection schemes for improved welfare in livestock can be feasible and optimized based on recently developed (or developing) technologies. Efficient implementation of genetic and genomic selection for improved animal welfare also requires the integration of a multitude of scientific fields such as cell and molecular biology, neuroscience, immunology, stress physiology, computer science, engineering, quantitative genomics, and bioinformatics.

Emotion estimation using a wearable heart rate monitoring device in Asian elephants (Elephas maximus) during veterinary clinical procedures

Fatal accidents in captive elephants occasionally occur because humans are unable to gauge elephants’ emotions solely by their behavior. The intellectual capacity of elephants makes them capable of understanding circumstantial changes and associated emotions, allowing them to react accordingly. Physiological markers, such as heart rate variability, may be effective in determining an elephant’s emotional state. In this study, a wearable heart rate monitor was used to determine the emotional state of a female Indian captive elephant (Elephas maximus indicus). The average heart rate was higher when the elephant underwent painful treatment than when it underwent non-painful treatment. In addition, the heart rate increased both before and after the treatment, which included radiography and blood collection.

Infrared thermography of agonistic behaviour in pigs

Infrared thermography (IRT) or thermal imaging is increasingly being used as a non-invasive method to gain information on animals' physiological and emotional state. IRT has the potential to serve as a non-invasive quantitative assessment method but few studies have examined its utility in predicting welfare-relevant outcomes of dynamic scenarios relevant to commercial farming. This study used 1284 thermal images taken from 46 pigs in a controlled test environment while they engaged in an agonistic encounter (dyadic contest) at 13 wk. of age. Images were taken of the complete body from a dorsal perspective. A pilot study indicated that a rectangular thermal window on the back region was the most suitable and reliable area for obtaining temperature data in this situation. From this thermal window, the average, minimum and maximum temperature, standard deviation and coefficient of variation (CV) were obtained. These were analysed in relation to contest phase (from non-contact assessment, through escalated fighting to retreat), fight occurrence, contest duration, contest outcome (winner/loser status) and changes in blood glucose, blood lactate, and skin injuries. Variables showed a strong change in response to the moment of contest resolution (retreat of the loser); temperatures reduced sharply and CV increased, but did not differ between winners and losers. Contests that included a fight showed lower temperatures. Contest duration, body weight and sex only had minor influences on the temperatures. As the drop in temperature at contest resolution was irrespective of contest intensity, and the pattern was similar in winners and losers, this data potentially reflects vasoconstriction as a result of psychological stress rather than solely a physiological change. The study shows that peripheral temperature, as recorded by IRT, responds to the intensity and phases of a contest and may allow new insight into the physiological and welfare outcomes of aggressive behaviour.

Automated bioacoustics: methods in ecology and conservation and their potential for animal welfare monitoring

Vocalizations carry emotional, physiological and individual information. This suggests that they may serve as potentially useful indicators for inferring animal welfare. At the same time, automated methods for analysing and classifying sound have developed rapidly, particularly in the fields of ecology, conservation and sound scene classification. These methods are already used to automatically classify animal vocalizations, for example, in identifying animal species and estimating numbers of individuals. Despite this potential, they have not yet found widespread application in animal welfare monitoring. In this review, we first discuss current trends in sound analysis for ecology, conservation and sound classification. Following this, we detail the vocalizations produced by three of the most important farm livestock species: chickens ( Gallus gallus domesticus), pigs ( Sus scrofa domesticus) and cattle ( Bos taurus). Finally, we describe how these methods can be applied to monitor animal welfare with new potential for developing automated methods for large-scale farming.

Infrared Thermography as an Indicator of Heat Loss in Fur-Chewing Chinchillas (Chinchilla Lanigera)

Fur-chewing is a common problem in chinchilla (Chinchilla lanigera). It may affect the welfare of animals due to heat loss, thereby possibly impacting food and water intake to maintain body temperature. In this context, infrared thermography seems to be a suitable method of measuring heat emissions from the surface of objects. Sexually mature male domestic chinchillas were divided into two groups: "non-fur chewers", exhibiting normal behaviour (n = 25), and "fur chewers" displaying fur-chewing behaviour (n = 23). Food and water intake (mean ± SD) measured in the control animals amounted to 20.7 ± 4.52 g and 15.9 ± 3.45 mL, while in fur-chewing chinchillas were 25% and 33% higher, respectively. Metabolic energy intake, were calculated 2.2 and 2.8 W for the control and fur-chewing animals, respectively. Heat flux through chewed areas was 6.06 mW cm-2, which is 2.8 times higher than through undamaged chinchilla fur. To sum up, thermal imagingexplicitly shows that fur-chewing causes increased heat loss. Disturbances in the maintenance of thermal homeostasis may be an additional factor that reduces the welfare of these animals.

Assessing the welfare of kennelled dogs-A review of animal-based measures

Hundreds of thousands of dogs are housed in kennels worldwide, yet there are no standard protocols for assessing the welfare of dogs in these environments. Animal science is focusing increasingly on the importance of animal-based measures for determining welfare states, and those measures that have been used with kennelled dogs are reviewed in this paper with particular focus on their validity and practicality. From a physiological standpoint, studies using cortisol, heart rate and heart rate variability, temperature changes, and immune function are discussed. Behavioural measures are also of great relevance when addressing canine welfare, thus studies on fear and anxiety behaviours, abnormal behaviours like stereotypies, as well as responses to strangers and novel objects are reviewed. Finally, a limited number of studies attempting to use cognitive bias and learning ability are also mentioned as cognitive measures. The literature to date provides a strong background for which measures may be useful in determining the welfare of kennelled canines, however more research is needed to further assess the value of using these methods, particularly in regard to the large degree of individual differences that exist between dogs.

Detecting and Predicting Emerging Disease in Poultry With the Implementation of New Technologies and Big Data: A Focus on Avian Influenza Virus

Future demands for food will place agricultural systems under pressure to increase production. Poultry is accepted as a good source of protein and the poultry industry will be forced to intensify production in many countries, leading to greater numbers of farms that house birds at elevated densities. Increasing farmed poultry can facilitate enhanced transmission of infectious pathogens among birds, such as avian influenza virus among others, which have the potential to induce widespread mortality in poultry and cause considerable economic losses. Additionally, the capability of some emerging poultry pathogens to cause zoonotic human infection will be increased as greater numbers of poultry operations could increase human contact with poultry pathogens. In order to combat the increased risk of spread of infectious disease in poultry due to intensified systems of production, rapid detection and diagnosis is paramount. In this review, multiple technologies that can facilitate accurate and rapid detection and diagnosis of poultry diseases are highlighted from the literature, with a focus on technologies developed specifically for avian influenza virus diagnosis. Rapid detection and diagnostic technologies allow for responses to be made sooner when disease is detected, decreasing further bird transmission and associated costs. Additionally, systems of rapid disease detection produce data that can be utilized in decision support systems that can predict when and where disease is likely to emerge in poultry. Other sources of data can be included in predictive models, and in this review two highly relevant sources, internet based-data and environmental data, are discussed. Additionally, big data and big data analytics, which will be required in order to integrate voluminous and variable data into predictive models that function in near real-time are also highlighted. Implementing new technologies in the commercial setting will be faced with many challenges, as will designing and operating predictive models for poultry disease emergence. The associated challenges are summarized in this review. Intensified systems of poultry production will require new technologies for detection and diagnosis of infectious disease. This review sets out to summarize them, while providing advantages and limitations of different types of technologies being researched.

Effects of Short Transport and Prolonged Fasting in Beef Calves

Simple Summary

Marketing is inherently stressful for animals because they are removed from their home environment, handled, and transported. When sold at a livestock market, the events associated with transport are duplicated, in that animals are delivered to and then transported from the market, animals are kept confined in an unknown environment and are often mixed with unfamiliar animals, and fasting times increase. For calves, the stress of weaning is added, because the weaning process often takes place moments before being loaded for transport. In Chile, approximately one million cattle go through livestock markets annually and over 30% of them, being the largest category, are calves. Some studies have shown that calves sold through markets suffer from extended fasting periods, even when exposed to only short transportation times. The aim of this study was to determine the consequences of a short transportation time followed by an extended period without food and water. This was undertaken by measuring variables related to stress in beef calves. The results obtained showed a significant physiological effect on body temperature, blood indicators and live weight (LW). Calves lost a mean of 10 kg each after 24 h of fasting. LW loss is probably the most significant economic effect, since animals are traded based on weight. Further studies to measure the impact during true, commercial marketing are needed.

Abstract

Marketing is a stressful process for beef calves, because they are removed from their environment, often weaned just before loading, loaded, transported, and unloaded. It also involves extended periods without food and water and mixing with unfamiliar animals in an unknown environment. Some studies have shown that calves sold through markets are exposed to extended fasting periods even when they undergo only short transportation times. The aim of this controlled study was to determine the consequences for beef calves of a short transportation time followed by a prolonged time without food and water on their tympanic temperature (TT), maximum eye temperature (MET), blood variables related to stress, and live weight. Ten calves were transported for 3 h and then kept in an outdoor pen for 21 h, completing a 24 h fasting period. Sampling took place before loading, after transport and unloading, and then after completing 24 h without food and water. TT, MET, blood glucose, and creatine kinase (CK) increased significantly after transportation. Live weight decreased across sample times (mean of 10 kg per calf after 24 h of fasting), which was consistent with the higher concentration of β-HB found after fasting. Further studies to measure the actual consequences of true, commercial marketing on calf welfare and productivity are needed.

Technology and Poultry Welfare

Consideration of animal welfare is essential to address the consumers’ demands and for the long term sustainability of commercial poultry. However, assessing welfare in large poultry flocks, to be able to detect potential welfare risks and to control or minimize its impact is difficult. Current developments in technology and mathematical modelling open new possibilities for real-time automatic monitoring of animal welfare and health. New technological innovations potentially adaptable to commercial poultry are appearing, although their practical implementation is still being defined. In this paper, we review the latest technological developments with potential to be applied to poultry welfare, especially for broiler chickens and laying hens. Some of the examples that are presented and discussed include the following: sensors for farm environmental monitoring, movement, or physiological parameters; imaging technologies such as optical flow to detect gait problems and feather pecking; infrared technologies to evaluate birds’ thermoregulatory features and metabolism changes, that may be indicative of welfare, health and management problems. All these technologies have the potential to be implemented at the commercial level to improve birds’ welfare and to optimize flock management, therefore, improving the efficiency of the system in terms of use of resources and, thus, long term sustainability.

An instantaneous approach for determining the infrared emissivity of swine surface and the influencing factors

Infrared thermal imaging technology has been widely employed in temperature measurements of human and animals and its accuracy relies on the determination process of the emissivity of the target to a large extent. However, common used methods were unable to determine the emissivity of the surface of living animals and thus lower the accuracy. In this paper, we suggested a new approach to acquire the infrared emissivity of living swine in real time. In the approach, the surface temperature of swine and reference body were measured to compute the emissivity and the measurement process was completed in a non-contact and non-invasive manner. We changed the surface reflection energy of animals and reference body by changing the ambient radiant energy and obtain the surface emissivity in real time without confirming the actual temperature of animal surface. In this way, the infrared emissivity of the animal surface can be determined instantaneously and without knowing the real temperature. Both swine specimen and a living swine were used in this study. Using this method, we measured the emissivity of different body sites of the swine. The results showed that the emissivity values at different body sites show the significant differences. The emissivity values at trotter and eye were respectively 0.895 and 0.930 and the emissivity on swine surface varied from 0.945 to 0.978. More important, the distribution of the infrared emissivity on a living swine was explored and the detailed differences of the emissivity on a swine surface can be cleanly seen. Furthermore, we studied the influencing factors on the emissivity of animal surface, through measuring the emissivity distribution on swine surface when pig specimens were sprayed with water on the surface or heated using this method. This study is of great significance for the accurate measurement of swine surface temperature.

BEM-ESTAR DE GALINHAS POEDEIRAS EM DIFERENTES DENSIDADES DE ALOJAMENTO

O estudo foi realizado com objetivo de avaliar os parâmetros fisiológicos de poedeiras alojadas em diferentes densidades de alojamento e períodos. Foram utilizadas 150 poedeiras Dekalb White com 20 semanas de idade alojadas em um galpão convencional com gaiolas metálicas com duas subdivisões de 50x45x40 cm2 e distribuídas em três tratamentos: 8 aves por gaiola (562,5 cm2/ave); 10 aves por gaiola (450 cm2/ave) e 12 aves por gaiola (375 cm2/ave), com cinco repetições cada. Avaliaram-se parâmetros fisiológicos (frequência respiratória, temperatura cloacal e temperatura superficial) e condições ambientais (temperatura ambiente e umidade relativa) durante três ciclos de 28 dias. Adotou-se um delineamento inteiramente casualizado com arranjo fatorial 3x3 (três densidades de alojamento e três períodos). Os resultados demonstraram que a densidade de alojamento não prejudicou a frequência respiratória e a temperatura superficial, porém, a temperatura cloacal diferiu significativamente, sendo superior às 16 horas e a densidade de alojamento com 10 aves/gaiola permaneceu intermediário às outras densidades. Os parâmetros voltados à busca do conforto térmico evidenciaram que nos horários mais quentes do dia (até as 16:00 horas), independente da densidade, as aves apresentaram temperaturas maiores que na parte da manhã.