Using infrared thermography to detect subclinical mastitis in dairy cows in compost barn systems

Early Detection of Sub-clinical Mastitis in Murrah Buffaloes through Udder Thermogram Analysis during the Natural Progression of Infection

Mastitis is a global production disease that needs an intelligent solution to tackle effectively. Infrared Thermography (IRT) is a non-invasive technology that could be incorporated into routine day-to-day farm activities to monitor the health status of the animals. In this study, the udder health status was routinely monitored for 30 days among 41 Murrah buffaloes via IRT and the California Mastitis Test (CMT). Further, somatic cell count (SCC), microbial identification, and milk quality parameters were also estimated for representative samples. The thermal imaging data obtained was tabulated and back propagated from the 0th day to the -10th day and front propagated from the 0th day to +10th day for all the udder quarters. Results revealed that on the 0th day, the mean of udder skin surface temperature (USST) and teat skin surface temperature (TSST) showed a difference (p < 0.05) in the sub-clinical mastitis (SCM) and clinical mastitis (CM) affected quarters to the healthy quarters, and their degree of difference was the highest. The indication of infection was signaled during the -9th to -5th day to the 0th day in SCM and CM cases. There was a steep increment in the temperature from -2nd and -1st day to the 0th day of infection. Sometimes, some quarters show an increment in temperature due to mastitis during morning hours but recover by evening milking due to the animal's innate immune system. Thus, the initiation period in which the udder gets assaulted is crucial in the early assessment of SCM by monitoring temperature change using IRT.

Thermal Imaging and Dimensionality Reduction Techniques for Subclinical Mastitis Detection in Dairy Sheep

Subclinical mastitis is a common and economically significant disease that affects dairy sheep production. Thermal imaging presents a promising avenue for non-invasive detection, but existing methodologies often rely on simplistic temperature differentials, potentially leading to inaccurate assessments. This study proposes an advanced algorithmic approach integrating thermal imaging processing with statistical texture analysis and t-distributed stochastic neighbor embedding (t-SNE). Our method achieves a high classification accuracy of 84% using the support vector machines (SVM) algorithm. Furthermore, we introduce another commonly employed evaluation metric, correlating thermal images with commercial California mastitis test (CMT) results after establishing threshold conditions on statistical features, yielding a sensitivity (the true positive rate) of 80% and a specificity (the true negative rate) of 92.5%. The evaluation metrics underscore the efficacy of our approach in detecting subclinical mastitis in dairy sheep, offering a robust tool for improved management practices.

Correlation of udder thermogram and somatic cell counts as a tool for detection of subclinical mastitis in buffaloes

This study aimed to monitor the mammary health of 37 multiparous Murrah buffaloes through infrared thermography (IRT). Based on the California Mastitis Test (CMT) and milk somatic cell counts (SCC), buffaloes were grouped into healthy (H, n = 16), subclinical mastitis (SCM, n = 10), and clinical mastitis (CM, n = 11). Buffaloes were milked twice daily in the morning (5:00-6:00 AM) and evening (5:00-6:00 PM). Rectal temperature and respiratory rates were recorded, CMT was performed and thermal images of the mammary gland of all the buffaloes were taken before and after each milking. Milk samples were analysed after each milking for SCC, fat, Solids-Not-Fat (SNF), density, protein, lactose, salts, conductivity, and pH immediately in the laboratory from fresh milk samples. The surface temperature of the periocular region of both the eyes, muzzle, flank, and vagina were also taken. Thermal images were used to assess the surface temperature of the udder (USST), teat apex (TAT), teat barrel (TB1T), teat base (TB2T), and teat skin surface (TSST). Eye and USST showed significantly higher temperatures (p < 0.05), whereas skin surface temperatures (SST) of different body parts were non-significant in both SCM and CM animals than buffaloes in the H group. Milk SCC showed a positive correlation with conductivity (r > 0.7), salts, and pH (r < 0.6) and a negative correlation with fat, SNF, density, protein, and lactose. TAT, TB1T, TB2T, TSST, and USST were positively correlated with milk SCC. Receiver Operating Characteristic (ROC) analysis of H and SCM groups showed that USST before milking had optimum sensitivity (Se = 0.80) and specificity (Sp = 0.906) among the various skin temperatures recorded. Thermal images captured during the morning showed higher sensitivity compared to images taken in the evening. Results indicate IRT can be used to monitor the mammary health of buffaloes but using IRT in conjunction with milk SCC can help in the accurate prediction of SCM in dairy buffaloes.

Reliability of udder infrared thermography as a non-invasive technology for early detection of sub-clinical mastitis in Sahiwal (Bos indicus) cows under semi-intensive production system

The present study focused on Sahiwal cows, a prominent milch breed in tropical India, to correlate udder temperature with physiological markers of stress and inflammation during subclinical mastitis (SCM). The primary goal was to assess the potential of udder infrared thermography for the early detection of SCM under the semi-intensive production. Cows were categorized based on milk somatic cell counts (SCC), with healthy (H) cows having SCC <2 × 105 cells/mL and no history of mastitis, and cows with subclinical mastitis (SCM) and initial stages of clinical mastitis (CM) having quarter milk SCC of 2-5 × 105 and >5 × 105 cells/mL, respectively. Firstly, udder thermograms were analysed for udder skin surface temperature (USST), teat skin surface temperature (TSST), and teat apex temperature (TAT) using Fluke software to determine the optimal site for temperature measurement during intramammary infection. Secondly, milk samples were collected for automatic estimation of compositional changes, electrical conductivity, and pH. Thirdly, milk whey was separated for quantifying stress and inflammatory indicators, including cortisol, prolactin, and acute-phase proteins (APPs): milk amyloid A and milk haptoglobin using bovine-specific ELISA kits. Significant increases (p < 0.01) in USST, TSST, TAT, cortisol, and APPs were observed in SCM and CM compared to healthy cows, while prolactin levels decreased (p < 0.01). The correlation matrix revealed strong positive correlations of SCC with USST (r = 0.84, p < 0.01). In ROC analysis, USST demonstrated cut-off values of 37.74 and 39.58 °C, with accuracy (p < 0.05) of 98% for SCM and 95% for CM, surpassing both TAT and TSST. Therefore, the combination of these non-invasive methods increases the reliability and accuracy of infrared thermography for early detection of SCM, providing valuable insights for the development of a protocol for routine screening and udder health monitoring in indigenous dairy cows.

Thermal imaging and computer vision technologies for the enhancement of pig husbandry: a review

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

Detection of canine obstructive nasal disease using infrared thermography: A pilot study

Infrared thermography detects variations in heat signature and is utilized in other species to non-invasively identify respiratory disease. This study aimed to determine if infrared thermography could be used to detect nasal disease in dogs. Eight dogs presenting for nasal disease (ND group) and ten healthy control dogs (C group) were enrolled. Dorsal and rostral images of the nose were acquired using a Fluke TiX580 60Hz thermal imaging camera. Images were analyzed using the accompanying software. Regions of interest were defined over the right and left nasal passages to determine the maximum (max), average (avg), and minimum (min) temperatures. Temperatures were compared between ND and C groups, and correlation to disease state (ND or C) was evaluated. Temperature differences and imaging patterns were subjectively compared with diagnosis based on computed tomography (CT) and histopathology. The ND group consisted of 5 spayed females and 3 neutered males. Clinical sings included unilateral epistaxis (n = 4); bilateral serous discharge and sneezing (n = 1); bilateral mucopurulent discharge, epistaxis, and sneezing (n = 1); unilateral mucoid discharge, epistaxis and sneezing (n = 1); and sneezing and unilateral epistaxis (n = 1). Temperatures were significantly different between ND and C groups on dorsal (max p = <0.001, avg p = 0.001, min p = <0.001) and rostral (max p = <0.001, avg p = <0.001, min p = 0.005) images. Temperature positively correlated to disease status (ND vs C group) in both dorsal and rostral images. Subjective analysis of images allowed correct identification of abnormal or normal 27/36 times. Obstructive nasal disease results in a local temperature increase in the affected nasal passage that can be non-invasively detected by infrared thermography.

Dilution Reduces Sample Matrix Effects for Rapid, Direct, and Miniaturised Phenotypic Antibiotic Susceptibility Tests for Bovine Mastitis

The time-consuming nature of current methods for detecting antimicrobial resistance (AMR) to guide mastitis treatment and for surveillance, drives innovation towards faster, easier, and more portable technology. Rapid on-farm testing could guide antibiotic selection, reducing misuse that contributes to resistance. We identify challenges that arise when developing miniaturized antibiotic susceptibility tests (AST) for rapid on-farm use directly in milk. We experimentally studied three factors: sample matrix (specifically milk or spoiled milk); the commensal bacteria found in fresh bovine milk; and result time on the performance of miniaturised AST. Microfluidic "dip-and-test" devices made from microcapillary film (MCF) were able to monitor Gram-negative bacterial growth colourimetrically even in the presence of milk and yoghurt (used to simulate spoiled milk samples), as long as this sample matrix was diluted 1:5 or more in growth medium. Growth detection kinetics using resazurin was not changed by milk at final concentrations of 20% or lower, but a significant delay was seen with yoghurt above 10%. The minimum inhibitory concentration (MIC) for ciprofloxacin and gentamicin was increased in the presence of higher concentrations of milk and yoghurt. When diluted to 1% all observed MIC were within range, indicating dilution may be sufficient to avoid milk matrix interfering with microfluidic AST. We found a median commensal cell count of 6 × 105 CFU/mL across 40 healthy milk samples and tested if these bacteria could alter microfluidic AST. We found that false susceptibility may be observed at early endpoint times if testing some pathogen and commensal mixtures. However, such errors are only expected to occur when a susceptible commensal organism is present at higher cell density relative to the resistant pathogen, and this can be avoided by reading at later endpoints, leading to a trade-off between accuracy and time-to-result. We conclude that with further optimisation, and additional studies of Gram-positive organisms, it should be possible to obtain rapid results for microfluidic AST, but a trade-off is needed between time-to-result, sample dilution, and accuracy.

Mastitis in Dairy Cattle: On-Farm Diagnostics and Future Perspectives

Mastitis is one of the most important diseases in dairy cattle farms, and it can affect the health status of the udder and the quantity and quality of milk yielded. The correct management of mastitis is based both on preventive and treatment action. With the increasing concern for antimicrobial resistance, it is strongly recommended to treat only the mammary quarters presenting intramammary infection. For this reason, a timely and accurate diagnosis is fundamental. The possibility to detect and characterize mastitis directly on farm would be very useful to choose the correct management protocol. Some on-field diagnostic tools are already routinely applied to detect mastitis, such as the California Mastitis Test and on-farm culture. Other instruments are emerging to perform a timely diagnosis and to characterize mastitis, such as Infra-Red Thermography, mammary ultrasound evaluation and blood gas analysis, even if their application still needs to be improved. The main purpose of this article is to present an overview of the methods currently used to control, detect, and characterize mastitis in dairy cows, in order to perform a timely diagnosis and to choose the most appropriate management protocol, with a specific focus on on-farm diagnostic tools.

Assessment of heat production and methane emission using infrared thermography in lactating Holstein and Gyrolando-F1 (½ Holstein ½ Gyr) crossbreed cows

Infrared thermography (IRT) is a non-invasive and efficient tool to detect changes in the animal's body surface temperature, which is directly associated with the animal's energy loss. Methane emission represents a significant energy loss, particularly in ruminants, as well as heat production. Therefore, the aim of this study was to correlate skin temperature measured using IRT with heat production (HP) and methane emission in lactating Holstein and crossbred ½ Holstein x ½ Gyr (Gyrolando-F1) cows. Six Gyrolando-F1 and four Holstein cows, all primiparous, at mid lactation were used to evaluate daily HP and methane emission using indirect calorimetry in respiratory chambers. Thermographic images were taken at anus, vulva, ribs (on the right side), left flank, right flank, right front foot, upper lip, masseter and eye; IRT was performed every hour during 8 h after the morning feeding. Cows received the same diet ad libitum. Daily methane emission was positively correlated with IRT taken at the right front foot 1 h after feeding in Gyrolando-F1 cows (r = 0.85, P < 0.05) and with IRT taken at the eye 5 h after feeding in Holstein cows (r = 0.88, P < 0.05). HP was positively correlated with IRT taken at the eye 6 h after feeding in Gyrolando-F1 cows (r = 0.85, P < 0.05) and with IRT taken at the eye 5 h after feeding in Holstein cows (r = 0.90, P < 0.05). Infrared thermography was positively correlated with HP and methane emission in both Holstein and Gyrolando-F1 lactating cows, although the anatomical points and times of image acquisition yielding the greatest correlation coefficients varies among breeds.

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.

Assessment of Pain and Inflammation in Domestic Animals Using Infrared Thermography: A Narrative Review

Pain assessment in domestic animals has gained importance in recent years due to the recognition of the physiological, behavioral, and endocrine consequences of acute pain on animal production, welfare, and animal model validity. Current approaches to identifying acute pain mainly rely on behavioral-based scales, quantifying pain-related biomarkers, and the use of devices monitoring sympathetic activity. Infrared thermography is an alternative that could be used to correlate the changes in the superficial temperature with other tools and thus be an additional or alternate acute pain assessment marker. Moreover, its non-invasiveness and the objective nature of its readout make it potentially very valuable. However, at the current time, it is not in widespread use as an assessment strategy. The present review discusses scientific evidence for infrared thermography as a tool to evaluate pain, limiting its use to monitor acute pain in pathological processes and invasive procedures, as well as its use for perioperative monitoring in domestic animals.

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.

Compost Dairy Barn Layout and Management Recommendations in Kentucky: A Descriptive Study

This study was conducted to describe the building layout and dimensions, characterize the bedding material, and observe the management practices in 42 compost-bedded pack (CBP) barns in Kentucky (USA). The average herd size found in the study was 90 cows and the breeds consisted of Jersey (6.8%), Holstein (72.7%), and mixed (20.5%). The average CBP barn dimensions were 49.1 m (length) by 21.9 m (width). Many of these barns had feed alleys and driveways; overshot ridges with frequent orientation from NE to SW; and green sawdust, kiln-dried sawdust, or a mixture of both as the most common bedding materials. The bed-turning process was performed mechanically at depths of less than 0.25 m, and the loading of fresh material was performed every one to five weeks, varying by season, weather conditions, barn size, and cow density. The average bedding moisture content was found to be 59.0% (wet bulb-w.b.) and ranged from 36.2 to 71.8%. Coliforms were not present in barns that had a higher compost temperature, and the E. coli, Bacillus, and Streptococcus counts were higher in the barns that had a lower moisture content. In conclusion, it was observed that heterogeneous management was used among the barns and that the producers were satisfied with the compost barn system.

Udder Health Monitoring for Prevention of Bovine Mastitis and Improvement of Milk Quality

To maximize milk production, efficiency, and profits, modern dairy cows are genetically selected and bred to produce more and more milk and are fed copious quantities of high-energy feed to support ever-increasing milk volumes. As demands for increased milk yield and milking efficiency continue to rise to provide for the growing world population, more significant stress is placed on the dairy cow's productive capacity. In this climate, which is becoming increasingly hotter, millions of people depend on the capacity of cattle to respond to new environments and to cope with temperature shocks as well as additional stress factors such as solar radiation, animal crowding, insect pests, and poor ventilation, which are often associated with an increased risk of mastitis, resulting in lower milk quality and reduced production. This article reviews the impact of heat stress on milk production and quality and emphasizes the importance of udder health monitoring, with a focus on the use of emergent methods for monitoring udder health, such as infrared thermography, biosensors, and lab-on-chip devices, which may promote animal health and welfare, as well as the quality and safety of dairy products, without hindering the technological flow, while providing significant benefits to farmers, manufacturers, and consumers.

Thermography for disease detection in livestock: A scoping review

Infra-red thermography (IRT) offers potential opportunities as a tool for disease detection in livestock. Despite considerable research in this area, there are no common standards or protocols for managing IRT parameters in animal disease detection research. In this review, we investigate parameters that are essential to the progression of this tool and make recommendations for their use based on the literature found and the veterinary thermography guidelines from the American Academy of Thermology. We analyzed a defined set of 109 articles concerned with the use of IRT in livestock related to disease and from these articles, parameters for accurate IRT were identified and sorted into the fields of camera-, animal- or environment-related categories to assess the practices of each article in reporting parameters. This review demonstrates the inconsistencies in practice across peer-reviewed articles and reveals that some important parameters are completely unreported while others are incorrectly captured and/or under-represented in the literature. Further to this, our review highlights the lack of measured emissivity values for live animals in multiple species. We present guidelines for the standards of parameters that should be used and reported in future experiments and discuss potential opportunities and challenges associated with using IRT for disease detection in livestock.

Effect of distance and daily periods on heat-stressed pigs and pre-slaughter losses in a semiarid region

Effective planning animal transport is essential to safeguard animal welfare and reduce production losses. Environmental conditions, specifically extreme temperatures in combination with ranges of relative humidity are highlighted as one of the main risk factors for production losses during transport (e.g., fatalities). The majority of research evaluating both welfare and production impacts of pig transport have been primarily undertaken in Europe and North America, which cover a relatively limited range of distinct climates (e.g., temperate, sub-arctic, etc.). As a result, research on pig transport in semi-arid conditions is lacking. In this study, we evaluated the effects of both distance (short, 30 km; and long, 170 km) and transport daily periods (morning, (05:00-11:00); afternoon (12:00-17:00); and night, (23:00-04:00)) on the preslaughter losses and heat stress of pigs in commercial transport in a semiarid region. Across 19 journeys of standard slaughter-weight pig loads (124.0 ± 2.8 kg), 684 focal animals (36 per journey) were evaluated. For each journey, the load's thermal profile (THI_adj and enthalpy) and physiological responses of individual pigs were recorded. On arrival at designated slaughterhouses, the percentage pig of non-ambulatory non-injured (NANI), non-ambulatory injured (NAI), death on arrival (DOA), and total losses were recorded. Short journeys in the afternoon were shown to be more detrimental to the thermal comfort of pigs, with higher rectal temperatures recorded. The highest percentage of total losses and DOA occurred in afternoon journeys, irrespective of distance, followed by the morning, with the lowest losses observed in pigs transported at night. Additionally, total losses and DOA were further exacerbated by journey distance, with higher rates observed in short journeys. Higher percentage averages of NANI and NAI were observed in shorter journeys, but daily periods effects were only observed for NANI. These results further demonstrate the welfare and production loss risks associated with journey distance and time of day (representing varying environmental conditions) during road transport of pigs, whilst providing novel data in semiarid conditions. Careful and effective planning for pig transportation is essential to minimize heat stress and production losses. Consideration of the thermal environment on the day of travel, as well as providing flexibility to adjust travel times (e.g., early morning or evening), should help to mitigate risks of heat stress and production losses during pig transport.

Progress on Infrared Imaging Technology in Animal Production: A Review

Infrared thermography (IRT) imaging technology, as a convenient, efficient, and contactless temperature measurement technology, has been widely applied to animal production. In this review, we systematically summarized the principles and influencing parameters of IRT imaging technology. In addition, we also summed up recent advances of IRT imaging technology in monitoring the temperature of animal surfaces and core anatomical areas, diagnosing early disease and inflammation, monitoring animal stress levels, identifying estrus and ovulation, and diagnosing pregnancy and animal welfare. Finally, we made prospective forecast for future research directions, offering more theoretical references for related research in this field.

Carnauba (copernicia prunifera) straw as an alternative bedding material for dairy cows housed in a Compost barn system

ABSTRACT The replacement of bedding in compost dairy barns (CB) comprises a recurrent management practice, but bedding materials are often not readily available in all regions and the choice of alternative materials is necessary. The objective was to evaluate the thermal attributes of carnauba straw (CS) bedding in compost dairy barn facilities. Environmental monitoring operations were performed at a commercial farm located in Northeast Brazil. Mini weather stations were used to evaluate environmental variables. The THI was evaluated as one of the comfort parameters. Analysis of the spatial distribution of bed surface temperature (BST) in the CB was performed using geostatistical techniques. The cows remained out of the comfort zone according to THI results. The BST indicated satisfactory performance and from the thermal point of view can be used as alternative bedding material in CB facilities. However, it was observed that the CS showed fast biomass degradation compared to conventional materials, widely known. In addition, inadequate temperature values (< 45°C) were found in the deeper of the CS bed, signaling higher risks of pathogenic microbial activity. Additional studies are needed for searching the proper management plans that increase the life span of the bed formed by carnauba straw.

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).