Infrared thermography and behavioral biometrics associated with estrus indicators and ovulation in estrus-synchronized dairy cows housed in tiestalls

The Potential of Infrared Thermography for Early Pregnancy Diagnosis in Nili-Ravi Buffaloes

This study was designed to explore the potential of infrared thermography (IRT) as an alternate approach for early pregnancy diagnosis in buffaloes. The surface temperature (ST) of different regions (eyes, muzzle, flanks, and vulva) was determined in 27 buffaloes using IRT from the day of artificial insemination (AI; Day 0), and measurement was repeated every fourth day until Day 24 post-AI. From all regions, the ST in each thermograph was recorded at three temperature values (maximum, average, minimum). Pregnancy status was confirmed through ultrasonography on Day 30, and animals were retrospectively grouped as pregnant or non-pregnant for analysis of thermographic data. In pregnant buffaloes, all three values of ST were significantly greater (p ≤ 0.05) for the left flank, while, in the left eye and vulva, only the maximum and average values were significantly greater. By contrast, the maximum ST of the muzzle was significantly lower (p ≤ 0.05) in pregnant buffaloes compared to non-pregnant buffaloes. However, the ST of the right eye and right flank did not show significant temperature variation at any value. These findings suggest that IRT has the potential to identify thermal changes associated with pregnancy in buffaloes at an early stage.

Early prediction of oestrus for herd fertility management in cattle and buffaloes - a review

Oestrus is defined as a period when a female animal exhibits characteristic sexual behaviour in the presence of a mature male. Oestrous manifestation in dairy animals is due to the oestrogen (E2) effect on the central nervous system (CNS). It is a critical issue to be considered on a priority basis. Inefficient oestrous detection reduces the fertility status of the herd. The primary and most reliable indicator of oestrus is standing to be mounted by a bull or another female herd mate, signalling receptivity and the pre-ovulatory state in dairy cattle. Oestrous detection is primarily a management challenge requiring skill and vigilance. To improve the efficiency of oestrous detection in dairy cattle, visual observation is one of the best methods if done three times a day; however, heat detection aids, if combined, give better results. However, techniques like using teaser bulls, tail painting, chin ball markers, ultrasound (USG) examination, hormonal analysis and examination of cervicovaginal mucus (CVM) improve oestrous detection efficiency. Moreover, the changes in production systems have reduced the expression of oestrous behaviour among cows, due to higher oestrogen (E2) metabolism. Therefore, automated systems, such as pedometers, accelerometers and acoustic sensors like infrared thermography (IRT) and image processing, have significantly enhanced reproductive performance by facilitating oestrous detection and optimizing insemination schedules. From this review, we would conclude that oestrous detection alone contributes considerably to the reproductive status of the herd; therefore, applying different methods of oestrous detection reduces the incidence of missed oestrus and improves the fertility status of the herd.

Capturing temperature changes on the ocular surface along with estrus and ovulation using infrared thermography in Japanese Black cows

Pre-ovulatory follicles are cooler than the neighboring reproductive organs in cows. Thus, measuring the temperature of reproductive organs could be a useful method for predicting estrus and ovulation in cows, and the establishment of a non-invasive technique is required. In this study, we used infrared thermography (IRT) to measure ocular surface temperature as a potential surrogate for reproductive organ temperature. Five Japanese Black cows with synchronized estrus were subjected to temperature measurements in five regions of the ocular surface, including the nasal conjunctiva, nasal limbus, center cornea, temporal limbus, and temporal conjunctiva, twice a day (0800 h and 1600 h) during the experimental period. The temperatures in the five regions significantly declined in cows from estrus to ovulation. To the best of our knowledge, this study is the first to use IRT to show a temperature decrease in the ocular surface along with estrus to ovulation in Japanese Black cows.

Increase of body temperature immediately after ovulation in mares

To successfully inseminate mares, precise detection of ovulation time is crucial, especially when using frozen-thawed semen. Monitoring body temperature, as has been described in women, could be a non-invasive way to detect ovulation. The objective of this study was to investigate the relationship between the time of ovulation and the variation of body temperature in mares based on automatic continuous measurements during estrus. The experimental group included 21 mares for 70 analyzed estrous cycles. When the mares showed estrous behavior, they were administered intramuscular deslorelin acetate (2.25 mg) in the evening. At the same time, monitoring of body temperature using a sensor device fixed at the left lateral thorax was started and continued for over 60 h. In 2-hour intervals, transrectal ultrasonography was performed to detect ovulation. Estimated body temperature in the 6 h following ovulation detection was on average 0.06°C +/- 0.05°C (mean +/- SD) significantly higher when compared with body temperature at the same time on the preceding day (p=0.01). In addition, a significant effect of PGF_2α administration for estrus induction on the body temperature was found, being significantly higher until 6 h before ovulation compared to that of uninduced cycles (p=0.005). In conclusion, changes in body temperature during estrus in mares were related to ovulation. The increase in body temperature immediately after ovulation might be used in the future to establish automatized and non-invasive systems to detect ovulation. However, the identified temperature rise is relatively small on average and hardly identifiable in the individual mares.

Infrared Thermography as a Potential Non-Invasive Tool for Estrus Detection in Cattle and Buffaloes

The productivity of dairy animals has significantly increased over the past few decades due to intense genetic selection. However, the enhanced yield performance of milk animals caused a proportional increase in stress and compromised reproductive efficiency. Optimal reproductive performance is mandatory for the sustainable production of dairy animals. Reproductive efficiency is marked by proper estrus detection and precise breeding to achieve maximum pregnancies. The existing conventional methods of estrus detection are somewhat labor intensive and less efficient. Similarly, the modern automated methods that rely on detecting physical activity are expensive, and their efficiency is affected by factors such as type of housing (tie stall), flooring, and environment. Infrared thermography has recently emerged as a technique that does not depend on monitoring physical activity. Furthermore, infrared thermography is a non-invasive, user-friendly, and stress-free option that aids in the detection of estrus in dairy animals. Infrared thermography has the potential to be considered a useful non-invasive tool for detecting temperature fluctuations to generate estrus alerts without physical contact in cattle and buffaloes. This manuscript highlights the potential use of infrared thermography to understand reproductive physiology and practical implementation of this technique through discussing its advantages, limitations, and possible precautions.

Infrared thermography as a tool for the measurement of negative emotions in dairy cows

In commercial dairy cows, the conditions in which they are kept may lead to negative emotional states associated with the development of chronic physiological and behavioural abnormalities that may compromise their health, welfare and productivity. Such states include fear, stress or anxiety. Behavioural rather than physiological tests are more likely to be used to indicate these states but can be limited by their subjectivity, need for specialised infrastructure and training (of the operator and sometimes the animal) and the time-consuming nature of data collection. Popularly used physiological measures such as blood cortisol may be more appropriate for acute rather than chronic assessments but are easily confounded, for example by a response to the act of measurement per se. More sophisticated physiological measures such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) may be impractical due to cost and time and, like blood cortisol, have the confounding associated with the act of measurement. By contrast, infrared thermography of external body surfaces is remote, non-invasive, easily repeated and follows an objective methodology, allowing longitudinal data acquisition for the inference of changes in chronic emotional state over time. The objective of this review was to investigate the potential of infrared thermography to measure cow emotions. In lactating dairy cows, maximum IRT of the eyes and coronary band of the limbs seem to be most representative of thermoregulatory changes, which are repeatable and correlate with behavioural and physiological indicators of emotional state. IRT methodologies have the potential to become a fundamental tool for the objective assessment of welfare state in dairy cows.

Diagnosis of lameness via data mining algorithm by using thermal camera and image processing method in Brown Swiss cows

Lameness is one of the culling factors such as mastitis, low milk yield, and infertility that cause economic losses in herd management as they threaten animal health and welfare. The purpose of this study was to evaluate the early detection of lameness in Brown Swiss cattle by using a data mining algorithm by both integrating lameness scores and some image parameters such as Lab (CIE L*, a*, b*), HSB (hue, saturation, brightness), RGB (red, green, blue) by processing thermal images with ImageJ program. In the study, the variables obtained as a result of processing the skin surface temperatures and thermal images taken at the fetlock joint of 33 Brown Swiss cattle were used as independent variables. Also, healthy cows (lameness scores 1 and 2) and unhealthy cows (lameness scores 3, 4, and 5) used in the diagnosis of lameness were used as a binary response variable. Classification and regression tree (CART) was used as a data mining algorithm in the diagnosis of lameness. As a result, the CART algorithm correctly classified 12 of the 13 heads unhealthy cows according to locomotion scores. According to locomotion scores by using CART analysis in this study, independent variables that are used to classify healthy and unhealthy (lame) animals were determined as maximum temperature (Tmax), green (mean), L (max), and age (P<0.05). The cut-off values of these independent variables were predicted as 32.40, 149.14, 97.11, and 5.50 for Tmax, green (mean), L (max), and age, respectively. Also, the sensitivity, specificity, and area under the ROC curve (AUC) of the CART algorithm for locomotion scoring were found as 92.31%, 95%, and 93.7% respectively. The area under ROC curve (AUC) was found to be significant in the diagnosis of lameness (P<0.01). Results showed that the use of CART classification algorithm together with thermal camera and image processing methods is a usefull tool in the detection of lameness in the herds. It is recommended that more comprehensive studies by increasing the number of animals in the future would be more beneficial.

Evaluating automated infrared thermography and vulva exposure tracking as components of an estrus detection platform in a commercial dairy herd

The primary objective of this study was to develop an automated infrared thermography platform (Estrus BenchMark) capable of measuring skin temperature and tail movements as a means of identifying cows in estrus. The secondary objective was to evaluate the accuracy of Estrus BenchMark to detect estrus compared to in-line milk progesterone (P₄) analysis (Herd Navigator System) in a commercial dairy herd managed under a robotic milking system. Data were collected on forty-six cows from 45 to 120 d after calving. Cows were flagged in estrus when milk P₄ fell below 5 ng/mL. The Estrus BenchMark true positive estrus alerts (Sensitivity; Se%) were compared to Herd Navigator System estrus alerts at different time-windows (±12 h, ±24 h, ±48 h, and ±72 h) relative to the Estrus BenchMark estrus alerts for all the estrus alerts (AE) and confidence-quality estrus (CQE; >80% quality) alerts identified by Herd Navigator System. The Estrus BenchMark captured skin temperature and tail movements resulting in vulva exposure (left tail movements, LTail; right tail movements, RTail; and pooled tail movements, PTail) for each milking event. Skin temperature tended to increase when the milk P₄ concentration (Least-Squares Means ± SE) dropped for AE (estrus day [d 0]; P₄; 3.51 ± 0.05 ng/mL, Skin temperature; 33.31 ± 2.38 °C) compared with d -7 (P₄; 20.22 ± 0.73 ng/mL; Skin temperature: 32.05 ± 3.77 °C). The increase in skin temperature, however, was significant in cows with CQE > 80% at d 0 (32.75 ± 0.29 °C) compared to d -7 (31.80 ± 0.28 °C). The prevalence of tail movements to expose vulva was greater (P = 0.01) in AE at d 0 (LTail: 62.50%; PTail; 68.75%; and RTail: 56.25%) compared with d -7 (LTail: 18.75%; PTail: 9.37%: and RTail: 9.37%), and d +4 (LTail: 9.37%; PTail: 9.37%; and RTail: 12.5%). Moreover, the higher prevalence of tail movements at d 0 was observed in cows with CQE > 80% (LTail; 65%, PTail; 80%, and RTail; 70%) compared to those with CQE < 80%. The highest Estrus BenchMark Youden index (YJ; 0.45), diagnostic odds ratio (DOR; 9.04), and Efficiency (0.77) were achieved for AE in a ±48 h window and at ±72 h window for CQE (YJ; 0.66, DOR; 25.29, and Efficiency 0.76) relative to Herd Navigator System estrus alerts. The highest Estrus BenchMark resulted in 58% estrus detection rates for AE and 80% for cows with CQE compared to the Herd Navigator System.

Industry 4.0 and Precision Livestock Farming (PLF): An up to Date Overview across Animal Productions

Precision livestock farming (PLF) has spread to various countries worldwide since its inception in 2003, though it has yet to be widely adopted. Additionally, the advent of Industry 4.0 and the Internet of Things (IoT) have enabled a continued advancement and development of PLF. This modern technological approach to animal farming and production encompasses ethical, economic and logistical aspects. The aim of this review is to provide an overview of PLF and Industry 4.0, to identify current applications of this rather novel approach in different farming systems for food producing animals, and to present up to date knowledge on the subject. Current scientific literature regarding the spread and application of PLF and IoT shows how efficient farm animal management systems are destined to become. Everyday farming practices (feeding and production performance) coupled with continuous and real-time monitoring of animal parameters can have significant impacts on welfare and health assessment, which are current themes of public interest. In the context of feeding a rising global population, the agri-food industry and industry 4.0 technologies may represent key features for successful and sustainable development.

Business analysis of IRT, Visual observation, and Ovsynch as breeding strategies in Alberta dairies

The dairy industry is searching for new technologies to address low (<50%) estrus detection. However, the lack of information on the potential economic benefits regarding new technology implementation has led some dairy producers to continue using conventional estrus detection methods (e.g. visual observation of standing to be mounted). The objective of this study was to compare the costs of infrared thermography (IRT), visual observation (VO) and ovulation synchronization (Ovsynch: OVS) as breeding strategies at different accuracy levels (Sensitivity [Se], Specificity [Sp]) and pregnancy rates (PR). The costs associated with Breeding, Feeding, Operation Costs, Return to Equity and Culling Risk per estrus detection rate (ER; 30-100%, conception rate for OVS; 30-100%), PR [PR per Parity group; 1-2 (50%), 3-4 (43%), and >4 (41%)], and ER accuracy determined the potential financial benefit of each breeding method for a representative farm. Breeding Cost results (Canadian dollars per cow; CAD/cow) showed a higher cost of OVS (138.99) as compared to VO (115.78) and IRT (127.69). Pregnancy Costs were affected by Breeding Cost; however, ER had a significant effect on PR expense for each method, IRT (ER; 30%: 210.38; 100%: 132.19), VO (ER; 30%: 205.93; 100%: 129.39), and OVS (ER; 30%: 247.21; 100%: 155.33). The minimum Se level with a positive Financial Effect for IRT and VO was 60% with a Sp of 100%, and for the OVS was Se 65% and Sp 100%. However, when the Se was 100% a positive Financial Effect was observed with a minimum Sp of 85% for IRT and 75% for VO. Culling Risk was reduced if ER increases differently depending on the parity group. Implementing of IRT as an estrus detection method yields a competitive breeding cost compared to VO and OVS. Further, breeding methods must accomplish at least ∼60% accuracy to have a positive net return.

Contribution of Precision Livestock Farming Systems to the Improvement of Welfare Status and Productivity of Dairy Animals

Although the effects of human–dairy cattle interaction have been extensively examined, data concerning small ruminants are scarce. The present review article aims at highlighting the effects of management practices on the productivity, physiology and behaviour of dairy animals. In general, aversive handling is associated with a milk yield reduction and welfare impairment. Precision livestock farming systems have therefore been applied and have rapidly changed the management process with the introduction of technological and computer innovations that contribute to the minimization of animal disturbances, the promotion of good practices and the maintenance of cattle’s welfare status and milk production and farms’ sustainability and competitiveness at high levels. However, although dairy farmers acknowledge the advantages deriving from the application of precision livestock farming advancements, a reluctance concerning their regular application to small ruminants is observed, due to economic and cultural constraints and poor technological infrastructures. As a result, targeted intervention training programmes are also necessary in order to improve the efficacy and efficiency of handling, especially of small ruminants.

Allonursing in Wild and Farm Animals: Biological and Physiological Foundations and Explanatory Hypotheses

The dams of gregarious animals must develop a close bond with their newborns to provide them with maternal care, including protection against predators, immunological transference, and nutrition. Even though lactation demands high energy expenditures, behaviors known as allonursing (the nursing of non-descendant infants) and allosuckling (suckling from any female other than the mother) have been reported in various species of wild or domestic, and terrestrial or aquatic animals. These behaviors seem to be elements of a multifactorial strategy, since reports suggest that they depend on the following: species, living conditions, social stability, and kinship relations, among other group factors. Despite their potential benefits, allonursing and allosuckling can place the health and welfare of both non-filial dams and alien offspring at risk, as it augments the probability of pathogen transmission. This review aims to analyze the biological and physiological foundations and bioenergetic costs of these behaviors, analyzing the individual and collective advantages and disadvantages for the dams' own offspring(s) and alien neonate(s). We also include information on the animal species in which these behaviors occur and their implications on animal welfare.

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).

Evaluation of infrared thermography combined with behavioral biometrics for estrus detection in naturally cycling dairy cows

Low estrus detection rates (>50%) are associated to extended calving intervals, low economic profit and reduced longevity in Holstein dairy cows. The objective of this study was to evaluate the accuracy of infrared thermography and behavioral biometrics combined as potential estrus alerts in naturally (not induced) cycling dairy cows housed in a tie-stall barn. Eighteen first lactation cows were subjected to transrectal ultrasonography to determine spontaneous ovulation. The dominant follicle (DF) disappearance was used retrospectively as an indirect indicator of ovulation, and to establish the estrus period (48-24 h prior the DF disappearance). Raw skin temperature (Raw IR) and residual skin temperature (Res IR) were recorded using an infrared camera at the Vulva area with the tail (Vtail), Vulva area without the tail (Vnotail), and Vulva's external lips (Vlips) at AM and PM milking from Day 14 until two days after ovulation was confirmed. Behavioral biometrics were recorded on the same schedule as infrared scan. Behavioral biometrics included large hip movements (L-hip), small hip movements (S-hip), large tail movements and small tail movements to compare behavioral changes between estrus and nonestrus periods. Significant increases in Raw IR skin temperature were observed two days prior to ovulation (Vtail; 35.93 ± 0.27 °C, Vnotail; 35.59 ± 0.27 °C, and Vlips; 35.35 ± 0.27 °C) compared to d -5 (Proestrus; Vtail; 35.29 ± 0.27 °C, Vnotail; 34.93 ± 0.31 °C, and Vlips; 34.68 ± 0.27 °C). No significant changes were found for behavioral parameters with the exception of S-hip movements, which increased at two days before ovulation (d -2; 11.13 ± 1.44 Events/5min) compared to d -5 (7.30 ± 1.02 Events/5min). To evaluate the accuracy of thermal and behavioral biometrics, receiver operating characteristic curve analysis was performed using Youden index (YJ), diagnostic odds ratio, positive likelihood ratio (LR+), Sensitivity, Specificity and Positive predicted value to score the estrus alerts. The greatest accuracy achieved using thermal parameters was for Res IR Vtail PM (YJ = 0.34) and L-hip PM (YJ = 0.27) for behavioral biometrics. Combining thermal and behavioral parameters did not improve the YJ index score but reduced the false-positive occurrence observed by increasing the diagnostic odds ratio (26.62), LR+ (12.47), Specificity (0.97) and positive predicted value (0.90) in a Res IR Vtail PM, S-hip AM, S-hip PM combination. The combination of thermal and behavioral parameters increased the accuracy of estrus detection compared to either thermal or behavioral biometrics, independently in naturally cycling cows during milking.

Infrared thermography reveals surface body temperature changes during proestrus and estrus reproductive phases in Gyr heifers (Bos taurus indicus)

Our aim was to evaluate the application of infrared thermography (IRT) to detect body surface temperature variation of body regions during the proestrus and estrus phases of the reproductive cycle of Gyr heifers and investigate environmental factors that could affect these measurements. Fifty-seven heifers were submitted to an ovulation synchronization protocol. This was followed by monitoring the heifers every 12 h over 60 h. Heifers were monitored for rectal and vaginal temperature using a digital thermometer. The surface temperature of the eye, vulva, and muzzle regions were monitored by IRT. Meteorological data was recorded for temperature and humidity. Observation of sexual behavior was performed to monitor estrus onset. Transrectal ultrasonography was used to identify the dominant follicle and confirm ovulation of all heifers. We observed a decrease in temperature of the rectum and vagina, as well as in the eye and vulva regions within the first 12 h after the completion of the synchronization. This period coincides with the expected proestrus phase of the estrous cycle. A progressive increase in all temperatures was noticed in the following 36 h, which coincides with the estrus phase of the reproductive cycle. The regions evaluated around the vulva and eye exhibited the highest temperature and experienced less environmental distortion than the muzzle area thermographs. Environmental factors, such as rainfall and temperature-humidity index, influenced the IRT readings altering the radiation patterns detected. In conclusion, IRT is an effective method to detect temperature variation during the proestrus and estrus phases in Gyr heifers. Furthermore, biological and environmental effects should be considered when collecting and interpreting IRT data in livestock.