Comparative evaluation of thermography, infrared, mercury, digital, and ecological thermometers for body temperature measurements in cattle

Comparative evaluation of thermography, infrared, mercury, digital, and ecological thermometers for body temperature measurements in cattle | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparative evaluation of thermography, infrared, mercury, digital, and ecological thermometers for body temperature measurements in cattle Ana Carolina Pinheiro, Rodrigo Siuffi Abbud, Kelly Grayce Perestrelo, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8182408/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 2 You are reading this latest preprint version Abstract Following the global ban on mercury thermometers due to their toxicological risks, alternative devices such as digital, ecological (galinstan-based), and infrared thermometers, as well as infrared thermography, have emerged for veterinary use. This study aimed to evaluate the accuracy and agreement of these alternatives compared to the mercury thermometer for measuring body temperature in cattle. Twenty-four clinically healthy or stable cattle were monitored twice daily over five consecutive days. Rectal temperatures were recorded using mercury, digital, and ecological thermometers. Infrared thermometers and thermographic cameras were used to assess cutaneous temperatures at the forehead, eyes, axillae, and perineum. Correlation analyses (Pearson or Spearman) and Bland–Altman plots were applied to determine agreement. Infrared thermography and infrared thermometer measurements at the eyes and perineum exhibited the highest correlations but failed to meet clinical agreement standards. In contrast, both ecological and digital thermometers showed strong correlation (r ≥ 0.85) and acceptable agreement limits with the mercury thermometer (mean difference < 0.3°C; SD < 0.5°C), indicating their suitability as substitutes in clinical practice. Despite the promise of infrared techniques for non-invasive screening, further validation is needed before clinical implementation. infrared thermography digital thermometer galinstan thermometer cattle body temperature mercury replacement Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Fever is a fundamental physiological response to infection, inflammation, or another condition, primarily mediated by pro-inflammatory cytokines that affect thermoregulatory centers in the hypothalamus (Li et al. 2020 ). As such, body temperature measurement is a critical diagnostic parameter in clinical assessments and health monitoring of livestock. Even subtle increases in core temperature, such as a 1°C rise, can lead to significant reductions in productivity, particularly in heat-sensitive species like cattle (McDowell et al. 1976 ; Salles et al. 2016 ). Traditionally, mercury-in-glass thermometers have been considered the gold standard for core temperature measurement due to their precision and reliability (Burfeind et al. 2010 ). However, given mercury’s environmental toxicity and associated health risks, its use has been restricted or banned in several countries, including those in the European Union (Pecoraro et al. 2021 ). As a result, digital thermometers have become the most common alternative in both human and veterinary medicine (Kreissl and Neiger 2015 ). In recent years, non-invasive infrared technologies have gained attention as potential tools for rapid and contactless assessment of body surface temperature. These include handheld infrared thermometers and infrared thermographic cameras, which detect infrared radiation emitted by the body and convert it into temperature readings (Hoffman et al. 2023 ; Katsoulos et al. 2016 ). These tools have shown utility in detecting early signs of respiratory disease (Schaefer et al., 2007 ), digital dermatitis (Alsaaod et al. 2014 ), mastitis (Zaninelli et al. 2018 ), and stress responses (Arfuso et al. 2022 ). However, surface temperature is influenced by environmental variables such as wind, ambient temperature, and humidity (Church et al. 2014 ), potentially limiting the consistency of these methods. In addition to digital and infrared technologies, ecological thermometers—galinstan-based devices composed of gallium, indium, and tin—have been introduced as non-toxic, mercury-free alternatives that mimic the mechanical principle of mercury thermometers (Baura 2021 ). Although their reliability has been demonstrated in humans (Dante et al. 2021 ), their performance in veterinary settings remains underexplored. This study aimed to evaluate and compare the efficiency of digital, ecological, infrared, and thermographic thermometers in estimating body temperature in cattle, using mercury thermometers as the reference standard. Materials and methods Animals and Experimental Design The study was conducted using 24 cattle of varying breeds, ages, and sexes from multiple veterinary facilities and research institutions in Brazil. Animals were either clinically healthy or in stable condition, as determined by physical examination. Age distribution was as follows: 45% were ≤ 1 year old, 33% were between 1–3 years, and 22% were over 3 years. Body temperatures were measured twice daily—between 7:00–9:00 a.m. and 1:00–3:00 p.m.—for five consecutive days, totalling 240 observations per thermometer. Environmental temperature and humidity were recorded during each session using a digital thermometer-hygrometer (HTC-1®, Underbody), as these parameters affect skin temperature (Church et al. 2014 ) and because these data were added in the infrared thermography settings before taking the images. The animals were kept in a place without sunlight or wind, since previous studies using infrared thermography and an infrared thermometer maintained a controlled room (Freitas et al. 2018 ; Kreissl & Neiger 2015 ). Measurement Procedures Each animal underwent a standardized sequence of measurements: Infrared thermography (IRA) using a FLIR T620 camera. Infrared thermometer (INFRA) using a RESTAR® device. Rectal thermometry using a mercury thermometer (MER), digital thermometer (DIG; G-TECH®), and ecological thermometer (ECO; Geratherm® Galinstan). Infrared measurements were taken from six anatomical locations (Fig. 1 ): Forehead (FH): at the level of the interfrontal suture, above the supraorbital sulcus Lacrimal glands: right eye (RE) and left eye (LE) Axillae: right (RA) and left (LA) Perineum (PE) Infrared thermography images were captured at 1 meter from the animal, at a 45–90° angle. Emissivity was set to 0.98, and environmental data were input into FLIR Thermal Studio software before image acquisition (Fig. 2 ). A circular area (1.5 cm diameter) was placed over each anatomical region in the thermal image to extract the maximum surface temperature, which was used for analysis due to its superior sensitivity and reduced variability (Johnson et al. 2011 ; Peng et al. 2019 ). Infrared thermometer readings were obtained at a fixed 5 cm distance using a ruler to standardize positioning (Fig. 3 ). To avoid interference, rectal measurements were performed after cutaneous ones. A stable reading was recorded once the same value appeared in three consecutive scans. If the device returned a “low” reading (< 33.8°C), the value was excluded. Statistical Analysis Statistical analyses were conducted using SAS software (v9.4). Pearson or Spearman correlation coefficients were calculated to assess linear relationships between devices. Correlation strength was interpreted as follows: weak (r < 0.39), moderate (0.40 ≤ r < 0.69), strong (0.70 ≤ r < 0.89), and very strong (r ≥ 0.90) (Schober et al. 2018 ). Agreement between devices was assessed using Bland–Altman plots. A method was considered clinically acceptable if the standard deviation (SD) of differences was < 0.5°C and the mean of differences (Me) was within ± 0.3°C. A linear regression was used to assess proportional bias. These thresholds were based on Burfeind et al. ( 2010 ), who reported that measurement error could result from technique (± 0.5°C), thermometer type (± 0.3°C), and insertion depth (± 0.4°C). Results A total of 238 temperature readings per device were obtained. Two animals were excluded on the fifth afternoon due to early discharge, resulting in slight data loss. Infrared thermometers returned a “low” reading (< 33.8°C) in several instances, which were excluded from the analysis. This occurred in all regions, most frequently in the forehead (46.7%) and right axilla (25.2%), particularly in morning measurements (29%) when ambient temperature was lower (mean 20.0°C vs. 24.6°C in the afternoon). Descriptive statistics indicated that digital (DIG) and ecological (ECO) thermometers showed the closest agreement with mercury (MER) in both mean and median temperatures. IRA-derived temperatures exhibited greater variability compared to INFRA and rectal devices. Among IRA readings, forehead (FHX) showed the widest interquartile range, while the eyes and perineum showed more stable distributions. Table 1 summarizes the Pearson correlation coefficients and Bland–Altman agreement data between MER and each alternative device. The strongest correlations with MER were observed for ECO (r = 0.90) and DIG (r = 0.85). Among INFRA sites, the highest correlations were RE (right eye, r = 0.61), LE (left eye, r = 0.63), and PE (perineum, r = 0.49). For IRA, FHX (forehead, r = 0.65), REX (right eye, r = 0.64), LEX (left eye, r = 0.66). Table 1 Bland–Altman statistics and correlation coefficients comparing infrared and thermographic temperature measurements with mercury thermometers in cattle (n = 238). Region Bland-Altman Correlation Me SD r p-value INFRA FH 2.29 0.98 0.43 < .0001 RE 1.01 0.67 0.61 < .0001 LE 1.09 0.73 0.63 < .0001 RA 1.74 0.95 0.28 < .0001 LA 1.67 0.97 0.32 < .0001 PE 0.67 0.72 0.49 < .0001 IRA FHX 6.58 2.38 0.65 < .0001 REX 1.79 0.71 0.64 < .0001 LEX 1.83 0.74 0.66 < .0001 RAX 4.13 1.41 0.44 < .0001 LAX 4.13 1.54 0.41 < .0001 PEX 1.72 1.12 0.49 < .0001 Me = mean difference; SD = standard deviation; r = correlation coefficient; ECO = ecological thermometer; DIG = digital thermometer; INFRA = infrared thermometer ; IRA = infrared thermography; FH = forehead infrared thermometer; RE = right eye infrared thermometer; LE = left eye infrared thermometer; RA = right axilla infrared thermometer; LA = left axilla infrared thermometer; PE = perineum infrared thermometer; FHX = forehead infrared thermography; REX = right eye infrared thermography; LEX = left eye thermography; RAX = right axilla infrared thermography; LAX = left axilla infrared thermography; PEX = perineum infrared thermography. Despite moderate to strong correlations, none of the INFRA or IRA regions met the agreement thresholds for clinical replacement. ECO and DIG, however, met all criteria: ECO SD = 0.33°C, Me = 0.16°C, p > 0.05 (no systematic bias) and DIG: SD = 0.39°C, Me = 0.21°C, p > 0.05 (no systematic bias). Bland–Altman plots confirmed the agreement of ECO and DIG with MER (Fig. 4 – 5 ). In contrast, INFRA and IRA systematically underestimated body temperature. For example, INFRA (FH): Me = 2.29°C, SD = 0.98°C and IRA (FHX): Me = 6.58°C, SD = 2.38°C. Eyes (RE, LE, REX, LEX) and perineum (PE, PEX) presented lower mean differences compared to other regions, though still outside acceptable thresholds. Ambient temperature was positively correlated (p < 0.05) with all INFRA and IRA measurements. The strongest correlations were observed in FHX (r = 0.84), FH (r = 0.78). LE (r = 0.78) and RE (r = 0.76). Relative humidity showed significant negative correlations but did not strongly influence any specific measurement site. Discussion This study demonstrated that ecological (galinstan-based) and digital thermometers are reliable alternatives to mercury thermometers for measuring rectal temperature in cattle. Both presented strong correlation coefficients (r ≥ 0.85), narrow limits of agreement, and no evidence of systematic bias, confirming their clinical equivalence to the traditional gold standard. These findings are consistent with studies in human medicine that support the clinical interchangeability of ecological and digital devices with mercury thermometers (Dante et al. 2021 ; Smith 2003 ). In contrast, neither infrared thermometers (INFRA) nor infrared thermography (IRA) met the criteria for agreement with mercury thermometers. Although moderate correlations were observed for eye and perineum measurements (e.g., RE, LE, PE, REX, LEX, PEX), the standard deviations exceeded clinically acceptable thresholds (SD > 0.5°C). These results suggest that, while these regions are promising for future non-invasive assessments, they currently lack the precision required for routine clinical use. The eyes, especially the lacrimal region, exhibited the best performance among cutaneous sites, as observed in other studies (George et al. 2014 ; Giannetto et al. 2021). However, inconsistencies in correlation strength across the literature may be explained by the influence of stress. Eye temperature is particularly sensitive to sympathetic activation and cortisol release during handling or restraint, potentially causing either vasoconstriction and cooling (Stewart et al. 2008 ) or a transient increase in surface temperature (Arfuso et al. 2022 ). These stress-induced variations, combined with the known susceptibility of surface temperatures to environmental factors such as wind and solar radiation (Church et al. 2014 ), may explain the lack of agreement with core temperature. Notably, sites with hairless skin, such as the eyes and perineum, yielded less variable IRA readings, likely due to higher emissivity and reduced interference from hair color or density (Riaz et al. 2023 ). Nonetheless, even in these areas, the mean temperature differences relative to rectal readings remained clinically significant (e.g., PEX Me = 1.72°C). Infrared thermography tended to yield lower surface temperatures compared to INFRA, which may be attributed to differences in measurement protocol (1 meter versus 5 cm distance) and limitations in environmental control. Despite efforts to shelter animals from direct sunlight and wind, it is likely that airflow influenced skin cooling in some sessions, particularly given the open-sided facilities. Similarly, the INFRA device frequently failed to register values below 33.8°C, especially in the forehead and axillae during morning sessions. This limitation compromises its utility in field conditions where ambient temperature fluctuates, a finding supported by the significant positive correlation between ambient and surface temperatures in all regions examined. The tendency of INFRA and IRA to underestimate body temperature is consistent with prior research in both veterinary and human medicine (Pecoraro et al. 2021 ; Peng et al. 2019 ). From a physiological perspective, skin temperature is inherently more variable than core temperature, being influenced by heat exchange processes (radiation, convection, conduction, and evaporation) which are modulated by environmental and behavioural factors (Baura 2021 ). Taken together, these results reinforce the importance of validating non-invasive temperature assessment methods for each species and context. While ecological and digital rectal thermometers are confirmed as clinically reliable, infrared-based devices should not yet replace rectal measurements in cattle, though specific sites like the eyes and perineum show potential for further investigation under more controlled conditions. Conclusion This study demonstrated that both digital and ecological rectal thermometers are accurate, clinically reliable alternatives to mercury thermometers for measuring body temperature in cattle. Their strong correlations and narrow limits of agreement confirm that they can be safely implemented in veterinary practice without compromising diagnostic accuracy. In contrast, infrared thermometry and thermography, while offering practical, non-invasive advantages, did not meet clinical agreement standards with mercury thermometers in any of the anatomical regions assessed. Among the evaluated sites, the eyes and perineum showed the highest potential, with moderate correlation and reduced variability, particularly in hairless areas. However, their performance remains insufficient for standalone clinical use. Future studies under controlled environmental conditions and involving larger populations are warranted to refine the use of infrared techniques in cattle and to explore their potential for early disease detection, stress assessment, or herd-level monitoring. Declarations Acknowledgments The authors would like to thank the staff and students of FMVZ-USP, FZEA-USP, and the Pirassununga Air Force Academy for their assistance with data collection and animal handling during this study. Statement of Animal Rights All procedures involving animals were conducted in accordance with institutional ethical guidelines and approved by the Ethics Committee on Animal Use of the School of Veterinary Medicine and Animal Science, University of São Paulo (CEUA-FMVZ/USP protocol number 1999161122). Funding Sources This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Conflict of interest The authors declare no relevant financial or non-financial interests. Author Contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Ana Carolina Pinheiro, Rodrigo Siuffi Abbud, Kelly Grayce Perestrelo, Jennifer Evangelista de Amorim, Julia Marques Nascimento Freitas and Maria Claudia Araripe Sucupira. The first draft of the manuscript was written by Ana Carolina Pinheiro and Maria Claudia Araripe Sucupira, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Data Availability The datasets generated and analyzed during the current study are available in the Mendeley Data repository: Pinheiro, Ana Carolina (2025), Bovine Thermometry, Mendeley Data, V1, https://doi.org/10.17632/vck3bxgmzp. References Alsaaod M, Syring C, Dietrich J, Doherr MG, Gujan T, Steiner A (2014) A field trial of infrared thermography as a non-invasive diagnostic tool for early detection of digital dermatitis in dairy cows. Vet J 199:281–285. https://doi.org/10.1016/j.tvjl.2013.11.028 Arfuso F, Acri G, Piccione G, Sansotta C, Fazio F, Giudice E, Giannetto C (2022) Eye surface infrared thermography usefulness as a noninvasive method of measuring stress response in sheep during shearing: Correlations with serum cortisol and rectal temperature values. 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Sensors 18:862. https://doi.org/10.3390/s18030862 Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 25 Nov, 2025 First submitted to journal 22 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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10:37:58","extension":"png","order_by":29,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":49580,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8182408/v1/68ddc01c5a79bb7275b05a36.png"},{"id":97688071,"identity":"592cfa21-5910-4b51-abd6-4c7070e199f4","added_by":"auto","created_at":"2025-12-08 10:37:59","extension":"xml","order_by":30,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":79563,"visible":true,"origin":"","legend":"","description":"","filename":"TROPD25022970structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8182408/v1/687f5098535f17e0d18546fe.xml"},{"id":97688065,"identity":"bc27d1db-3468-4329-8be8-cf879e10d081","added_by":"auto","created_at":"2025-12-08 10:37:58","extension":"html","order_by":31,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":88284,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8182408/v1/27705abd131681c70ceb6246.html"},{"id":97688036,"identity":"7a25cd9e-af4d-430d-8b1a-631645306fe4","added_by":"auto","created_at":"2025-12-08 10:37:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":301598,"visible":true,"origin":"","legend":"\u003cp\u003eAnatomical locations used for infrared measurement. (a) Forehead (FE), lacrimal gland (RE = right eye; LE = left eye); (b) Axillae (RA = right axilla; LA = left axilla); (c) Perineum (PE) in females; (d) perineum (PE) in males.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-8182408/v1/d78e6ac00b0d8bc19f847ebc.png"},{"id":97892623,"identity":"b9a60611-eaa6-4f35-a6ce-fbd1ceabf2a5","added_by":"auto","created_at":"2025-12-10 15:16:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":570574,"visible":true,"origin":"","legend":"\u003cp\u003eInfrared thermography images captured from FLIR Thermal Studio Software. (a) Left lacrimal gland; (b) Forehead; (c) Right axilla; (d) Perineum.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-8182408/v1/a32ef978a57cdd64f0934fdb.png"},{"id":97688039,"identity":"34c2f35d-8459-46b8-a748-1ab2545851a7","added_by":"auto","created_at":"2025-12-08 10:37:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":444000,"visible":true,"origin":"","legend":"\u003cp\u003eTemperature measurement using an infrared thermometer in the left axilla region, at a standardized distance of 5 cm using a ruler. The display shows “low” temperature.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-8182408/v1/0b6392cfd1c8c6a7e1462a58.png"},{"id":97892575,"identity":"700af2b5-890e-4bc4-a1b8-f84a40e85161","added_by":"auto","created_at":"2025-12-10 15:15:27","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":147925,"visible":true,"origin":"","legend":"\u003cp\u003eEcological thermometer graphics. (a) Bland-Altman plot showing agreement between ecological and mercury thermometers (∆ = MER – ECO) in 24 cattle (n=238). (b) Correlation between ECO and MER (r = 0,90).\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-8182408/v1/36a929a4046b8d9656757c25.png"},{"id":97688037,"identity":"6d02e6af-276c-4cc4-92e8-74f708b38f31","added_by":"auto","created_at":"2025-12-08 10:37:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":151429,"visible":true,"origin":"","legend":"\u003cp\u003eDigital thermometer graphics. (a) Bland-Altman plot of agreement between digital and mercury thermometers (∆ = MER – DIG). (b) Correlation plot for DIG and MER (r = 0,85).\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-8182408/v1/ec333c4fde858c223b83db52.png"},{"id":98622789,"identity":"cdffb883-66e6-4c3b-98c1-4b0b245d62c9","added_by":"auto","created_at":"2025-12-19 17:02:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2034848,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8182408/v1/81d7ecec-335c-4483-815d-ff51717275a4.pdf"}],"financialInterests":"","formattedTitle":"Comparative evaluation of thermography, infrared, mercury, digital, and ecological thermometers for body temperature measurements in cattle","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFever is a fundamental physiological response to infection, inflammation, or another condition, primarily mediated by pro-inflammatory cytokines that affect thermoregulatory centers in the hypothalamus (Li et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). As such, body temperature measurement is a critical diagnostic parameter in clinical assessments and health monitoring of livestock. Even subtle increases in core temperature, such as a 1\u0026deg;C rise, can lead to significant reductions in productivity, particularly in heat-sensitive species like cattle (McDowell et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Salles et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTraditionally, mercury-in-glass thermometers have been considered the gold standard for core temperature measurement due to their precision and reliability (Burfeind et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). However, given mercury\u0026rsquo;s environmental toxicity and associated health risks, its use has been restricted or banned in several countries, including those in the European Union (Pecoraro et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). As a result, digital thermometers have become the most common alternative in both human and veterinary medicine (Kreissl and Neiger \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn recent years, non-invasive infrared technologies have gained attention as potential tools for rapid and contactless assessment of body surface temperature. These include handheld infrared thermometers and infrared thermographic cameras, which detect infrared radiation emitted by the body and convert it into temperature readings (Hoffman et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Katsoulos et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). These tools have shown utility in detecting early signs of respiratory disease (Schaefer et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), digital dermatitis (Alsaaod et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), mastitis (Zaninelli et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and stress responses (Arfuso et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, surface temperature is influenced by environmental variables such as wind, ambient temperature, and humidity (Church et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), potentially limiting the consistency of these methods.\u003c/p\u003e\u003cp\u003eIn addition to digital and infrared technologies, ecological thermometers\u0026mdash;galinstan-based devices composed of gallium, indium, and tin\u0026mdash;have been introduced as non-toxic, mercury-free alternatives that mimic the mechanical principle of mercury thermometers (Baura \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although their reliability has been demonstrated in humans (Dante et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), their performance in veterinary settings remains underexplored.\u003c/p\u003e\u003cp\u003eThis study aimed to evaluate and compare the efficiency of digital, ecological, infrared, and thermographic thermometers in estimating body temperature in cattle, using mercury thermometers as the reference standard.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eAnimals and Experimental Design\u003c/p\u003e\u003cp\u003eThe study was conducted using 24 cattle of varying breeds, ages, and sexes from multiple veterinary facilities and research institutions in Brazil. Animals were either clinically healthy or in stable condition, as determined by physical examination.\u003c/p\u003e\u003cp\u003eAge distribution was as follows: 45% were \u0026le;\u0026thinsp;1 year old, 33% were between 1\u0026ndash;3 years, and 22% were over 3 years. Body temperatures were measured twice daily\u0026mdash;between 7:00\u0026ndash;9:00 a.m. and 1:00\u0026ndash;3:00 p.m.\u0026mdash;for five consecutive days, totalling 240 observations per thermometer. Environmental temperature and humidity were recorded during each session using a digital thermometer-hygrometer (HTC-1\u0026reg;, Underbody), as these parameters affect skin temperature (Church et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and because these data were added in the infrared thermography settings before taking the images. The animals were kept in a place without sunlight or wind, since previous studies using infrared thermography and an infrared thermometer maintained a controlled room (Freitas et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kreissl \u0026amp; Neiger \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMeasurement Procedures\u003c/p\u003e\u003cp\u003eEach animal underwent a standardized sequence of measurements:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eInfrared thermography (IRA) using a FLIR T620 camera.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eInfrared thermometer (INFRA) using a RESTAR\u0026reg; device.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eRectal thermometry using a mercury thermometer (MER), digital thermometer (DIG; G-TECH\u0026reg;), and ecological thermometer (ECO; Geratherm\u0026reg; Galinstan).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eInfrared measurements were taken from six anatomical locations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e):\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eForehead (FH): at the level of the interfrontal suture, above the supraorbital sulcus\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eLacrimal glands: right eye (RE) and left eye (LE)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eAxillae: right (RA) and left (LA)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePerineum (PE)\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eInfrared thermography images were captured at 1 meter from the animal, at a 45\u0026ndash;90\u0026deg; angle. Emissivity was set to 0.98, and environmental data were input into FLIR Thermal Studio software before image acquisition (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). A circular area (1.5 cm diameter) was placed over each anatomical region in the thermal image to extract the maximum surface temperature, which was used for analysis due to its superior sensitivity and reduced variability (Johnson et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Peng et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eInfrared thermometer readings were obtained at a fixed 5 cm distance using a ruler to standardize positioning (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). To avoid interference, rectal measurements were performed after cutaneous ones. A stable reading was recorded once the same value appeared in three consecutive scans. If the device returned a \u0026ldquo;low\u0026rdquo; reading (\u0026lt;\u0026thinsp;33.8\u0026deg;C), the value was excluded.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses were conducted using SAS software (v9.4). Pearson or Spearman correlation coefficients were calculated to assess linear relationships between devices. Correlation strength was interpreted as follows: weak (r\u0026thinsp;\u0026lt;\u0026thinsp;0.39), moderate (0.40\u0026thinsp;\u0026le;\u0026thinsp;r\u0026thinsp;\u0026lt;\u0026thinsp;0.69), strong (0.70\u0026thinsp;\u0026le;\u0026thinsp;r\u0026thinsp;\u0026lt;\u0026thinsp;0.89), and very strong (r\u0026thinsp;\u0026ge;\u0026thinsp;0.90) (Schober et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAgreement between devices was assessed using Bland\u0026ndash;Altman plots. A method was considered clinically acceptable if the standard deviation (SD) of differences was \u0026lt;\u0026thinsp;0.5\u0026deg;C and the mean of differences (Me) was within \u0026plusmn;\u0026thinsp;0.3\u0026deg;C. A linear regression was used to assess proportional bias. These thresholds were based on Burfeind et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), who reported that measurement error could result from technique (\u0026plusmn;\u0026thinsp;0.5\u0026deg;C), thermometer type (\u0026plusmn;\u0026thinsp;0.3\u0026deg;C), and insertion depth (\u0026plusmn;\u0026thinsp;0.4\u0026deg;C).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 238 temperature readings per device were obtained. Two animals were excluded on the fifth afternoon due to early discharge, resulting in slight data loss. Infrared thermometers returned a \u0026ldquo;low\u0026rdquo; reading (\u0026lt;\u0026thinsp;33.8\u0026deg;C) in several instances, which were excluded from the analysis. This occurred in all regions, most frequently in the forehead (46.7%) and right axilla (25.2%), particularly in morning measurements (29%) when ambient temperature was lower (mean 20.0\u0026deg;C vs. 24.6\u0026deg;C in the afternoon).\u003c/p\u003e\u003cp\u003eDescriptive statistics indicated that digital (DIG) and ecological (ECO) thermometers showed the closest agreement with mercury (MER) in both mean and median temperatures. IRA-derived temperatures exhibited greater variability compared to INFRA and rectal devices. Among IRA readings, forehead (FHX) showed the widest interquartile range, while the eyes and perineum showed more stable distributions.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the Pearson correlation coefficients and Bland\u0026ndash;Altman agreement data between MER and each alternative device. The strongest correlations with MER were observed for ECO (r\u0026thinsp;=\u0026thinsp;0.90) and DIG (r\u0026thinsp;=\u0026thinsp;0.85). Among INFRA sites, the highest correlations were RE (right eye, r\u0026thinsp;=\u0026thinsp;0.61), LE (left eye, r\u0026thinsp;=\u0026thinsp;0.63), and PE (perineum, r\u0026thinsp;=\u0026thinsp;0.49). For IRA, FHX (forehead, r\u0026thinsp;=\u0026thinsp;0.65), REX (right eye, r\u0026thinsp;=\u0026thinsp;0.64), LEX (left eye, r\u0026thinsp;=\u0026thinsp;0.66).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBland\u0026ndash;Altman statistics and correlation coefficients comparing infrared and thermographic temperature measurements with mercury thermometers in cattle (n\u0026thinsp;=\u0026thinsp;238).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRegion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eBland-Altman\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eCorrelation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"5\" nameend=\"c2\" namest=\"c1\" rowspan=\"6\"\u003e\u003cp\u003eINFRA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"5\" nameend=\"c2\" namest=\"c1\" rowspan=\"6\"\u003e\u003cp\u003eIRA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFHX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eREX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLEX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRAX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLAX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePEX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eMe\u0026thinsp;=\u0026thinsp;mean difference; SD\u0026thinsp;=\u0026thinsp;standard deviation; r\u0026thinsp;=\u0026thinsp;correlation coefficient; ECO\u0026thinsp;=\u0026thinsp;ecological thermometer; DIG\u0026thinsp;=\u0026thinsp;digital thermometer; INFRA\u0026thinsp;=\u0026thinsp;infrared thermometer ; IRA\u0026thinsp;=\u0026thinsp;infrared thermography; FH\u0026thinsp;=\u0026thinsp;forehead infrared thermometer; RE\u0026thinsp;=\u0026thinsp;right eye infrared thermometer; LE\u0026thinsp;=\u0026thinsp;left eye infrared thermometer; RA\u0026thinsp;=\u0026thinsp;right axilla infrared thermometer; LA\u0026thinsp;=\u0026thinsp;left axilla infrared thermometer; PE\u0026thinsp;=\u0026thinsp;perineum infrared thermometer; FHX\u0026thinsp;=\u0026thinsp;forehead infrared thermography; REX\u0026thinsp;=\u0026thinsp;right eye infrared thermography; LEX\u0026thinsp;=\u0026thinsp;left eye thermography; RAX\u0026thinsp;=\u0026thinsp;right axilla infrared thermography; LAX\u0026thinsp;=\u0026thinsp;left axilla infrared thermography; PEX\u0026thinsp;=\u0026thinsp;perineum infrared thermography.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e Despite moderate to strong correlations, none of the INFRA or IRA regions met the agreement thresholds for clinical replacement. ECO and DIG, however, met all criteria: ECO SD\u0026thinsp;=\u0026thinsp;0.33\u0026deg;C, Me\u0026thinsp;=\u0026thinsp;0.16\u0026deg;C, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05 (no systematic bias) and DIG: SD\u0026thinsp;=\u0026thinsp;0.39\u0026deg;C, Me\u0026thinsp;=\u0026thinsp;0.21\u0026deg;C, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05 (no systematic bias).\u003c/p\u003e\u003cp\u003eBland\u0026ndash;Altman plots confirmed the agreement of ECO and DIG with MER (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In contrast, INFRA and IRA systematically underestimated body temperature. For example, INFRA (FH): Me\u0026thinsp;=\u0026thinsp;2.29\u0026deg;C, SD\u0026thinsp;=\u0026thinsp;0.98\u0026deg;C and IRA (FHX): Me\u0026thinsp;=\u0026thinsp;6.58\u0026deg;C, SD\u0026thinsp;=\u0026thinsp;2.38\u0026deg;C.\u003c/p\u003e\u003cp\u003eEyes (RE, LE, REX, LEX) and perineum (PE, PEX) presented lower mean differences compared to other regions, though still outside acceptable thresholds.\u003c/p\u003e\u003cp\u003eAmbient temperature was positively correlated (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) with all INFRA and IRA measurements. The strongest correlations were observed in FHX (r\u0026thinsp;=\u0026thinsp;0.84), FH (r\u0026thinsp;=\u0026thinsp;0.78). LE (r\u0026thinsp;=\u0026thinsp;0.78) and RE (r\u0026thinsp;=\u0026thinsp;0.76). Relative humidity showed significant negative correlations but did not strongly influence any specific measurement site.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study demonstrated that ecological (galinstan-based) and digital thermometers are reliable alternatives to mercury thermometers for measuring rectal temperature in cattle. Both presented strong correlation coefficients (r\u0026thinsp;\u0026ge;\u0026thinsp;0.85), narrow limits of agreement, and no evidence of systematic bias, confirming their clinical equivalence to the traditional gold standard. These findings are consistent with studies in human medicine that support the clinical interchangeability of ecological and digital devices with mercury thermometers (Dante et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Smith \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn contrast, neither infrared thermometers (INFRA) nor infrared thermography (IRA) met the criteria for agreement with mercury thermometers. Although moderate correlations were observed for eye and perineum measurements (e.g., RE, LE, PE, REX, LEX, PEX), the standard deviations exceeded clinically acceptable thresholds (SD\u0026thinsp;\u0026gt;\u0026thinsp;0.5\u0026deg;C). These results suggest that, while these regions are promising for future non-invasive assessments, they currently lack the precision required for routine clinical use.\u003c/p\u003e\u003cp\u003eThe eyes, especially the lacrimal region, exhibited the best performance among cutaneous sites, as observed in other studies (George et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Giannetto et al. 2021). However, inconsistencies in correlation strength across the literature may be explained by the influence of stress. Eye temperature is particularly sensitive to sympathetic activation and cortisol release during handling or restraint, potentially causing either vasoconstriction and cooling (Stewart et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) or a transient increase in surface temperature (Arfuso et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These stress-induced variations, combined with the known susceptibility of surface temperatures to environmental factors such as wind and solar radiation (Church et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), may explain the lack of agreement with core temperature.\u003c/p\u003e\u003cp\u003eNotably, sites with hairless skin, such as the eyes and perineum, yielded less variable IRA readings, likely due to higher emissivity and reduced interference from hair color or density (Riaz et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Nonetheless, even in these areas, the mean temperature differences relative to rectal readings remained clinically significant (e.g., PEX Me\u0026thinsp;=\u0026thinsp;1.72\u0026deg;C).\u003c/p\u003e\u003cp\u003eInfrared thermography tended to yield lower surface temperatures compared to INFRA, which may be attributed to differences in measurement protocol (1 meter versus 5 cm distance) and limitations in environmental control. Despite efforts to shelter animals from direct sunlight and wind, it is likely that airflow influenced skin cooling in some sessions, particularly given the open-sided facilities.\u003c/p\u003e\u003cp\u003eSimilarly, the INFRA device frequently failed to register values below 33.8\u0026deg;C, especially in the forehead and axillae during morning sessions. This limitation compromises its utility in field conditions where ambient temperature fluctuates, a finding supported by the significant positive correlation between ambient and surface temperatures in all regions examined.\u003c/p\u003e\u003cp\u003eThe tendency of INFRA and IRA to underestimate body temperature is consistent with prior research in both veterinary and human medicine (Pecoraro et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Peng et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). From a physiological perspective, skin temperature is inherently more variable than core temperature, being influenced by heat exchange processes (radiation, convection, conduction, and evaporation) which are modulated by environmental and behavioural factors (Baura \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTaken together, these results reinforce the importance of validating non-invasive temperature assessment methods for each species and context. While ecological and digital rectal thermometers are confirmed as clinically reliable, infrared-based devices should not yet replace rectal measurements in cattle, though specific sites like the eyes and perineum show potential for further investigation under more controlled conditions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrated that both digital and ecological rectal thermometers are accurate, clinically reliable alternatives to mercury thermometers for measuring body temperature in cattle. Their strong correlations and narrow limits of agreement confirm that they can be safely implemented in veterinary practice without compromising diagnostic accuracy.\u003c/p\u003e\u003cp\u003eIn contrast, infrared thermometry and thermography, while offering practical, non-invasive advantages, did not meet clinical agreement standards with mercury thermometers in any of the anatomical regions assessed. Among the evaluated sites, the eyes and perineum showed the highest potential, with moderate correlation and reduced variability, particularly in hairless areas. However, their performance remains insufficient for standalone clinical use.\u003c/p\u003e\u003cp\u003eFuture studies under controlled environmental conditions and involving larger populations are warranted to refine the use of infrared techniques in cattle and to explore their potential for early disease detection, stress assessment, or herd-level monitoring.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the staff and students of FMVZ-USP, FZEA-USP, and the Pirassununga Air Force Academy for their assistance with data collection and animal handling during this study.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Statement of Animal Rights\u003c/p\u003e\n\u003cp\u003eAll procedures involving animals were conducted in accordance with institutional ethical guidelines and approved by the Ethics Committee on Animal Use of the School of Veterinary Medicine and Animal Science, University of S\u0026atilde;o Paulo (CEUA-FMVZ/USP protocol number 1999161122).\u003c/p\u003e\u003cp\u003eFunding Sources\u003c/p\u003e\n\u003cp\u003eThis study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Conflict of interest\u003c/p\u003e\n\u003cp\u003eThe authors declare no relevant financial or non-financial interests.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Author Contributions\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Ana Carolina Pinheiro, Rodrigo Siuffi Abbud, Kelly Grayce Perestrelo, Jennifer Evangelista de Amorim, Julia Marques Nascimento Freitas and Maria Claudia Araripe Sucupira. The first draft of the manuscript was written by Ana Carolina Pinheiro and Maria Claudia Araripe Sucupira, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Data Availability\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are available in the Mendeley Data repository: Pinheiro, Ana Carolina (2025), Bovine Thermometry, Mendeley Data, V1, https://doi.org/10.17632/vck3bxgmzp.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlsaaod M, Syring C, Dietrich J, Doherr MG, Gujan T, Steiner A (2014) A field trial of infrared thermography as a non-invasive diagnostic tool for early detection of digital dermatitis in dairy cows. 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Sensors 18:862. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/s18030862\u003c/span\u003e\u003cspan address=\"10.3390/s18030862\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"tropical-animal-health-and-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trop","sideBox":"Learn more about [Tropical Animal Health and Production](https://www.springer.com/journal/11250)","snPcode":"11250","submissionUrl":"https://submission.nature.com/new-submission/11250/3","title":"Tropical Animal Health and Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"infrared thermography, digital thermometer, galinstan thermometer, cattle, body temperature, mercury replacement","lastPublishedDoi":"10.21203/rs.3.rs-8182408/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8182408/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFollowing the global ban on mercury thermometers due to their toxicological risks, alternative devices such as digital, ecological (galinstan-based), and infrared thermometers, as well as infrared thermography, have emerged for veterinary use. This study aimed to evaluate the accuracy and agreement of these alternatives compared to the mercury thermometer for measuring body temperature in cattle. Twenty-four clinically healthy or stable cattle were monitored twice daily over five consecutive days. Rectal temperatures were recorded using mercury, digital, and ecological thermometers. Infrared thermometers and thermographic cameras were used to assess cutaneous temperatures at the forehead, eyes, axillae, and perineum. Correlation analyses (Pearson or Spearman) and Bland\u0026ndash;Altman plots were applied to determine agreement. Infrared thermography and infrared thermometer measurements at the eyes and perineum exhibited the highest correlations but failed to meet clinical agreement standards. In contrast, both ecological and digital thermometers showed strong correlation (r\u0026thinsp;\u0026ge;\u0026thinsp;0.85) and acceptable agreement limits with the mercury thermometer (mean difference\u0026thinsp;\u0026lt;\u0026thinsp;0.3\u0026deg;C; SD\u0026thinsp;\u0026lt;\u0026thinsp;0.5\u0026deg;C), indicating their suitability as substitutes in clinical practice. Despite the promise of infrared techniques for non-invasive screening, further validation is needed before clinical implementation.\u003c/p\u003e","manuscriptTitle":"Comparative evaluation of thermography, infrared, mercury, digital, and ecological thermometers for body temperature measurements in cattle","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-08 10:37:53","doi":"10.21203/rs.3.rs-8182408/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorAssigned","content":"","date":"2025-11-26T00:32:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Tropical Animal Health and Production","date":"2025-11-22T15:21:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"tropical-animal-health-and-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trop","sideBox":"Learn more about [Tropical Animal Health and Production](https://www.springer.com/journal/11250)","snPcode":"11250","submissionUrl":"https://submission.nature.com/new-submission/11250/3","title":"Tropical Animal Health and Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"a3c631c7-d809-442d-a720-a3fbbbd24202","owner":[],"postedDate":"December 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-23T16:44:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-08 10:37:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8182408","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8182408","identity":"rs-8182408","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}