Using temperature-sensing reticular boluses to aid in the detection of production diseases in dairy cows

The Relationship between Reticuloruminal Temperature, Reticuloruminal pH, Cow Activity, and Clinical Mastitis in Dairy Cows

We hypothesized that reticuloruminal temperature, pH as well as cow activity can be used as parameters for the early diagnosis of clinical mastitis in dairy cows. Therefore, we aimed to detect the relationship between these factors and the disease. We randomly selected cows with clinical mastitis and clinically healthy cows (HG) out of 600 milking cows. We recorded the following parameters during the experiment: reticulorumen temperature (RR temp.), reticulorumen pH (RR pH), and cow activity. We used smaXtec boluses (smaXtec animal care technology^®, Graz, Austria). In this investigation, reticulorumen data obtained seven days before diagnosis were compared to HG data from the same time period. CM cows were observed on the same days as the healthy cows. The healthy group's RR pH was 7.32% higher than that of cows with CM. Reticulorumen temperature was also 1.25% higher in the CM group than in the control group. The healthy group had a higher average value for walking activity, which was 17.37% higher than the CM group. The data of reticulorumen pH changes during 24 h showed that during the day, the pH changed from 5.53 to 5.83 in the CM group. By contrast, pH changed from 6.05 to 6.31 in the control group. The lowest reticulorumen pH in the CM group was detected on the third day before diagnosis, which was 15.76% lower than the highest reticulorumen pH detected on the sixth day before diagnosis. The lowest reticulorumen pH in CM cows was detected at 0 and 1 days before diagnosis and it was 1.45% lower than the highest reticulorumen pH detected on the second day before diagnosis. The lowest walking activity in the CM group was detected 0 days before diagnosis, which was 50.60% lower than on the fifth day before diagnosis. Overall, the results confirmed our hypothesis that reticuloruminal temperature, reticuloruminal pH, and cow activity could be used as parameters for the early diagnosis of clinical mastitis in dairy cows.

[Body temperature measurement in pigs: Are infrared thermometers a non-invasive alternative?]

OBJECTIVE

Internal body temperature is an essential parameter in evaluation an animal's general health status. The rectal temperature as 'gold standard' requires restraining of the animal which may cause stress especially when not accustomed to handling procedures. Stress on the other hand should whenever possible be avoided as it negatively affects animal welfare and may increase body temperature. The present study evaluated whether measuring the body surface temperature with an infrared thermometer (IRT) may represent a stressless alternative method to rectal body temperature measurements.

MATERIAL AND METHODS

Twelve male fattening pigs were included in the study. Body temperature was measured once a week for 11 weeks. Body surface temperature measurements were performed in the areas of the forehead, caudal base of the ear and anus using two infrared thermometers (IRT1 and IRT2) each.

RESULTS

Throughout the study, all pigs were clinically healthy. Best repeatability was found for the rectal thermometer and IRT1 in the anus region. Homogeneity of variance was not found for the measurements of the three thermometers. Mean values of body temperature were significantly different (p<0,05) between thermometers and measurement points. Thereby, the type of thermometer and measurement point possessed a moderate to strong effect. The Bland-Altman plot shows that differences in the values of the thermometers and measurement points are within the acceptable range of variation (95% interval). However, the range of variation is too substantial for clinical assessment of the body temperature.

CONCLUSION

The repeatability of temperature data measured with IRT on the body surface of pigs is acceptable. For this procedure, restraining the animals is not necessary, therefore reducing the animal's stress level during the clinical examination. However, the correlation to the rectal body temperature is weak to moderate.

CLINICAL RELEVANCE

In order to use IRT for health monitoring in animals, reference values for respective IRT and measurement points need to be established. In the current study no case of hyper- or hypothermia occurred. Further research is warrented to evaluate whether IRT reliably detect fever.

Evaluation of reticuloruminal temperature for the prediction of clinical mastitis in dairy cows challenged with Streptococcus uberis

Automated monitoring devices have become increasingly utilized in the dairy industry, especially for monitoring or predicting disease status. While multiple automated monitoring devices have been developed for the prediction of clinical mastitis (CM), limitations in performance or applicability remain. The aims of this study were to (1) detect variations in reticuloruminal temperature (RRT) relative to an experimental intramammary challenge with Streptococcus uberis and (2) evaluate alerts generated automatically based on variation in RRT to predict initial signs of CM in the challenged cows based on severity of clinical signs and the concentration of bacteria (cfu/mL) in the infected quarter separately. Clinically healthy Holstein cows without a history of CM in the 60 d before the experiment (n = 37, parity 1 to 5, ≥120 d in milk) were included if they were microbiologically negative and had a somatic cell count under 200,000 cells/mL based on screening of quarter milk samples 1 wk before challenge. Each cow received an intra-reticuloruminal automated monitoring device before the trial and was challenged with 2,000 cfu of Strep. uberis 0140J in 1 rear quarter. Based on interrupted time series analysis, intramammary challenge with Strep. uberis increased RRT by 0.54°C [95% confidence interval (CI): 0.41, 0.66] at 24 h after the challenge, which remained elevated until the end of the study. Alerts based on RRT correctly classified 78.3% (95% CI: 65.8, 87.9) of first occurrences of CM at least 24 h in advance, with a sensitivity of 70.0% (95% CI: 50.6, 85.3) and a specificity of 86.7% (95% CI: 69.3, 96.2). The accuracy of CM for a given severity score was 90.9% (95% CI: 70.8, 98.9) for mild cases, 85.2% (95% CI: 72.9, 93.4) for moderate cases, and 92.9% (95% CI: 66.1, 99.8) for severe cases. Test characteristics of the RRT alerts to predict initial signs of CM improved substantially after bacterial count in the challenged quarter reached 5.0 log₁₀ cfu/mL, reaching a sensitivity of 73.5% (95% CI: 55.6, 87.1) and a specificity of 87.5% (95% CI: 71.0, 96.5). Overall, the results of this study indicated that RRT was affected by the intramammary challenge with Strep. uberis and the RRT-generated alerts had similar accuracy as reported for other sensors and algorithms. Further research that includes natural infections with other pathogens as well as different variations in RRT to determine CM status is warranted.

Invited review: integration of technologies and systems for precision animal agriculture-a case study on precision dairy farming

Precision livestock farming (PLF) offers a strategic solution to enhance the management capacity of large animal groups, while simultaneously improving profitability, efficiency, and minimizing environmental impacts associated with livestock production systems. Additionally, PLF contributes to optimizing the ability to manage and monitor animal welfare while providing solutions to global grand challenges posed by the growing demand for animal products and ensuring global food security. By enabling a return to the "per animal" approach by harnessing technological advancements, PLF enables cost-effective, individualized care for animals through enhanced monitoring and control capabilities within complex farming systems. Meeting the nutritional requirements of a global population exponentially approaching ten billion people will likely require the density of animal proteins for decades to come. The development and application of digital technologies are critical to facilitate the responsible and sustainable intensification of livestock production over the next several decades to maximize the potential benefits of PLF. Real-time continuous monitoring of each animal is expected to enable more precise and accurate tracking and management of health and well-being. Importantly, the digitalization of agriculture is expected to provide collateral benefits of ensuring auditability in value chains while assuaging concerns associated with labor shortages. Despite notable advances in PLF technology adoption, a number of critical concerns currently limit the viability of these state-of-the-art technologies. The potential benefits of PLF for livestock management systems which are enabled by autonomous continuous monitoring and environmental control can be rapidly enhanced through an Internet of Things approach to monitoring and (where appropriate) closed-loop management. In this paper, we analyze the multilayered network of sensors, actuators, communication, networking, and analytics currently used in PLF, focusing on dairy farming as an illustrative example. We explore the current state-of-the-art, identify key shortcomings, and propose potential solutions to bridge the gap between technology and animal agriculture. Additionally, we examine the potential implications of advancements in communication, robotics, and artificial intelligence on the health, security, and welfare of animals.

Screening microchip sites to predict body temperature in young calves

Thermal microchip sensors can automate body temperature measurements. The best site of implantation is still unknown, and the accuracy and precision of body temperature predictions based on microchip data need to be investigated. The aim of this study was to investigate the best site for microchip implant for monitoring body temperature in dairy calves. Seventeen calves were used (32.2 ± 5.2 kg of body weight) and the microchips were implanted four days after birth. The microchips were implanted at navel, ear and tail base (subcutaneous), neck (cleidocephalicus) and internal face of leg (gracilis) (intramuscular). Rectal temperature (RT, °C), obtained with a clinical thermometer, was considered as core temperature. Air temperature (AT), relative humidity (RH) and the temperature and humidity index (THI) were evaluated at the same time of rectal and microchip temperature measurements over 56 days. The range of AT, RH and THI was 7.6-34.4 °C, 17.5-99.0% and 50.6 to 91.5. The average for rectum, ear, neck, tail, leg, and navel were 38.7; 36.9; 38.0; 37.0, 37.8 and 37.0 °C. The intramuscular implantations had closest values to RT. The correlations between RT and ear, neck, tail, leg, and navel temperatures were 0.56, 0.60, 0.60, 0.53 e 0.48. The RT prediction based on microchip data had precision (r_c) ranged between 0.49 and 0.60 and accuracy (C_b) between 0.79 and 0.88. The inclusion of AT, RH and THI as predictive variables in models decrease the mean absolute error (23%) and increase the precision (21.3%) and accuracy (10.2%). The Concordance Correlation Coefficient and root-mean-square error for equations using tail or neck microchips were 0.68 and 0.67, and 0.29 and 0.28 °C, respectively. The tail base is a promising site for microchip implantation to predict rectal temperature. The inclusion of air temperature as a predictive variable in the models is recommended.

Efficacy of statistical process control procedures to identify deviations in continuously measured physiological and behavioral variables in beef heifers resulting from an experimentally combined viral-bacterial challenge

The objective of this experiment was to determine if statistical process control (SPC) procedures coupled with remote continuous data collection could accurately differentiate between animals experimentally inoculated with a viral-bacterial (VB) challenge or phosphate buffer solution (PBS). Crossbred heifers (N = 38; BW = 230 ± 16.4 kg) were randomly assigned to treatments by initial weight, average daily gain (ADG), bovine herpes virus 1, and Mannheimia haemolytica serum titers. Feeding behavior, dry matter intake (DMI), animal activity, and rumen temperature were continuously monitored remotely prior to and following VB challenge. VB-challenged heifers exhibited decreased (P < 0.01) ADG and DMI, as well as increased (P < 0.01) neutrophils and rumen temperature consistent with a bovine respiratory disease (BRD) infection. However, none of the heifers displayed overt clinical signs of disease. Shewhart and cumulative summation (CUSUM) charts were evaluated, with sensitivity and specificity computed on the VB-challenged heifers (n = 19) and PBS-challenged heifers (n = 19), respectively, and the accuracy was determined as the average of sensitivity and specificity. To address the diurnal nature of rumen temperature responses, summary statistics (mean, minimum, and maximum) were computed for daily quartiles (6-h intervals), and these quartile temperature models were evaluated separately. In the Shewhart analysis, DMI was the most accurate (95%) at deciphering between PBS- and VB-challenged heifers, followed by rumen temperature (94%) collected in the 2nd and 3rd quartiles. Rest was most the accurate accelerometer-based traits (89%), and meal duration (87%) and bunk visit (BV) frequency (82%) were the most accurate feeding behavior traits. Rumen temperature collected in the 3rd quartile signaled the earliest (2.5 d) of all the variables monitored with the Shewhart, followed by BV frequency (2.8 d), meal duration (2.8 d), DMI (3.0 d), and rest (4.0 d). Rumen temperature and DMI remained the most accurate variables in the CUSUM at 80% and 79%, respectively. Meal duration (58%), BV frequency (71%), and rest (74%) were less accurate when monitored with the CUSUM analysis. Furthermore, signal day was greater for DMI, rumen temperature, and meal duration (4.4, 5.0, and 3.7 d, respectively) in the CUSUM compared to Shewhart analysis. These results indicate that Shewhart and CUSUM charts can effectively identify deviations in feeding behavior, activity, and rumen temperature patterns for the purpose of detecting sub-clinical BRD in beef cattle.

Comparison of body temperature in donkeys using rectal digital, infrared, and mercury-in-glass thermometers during the hot-dry season in a tropical savannah

The study aimed at comparing variations in body temperature values recorded using rectal digital, infrared, and mercury-in-glass thermometers in donkeys during the hot-dry season, prevailing under tropical savannah conditions. Thirty donkeys that served as subjects were divided into three groups of adults, yearlings, and foals. Values of the body temperature of each donkey were recorded bihourly, starting from 06:00 h till 18:00 h, by digital (5-cm depth of insertion), mercury-in-glass (3 cm depth), and infrared thermometers. The values obtained by each type of the thermometer were compared with those recorded using a 15-cm digital probe (Model HI935007, Hanna Instruments, range -50.0 to 150.0°C; accuracy ± 0.2°C) which served as the gold standard. Dry-bulb temperature (34.00 ± 0.50°C), temperature-humidity index (79.65 ± 0.15), and wet-bulb globe temperature (28.00 ± 0.50) index peaked at 14:00 h. The mean body temperatures for rectal probe, digital, mercury-in-glass, and infrared thermometers were 38.35 ± 0.11°C, 37.24 ± 0.04°C, 36.76 ± 0.06°C, and 36.92 ± 0.07°C, respectively. In comparison to the rectal probe, the mean bias for digital (-1.11 ± 0.05°C), mercury-in-glass (-1.59 ± 0.07°C), and infrared thermometers (-1.38 ± 0.07°C) was large. The Passing-Bablok regression plot demonstrated significant deviation from linearity (p < 0.01) when digital, infrared, and mercury-in-glass thermometers were compared to the rectal probe. The area under the curve (AUC) for digital (AUC: 0.7005 ± 0.01 [95%: 0.6853 - 0.7310], infrared (AUC: 0.6711 ± 0.01 [95%: 0.6322 - 0.7100], and mercury-in-glass (AUC: 0.6321 ± 0.01 [95%: 0.6001 - 0.7873] thermometers showed poor accuracy with low sensitivity. In conclusion, the use of digital, mercury-in-glass, and infrared thermometers in recording body temperature in donkeys during the hot-dry season underestimated the values. Their use in measuring body temperature may result in wrong diagnosis, and compromise the control of hyperthermia and diseases associated with thermoregulatory impairments in donkeys.

Antibacterial effects assessment on some livestock pathogens, thermal stability and proposing a probable reason for different levels of activity of thanatin

There is a continuing need to prevent the increasing use of common antibiotic and find the replacement to combat the drug/antibiotic resistant bacteria such as antimicrobial peptides (AMPs) such as thanatin peptide. In this study, recombinant thanatin peptide was expressed in the HEK293 cell line. Then the antimicrobial properties of this peptide on some poultry and farm animal's pathogen strains were assessed. The thermal-stability of thanatin was predicted in various temperatures through in silico analysis. Afterwards, according to Minimum Inhibitory Concentration (MIC) results, Escherichia coli and Pseudomonas aeruginosa were chosen to test the hypothesis of LptA/LptD-thanatin interaction, computationally. Relative amino acid sequences and crystallography structures were retrieved and missed tertiary structures were predicted. The interaction of thanatin with LptA and LptD of Escherichia coli and Pseudomonas aeruginosa were analyzed subsequently. The antibacterial activity of thanatin peptide was evaluated between 6.25 and 100 μg/mL using minimum inhibitory concentration. Also, the amounts of minimum bactericidal concentrations (MBC) were between 12.5 and 200 μg/mL. The bioinformatics analysis followed by the in vitro assessment, demonstrated that thanatin would be thermally stable in the body temperature of poultry and farm animals. Thanatin could penetrate to the outer membrane domain of LptD in Escherichia coli and it could block the transition path of this protein while the entrance of LptD in Pseudomonas aeruginosa was blocked for thanatin by extra residues in comparison with Escherichia coli LptD. In addition, the quality of interaction, with regard to the number and distance of interactions which leads to higher binding energy for thanatin and LptD of Escherichia coli was much better than Pseudomonas aeruginosa. But the site and quality of interaction for thanatin and LptA was almost the same for Escherichia coli and Pseudomonas aeruginosa. Accordingly, thanatin can prevent the assembly of LptA periplasmic bridge in both pathogens. The antibacterial and thermal stability of the thanatin peptide suggested that thanatin peptide might serve as a natural alternative instead of common antibiotics in the veterinary medicine. The outcome of this in silico study supports the MIC results. Therefore, a probable reason for different level of activity of thanatin against Escherichia coli and Pseudomonas aeruginosa might be the quality of LptA/LptD-thanatin interaction.

Do we automatically detect health- or general welfare-related issues? A framework

The early detection of health disorders is a central goal in livestock production. Thus, a great demand for technologies enabling the automated detection of such issues exists. However, despite decades of research, precision livestock farming (PLF) technologies with sufficient accuracy and ready for implementation on commercial farms are rare. A central factor impeding technological development is likely the use of non-specific indicators for various issues. On commercial farms, where animals are exposed to changing environmental conditions, where they undergo different internal states and, most importantly, where they can be challenged by more than one issue at a time, such an approach leads inevitably to errors. To improve the accuracy of PLF technologies, the presented framework proposes a categorization of the aim of detection of issues related to general welfare, disease and distress and defined disease. Each decision level provides a different degree of information and therefore requires indicators varying in specificity. Based on these considerations, it becomes apparent that while most technologies aim to detect a defined health issue, they facilitate only the identification of issues related to general welfare. To achieve detection of specific issues, new indicators such as rhythmicity patterns of behaviour or physiological processes should be examined.

Scoping review on clinical definition of bovine respiratory disease complex and related clinical signs in dairy cows

Bovine respiratory disease complex (BRD) is a worldwide multifactorial infectious disease. Antimicrobials are commonly used for treating BRD because bacteria are often involved. The clinical diagnosis of BRD is a challenge, especially in adult dairy cows, where information on this syndrome is scant. Having a definition based on consistent and reliable clinical signs would improve the accuracy of BRD diagnosis and could help to develop an optimal treatment approach by an early detection. The aim of this scoping review was to review clinical signs that could be recognized by producers in dairy cattle suffering from naturally occurring infectious respiratory disease, as reported in the literature. A review of the literature was performed for articles published between January 1, 1990 and January 1, 2020. The search of literature in English, French, and Italian languages included 2 different databases (Pubmed, https://pubmed.ncbi.nlm.nih.gov/; CAB abstract, https://www.cabi.org/publishing-products/cab-abstracts/). Clinical signs were categorized as follows: (1) "general manifestations of disease," which included behavioral changes or fever; (2) "alterations in respiratory function," which included clinical signs specifically associated with the respiratory tract examination; and (3) "clinical signs of other body systems," which included clinical signs related to other systems such as diarrhea or subcutaneous emphysema. The focus of the review was on clinical signs that could be monitored by animal handlers and producers. A total of 1,067 titles were screened, and 23 studies were finally included. The most common general clinical signs were increased body temperature (reported in 83% of studies, n = 19), change in feed intake (26%, n = 6), altered mentation (22%, n = 5), and decreased milk production (17%, n = 4). The alterations in respiratory function noted were nasal discharge (74%, n = 17), cough (65%, n = 15), altered respiratory dynamic or dyspnea (61%, n = 14), increased respiratory rate (43%, n = 10), and ocular discharge or lacrimation (30%, n = 7). The clinical signs associated with infectious respiratory disease reported in the 23 studies generally lacked a clear description of what constitutes a deviation from normality (0-50% of studies clearly reported what was considered normal versus abnormal depending on the clinical signs). This limitation prevented any comparison between studies that apparently reported the same "clinical sign," but possibly referred to a different assessment and definition of what was considered normal versus abnormal. Therefore, the definition of clinical signs in a repeatable way with validated interobserver agreement to determine the optimal combination for the diagnosis of BRD in dairy cows is needed. This could lead to a more judicious use of antimicrobials for respiratory disease in adult dairy cows.

Monitoring and Improving the Metabolic Health of Dairy Cows during the Transition Period

Simple Summary

The transition from late gestation to early lactation is a challenging period for dairy cows. A successful transition period depends on metabolic adaptation to the new physiological state in early lactation and proper management in order to support the cow’s requirements. This review paper will discuss various aspects of routine and consistent approaches to collect and analyze herd records, to detect unintended disruptions in performance. In addition, we discuss how to incorporate methods to assess health, production, nutrition, and welfare information to monitor cows during the transition period. Lastly, we discuss management strategies that can be implemented to improve the metabolic health and performance of transition dairy cows.

Abstract

The peripartum period of a dairy cow is characterized by several physiological and behavioral changes in response to a rapid increase in nutrient demands, to support the final stages of fetal growth and the production of colostrum and milk. Traditionally, the transition period is defined as the period 3 weeks before and 3 weeks after parturition. However, several researchers have argued that the transition period begins at the time of dry-off (~60–50 days prior to calving) and extends beyond the first month post-calving in high producing dairy cows. Independent of the definition used, adequate adaptation to the physiological demands of this period is paramount for a successful lactation. Nonetheless, not all cows are successful in transitioning from late gestation to early lactation, leading to approximately one third of dairy cows having at least one clinical disease (metabolic and/or infectious) and more than half of the cows having at least one subclinical case of disease within the first 90 days of lactation. Thus, monitoring dairy cows during this period is essential to detect early disease signs, diagnose clinical and subclinical diseases, and initiate targeted health management to avoid health and production impairment. In this review, we discuss different strategies to monitor dairy cows to detected unintended disruptions in performance and management strategies that can be implemented to improve the metabolic health and performance of dairy cows during the transition period.

Sampling strategy and measurement device affect vaginal temperature outcomes in lactating dairy cattle

Body temperature (BT) is widely used to evaluate health and heat load status in cattle. Despite its importance, studies vary in how BT is measured and in the biological interpretation of the results. Costs, practicality, labor, and welfare concerns can affect how BT is measured, including frequency of measurement and the type of device used. Inaccurate BT outcomes may have implications for cattle welfare; for example, animals may only receive treatment when fever is identified. Our objectives were (1) to compare measurement of vaginal temperature (VT) using relatively small, inexpensive, and low-accuracy loggers (±0.5 to ±1°C, iButton range; Embedded Data Systems, Lawrenceburg, KY) to a high-accuracy logger (±0.1°C; StarOddi, Gardabaer, Iceland), and (2) to evaluate how different BT sampling strategies correspond to 24-h VT in lactating dairy cows. To address the first objective, VT data from 54 cows were recorded every 45 min for 12 d/cow, on average, using 2 different types of temperature loggers (StarOddi DST centi-T and iButton DS1921H or DS1922L) attached to a shortened, hormone-free controlled internal drug release insert. Average VT obtained from both loggers were compared using mixed models and regression analyses. In addition, we tested the consistency of the low-accuracy loggers in detecting cows with elevated BT using the kappa coefficient of concordance. To address the second objective, VT data from 20 cows were recorded every min for 9 to 11 d/cow using StarOddi loggers. Using these data, we estimated average VT using 11 sampling strategies (every 5, 10, 15, 30, 45, 60, and 120 min, 1×/d recorded in the morning or afternoon, 2×/d, or 3×/d). Estimates and observed means were compared using linear regression. Compared with StarOddi loggers, the iButtons either underestimated (H model: 38.7 vs. 38.0 ± 0.06°C) or overestimated VT (L model: 38.7 vs. 39.2 ± 0.04°C). When considering elevated or fever VT thresholds, iButtons did not correctly classify animals; kappa coefficients of concordance were ≤0.35. Measuring VT as often as every 120 min resulted in more accurate estimates compared with strategies that recorded it once to thrice per day. These results indicate that the type of device (i.e., data logger) and sampling strategies affect BT outcomes and that these decisions affect the interpretation of BT data.

Evaluation of lameness detection using radar sensing in ruminants

BACKGROUND

Lameness is a major health, welfare and production-limiting condition for the livestock industries. The current 'gold-standard' method of assessing lameness by visual locomotion scoring is subjective and time consuming, whereas recent technological advancements have enabled the development of alternative and more objective methods for its detection.

METHODS

This study evaluated a novel lameness detection method using micro-Doppler radar signatures to categorise animals as lame or non-lame. Animals were visually scored by veterinarian and radar data were collected for the same animals.

RESULTS

A machine learning algorithm was developed to interpret the radar signatures and provide automatic classification of the animals. Using veterinary scoring as a standard method, the classification by radar signature provided 85 per cent sensitivity and 81 per cent specificity for cattle and 96 per cent sensitivity and 94 per cent specificity for sheep.

CONCLUSION

This radar sensing method shows promise for the development of a highly functional, rapid and reliable recognition tool of lame animals, which could be integrated into automatic, on-farm systems for sheep and cattle.

Application of microchip and infrared thermography for monitoring body temperature of beef cattle kept on pasture

The monitoring of body temperature is important for the diagnosis of the physiological state of the animal, being dependent on available methods and their applicability within production systems. This work evaluated techniques to monitor the body temperature of beef cattle kept on pasture and their ability to predict internal temperature. Twenty-three adult bovine females were monitored for six months, and collection data carried out in eleven campaigns (D0-D10) twelve days apart. During collections, the surface temperatures of ear base (ET, ^oC) and ocular globe (OGT, ^oC) were measured by infrared thermography, and the subcutaneous temperature (ST, ^oC) was measured with the use of transponder containing an implantable microchip. Rectal temperature (RT, ^oC) was considered as a reference for body temperature. Temperature and Humidity Index (THI), Black Globe Temperature and Humidity Index (BGHI) and Radiant Heat Load (RHL, W/m²) were calculated. ET (33.32 ± 0.12 °C), ST (36.10 ± 0.07 °C), OGT (37.40 ± 0.06 °C) and RT (38.83 ± 0.03 °C) differed significantly (P˂0.05). There was positive correlation of RT with OGT (r = 0.392), ET (r = 0.264) and ST (r = 0.236) (P˂0.05). Considering the bioclimatic indicators, the highest magnitude correlations were observed between ET and THI (r = 0.71), ET and BGHI (r = 0.65), and ET and RHL (r = 0.48). The use of microchip represented a practical method, but with limited predictability. On the other hand, infrared thermography proved to be safe and non-invasive, presenting greater precision for inference of internal body temperature. ET was more influenced by meteorological conditions.

Infrared thermography measured body surface temperature and its relationship with rectal temperature in dairy cows under different temperature-humidity indexes

The aim of this study was to better understand the inflection point of RT and BSTs and measure different body surface temperatures (BSTs) under different temperature-humidity index (THI) conditions. A total of 488 Holstein dairy cows were chosen to manually measure rectal temperature (RT) and BSTs including left side of eye, ear, cheek, forehead, flank, rump, fore udder, and rear udder by infrared thermography for 14 times. Those measurements included six times under high THI (THI > 78), three times under moderate THI (72 ≤ THI ≤ 78), and five times under low THI (THI < 72). Results showed that BSTs were affected by THI conditions (P < 0.01). The THI conditions where mean and maximum forehead temperatures started to increase rapidly (71.4 and 66.8) were lower than that where RT started to increase rapidly (74.1). The correlation coefficients of mean and maximum forehead temperatures to THI were 0.808 and 0.740, and were 0.557 and 0.504 to RT, all showing the highest as compared to other region temperatures with THI and RT, respectively. Thus, we conclude that BSTs are more sensitive to thermal environment than RT, suggesting the variability of BST to reflect body core temperature. In addition, the forehead is a relatively reliable region to assess the heat stress reflecting RT compared to the eye, ear, cheek, flank, rump, fore udder, and rear udder regions.

Comparison of different measuring methods for body temperature in lactating cows under different climatic conditions

The aim of the research described here was to compare different methods of body temperature (BT) measurements in dairy cows. It was hypothesised that reticular temperature (RET) values reflect the physiological status of the animals in an equivalent way to rectal (RT) and vaginal (VT) measurements. RT, VT and RET temperatures of twelve lactating Holstein–Friesian cows were measured over five consecutive days in June and October 2013. While RT and VT were manually measured three times a day, RET was automatically recorded at 10 min intervals using a bolus in the reticulum. For comparison with RT and VT, different RET values were used: single values at the respective recording times (RET-SIN), and mean (RET-MEAN) and median (RET-MED) values of 2 h prior to RT and VT measurements. Overall, body temperatures averaged 38·1 ± 0·6, 38·2 ± 0·4, 38·7 ± 0·9, 38·5 ± 0·7 and 38·7 ± 0·5 °C for RT, VT, RET-SIN, RET-MEAN and RET-MED, respectively. RT and VT were lower than all RET measurements, while RET-SIN and RET-MED were higher than RET-MEAN (P < 0·001). RET-MEAN and RET-MED values were higher in the morning, whereas RT and VT were greatest in the evening (P < 0·001). Overall, records of RT and VT were strongly correlated (r = 0·75; P < 0·001). In contrast to RET-SIN and RET-MEAN, RET-MED was higher correlated to RT and VT. In June, coefficients were higher between all methods than in October. Relation of barn T to RT and VT was stronger when compared to RET measurements. RET-SIN was higher correlated to barn T than RET-MEAN or RET-MED. Correlation between VT and barn T was strongest (r = 0·48; P < 0·001). In summary, RET-MED showed highest correlation with VT and RT. However, single RET measurements (influenced by water or feed intake) can lead to extreme variations and differences to single VT and RT values.

Body Temperature Monitoring Using Subcutaneously Implanted Thermo-loggers from Holstein Steers

Body temperature (BT) monitoring in cattle could be used to early detect fever from infectious disease or physiological events. Various ways to measure BT have been applied at different locations on cattle including rectum, reticulum, milk, subcutis and ear canal. In other to evaluate the temperature stability and reliability of subcutaneous temperature (ST) in highly fluctuating field conditions for continuous BT monitoring, long term ST profiles were collected and analyzed from cattle in autumn/winter and summer season by surgically implanted thermo-logger devices. Purposes of this study were to assess ST in the field condition as a reference BT and to determine any location effect of implantation on ST profile. In results, ST profile in cattle showed a clear circadian rhythm with daily lowest at 05:00 to 07:00 AM and highest around midnight and rather stable temperature readings (mean±standard deviation [SD], 37.1°C to 37.36°C±0.91°C to 1.02°C). STs are 1.39°C to 1.65°C lower than the rectal temperature and sometimes showed an irregular temperature drop below the normal physiologic one: 19.4% or 36.4% of 54,192 readings were below 36.5°C or 37°C, respectively. Thus, for BT monitoring purposes in a fever-alarming-system, a correction algorithm is necessary to remove the influences of ambient temperature and animal resting behavior especially in winter time. One way to do this is simply discard outlier readings below 36.5°C or 37°C resulting in a much improved mean±SD of 37.6°C±0.64°C or 37.8°C±0.55°C, respectively. For location the upper scapula region seems the most reliable and convenient site for implantation of a thermo-sensor tag in terms of relatively low influence by ambient temperature and easy insertion compared to lower scapula or lateral neck.

Body temperature in early postpartum dairy cows

A strategy widely adopted in the modern dairy industry is the introduction of postpartum health monitoring programs by trained farm personnel. Within these fresh cow protocols, various parameters (e.g., rectal temperature, attitude, milk production, uterine discharge, ketones) are evaluated during the first 5 to 14 days in milk (DIMs) to diagnose relevant diseases. It is well documented that 14% to 66% of healthy cows exhibit at least one temperature of 39.5 °C or greater within the first 10 DIM. Although widely adopted, data on diagnostic performance of body temperature (BT) measurement to diagnose infectious diseases (e.g., metritis, mastitis) are lacking. Therefore, the objective of this study was to identify possible factors associated with BT in postpartum dairy cows. A study was conducted on a commercial dairy farm including 251 cows. In a total of 217 cows, a vaginal temperature logger was inserted from DIM 2 to 10, whereas 34 cows did not receive a temperature logger as control. Temperature loggers measured vaginal temperature every 10 minutes. Rectal temperature was measured twice daily in all cows. On DIM 2, 5, and 10, cows underwent a clinical examination. Body temperature was influenced by various parameters. Primiparous cows had 0.2 °C higher BT than multiparous cows. Multiparous cows that calved during June and July had higher BT than those that calved in May. In primiparous cows, this effect was only evident from DIM 7 to 10. Furthermore, abnormal calving conditions (i.e., assisted calving, dead calf, retained placenta, twins) affected BT in cows. This effect was more pronounced in multiparous cows. Abnormal vaginal discharge did increase BT in primiparous and multiparous cows. Primiparous cows suffering from hyperketonemia (beta-hydroxybutyrat ≥ 1.4 mmol/L) had higher BT than those not affected. In multiparous cows, there was no association between hyperketonemia and BT. The results of this study clearly demonstrate that BT is influenced by various parameters in dairy cows. Therefore, these parameters have to be considered when interpreting measurements of BT in dairy cows. This information helps to explain the high incidence of type I and II errors when measuring BT and clearly illustrates that measures of BT should not be used as a single criterion to decide whether or not to provide antibiotic treatment to dairy cows. However, research-based test characteristics of other parameters (e.g., vaginal discharge) alone or in combination with BT are still lacking.