Heat tolerance, biochemical, and hematological responses of Holstein cows under different feeding and environmental conditions in the semi-arid region of Brazil

Heat tolerance, biochemical, and hematological responses of Holstein cows under different feeding and environmental conditions in the semi-arid region of Brazil | 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 Heat tolerance, biochemical, and hematological responses of Holstein cows under different feeding and environmental conditions in the semi-arid region of Brazil David Ramos da Rocha, Ana Elisa Custódio Montes Cândido, Aline da Silva Rocha, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5932595/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study evaluated heat tolerance and changes in biochemical and blood parameters in dairy cows under varying environmental and dietary conditions. Sixteen adult Holstein cows were used in four treatments: full sun with or without concentrate in the diet and shade with or without concentrate. Environmental parameters assessed included air temperature, relative humidity, and temperature-humidity index (THI). The cows' rectal temperature, respiratory rate, heat tolerance index, and blood parameters were also evaluated. Results showed that the cows experienced mild to severe heat stress, with the highest air temperature, humidity, and THI recorded in full sun during the afternoon (p < 0.05). Rectal temperature and heat tolerance index were also higher (p 0.05). Weight loss was greater (p < 0.05) in cows exposed to full sun. Cows in the sun with concentrate exhibited altered plasma glucose, triglyceride, and cholesterol levels (p < 0.05). Shaded cows had higher red blood cell counts but lower hemoglobin, hematocrit, mean corpuscular volume, and mean corpuscular hemoglobin levels (p < 0.05). Sun-exposed cows with concentrate had fewer monocytes, lymphocytes, and platelets but increased eosinophils (p < 0.05). Overall, cows kept in shade with concentrate demonstrated better heat tolerance and metabolic and hematological profiles. Ambience high temperatures dairy cattle heat stress 1. Introduction The environment directly influences animal performance and affects physiological and behavioral responses in a production system. These challenges are very common in northeastern Brazil, as this semi-arid region has high levels of air temperature, solar radiation, and low levels of rainfall (Mascarenhas et al. 2023 ). Dairy cattle of European origin, kept in thermally stressful conditions, activate their thermoregulation process, modifying physiological parameters, which can lead to a reduction in food intake, impair liver functions, causing a consequent drop in performance (Araújo do Nascimento et al . 2022), as well as reducing reproductive capacity (Habeeb et al. 2023 ). Heat stress significantly alters feed intake, increasing the proportion of concentrate consumed compared to forage (Uyeno et al. 2010 ). Additionally, microbial metabolic efficiency is directly related to heat generation in the rumen, which can be indirectly estimated through bacterial growth efficiency (Kim et al. 2020 ). Metabolic and hematological parameters are widely used in studies to evaluate the effects of the thermal environment on animals. Changes in blood cell counts are correlated with heat stress, showing variations in hematocrit values, erythrocyte count, and hemoglobin. In addition, other parameters are considered important in evaluating heat stress conditions, such as cortisol, non-esterified fatty acids, thyroid hormones, total proteins, and heat shock transcription factors, among others (Sejian et al. 2018 ). It is known that animals attempt to regulate their body temperature by increased breathing rate, which can result in fluid loss through the respiratory system, leading to a reduction in blood plasma volume and altering the concentration of hematocrits (Vieira et al. 2022 ). In addition to the red blood cell series, the leukogram is frequently used to assess the effects of stress caused by the environment. Metabolic profiling is increasingly recognized as a disease prevention tool and has demonstrated efficacy as a platform for identifying alterations resulting from adverse environmental factors (Jo et al. 2021 ). The global and differential leukocyte count constitutes what is known as the leukogram, composed of five primary cell types (monocytes, neutrophils, eosinophils, basophils, and lymphocytes), but total counts do not differentiate between these cell types (Monteiro et al. 2020 ). On the other hand, several factors affect the biochemical profile of blood, including age, sex, weather conditions, and management practices (Conçeição et al. 2019 ). Among the cell types, studies have shown that heifers exposed to temperatures of 40°C exhibit a reduction in lymphocyte count and an increase in neutrophil count (Bagath et al. 2019 ), along with changes in other parameters such as hemoglobin levels and intermediate metabolites. Consequently, these metabolite analyses and hematometry are essential tools for evaluating physiological adaptations, providing insights into the processes governing animal-environment interactions. Thus, blood parameters can be considered homeostatic and responsive indicators for different environmental conditions. Breeds of European origin, particularly the Holstein breed, tend to suffer more from heat stress due to their reduced ability to adapt to hot climates, which is associated with their higher metabolic rate and lower heat dissipation capacity (Mylostyvyi et al. 2021 ). Approximately 70% of Brazil’s milk production comes from Holstein-Zebu crossbred cows (Martins Neto et al. 2018 ). However, Holstein cows are also commonly raised in semi-arid regions, where the harsh climate can significantly influence the milk productivity of these animals. The objective of this study was to evaluate the effects of the thermal environment and concentrate supplementation in the diet on the physiological responses, heat tolerance, performance, and hematological and biochemical parameters of cows raised under semi-arid conditions. 2. Materials and Methods 2.1. Execution site This study was conducted at the Federal University of Vale do São Francisco, Agricultural Sciences Campus (CCA), Dairy Cattle Unit, located in Petrolina, PE (9°32’32.29 “S and 40°32’55” W) at an altitude of 376 m. The region’s climate is classified as semi-arid (BSh), according to the Köppen climate classification, with an average air temperature of 22.1°C and a maximum of 34°C (Teixeira 2011 ). 2.2. Experimental animals The animal study protocol was approved by the Ethics Committee of the Federal University of Vale do São Francisco (protocol code 0002/170316). Sixteen Holstein females were used, aged between three and five years, with an average weight of 620 ± 25 kg, characterized by a black and white spotted coat with a predominance of white and depigmented skin, and randomly distributed across treatments. The cows were non-lactating, non-pregnant, and in reproductive anestrus, for at least 12 months. The body condition score (BSC) of the cows was between 3.5 and 3.75, considered adequate for their condition. The diet was formulated based on the maintenance requirements of the animals (National Academies of Sciences 2021), and provided twice daily in collective troughs (by treatment). The diet for the group without concentrate supplementation consisted exclusively of elephant grass green ad libitum ( Cenchrus purpureus , cultivar Napier; 26.0% dry matter, 93.4% organic matter, 3.5% crude protein, 3.1% ether extract, 87.0% neutral detergent fiber, 47.1% acid detergent fiber, and 6.4% lignin). In addition to the green elephant grass at will, the others groups received a diet with a forage-to-concentrate ratio of 40:60, ensuring a 35% NDF intake derived from forage. The concentrate consisted of corn (78%), cottonseed meal (21%), and mineral salt (1%), being supplied at 1% of body weight. The cows had ad libitum access to water. 2.3. Experimental procedure During the experimental period, the animals were divided into four treatments and four replications, comprising two environments (sun and shade) and two feeding regimes (with and without concentrate). The treatments were: animals exposed to the sun without concentrate in the diet, animals exposed to the sun with concentrate in the diet, animals kept in the shade with concentrate in the diet, and animals kept in the shade without concentrate in the diet, simultaneously. The experimental period lasted 30 days, including 10 days of adaptation. The animals in the shade treatment were housed in a free-stall system (3.3 m²/animal) throughout the experiment. The facility features a ridge opening 1.20 m wide, a roof covered with ceramic tiles, a ceiling height of 2.60 m, eaves extending 1.50 m, and open sides. The flooring is made of grooved concrete to facilitate the drainage of wastewater. In addition to the covered area in the free stall, the facility includes a shaded area measuring 7.8 m in width and 60.0 m in length. Conversely, the animals in the full-sun treatment were exposed to direct sunlight (9.0 m²/animal) throughout the experimental period and housed in collective pens without any alternative systems to mitigate heat stress. Data on the thermal environment and physiological parameters and calculations of the temperature-humidity index (THI) and heat tolerance were collected three times a week (monday, wednesday and friday), at 8:00 a.m., 12:00 p.m., and 4:00 p.m. At the end of the experiment, blood samples were collected from the animals via venipuncture of the coccygeal vein for biochemical and hematological analysis. 2.4. Assessment of environmental parameters and temperature-humidity index (THI) Air temperature (AT) and relative humidity (RH) data were obtained using a thermohygrometer (Incoterm, São Paulo, Brazil) installed in each experimental room at the average height of the animals’ bodies. The THI was calculated following the method outlined by Mader et al. ( 2006 ): THI = (0.8 × AT) + [(RH / 100) × (AT − 14.4)] + 46.4, where AT represents air temperature (°C) and RH represents relative humidity (%). 2.5. Assessment of physiological parameters and heat tolerance index (HTI) Rectal temperature was measured using a digital veterinary clinical thermometer (Incoterm, São Paulo, Brazil) inserted into the animal’s rectum for two minutes (Rocha et al. 2012 ). Respiratory rate (RR) was determined by visual observation, counting flank movements for 60 seconds using a stopwatch (Costa et al. 2015 ). The result was then multiplied by four to calculate the movements per minute. The heat tolerance index (HTI) was calculated based on the Benezra index, using the formula: HTI = RT/38.33 + RR/23, where RT represents rectal temperature and RR represents respiratory rate during the collection periods. The animals were weighed individually using a digital scale (TEXAS-Model B-01) at the beginning and end of the experimental period. Weight gain (WG) was calculated using the formula: WG = final weight - initial weight. 2.6. Biochemical and hematological analyses Blood samples were collected via puncture of the coccygeal vein at the end of the experimental period, using vacuum tubes containing 10% ethylenediaminetetraacetic acid (EDTA) from Biocon® (Taipei, Taiwan). The collection was performed at 8:00 a.m. by a veterinarian from the Federal University of Vale do São Francisco. The blood was divided equally into two aliquots. The first aliquot was used for hematological analyses of the white and red blood cell series. The second aliquot was centrifuged at 3000 g at 4°C for 10 minutes to separate the plasma for biochemical determinations. The blood from the first aliquot was sent to the clinical laboratory (Alpha Veterinary Clinical Analysis Laboratory, Petrolina, Pernambuco, Brazil) for analysis. An automatic hematology analyzer (model BC 5000 VET, Belém-PA, Brazil) was used for the evaluation. The metabolites measured in the plasma were glucose (mg/dL), albumin (g/dL), triglycerides (mg/dL), and total cholesterol (mg/dL), analyzed using colorimetric reagent methods (Labtest®), within a maximum of 24 hours after collection. The analyses were performed using a water bath (Model NT265, Piracicaba-SP, Brazil) and a spectrophotometer (Thermo Scientific, GENESYS 10S UV-VIS model). For glucose analysis, 10 µL of plasma from each sample was mixed with 10 µL of standard solution (100 mg/dL glucose) in 1.0 mL of reagent. After incubation in a water bath at 37°C for 10 minutes, the reading was performed at a wavelength of 505 nm using a spectrophotometer. The standard solution contained 100 mg/dL of glucose. The calculation was performed using the following formula: sample absorbance / standard absorbance × standard concentration (100 mg/dL). Triglycerides were analyzed using 10 µL of plasma from each sample, 10 µL of standard solution (200 mg/dL triglycerides and 0.045% sodium azide), and 1.0 mL of reagent. After incubation in a water bath at 37°C for 10 minutes, the reading was performed at a wavelength of 505 nm using a spectrophotometer. The standard solution contained 200 mg/dL of triglycerides. The calculation was performed using the following formula: sample absorbance / standard absorbance × standard concentration (200 mg/dL). Total cholesterol was analyzed using 10 µL of plasma from each sample, 10 µL of standard solution (sodium azide mmol/L, 200 mg/dL), and 1.0 mL of reagent. After incubation in a water bath at 37°C for 10 minutes, the reading was performed at a wavelength of 500 nm using a spectrophotometer. The standard solution contained 200 mg/dL. The calculation was performed using the following formula: sample absorbance / standard absorbance × standard concentration (200 mg/dL). Total proteins were analyzed using 20 µL of plasma from each sample, 10 µL of standard solution (4 g/dL bovine albumin and 14.6 nmol/L sodium azide), and 1.0 mL of reagent. After incubation in a water bath at 37°C for 10 minutes, the reading was performed at a wavelength of 545 nm using a spectrophotometer. The standard solution contained 4 g/dL. The calculation was performed using the following formula: sample absorbance / standard absorbance × standard concentration (4 g/dL). Albumin was analyzed using 10 µL of plasma from each sample, 10 µL of standard solution (3.8 g/dL bovine albumin and 0.1% sodium azide), and 1.0 mL of reagent. After 2 minutes at room temperature, the reading was performed at a wavelength of 630 nm using a spectrophotometer. The standard solution contained 3.5 g/dL. The calculation was performed using the following formula: sample absorbance / standard absorbance × standard concentration (3.8 g/dL). Urea was determined using 10 µL of plasma from each sample, 10 µL of standard solution (70 mg/dL urea and 7.7 nmol/L sodium azide), and 1.0 mL of reagent. Two absorbance readings were taken at 30 and 90 seconds. The absorbance difference between 90 and 30 seconds was then calculated. The reading was performed at a wavelength of 340 nm using a spectrophotometer. The calculation was performed using the following formula: sample absorbance / standard absorbance × standard concentration (70 mg/dL). Total plasma amino acids were analyzed according to Copley ( 1941 ). An appropriate volume of 20 µL of plasma was added to 1.0 mL of 0.1% ninhydrin solution in propanol. The reaction tubes were incubated at 40°C for 40 minutes in a water bath set at 45°C, and the optical reading was performed at 570 nm. The free amino acid concentration was estimated against an alpha-aminoacetic acid standard containing 150 moles. The hematocrit, erythrocyte count, and total hemoglobin were analyzed to assess hematological parameters, and the mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC) were calculated. Hematocrit was measured using a heparinized microcapillary tube filled to two-thirds of its total volume, then centrifuged at 12,000 rpm for 5 minutes. Hemoglobin concentration was determined using the cyanmethemoglobin method with Drabkin reagent, and absorbance was read at 540 nm. The erythrocyte count was conducted in a Neubauer chamber using the reagent (Natt and Herrick 1952 ). The mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC) were calculated using the absolute hematocrit (Hct) values, hemoglobin (Hb) concentration, and erythrocyte count. The hematological parameters were estimated using the following equations: MCV (fL) = (Hct / erythrocyte count) × 10 MCH (pg) = (Hb / erythrocyte count) × 10 MCHC (g/dL) = (Hb / Hct) × 100 Approximately 5.0 mL of blood was collected in Vacutainer-type tubes containing a 10% EDTA solution (1 mg/mL of blood) as an anticoagulant was kept under refrigeration and transported to the laboratory to obtain the leukogram to determine the leukocyte variables. The leukogram consisted of leukometry using a Neubauer chamber and differential leukocyte counting in blood smears stained using the Wright and Leishman method (Schalm et al. 1981 ). In each blood smear, 100 leukocytes were differentiated and classified based on their morphological and staining characteristics into band neutrophils, segmented neutrophils, eosinophils, basophils, lymphocytes, and monocytes. 2.7. Statistical analysis The experiment was designed and analyzed as recommended by Sampaio ( 2002 ). A completely randomized design was used. All variables were tested for normality using the Shapiro-Wilk test and for homoscedasticity using Levene’s test, and they were subjected to analysis of variance (ANOVA). The means were compared using the Tukey test at a 5% significance level, employing the R® statistical package. For environmental and physiological parameters the following model was used: Yijk = µ + Ti + Hj + THij + αijk, where: µ, overall average effect; Ti, effect of treatment i, i = Full sun, Shade, Full sun + Concentrate and Shade + Concentrate; Hj, effect of hours j, j = 8:00 a.m., 12:00 p.m., and 4:00 p.m.; THij, effect of the interaction between the treatment i and hour j; αijk, random error associated with treatment i, in the hour j, repetition k. For the other variables, the following model was used: Yij = µ + Ti + βij, where: µ, overall average effect; Ti, effect of treatment i, i = Full sun, Shade, Full sun + Concentrate and Shade + Concentrate; βij, random error associated with treatment i, repetition j. 3. Results 3.1. Environmental parameters The air temperature (AT) was significantly higher (p < 0.05) in sunny conditions at 12:00 p.m. and 4:00 p.m. compared to 8:00 a.m., with a maximum value at 12:00 p.m. (Table 1 ). In shaded conditions, a similar pattern was observed, with higher temperatures in the afternoon (12:00 p.m. and 4:00 p.m.) and the highest average (p < 0.05) and maximum temperatures recorded at 4:00 p.m. Additionally, in sunny conditions, the highest average (p < 0.05) and maximum temperature values were observed during the afternoon time points. Table 1 Environmental parameters measured under full sun and shade conditions at 8:00 a.m., 12:00 p.m., and 4:00 p.m. Treatment Time Temperature (ºC) Relative humidity (%) THI Full sun 08:00 a.m. Maximum 33.6 58.0 79.0 Average 29.7Ab 47.3Ba 77.3Ab 12:00 p.m. Maximum 38.6 35.0 83.1 Average 35.7Aa 29.0Bb 81.1Aa 4:00 p.m. Maximum 37.9 40.0 82.4 Average 35.7Aa 27.7Bb 80.8Aa Shade 08:00 a.m. Maximum 28.6 67.0 76.0 Average 26.8Bc 54.0 Aa 74.5Bb 12:00 p.m. Maximum 30.9 49.0 77.9 Average 30.0Bb 41.1Ab 76.8Bc 4:00 p.m. Maximum 37.4 67.0 83.7 Average 31.4Ba 38.2Ab 78.0Ba SEM 0.1979 0.9271 0.1854 SEM - Standard Error of the Mean. Means followed by different uppercase letters in the column differ significantly (p < 0.05) between treatments at the same time of day. Means followed by different lowercase letters in the columndiffer significantly (p < 0.05) between times within the same treatment. In both environmental conditions, the average relative humidity (RH) values were significantly higher (p < 0.05) in the morning (8:00 a.m.) compared to the afternoon (12:00 p.m. and 4:00 p.m.). Additionally, the highest average (p < 0.05) and maximum RH values were observed in the shaded environment when compared to the sunny environment. The temperature-humidity index (THI) under sunny conditions showed the highest values in the afternoon (p < 0.05) compared to the morning, with the highest average and maximum values recorded at 12:00 p.m. A similar pattern was observed under shaded conditions, except at 4:00 p.m., when the highest maximum and average values were recorded (p < 0.05). Additionally, THI under sunny conditions was consistently higher (p < 0.05) than under shaded conditions. 3.2. Physiological parameters The highest (p < 0.05) average rectal temperature (RT) values under sunny conditions were observed in the afternoon (12:00 p.m. and 4:00 p.m.) compared to the morning (8:00 a.m.). A similar pattern was observed in sunny conditions when concentrate was added to the animals’ diet (Table 2 ). There was no significant difference (p > 0.05) in RT values across the studied times in the shaded area. However, when animals in the shade were fed concentrate, there was a 0.5°C increase in RT at 4:00 p.m. compared to the morning. No significant difference (p > 0.05) was found between treatments at 8:00 a.m., and no difference (p > 0.05) was observed at 12:00 p.m. between shaded and sunny conditions. At 4:00 p.m., under sunny conditions with the addition of concentrate to the diet, the highest average RT value (p < 0.05) was recorded compared to other treatments, along with the highest maximum RT value (40°C). Table 2 Physiological parameters of cows exposed to shade and sun, with and without concentrate supplementation in the diet. Treatment Time RT (ºC) RF (bpm) HTI Full sun 08:00 a.m. Maximum 39.0 64.0 3.8 Average 38.0Ab 45.0Ab 3.0Ab 12:00 p.m. Maximum 39.20 100.00 5.4 Average 38.6Aa 62.0Ba 3.7Ba 4:00 p.m. Maximum 39.40 88.00 4.8 Average 38.6Aa 56.0Ba 3.4Ba Shade 08:00 a.m. Maximum 38.4 56.0 3.4 Average 38.0Aa 32.0Ba 2.4Ba 12:00 p.m. Maximum 38.7 48.0 3.1 Average 38.0Ba 30.0Ca 2.3Ca 4:00 p.m. Maximum 38.9 60.0 3.6 Average 38.2Ba 36.0Ca 2.6Ca Full sun + Concentrate 08:00 a.m. Maximum 39.0 80.0 4.5 Average 37.7Ab 52.0Ac 3.2Ab 12:00 p.m. Maximum 39.5 100.0 5.4 Average 38.7Aa 70.0Aa 4.0Aa 4:00 p.m. Maximum 40.0 100.0 5.4 Average 38.9Aa 63.0Ab 3.7Aa Shade + Concentrate 08:00 a.m. Maximum 38.7 48.0 3.1 Average 38.0Ab 33.0Ba 2.4Ba 12:00 p.m. Maximum 38.1 52.0 3.3 Average 38.2Bab 34.3Ca 2.5Ca 4:00 p.m. Maximum 39.1 52.0 3.3 Average 38.5Aa 37.0Ca 2.6Ca SEM 0.0826 1.5191 0.0664 SEM - Standard Error of the Mean; RT - Rectal Temperature; RF - Respiratory Frequency; HTI - Heat Tolerance Index; AHTI - Means followed by different uppercase letters in the column differ significantly (p < 0.05) between treatments at the same time of day. Means followed by different lowercase letters in the column differ significantly (p < 0.05) between times within the same treatment. The respiratory frequency (RF) of animals exposed to the sun showed higher average and maximum values in the afternoon (12:00 p.m. and 4:00 p.m.) (p 0.05) in RF across the times studied; however, the highest maximum value (60 bpm) was observed at 4:00 p.m. When animals were exposed to the sun with concentrate supplementation in the diet, there was a similar pattern to the sun treatment; however, the highest average value (p 0.05). However, the highest maximum value was recorded in the afternoon (Table 2 ), following a pattern similar to that observed in the shade-only treatment. In the sun treatment with added concentrate, the highest average (p < 0.05) and maximum RF values were observed at 12:00 p.m. The heat tolerance index (HTI) showed that under sunny conditions, the highest average (p 0.05) between the times studied; however, the highest value was recorded at 4:00 p.m. A similar tolerance pattern was observed in shaded conditions with concentrate supplementation. Under sunny conditions with concentrate supplementation, higher average HTI values (p < 0.05) were observed in the afternoon (12:00 p.m. and 4:00 p.m.) compared to the morning, and the highest maximum HTI values were also recorded. 3.3. Weight gain and biochemical and hematological parameters The animals in the shade showed higher average daily gains (p < 0.05). Regarding biochemical parameters, animals exposed to full sun had lower (p < 0.05) concentrations of glucose and triglycerides (Table 3 ). Table 3 Weight gain and blood biochemical parameters of cows exposed to shade and sun, with and without concentrate supplementation in the diet. Variables With concentrate Without concentrate SEM Full sun Shade Full sun Shade Weight gain (kg/day) -2.37b 0.60a -3.41b -0.41a 0.44 Glucose (mg/dL) 53.85c 73.88ab 62.88b 82.82a 3.27 Triglycerides (mg/dL) 17.21b 24.27a 14.36c 18.61b 1.11 Cholesterol (mg/dL) 65.03ab 74.81a 55.41b 66.82ab 4.12 Total Proteins (g/dL) 4.37a 3.91a 4.14a 4.10a 0.14 Albumin (mg/dL) 6.67a 6.70a 6.49a 7.38a 0.27 Amino acids (µL/mL plasma) 4.26a 5.53a 5.31a 5.65a 0.21 Urea (mg/dL) 17.50a 18.52a 17.71a 19.03a 0.76 SEM - Standard Error of the Mean. Means followed by different letters in the lines differ significantly according to the Tukey test (p ≤ 0.05). Plasma cholesterol levels were significantly lower (p < 0.05) in animals exposed to the sun without concentrate supplementation compared to those in the shade with concentrate. The other metabolites (total protein, albumin, free amino acids, and urea) did not show significant differences (p > 0.05) in response to the environmental and feeding conditions assessed. In the hematological parameters of the red blood cell series, animals in the shade with concentrate supplementation had higher (p < 0.05) red blood cell concentrations but lower hemoglobin, hematocrit, mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH) levels compared to those in the shade without concentrate (Table 4 ). The mean corpuscular hemoglobin concentration (MCHC) did not differ significantly (p > 0.05) between treatments. Table 4 Hematimetric parameters of the blood of cows exposed to shade and sun, with and without concentrate supplementation in the diet. Variables With concentrate Without concentrate SEM Full sun Shade Full sun Shade Red blood cells (million/mm 3 ) 5.91b 6.65a 5.75b 5.83b 0.15 Hemoglobin (g/dL) 11.54ab 11.99a 11.53ab 10.15b 0.33 Hematocrit (%) 34.63ab 36.00a 34.60ab 30.46b 1.00 Corpuscular volume (fL) 58.78ab 54.27ab 61.82a 52.32b 8.02 Corpuscular hemoglobin (pg) 19.52ab 18.08ab 20.58a 17.41b 2.67 CHC (%) 33.32a 33.32a 33.32a 33.31a 4.16 SEM - Standard Error of the Mean; CHC - Corpuscular Hemoglobin Concentration. Means followed by different letters in the lines differ significantly according to the Tukey test (p ≤ 0.05). Depending on the treatments, no significant differences (p > 0.05) were observed in the total leukocyte count, band neutrophils, or segmented neutrophils in the animals’ blood. On the other hand, animals exposed to the sun with concentrate supplementation showed the lowest values (p < 0.05) for lymphocytes, monocytes, and platelets. The highest percentage (p < 0.05) of eosinophils was observed in animals exposed to the sun with available concentrate (Table 5 ). Table 5 Leukogram and platelet count in the blood of cows exposed to shade and sun, with and without concentrate supplementation in the diet. Variables With concentrate Without concentrate SEM Full sun Shade Full sun Shade Leukocytes (mil/mm³) 4.905a 5.745a 5.272a 5.046a 0.79 Rods (%) 1.75a 1.25a 1.50a 1.00a 0.67 Segmented (%) 51.00a 46.75a 40.25a 45.50a 5.99 Eosinophils (%) 23.75a 4.50c 15.50b 12.50b 4.56 Lymphocytes (%) 20.00b 40.25a 37.25ab 37.00ab 7.53 Monocytes (%) 1.00b 3.00ab 5.50a 3.75ab 0.94 Platelets (mil/mm³) 159.25b 432.75a 417.50a 276.50ab 68.00 SEM - Standard Error of the Mean. Means followed by different letters in the lines differ significantly according to the Tukey test (p ≤ 0.05). 4. Discussion All temperature values in both conditions (sun and shade) exceeded the comfort zone limits for Holstein cattle, which range from 1°C to 16°C (Pilatti et al. 2020 ). Maximum temperatures above 35°C were recorded, approximately 20°C above the normal comfort limit, causing physiological changes (Sammad et al. 2020 ) in these animals and impairing milk production and reproductive functions (Bhimte et al. 2018 ). This maximum temperature is also at the upper limit of the comfort range for Zebu cattle (Rohleder et al. 2022 ), indicating that even animals considered tolerant are susceptible to heat stress in semi-arid regions. In conditions of low relative humidity (RH), animals may experience dehydration, as well as irritation of the skin and mucous membranes (Zero et al. 2015 ). Conversely, under high RH conditions, thermoregulatory mechanisms can be compromised, impairing heat loss and increasing heat load, which ultimately leads to heat stress (Chauhan et al. 2021 ). The THI values indicate that under sunny conditions, the animals were subjected to a critical environmental situation (71 to 78) as early as 8:00 a.m. However, the environment became dangerous at 12:00 p.m. and 4:00 p.m. (79 to 83). Animal comfort does not depend exclusively on air temperature (AT) or relative humidity (RH) but rather on a combination of these climatic elements. In situations of high RH and AT, animal comfort is significantly impaired because heat loss through evaporation, primarily via panting and perspiration, becomes less effective (Becker et al. 2020 ). Therefore, the temperature-humidity index (THI) is used to predict the level of discomfort in these situations. According to Hahn (1985), even under shaded conditions, the environment is classified as critical at both times, with values approaching the danger threshold at 4:00 p.m. For the maximum THI data under sunny conditions, the environment is in a critical state in the morning (8:00 a.m.), with danger values at 12:00 p.m. and 4:00 p.m. Pereira ( 2005 ) states that THI values above 82 already indicate emergency conditions for animals. A similar pattern of increasing maximum values is observed under shaded conditions, where the environment transitions from a critical state at 8:00 a.m. and 12:00 p.m. to an emergency condition at 4:00 p.m. The average and maximum THI values recorded for the sunny period at 8:00 a.m. are classified as mild environmental conditions (72–79), while for the other times, they are considered moderate environmental stress (80–89). Under shaded conditions, the average THI values for all studied times were classified as mild, while only the average value at 4:00 p.m. was moderate, according to the Johnson scale (Johnson 1987 ). These findings indicate that animals are exposed to stressful environmental conditions, even in shaded conditions when kept in semi-arid climates (Reis et al. 2021 ), directly affecting milk production, reproduction, and overall well-being (Tao et al. 2020 ). However, the physiological responses of the animals will ultimately determine their tolerance to specific environmental conditions (Table 2 ). The normal rectal temperature (RT) for dairy animals ranges between 38°C and 39.3°C (Preez 2000 ). The average RT values recorded under sun, shade, shade with concentrate supplementation, and sun with concentrate supplementation conditions were within this normal range. However, when analyzing the maximum RT values, Diniz et al . (Diniz et al. 2020 ) reported that animals experience heat stress (RT above 39.3°C) during midday in sunny conditions (12:00 p.m. and 4:00 p.m.). These findings align with those of Patbandha et al. ( 2020 ), who observed that RT is higher in the afternoon than in the morning. According to Bianca’s classification (Bianca 1961 ), the average RT values in the shaded environment indicate mild stress, as thermoregulatory mechanisms, particularly respiratory frequency, effectively maintained body temperature within the normal range. Conversely, in the sunny afternoon, animals experienced moderate stress, where thermoregulatory mechanisms were intensified to maintain homeothermy, albeit at a higher RT level. Wang et al. ( 2021 ) highlighted that increased body temperature negatively affects feed intake and other physiological responses, such as fertility. The respiratory frequency (RF) values obtained were outside the normal range for cattle, which is between 10 and 30 bpm (Cunningham 1999 ), except in the shade treatment without concentrate supplementation. According to Dißmann et al. ( 2022 ), the average RF for cattle ranges between 24 and 36 bpm, indicating that the RF values in the shaded environment fall within the normal range. In contrast, under sunny conditions, the animals showed significantly altered average RF values at 12:00 p.m. and 4:00 p.m., with maximum values reaching 100 bpm. The sun treatment with concentrate supplementation presented the highest RF values, likely due to the additional heat generated by the supply of concentrate in the diet. An animal is considered tolerant when it can maintain homeothermy under high-temperature conditions, as assessed by RT and RF values (Rocha et al. 2012 ). In the present study, animals kept under sunny conditions exhibited lower heat tolerance (the farther from a value of 2, the less tolerant the animal) compared to those kept in the shade. When evaluating the average data, animals kept in the sun and fed concentrate showed the worst heat tolerance levels in the afternoon (4.0 and 3.7), with maximum values reaching 5.4, reflecting their low adaptability to hot weather. These findings are consistent with those reported by Hahn (1985), Rocha et al. ( 2012 ), and Mylostyvyi et al. ( 2021 ), who observed that Holstein cattle exhibit lower heat tolerance in the afternoon. The weight loss observed in the animals in this study may be associated with heat stress (Tables 1 and 2 ) and the physiological strain on the animals, as evidenced by their hematological and biochemical profiles. Both animals exposed to the full sun and those in the shade without concentrate supplementation experienced weight loss, likely reflecting increased caloric expenditure required to maintain homeothermy under adverse environmental conditions (Joy et al. 2020 ). It is estimated that during heat stress, energy expenditure to sustain respiratory frequency and dissipate heat increases energy requirements by up to 25% in dairy cattle (Garner et al. 2016 ). Heat stress significantly affects feed intake, leading to a higher proportion of concentrate consumption compared to forage intake (Uyeno et al. 2010 ). Additionally, the efficiency of microbial metabolism is directly related to heat generation in the rumen, which can be indirectly estimated through bacterial growth efficiency (Kim et al. 2020 ). According to Meneses et al. ( 2021 ), heat stress affects body temperature indices and causes significant damage to the thermal homeostasis mechanisms in cows. This raises the hypothesis that providing concentrate to animals under heat stress may mitigate the effects of the heat increment from the digestion process, thereby enhancing weight gain and milk production in cows. In high-temperature environments, sensible heat loss mechanisms are insufficient to maintain animals within the thermoneutral zone, making skin evaporation the primary route for heat dissipation (Yan et al. 2021 ). Consequently, animal weight can be negatively affected by temperature, as animals kept in shaded environments exhibit higher productivity compared to those raised in unshaded environments (De Lemos et al. 2023 ), likely due to reduced energy expenditure for respiration and heat dissipation processes, as observed in this study. The reduction in blood glucose observed in animals exposed to higher environmental temperatures and lower relative humidity under sunny conditions can be attributed to the increased energy demand required for thermoregulation. Despite the lower concentrations, they remain within the normal range for cattle (Façanha et al. 2013 ). When an animal is exposed to an unsuitable environment, its initial response involves activation of the hypothalamic-pituitary-adrenal axis, triggering the release of glucocorticoids. This process makes glucose available to vital tissues, thereby maintaining homeostasis (Façanha et al. 2013 ; Vasconcelos et al. 2020 ). Energy is diverted to thermoregulation mechanisms, which involve the activation of physiological responses (Ortega and Szabó 2023 ). Triglycerides, along with fatty acids, are utilized in the formation of ketone bodies (acetone, acetoacetate, and β-hydroxybutyrate). Their reduction is also associated with decreased plasma glucose levels (Fletcher et al. 2001 ), which can predispose animals to ketosis. Ketosis occurs when an animal experiences a negative energy balance, often linked to poor nutritional management, where the energy provided by the diet is insufficient to meet the animal’s demands (Castro et al. 2023 ) or due to prolonged stress. The reduction in cholesterol levels may be related to lower nutrient availability, as the groups exposed to the sun exhibited greater weight losses. The hematological variations shown in this study are probably to compensate for losses in the body. Changes in red blood cells are due to their key role in transporting gases, transporting oxygen from the lungs to the tissues (Gomes et al. 2021 ). Changes in hematocrit concentrations occur in animals subjected to heat stress because as the temperature rises, the animals lose fluids through the respiratory system. There is an increase in the concentration of hematocrit in regulating body temperature that the animal conducts through respiration (evaporation) due to the significant loss of liquid through the respiratory system, which reduces blood plasma volume (Mattosinho et al. 2017 ). The increase in red blood cells during heat stress may result from the heightened oxygen demand of tissues (Teja et al. 2024 ), enabling their physiological needs to be met. This response leads to an elevation in erythrocyte levels, as heat stress induces dehydration in animals, resulting in hemoconcentration. The changes observed in the white blood cell series can be attributed to heat stress caused by environmental conditions and the caloric increase from the feed provided, as seen in animals exposed to the sun with concentrate supplementation (Table 5 ). Greater variations in the analyzed parameters were expected in animals exposed to the sun without concentrate. However, when concentrates were provided to the group in the sun, thermoregulatory parameters in these animals may have been more intensely affected due to the combined effects of heat stress and the caloric increase. Hematological changes are associated with heat stress, which can impact leukocyte, erythrocyte, and hemoglobin levels (Morar et al. 2018 ). Thus, different weather and management conditions significantly influence the constituent elements of the blood count (Carvalho et al. 2023 ). In addition to the heat stress caused by the environment, the caloric increase from concentrate supplementation can intensify hematological responses. According to Dal Más et al. ( 2020 ), animals grazing on low-nutritional-quality grass tend to reduce their dry matter intake, as this process generates greater heat during the ruminal degradation of fiber. Therefore, careful attention must be given to the nutrients provided in the feed, as those with a higher caloric increase during metabolism, such as protein and fiber, can elevate the animal’s internal temperature and impair its performance (Valentim et al. 2020 ). Attention must be given to feed management during conditions of thermal stress, including feeding frequency and scheduling meals during cooler periods of the day. As demonstrated in the present study, increasing the concentrate ratio in the diet can improve biochemical and hematological parameters in animals, as well as mitigate the decline in milk production (Yu et al. 2020 ). Diets containing more than 27% ground corn have been shown to reduce the effects of thermal stress (Calamari et al. 2001 ). For instance, observed lower rectal temperatures in animals, which aligns with the findings of the present study. The increased caloric intake and stress from sun exposure also explain the reduction in lymphocytes and monocytes, as well as the increase in eosinophils observed in cows exposed to the sun with concentrate supplementation. During heat stress, cortisol production increases, affecting physiological responses, including a reduction in lymphocyte proliferation, particularly T lymphocytes, which are suppressed in cases of acute heat stress (Park et al. 2021 ). Animals under severe stress exhibit a reduction in immune system cells and are more susceptible to pathogens. In this context, Eosinophils play a role in defense mechanisms against parasites and allergic reactions (Hooper et al. 2022 ). The reduction in platelet levels can be attributed to the heat stress experienced by the animals as the body attempts to maintain homeostasis. This change was more pronounced in the group exposed to the sun with concentrate supplementation, suggesting a higher level of stress in these animals. The tested environmental and feeding conditions induced hematological variations in specific white blood cells and platelets, as previously described. Total leukocyte levels, hematocrits, and red blood cell counts are known to be influenced by seasonal changes (Moura et al. 2023 ). Thus, animals possess a relative morphophysiological capacity to dissipate heat, which depends on factors such as the duration of exposure, the type of feed consumed, the energy expended to sustain cellular processes, and their physiological functions. However, they require an environment with natural or artificial shading to shield them from direct solar radiation, particularly in tropical regions (Hooper et al. 2018 ). 5. Conclusions It was concluded that Holstein cows kept under sunny conditions exhibited lower heat tolerance. Cows exposed to the sun, even when fed concentrate, were significantly influenced by the environment, resulting in weight loss and alterations in glucose, triglyceride, and plasma cholesterol concentrations. Animals kept in the sun and fed concentrate showed reduced levels of monocytes, lymphocytes, and platelets, along with increased eosinophil counts. Holstein cattle demonstrated better metabolic and hematological responses when provided with shade and concentrate supplementation in their diet. The harmful effects of heat stress in tropical conditions, particularly in semi-arid climates, are a significant concern, especially when using temperate-climate animals such as Holstein cattle. The thermal comfort range for these animals is much lower than the air temperature values typically found in tropical regions. Therefore, future research focused on selecting animals with heat resistance genes is necessary to enhance the full genetic potential of these animals in tropical conditions. Declarations Author Contributions: Methodology, D.R.R., J.F.B.M. and S.A.U.; investigation, D.R.S.O., H.D.R.C.R., A.B.G.C. and F.P.T.C.; writing—original draft preparation, A.E.C.M.C. and A.S.R.; writing—review and editing, D.R.R. and J.V.E.N.; supervision, D.R.R. and F.N.L.; funding acquisition, D.R.R. and J.V.E.N. All authors have read and approved the final version of the manuscript. Data availability: Data will be made available on reasonable request. Funding: This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. Additionally, this work received support from the following Brazilian research agencies: FACEPE and CNPq. Competing interests: The authors have no competing interests to declare that are relevant to the content of this article References Mascarenhas, N.M.H.; Furtado, D.A.; Souza, B.B. de; Sousa, O.B. de; Costa, A.N.L. da; Feitosa, J.V.; Silva, M.R. da; Batista, L.F.; Dornelas, K.C. Morphology of Coat and Skin of Small Ruminants Reared in the Brazilian Semi-Arid Region. J Therm Biol 2023 , 112 , 103418, doi:10.1016/J.JTHERBIO.2022.103418. Araújo do Nascimento, A.P.; Martins Castro, M.S.; de Sousa Oliveira, D.; Freitas Silveira, R.M.; Ortiz Vega, W.H.; Medeiros Nobre, M.E.; Andrioli, A.; Maria de Vasconcelos, A. Environmental Enrichment in Dairy Goats in a Semi-Arid Region: Thermoregulatory and Behavioral Responses. J Therm Biol 2022 , 106 , 103248, doi:10.1016/J.JTHERBIO.2022.103248. Habeeb, A.A.; Osman, S.F.; Teama, F.E.I.; Gad, A.E. The Detrimental Impact of High Environmental Temperature on Physiological Response, Growth, Milk Production, and Reproductive Efficiency of Ruminants. Trop Anim Health Prod 2023 , 55 , 1–15, doi:10.1007/S11250-023-03805-Y/FIGURES/1. Uyeno, Y.; Sekiguchi, Y.; Tajima, K.; Takenaka, A.; Kurihara, M.; Kamagata, Y. An rRNA-based analysis for evaluating the effect of heat stress on the rumen microbial composition of Holstein heifers. Anaerobe , 2010 , 16, 27–33. doi: 10.1016/j.anaerobe.2009.04.006 Kim, D.H.; Kim, M.H., Kim, S.B.; Son, J.K.; Lee, J.H.; Joo, S.S.; et al. Differential dynamics of the ruminal microbiome of jersey cows in a heat stress environment. Animals , 2020 , 10, 1127. doi: 10.3390/ani10071127. Sejian, V.; Bhatta, R.; Gaughan, J.B.; Dunshea, F.R.; Lacetera, N. Review: Adaptation of Animals to Heat Stress. Animal 2018 , 12 , s431–s444, doi:10.1017/S1751731118001945. Vieira, R.; Louvandini, H.; Barcellos, J.; Martins, C.F.; McManus, C. Path and Logistic Analysis for Heat Tolerance in Adapted Breeds of Cattle in Brazil. Livest Sci 2022 , 258 , 104888, doi:10.1016/J.LIVSCI.2022.104888. Jo, J.H.; Nejad, J.G.; Peng, D.Q.; Kim, H.R.; Kim, S.H.; Lee, H.G. Characterization of Short-Term Heat Stress in Holstein Dairy Cows Using Altered Indicators of Metabolomics, Blood Parameters, Milk MicroRNA-216 and Characteristics. Animals 2021 , Vol. 11, Page 722, 2021, 11, 722, doi:10.3390/ANI11030722. Monteiro, A.C.B.; Iano, Y.; França, R.P.; Arthur, R. Development of a Laboratory Medical Algorithm for Simultaneous Detection and Counting of Erythrocytes and Leukocytes in Digital Images of a Blood Smear. Deep Learning Techniques for Biomedical and Health Informatics 2020 , 165–186, doi:10.1016/B978-0-12-819061-6.00007-0. Conçeição, W.L.F.; Brito, D.R.B.; Rocha, T.G.; Da Silva, D.G.; Chaves, D.P.; Fagliari, J.J. Serum Biochemical Profile of Nellore and Girolando Cows Raised in State of Maranhão. Ciencia Animal Brasileira 2019 , 20, doi:10.1590/1089-6891V20E-33796. Bagath, M.; Krishnan, G.; Devaraj, C.; Rashamol, V.P.; Pragna, P.; Lees, A.M.; Sejian, V. The Impact of Heat Stress on the Immune System in Dairy Cattle: A Review. Res Vet Sci 2019 , 126 , 94–102, doi:10.1016/J.RVSC.2019.08.011. Mylostyvyi, R.; Lesnovskay, O.; Karlova, L.; Khmeleva, O.; Kalinichenko, O.; Orishchuk, O.; Tsap, S.; Begma, N.; Cherniy, N.; Gutyj, B.; et al. Brown Swiss Cows Are More Heat Resistant than Holstein Cows under Hot Summer Conditions of the Continental Climate of Ukraine. J. Anim. Behav. Biometeorol. 2021 , 9 , 0–0, doi:10.31893/JABB.21034/PDF/JABBNET-9-4-2134.PDF. Martins Neto, T.; Silva, C.B.; Ruas, J.R.M.; Silva, E.A.; Queiroz, D.S.; Costa, M.D.; Gomes, V.M.; Santos, L.H.T. Economic Viability F1 Holstein x Zebu Cows of Dairy from Different Maternal Bases and Birth Orders. Arq Bras Med Vet Zootec 2018 , 70 , 1959–1969, doi:10.1590/1678-4162-10054. Teixeira, A.H. C. Informações Agrometeorológicas Do Polo Petrolina, PE/Juazeiro, BA - 1963 a 2009. 2011 . National Academies of Sciences, Engineering, and Medicine (NASEM). 2021 . Nutrient Requirements of Dairy Cattle: Eighth Revised Edition . Washington, DC: The National Academies Press. https://doi.org/10.17226/25806 Mader T.L., Davis M.S., Brown-Brandl T. Environmental Factors Influencing Heat Stress in Feedlot Cattle. J. Anim. Sci . 2006 ; 84:712–719. doi: 10.2527/2006.843712x. Rocha, D.R.; Salles, M.G.F.; Moura, A.A.A.N.; Araújo, A.A. Índices de tolerância ao calor de vacas leiteiras no período chuvoso e seco no ceará. Rev. Acad. Ciênc. Anim. 2012 , 10 , 335–343, doi:10.7213/academica.7739. Costa, A.N.; Feitosa, J.V.; Júnior, P.A.; Souza, P.T.; Araújo, A.A. Hormonal profiles, physiological parameters, and productive and reproductive performances of Girolando cows in the state of Ceará-Brazil. Int J Biometeorol , 2015, 59(2), 231-6. doi:10.1007/s00484-014-0838-0. Copley, N.G. Alloxan and Ninhydrin Test ; Analyst 66.; 1941 . Natt, M.P.; Herrick, C.A. A New Blood Diluent for Counting the Erythrocytes and Leucocytes of the Chicken. Poult Sci 1952 , 31 , 735–738, doi:10.3382/PS.0310735. Schalm, O.W.; Jain, N.C.; Carrroll, E.J. Hematología Veterinaria ; Hemisferio Sur: Buenos Aires, 1981 ; ISBN 9789500042116. Sampaio, I.B.M., 2002 . Estatística aplicada à experimentação animal. FEP MVZ Editora, Belo Horizonte-MG Pilatti, J.A.; Vieira, F.M.C.; Pilatti, J.A.; Vieira, F.M.C. Environment, Behavior and Welfare Aspects of Dairy Cows Reared in Compost Bedded Pack Barns System. J. Anim. Behav. Biometeorol. 2020 , 5 , 97–105, doi:10.31893/2318-1265JABB.V5N3P97-105. Sammad, A.; Wang, Y.J.; Umer, S.; Lirong, H.; Khan, I.; Khan, A.; Ahmad, B.; Wang, Y. Nutritional Physiology and Biochemistry of Dairy Cattle under the Influence of Heat Stress: Consequences and Opportunities. Animals (Basel) 2020 , 10 , doi:10.3390/ANI10050793. Bhimte, A.; Thakur, N.; Lakhani, N.; Yadav, V.; Khare, A.; Lakhani, P. Endocrine Changes in Livestock during Heat and Cold Stress. J Pharmacogn Phytochem 2018 , 7 , 127–132. Rohleder, L.A.S.; Querino, C.A.S.; Alves, P.V.; Querino, J.K.A. da S.; Pedreira Junior, A.L.; Vaz, M.A.B. Evaluation of Environmental Parameters in a Microregion in Southern Amazonas State, Brazil, and Their Relationship with Heat Stress in Dairy Cattle. Ciência Animal Brasileira 2022 , 23 , e71625, doi:10.1590/1809-6891V23E-71625E. Zero, R.C.; Cano, L.M. da S.; Carneiro, L.G.; Lima, B.B. Fatores ambientais na resposta fisiologica e comportamental de vacas leiteiras. Nucleus Animalium 2015 , 7 , 93–103, doi:10.3738/1982.2278.1508. Chauhan, S.S.; Rashamol, V.P.; Bagath, M.; Sejian, V.; Dunshea, F.R. Impacts of Heat Stress on Immune Responses and Oxidative Stress in Farm Animals and Nutritional Strategies for Amelioration. Int J Biometeorol 2021 , 65 , 1231–1244, doi:10.1007/S00484-021-02083-3. Becker, C.A.; Collier, R.J.; Stone, A.E. Invited Review: Physiological and Behavioral Effects of Heat Stress in Dairy Cows. J Dairy Sci 2020 , 103 , 6751–6770, doi:10.3168/JDS.2019-17929. Hahn, G. L. Compensatory performance in livestock: Influence on environmental criteria. In: YOUSEF, M. K. (ed.). Stress physiology in livestock 1985 . Boca Raton: CRC Press, v.2, p.52-145. Pereira, J.C.C. Fundamentos de Bioclimatologia Aplicados À Produção Animal . ; FEPMVZ : Belo Horizonte, 2005 ; ISBN 8587144197. Johnson, H.D. Bioclimatology and the Adaptation of Livestock ; Elsevier, 1987 ; ISBN 0444426906. Reis, N.S.; Ferreira, I.C.; Mazocco, L.A.; Souza, A.C.B.; Pinho, G.A.S.; Neto, Á.M. da F.; Malaquias, J. V.; Macena, F.A.; Muller, A.G.; Martins, C.F.; et al. Shade Modifies Behavioral and Physiological Responses of Low to Medium Production Dairy Cows at Pasture in an Integrated Crop-Livestock-Forest System. Animals 2021 , 11, e2411. doi:10.3390/ANI11082411. Tao, S.; Orellana Rivas, R.M.; Marins, T.N.; Chen, Y.C.; Gao, J.; Bernard, J.K. Impact of Heat Stress on Lactational Performance of Dairy Cows. Theriogenology 2020 , 150 , 437–444, doi:10.1016/J.THERIOGENOLOGY.2020.02.048. Preez, J. Du Parameters for the Determination and Evaluation of Heat Stress in Dairy Cattle in South Africa. Onderstepoort j. vet. res. 2000 . Diniz, T.A.; Carvalho, C.C.S.; Ruas, J.R.M.; Santos, H.P.; Monção, F.P.; Silva, E.A.; Costa, M.D.; Rocha Júnior, V.R. Análise Termográfica Aplicada Na Produção de Calor Corporal de Vacas F1 HxZ Manejadas Em Diferentes Microclimas. Arq Bras Med Vet Zootec 2020 , 72 , 545–552, doi:10.1590/1678-4162-11107. Patbandha, T.K.; Mohanty, T.K.; Baithalu, R.K.; Kumaresan, A.; Bhakat, M.; Golher, D.; Lathwal, S.S.; Pathak, R. Evaluation of Rectal Temperature during the Post-Parturient Period in Crossbred Cows Reared under the Subtropical Climate. Indian J Anim Res 2020 , 54 , 110–115, doi:10.18805/IJAR.B-3734. Bianca, W. Heat Tolerance in Cattle-Its Concept, Measurement and Dependence on Modifying Factors. Int J Biometeorol 1961 , 5 , 5–30, doi:10.1007/BF02186917. Wang, N.; Zhou, C.; Basang, W.; Zhu, Y.; Wang, X.; Li, C.; Chen, L.; Zhou, X. Mechanisms by Which Mastitis Affects Reproduction in Dairy Cow: A Review. Reprod. Domest. Anim. 2021 , 56 , 1165–1175. Cunningham, J.G. Tratado de fisiologia veterinária 2.ed. Rio de Janeiro: Guanabara Koogan, 1999 . 454p. Dißmann, L.; Heinicke, J.; Jensen, K.C.; Amon, T.; Hoffmann, G. How Should the Respiration Rate Be Counted in Cattle? Vet Res Commun 2022 , 46 , 1221–1225, doi:10.1007/s11259-022-09984-7. Joy, A.; Dunshea, F.R.; Leury, B.J.; Clarke, I.J.; Digiacomo, K.; Chauhan, S.S. Resilience of Small Ruminants to Climate Change and Increased Environmental Temperature: A Review. Animals 2020 , 10 . Garner, J.B.; Douglas, M.L.; Williams, S.R.O.; Wales, W.J.; Marett, L.C.; Nguyen, T.T.T.; Reich, C.M.; Hayes, B.J. Genomic Selection Improves Heat Tolerance in Dairy Cattle. Sci Rep 2016 , 6 , doi:10.1038/srep34114. Meneses, J. A. M., Lopes de Sá, O. A. A., Coelho, C. F., Pereira, R. N., Batista, E. D., Ladeira, M. M., et al.. Effect of heat stress on ingestive, digestive, ruminal and physiological parameters of Nellore cattle feeding low- or high-energy diets. Livest. Sci. 2021, 252, 104676. doi: 10.1016/j.livsci.2021.104676 Yan, G.; Liu, K.; Hao, Z.; Li, H.; Shi, Z. Development and Evaluation of Thermal Models for Predicting Skin Temperature of Dairy Cattle. Comput Electron Agric 2021 , 188 , doi:10.1016/j.compag.2021.106363. Lemos, M.J.; Braga, T.V.S.; Leite, D.K.V.H.; Galindo, E.L. O. Efeito Climático Sobre a Produção de Leite de Vacas Guzerá Criadas Em Dois Ambientes Diferentes. Braz. J. Anim. Environ. Res , 2023 , 6 , 1721–1726, doi:10.34188/bjaerv6n2-062. Fontes, P.M.A.; Souza Junior, A. de; Carvalho, E.B. de; Gomes, L.P. de M.; Roier, E.C.R.; Moraes, R.F.F. de Comparação Do Perfil Hematológico e Bioquímico de Novilhas Da Raça Girolando No Primeiro Terço de Gestação Com o Período de Anestro. Rev Fluminense de Extensão Universitária 2023 , 13 , 06–11. Façanha, D.A.E.; Chaves, D.F.; Morais, J.H.G.; Vasconcelos, Â.M.; Costa, W.P.; Guilhermino, M.M. Methodological Tendencies of Adaptability Evaluation to Tropical Environment; 2013 ; Vasconcelos, A.M. de; Albuquerque, C.C. de; Carvalho, J.F. de; Façanha, D.A.E.; Lima, F.R.G.; Silveira, R.M.F.; Ferreira, J. Adaptive Profile of Dairy Cows in a Tropical Region. Int J Biometeorol 2020 , 64 , 105–113, doi:10.1007/s00484-019-01797-9. Ortega, A.D.S.V.; Szabó, C. Metabolism and Endocrine Alterations in Growing and Finishing Pigs under Different Duration of Heat Stress-a Review ; 2023 ; Vol. 41;. Fletcher, G.F.; Balady, G.J.; Amsterdam, E.A.; Chaitman, B.; Eckel, R.; Fleg, J.; Froelicher, V.F.; Leon, A.S.; Piña, I.L.; Rodney, R.; et al. Exercise Standards for Testing and Training. Circulation 2001 , 104 , 1694–1740, doi:10.1161/HC3901.095960. Castro, B.A.D. de; Pires, I.M.; Andrade, L.S. de Cetose Subclínica e Seu Impacto No Desempenho Reprodutivo de Vacas Leiteiras: Revisão de Literatura. Rev. Educ. Contin. Med. Vet. Zootec. CRMV-SP 2023 , 21 , 2023, doi:10.36440/RECMVZ.V21.38359. Gomes, L.G.O.; Fodra, J.D.; Massabni, A.C. Hematologia Dos Vertebrados: A Série Vermelha Do Sangue. Revista Brasileira Multidisciplinar 2021 , 24 , 226–243. Mattosinho, R.; De Oliveira1; Sampaio, A.J.; Savioli De Almeida1, ; Balarin, M.; Regina, S.; Fiorato, C.; André2, ; Vasques, G.M.; Benedetti3, ; et al. Alterações Hematológicas e Bioquímica Sérica de Equinos Atletas. Rev. Ciênc. Vet. Saúde Pública. 2017 , 4 , 082–091, doi:10.4025/REVCIVET.V4I1.35706. Teja, K.V.; Sreedhar, S.; Chakravarthi, M.K. A Study on the Effect of Housing on Haematological Parameters of Nellore Lambs. Indian Journal of Animal Production and Management 2024 , 37 , 342–349, doi:10.48165/ijapm.2023.37.4.13. Morar, D.; Ciulan, V.; Simiz, F.; Moț, T. Effect of Heat Stress on Haematological Parameters in Dairy Cows. Lucrări ştiinţifice medicină veterinară 2018 , 61 (2) , 65–70, doi:10.13140/RG.2.2.36806.22081. Carvalho, A. de B.; Figueiredo, J.R.D.O.; Silva, N.I.S. da; Leite, R.F.; Benício, T.M.A.; Silva1, M.R. Da; Mascarenhas, N.M.H.; Fernandes, D.L.; Silva, J.A.P. da C.; Souza, B.B. de Influência Dos Elementos Climáticos Na Produção Animal Nos Trópicos ; 2023 ; Dal Más, F.E.; Debiage, R.R.; Schuh, B.R.F.; Guirro, E.C.B.D.P. Estresse Térmico Em Bovinos Leiteiros-Impactos, Avaliação e Medidas de Controle ; 2020 ; Valentim, J.K.; Bittencourt, T.M.; D’Ávilla Lima, H.J.; Moraleco, D.D.; Del Solar Velarde, J.M.; da Cruz, M.S.; Procópio, D.P.; Lopes, Y.G.; Garcia, R.G. Thermoregulation of Broilers Fed with Diets Containing Dried Distillers Grain Levels. Rev. Acad. Ciênc. Anim.l 2020 , 18 , doi:10.7213/2596-2868.2020.18002. Yu, M.F.; Zhao, X.M,; Cai, H; Yi, J.M.; Hua G.H. Dihydropyridine enhances the antioxidant capacities of lactating dairy cows under heat stress condition. Animals . 2020 , 10(10), e1812. doi: 10.3390/ani10101812 Calamari, L.; Lombardi, G.; Maianti, M.G.; Calegari, F.; Stefanini, L. Effect of energy supplementation and protein source on milk production of dairy cows in warm season. In:Proceeding XIV ASPA National Congress. 2001 , 123–125. Park, D.S.; Gu, B.-H.; Park, Y.J.; Joo, S.S.; Lee, S.-S.; Kim, S.-H.; Kim, E.T.; Kim, D.H.; Lee, S.S.; Lee, S.J.; et al. Dynamic Changes in Blood Immune Cell Composition and Function in Holstein and Jersey Steers in Response to Heat Stress. Cell Stress Chaperones 2021 , 26 , 705–720, doi:10.1007/s12192-021-01216-2/Published. Hooper, H.B.; Pieruzzi, P.A.P.; Lima, J.H.V. de; Anobi, B.T.; Ferreira, K.N.A.; Silva, R.R. da; Gurtler, G.D.; Santarosa, B.P.; Silva, P. dos S. Cromoterapia Associada à Fitoterapia: Saúde Global e Controle de Parasitos de Bezerros de Aptidão Leiteira. Revista Brasileira de Práticas Integrativas e Complementares em Saúde 2022 , 2 , 26–43. Moura, D.M.F. de; Santos, N.S.; Silva, J.C. de S.; Oliveira, A.R.N. de; Abdalla, A.L. Efeito Do Ambiente Sobre as Respostas Fisiológicas de Caprinos Criados Em Clima Quente Recebendo Diferentes Fontes de Volumoso. Research, Society and Development 2023 , 12 , e16412842657, doi:10.33448/rsd-v12i8.42657. Hooper, H.B.; dos Santos Silva, P.; de Oliveira, S.A.; Merighe, G.K.F.; Negrão, J.A. Acute Heat Stress Induces Changes in Physiological and Cellular Responses in Saanen Goats. Int J Biometeorol. 2018 , 62 , 2257–2265, doi:10.1007/s00484-018-1630-3. Supplementary Files SupplementaryFile.xlsx Cite Share Download PDF Status: Posted Version 1 posted 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5932595","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":431554719,"identity":"8b8ff1b2-11c2-4a92-bdc6-31302f16d2a4","order_by":0,"name":"David Ramos da Rocha","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"Ramos da","lastName":"Rocha","suffix":""},{"id":431554720,"identity":"000118b8-4f6f-445b-8664-d6876182a6cf","order_by":1,"name":"Ana Elisa Custódio Montes 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Rios","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Hewerthon","middleName":"David Reis Carneiro","lastName":"Rios","suffix":""},{"id":431554728,"identity":"2368e971-86c0-421e-9ea9-454989d65b4e","order_by":9,"name":"Deise Rejane Silva de Oliveira","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Deise","middleName":"Rejane Silva","lastName":"de Oliveira","suffix":""},{"id":431554729,"identity":"674144be-a83d-43d2-80d5-749aa01b99dd","order_by":10,"name":"João Virgínio Emerenciano Neto","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYBACxgZkXgIQ8zMwPgBSB0jQItnAbIBXCyYwOEBAC3N788MHDBXb5Mzbew9+eFBzR874RjLb5wKGO/k4HdZzzNiA4cxtY5kz55IlEo49Mza7kcw8ewbDM8sGXFpmJJhJMLbdTpwhkWPGkMB2OHHbjfzDzDwMhw1w2jIj/ZsE47/b9TPk3wC1/DucuHlGMjMBLTlAWxpuJ0hI8JgxJLYdTtwgQUhLz5lig4Rjtw1n8OQYSyT2HTaWOPMYqMXgGU4thu3tGx98qLktL8F+xvDjj2+H5fjbQbZU3MGtpYEBEoNoAKcGBgZ53FKjYBSMglEwCqAAAGTYVh1WzGyaAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-3060-9696","institution":"UFRN: Universidade Federal do Rio Grande do Norte","correspondingAuthor":true,"prefix":"","firstName":"João","middleName":"Virgínio Emerenciano","lastName":"Neto","suffix":""}],"badges":[],"createdAt":"2025-01-30 20:50:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5932595/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5932595/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88701776,"identity":"e33a8891-9c9d-47bc-bc60-69990093ab27","added_by":"auto","created_at":"2025-08-09 22:08:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1327253,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5932595/v1/f4c3c05c-6211-4525-b281-c5dd032c0428.pdf"},{"id":79591785,"identity":"c3e2fe42-bf45-4b59-b984-6312715f157d","added_by":"auto","created_at":"2025-03-31 13:18:26","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":17492,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5932595/v1/92aa19d3f937128cb75459a3.xlsx"}],"financialInterests":"","formattedTitle":"Heat tolerance, biochemical, and hematological responses of Holstein cows under different feeding and environmental conditions in the semi-arid region of Brazil","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe environment directly influences animal performance and affects physiological and behavioral responses in a production system. These challenges are very common in northeastern Brazil, as this semi-arid region has high levels of air temperature, solar radiation, and low levels of rainfall (Mascarenhas et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Dairy cattle of European origin, kept in thermally stressful conditions, activate their thermoregulation process, modifying physiological parameters, which can lead to a reduction in food intake, impair liver functions, causing a consequent drop in performance (Ara\u0026uacute;jo do Nascimento \u003cem\u003eet al\u003c/em\u003e. 2022), as well as reducing reproductive capacity (Habeeb et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Heat stress significantly alters feed intake, increasing the proportion of concentrate consumed compared to forage (Uyeno et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Additionally, microbial metabolic efficiency is directly related to heat generation in the rumen, which can be indirectly estimated through bacterial growth efficiency (Kim et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMetabolic and hematological parameters are widely used in studies to evaluate the effects of the thermal environment on animals. Changes in blood cell counts are correlated with heat stress, showing variations in hematocrit values, erythrocyte count, and hemoglobin. In addition, other parameters are considered important in evaluating heat stress conditions, such as cortisol, non-esterified fatty acids, thyroid hormones, total proteins, and heat shock transcription factors, among others (Sejian et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). It is known that animals attempt to regulate their body temperature by increased breathing rate, which can result in fluid loss through the respiratory system, leading to a reduction in blood plasma volume and altering the concentration of hematocrits (Vieira et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition to the red blood cell series, the leukogram is frequently used to assess the effects of stress caused by the environment. Metabolic profiling is increasingly recognized as a disease prevention tool and has demonstrated efficacy as a platform for identifying alterations resulting from adverse environmental factors (Jo et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The global and differential leukocyte count constitutes what is known as the leukogram, composed of five primary cell types (monocytes, neutrophils, eosinophils, basophils, and lymphocytes), but total counts do not differentiate between these cell types (Monteiro et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOn the other hand, several factors affect the biochemical profile of blood, including age, sex, weather conditions, and management practices (Con\u0026ccedil;ei\u0026ccedil;\u0026atilde;o et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Among the cell types, studies have shown that heifers exposed to temperatures of 40\u0026deg;C exhibit a reduction in lymphocyte count and an increase in neutrophil count (Bagath et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), along with changes in other parameters such as hemoglobin levels and intermediate metabolites. Consequently, these metabolite analyses and hematometry are essential tools for evaluating physiological adaptations, providing insights into the processes governing animal-environment interactions. Thus, blood parameters can be considered homeostatic and responsive indicators for different environmental conditions.\u003c/p\u003e \u003cp\u003eBreeds of European origin, particularly the Holstein breed, tend to suffer more from heat stress due to their reduced ability to adapt to hot climates, which is associated with their higher metabolic rate and lower heat dissipation capacity (Mylostyvyi et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Approximately 70% of Brazil\u0026rsquo;s milk production comes from Holstein-Zebu crossbred cows (Martins Neto et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, Holstein cows are also commonly raised in semi-arid regions, where the harsh climate can significantly influence the milk productivity of these animals.\u003c/p\u003e \u003cp\u003eThe objective of this study was to evaluate the effects of the thermal environment and concentrate supplementation in the diet on the physiological responses, heat tolerance, performance, and hematological and biochemical parameters of cows raised under semi-arid conditions.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Execution site\u003c/h2\u003e \u003cp\u003eThis study was conducted at the Federal University of Vale do S\u0026atilde;o Francisco, Agricultural Sciences Campus (CCA), Dairy Cattle Unit, located in Petrolina, PE (9\u0026deg;32\u0026rsquo;32.29 \u0026ldquo;S and 40\u0026deg;32\u0026rsquo;55\u0026rdquo; W) at an altitude of 376 m. The region\u0026rsquo;s climate is classified as semi-arid (BSh), according to the K\u0026ouml;ppen climate classification, with an average air temperature of 22.1\u0026deg;C and a maximum of 34\u0026deg;C (Teixeira \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Experimental animals\u003c/h2\u003e \u003cp\u003e The animal study protocol was approved by the Ethics Committee of the Federal University of Vale do S\u0026atilde;o Francisco (protocol code 0002/170316). Sixteen Holstein females were used, aged between three and five years, with an average weight of 620\u0026thinsp;\u0026plusmn;\u0026thinsp;25 kg, characterized by a black and white spotted coat with a predominance of white and depigmented skin, and randomly distributed across treatments. The cows were non-lactating, non-pregnant, and in reproductive anestrus, for at least 12 months. The body condition score (BSC) of the cows was between 3.5 and 3.75, considered adequate for their condition.\u003c/p\u003e \u003cp\u003eThe diet was formulated based on the maintenance requirements of the animals (National Academies of Sciences 2021), and provided twice daily in collective troughs (by treatment). The diet for the group without concentrate supplementation consisted exclusively of elephant grass green ad libitum (\u003cem\u003eCenchrus purpureus\u003c/em\u003e, cultivar Napier; 26.0% dry matter, 93.4% organic matter, 3.5% crude protein, 3.1% ether extract, 87.0% neutral detergent fiber, 47.1% acid detergent fiber, and 6.4% lignin). In addition to the green elephant grass at will, the others groups received a diet with a forage-to-concentrate ratio of 40:60, ensuring a 35% NDF intake derived from forage. The concentrate consisted of corn (78%), cottonseed meal (21%), and mineral salt (1%), being supplied at 1% of body weight. The cows had ad libitum access to water.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Experimental procedure\u003c/h2\u003e \u003cp\u003eDuring the experimental period, the animals were divided into four treatments and four replications, comprising two environments (sun and shade) and two feeding regimes (with and without concentrate). The treatments were: animals exposed to the sun without concentrate in the diet, animals exposed to the sun with concentrate in the diet, animals kept in the shade with concentrate in the diet, and animals kept in the shade without concentrate in the diet, simultaneously. The experimental period lasted 30 days, including 10 days of adaptation.\u003c/p\u003e \u003cp\u003eThe animals in the shade treatment were housed in a free-stall system (3.3 m\u0026sup2;/animal) throughout the experiment. The facility features a ridge opening 1.20 m wide, a roof covered with ceramic tiles, a ceiling height of 2.60 m, eaves extending 1.50 m, and open sides. The flooring is made of grooved concrete to facilitate the drainage of wastewater. In addition to the covered area in the free stall, the facility includes a shaded area measuring 7.8 m in width and 60.0 m in length. Conversely, the animals in the full-sun treatment were exposed to direct sunlight (9.0 m\u0026sup2;/animal) throughout the experimental period and housed in collective pens without any alternative systems to mitigate heat stress.\u003c/p\u003e \u003cp\u003eData on the thermal environment and physiological parameters and calculations of the temperature-humidity index (THI) and heat tolerance were collected three times a week (monday, wednesday and friday), at 8:00 a.m., 12:00 p.m., and 4:00 p.m. At the end of the experiment, blood samples were collected from the animals via venipuncture of the coccygeal vein for biochemical and hematological analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Assessment of environmental parameters and temperature-humidity index (THI)\u003c/h2\u003e \u003cp\u003eAir temperature (AT) and relative humidity (RH) data were obtained using a thermohygrometer (Incoterm, S\u0026atilde;o Paulo, Brazil) installed in each experimental room at the average height of the animals\u0026rsquo; bodies. The THI was calculated following the method outlined by Mader et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2006\u003c/span\u003e): THI = (0.8 \u0026times; AT) + [(RH / 100) \u0026times; (AT \u0026minus;\u0026thinsp;14.4)]\u0026thinsp;+\u0026thinsp;46.4, where AT represents air temperature (\u0026deg;C) and RH represents relative humidity (%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Assessment of physiological parameters and heat tolerance index (HTI)\u003c/h2\u003e \u003cp\u003eRectal temperature was measured using a digital veterinary clinical thermometer (Incoterm, S\u0026atilde;o Paulo, Brazil) inserted into the animal\u0026rsquo;s rectum for two minutes (Rocha et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Respiratory rate (RR) was determined by visual observation, counting flank movements for 60 seconds using a stopwatch (Costa et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The result was then multiplied by four to calculate the movements per minute. The heat tolerance index (HTI) was calculated based on the Benezra index, using the formula: HTI\u0026thinsp;=\u0026thinsp;RT/38.33\u0026thinsp;+\u0026thinsp;RR/23, where RT represents rectal temperature and RR represents respiratory rate during the collection periods.\u003c/p\u003e \u003cp\u003eThe animals were weighed individually using a digital scale (TEXAS-Model B-01) at the beginning and end of the experimental period. Weight gain (WG) was calculated using the formula: WG\u0026thinsp;=\u0026thinsp;final weight - initial weight.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Biochemical and hematological analyses\u003c/h2\u003e \u003cp\u003eBlood samples were collected via puncture of the coccygeal vein at the end of the experimental period, using vacuum tubes containing 10% ethylenediaminetetraacetic acid (EDTA) from Biocon\u0026reg; (Taipei, Taiwan). The collection was performed at 8:00 a.m. by a veterinarian from the Federal University of Vale do S\u0026atilde;o Francisco. The blood was divided equally into two aliquots. The first aliquot was used for hematological analyses of the white and red blood cell series. The second aliquot was centrifuged at 3000 g at 4\u0026deg;C for 10 minutes to separate the plasma for biochemical determinations. The blood from the first aliquot was sent to the clinical laboratory (Alpha Veterinary Clinical Analysis Laboratory, Petrolina, Pernambuco, Brazil) for analysis. An automatic hematology analyzer (model BC 5000 VET, Bel\u0026eacute;m-PA, Brazil) was used for the evaluation.\u003c/p\u003e \u003cp\u003eThe metabolites measured in the plasma were glucose (mg/dL), albumin (g/dL), triglycerides (mg/dL), and total cholesterol (mg/dL), analyzed using colorimetric reagent methods (Labtest\u0026reg;), within a maximum of 24 hours after collection. The analyses were performed using a water bath (Model NT265, Piracicaba-SP, Brazil) and a spectrophotometer (Thermo Scientific, GENESYS 10S UV-VIS model).\u003c/p\u003e \u003cp\u003eFor glucose analysis, 10 \u0026micro;L of plasma from each sample was mixed with 10 \u0026micro;L of standard solution (100 mg/dL glucose) in 1.0 mL of reagent. After incubation in a water bath at 37\u0026deg;C for 10 minutes, the reading was performed at a wavelength of 505 nm using a spectrophotometer. The standard solution contained 100 mg/dL of glucose. The calculation was performed using the following formula: sample absorbance / standard absorbance \u0026times; standard concentration (100 mg/dL).\u003c/p\u003e \u003cp\u003eTriglycerides were analyzed using 10 \u0026micro;L of plasma from each sample, 10 \u0026micro;L of standard solution (200 mg/dL triglycerides and 0.045% sodium azide), and 1.0 mL of reagent. After incubation in a water bath at 37\u0026deg;C for 10 minutes, the reading was performed at a wavelength of 505 nm using a spectrophotometer. The standard solution contained 200 mg/dL of triglycerides. The calculation was performed using the following formula: sample absorbance / standard absorbance \u0026times; standard concentration (200 mg/dL).\u003c/p\u003e \u003cp\u003eTotal cholesterol was analyzed using 10 \u0026micro;L of plasma from each sample, 10 \u0026micro;L of standard solution (sodium azide mmol/L, 200 mg/dL), and 1.0 mL of reagent. After incubation in a water bath at 37\u0026deg;C for 10 minutes, the reading was performed at a wavelength of 500 nm using a spectrophotometer. The standard solution contained 200 mg/dL. The calculation was performed using the following formula: sample absorbance / standard absorbance \u0026times; standard concentration (200 mg/dL).\u003c/p\u003e \u003cp\u003eTotal proteins were analyzed using 20 \u0026micro;L of plasma from each sample, 10 \u0026micro;L of standard solution (4 g/dL bovine albumin and 14.6 nmol/L sodium azide), and 1.0 mL of reagent. After incubation in a water bath at 37\u0026deg;C for 10 minutes, the reading was performed at a wavelength of 545 nm using a spectrophotometer. The standard solution contained 4 g/dL. The calculation was performed using the following formula: sample absorbance / standard absorbance \u0026times; standard concentration (4 g/dL).\u003c/p\u003e \u003cp\u003eAlbumin was analyzed using 10 \u0026micro;L of plasma from each sample, 10 \u0026micro;L of standard solution (3.8 g/dL bovine albumin and 0.1% sodium azide), and 1.0 mL of reagent. After 2 minutes at room temperature, the reading was performed at a wavelength of 630 nm using a spectrophotometer. The standard solution contained 3.5 g/dL. The calculation was performed using the following formula: sample absorbance / standard absorbance \u0026times; standard concentration (3.8 g/dL).\u003c/p\u003e \u003cp\u003eUrea was determined using 10 \u0026micro;L of plasma from each sample, 10 \u0026micro;L of standard solution (70 mg/dL urea and 7.7 nmol/L sodium azide), and 1.0 mL of reagent. Two absorbance readings were taken at 30 and 90 seconds. The absorbance difference between 90 and 30 seconds was then calculated. The reading was performed at a wavelength of 340 nm using a spectrophotometer. The calculation was performed using the following formula: sample absorbance / standard absorbance \u0026times; standard concentration (70 mg/dL).\u003c/p\u003e \u003cp\u003eTotal plasma amino acids were analyzed according to Copley (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1941\u003c/span\u003e). An appropriate volume of 20 \u0026micro;L of plasma was added to 1.0 mL of 0.1% ninhydrin solution in propanol. The reaction tubes were incubated at 40\u0026deg;C for 40 minutes in a water bath set at 45\u0026deg;C, and the optical reading was performed at 570 nm. The free amino acid concentration was estimated against an alpha-aminoacetic acid standard containing 150 moles.\u003c/p\u003e \u003cp\u003eThe hematocrit, erythrocyte count, and total hemoglobin were analyzed to assess hematological parameters, and the mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC) were calculated. Hematocrit was measured using a heparinized microcapillary tube filled to two-thirds of its total volume, then centrifuged at 12,000 rpm for 5 minutes. Hemoglobin concentration was determined using the cyanmethemoglobin method with Drabkin reagent, and absorbance was read at 540 nm. The erythrocyte count was conducted in a Neubauer chamber using the reagent (Natt and Herrick \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1952\u003c/span\u003e). The mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC) were calculated using the absolute hematocrit (Hct) values, hemoglobin (Hb) concentration, and erythrocyte count. The hematological parameters were estimated using the following equations:\u003c/p\u003e \u003cp\u003eMCV (fL) = (Hct / erythrocyte count) \u0026times; 10\u003c/p\u003e \u003cp\u003eMCH (pg) = (Hb / erythrocyte count) \u0026times; 10\u003c/p\u003e \u003cp\u003eMCHC (g/dL) = (Hb / Hct) \u0026times; 100\u003c/p\u003e \u003cp\u003eApproximately 5.0 mL of blood was collected in Vacutainer-type tubes containing a 10% EDTA solution (1 mg/mL of blood) as an anticoagulant was kept under refrigeration and transported to the laboratory to obtain the leukogram to determine the leukocyte variables. The leukogram consisted of leukometry using a Neubauer chamber and differential leukocyte counting in blood smears stained using the Wright and Leishman method (Schalm et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). In each blood smear, 100 leukocytes were differentiated and classified based on their morphological and staining characteristics into band neutrophils, segmented neutrophils, eosinophils, basophils, lymphocytes, and monocytes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Statistical analysis\u003c/h2\u003e \u003cp\u003eThe experiment was designed and analyzed as recommended by Sampaio (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). A completely randomized design was used. All variables were tested for normality using the Shapiro-Wilk test and for homoscedasticity using Levene\u0026rsquo;s test, and they were subjected to analysis of variance (ANOVA). The means were compared using the Tukey test at a 5% significance level, employing the R\u0026reg; statistical package.\u003c/p\u003e \u003cp\u003eFor environmental and physiological parameters the following model was used: Yijk\u0026thinsp;=\u0026thinsp;\u0026micro;\u0026thinsp;+\u0026thinsp;Ti\u0026thinsp;+\u0026thinsp;Hj\u0026thinsp;+\u0026thinsp;THij\u0026thinsp;+\u0026thinsp;αijk, where: \u0026micro;, overall average effect; Ti, effect of treatment i, i\u0026thinsp;=\u0026thinsp;Full sun, Shade, Full sun\u0026thinsp;+\u0026thinsp;Concentrate and Shade\u0026thinsp;+\u0026thinsp;Concentrate; Hj, effect of hours j, j\u0026thinsp;=\u0026thinsp;8:00 a.m., 12:00 p.m., and 4:00 p.m.; THij, effect of the interaction between the treatment i and hour j; αijk, random error associated with treatment i, in the hour j, repetition k.\u003c/p\u003e \u003cp\u003eFor the other variables, the following model was used: Yij\u0026thinsp;=\u0026thinsp;\u0026micro;\u0026thinsp;+\u0026thinsp;Ti\u0026thinsp;+\u0026thinsp;βij, where: \u0026micro;, overall average effect; Ti, effect of treatment i, i\u0026thinsp;=\u0026thinsp;Full sun, Shade, Full sun\u0026thinsp;+\u0026thinsp;Concentrate and Shade\u0026thinsp;+\u0026thinsp;Concentrate; βij, random error associated with treatment i, repetition j.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Environmental parameters\u003c/h2\u003e \u003cp\u003eThe air temperature (AT) was significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in sunny conditions at 12:00 p.m. and 4:00 p.m. compared to 8:00 a.m., with a maximum value at 12:00 p.m. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In shaded conditions, a similar pattern was observed, with higher temperatures in the afternoon (12:00 p.m. and 4:00 p.m.) and the highest average (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and maximum temperatures recorded at 4:00 p.m. Additionally, in sunny conditions, the highest average (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and maximum temperature values were observed during the afternoon time points.\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\u003eEnvironmental parameters measured under full sun and shade conditions at 8:00 a.m., 12:00 p.m., and 4:00 p.m.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTemperature (\u0026ordm;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRelative humidity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTHI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eFull sun\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e08:00 a.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.7Ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.3Ba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e77.3Ab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e12:00 p.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.7Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.0Bb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e81.1Aa\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4:00 p.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.7Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.7Bb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80.8Aa\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eShade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e08:00 a.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.8Bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.0 Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74.5Bb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e12:00 p.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e77.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.0Bb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.1Ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76.8Bc\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4:00 p.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.4Ba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.2Ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78.0Ba\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1854\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSEM - Standard Error of the Mean. Means followed by different uppercase letters in the column differ significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between treatments at the same time of day. Means followed by different lowercase letters in the columndiffer significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between times within the same treatment.\u003c/p\u003e \u003cp\u003eIn both environmental conditions, the average relative humidity (RH) values were significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the morning (8:00 a.m.) compared to the afternoon (12:00 p.m. and 4:00 p.m.). Additionally, the highest average (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and maximum RH values were observed in the shaded environment when compared to the sunny environment.\u003c/p\u003e \u003cp\u003eThe temperature-humidity index (THI) under sunny conditions showed the highest values in the afternoon (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) compared to the morning, with the highest average and maximum values recorded at 12:00 p.m. A similar pattern was observed under shaded conditions, except at 4:00 p.m., when the highest maximum and average values were recorded (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, THI under sunny conditions was consistently higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) than under shaded conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e\u003cem\u003e3.2. Physiological parameters\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eThe highest (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) average rectal temperature (RT) values under sunny conditions were observed in the afternoon (12:00 p.m. and 4:00 p.m.) compared to the morning (8:00 a.m.). A similar pattern was observed in sunny conditions when concentrate was added to the animals\u0026rsquo; diet (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). There was no significant difference (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in RT values across the studied times in the shaded area. However, when animals in the shade were fed concentrate, there was a 0.5\u0026deg;C increase in RT at 4:00 p.m. compared to the morning. No significant difference (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) was found between treatments at 8:00 a.m., and no difference (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) was observed at 12:00 p.m. between shaded and sunny conditions. At 4:00 p.m., under sunny conditions with the addition of concentrate to the diet, the highest average RT value (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was recorded compared to other treatments, along with the highest maximum RT value (40\u0026deg;C).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhysiological parameters of cows exposed to shade and sun, with and without concentrate supplementation in the diet.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRT (\u0026ordm;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRF (bpm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHTI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eFull sun\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e08:00 a.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.0Ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.0Ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.0Ab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e12:00 p.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.6Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.0Ba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.7Ba\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4:00 p.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.6Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56.0Ba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.4Ba\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eShade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e08:00 a.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.0Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.0Ba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.4Ba\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e12:00 p.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.0Ba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.0Ca\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.3Ca\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4:00 p.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.2Ba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.0Ca\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.6Ca\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eFull sun\u0026thinsp;+\u0026thinsp;Concentrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e08:00 a.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.7Ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.0Ac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.2Ab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e12:00 p.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.7Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.0Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.0Aa\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4:00 p.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.9Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.0Ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.7Aa\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eShade\u0026thinsp;+\u0026thinsp;Concentrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e08:00 a.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.0Ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.0Ba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.4Ba\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e12:00 p.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.2Bab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.3Ca\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.5Ca\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4:00 p.m.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.5Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.0Ca\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.6Ca\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0826\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0664\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSEM - Standard Error of the Mean; RT - Rectal Temperature; RF - Respiratory Frequency; HTI - Heat Tolerance Index; AHTI - Means followed by different uppercase letters in the column differ significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between treatments at the same time of day. Means followed by different lowercase letters in the column differ significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between times within the same treatment.\u003c/p\u003e \u003cp\u003eThe respiratory frequency (RF) of animals exposed to the sun showed higher average and maximum values in the afternoon (12:00 p.m. and 4:00 p.m.) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) when compared to the morning. In shaded conditions, there was no significant difference (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in RF across the times studied; however, the highest maximum value (60 bpm) was observed at 4:00 p.m. When animals were exposed to the sun with concentrate supplementation in the diet, there was a similar pattern to the sun treatment; however, the highest average value (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was recorded at 12:00 p.m.\u003c/p\u003e \u003cp\u003eIn shaded conditions with concentrate supplementation in the diet, the RF of animals did not differ significantly between the times studied (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, the highest maximum value was recorded in the afternoon (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), following a pattern similar to that observed in the shade-only treatment. In the sun treatment with added concentrate, the highest average (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and maximum RF values were observed at 12:00 p.m.\u003c/p\u003e \u003cp\u003eThe heat tolerance index (HTI) showed that under sunny conditions, the highest average (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and maximum values were observed in the afternoon compared to the morning. In shaded conditions, there was no significant difference (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) between the times studied; however, the highest value was recorded at 4:00 p.m. A similar tolerance pattern was observed in shaded conditions with concentrate supplementation. Under sunny conditions with concentrate supplementation, higher average HTI values (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were observed in the afternoon (12:00 p.m. and 4:00 p.m.) compared to the morning, and the highest maximum HTI values were also recorded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Weight gain and biochemical and hematological parameters\u003c/h2\u003e \u003cp\u003eThe animals in the shade showed higher average daily gains (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Regarding biochemical parameters, animals exposed to full sun had lower (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) concentrations of glucose and triglycerides (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWeight gain and blood biochemical parameters of cows exposed to shade and sun, with and without concentrate supplementation in the diet.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eWith concentrate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eWithout concentrate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFull sun\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShade\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFull sun\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eShade\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight gain (kg/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.37b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.60a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.41b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.41a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlucose (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.85c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.88ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.88b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82.82a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriglycerides (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.21b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.27a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.36c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.61b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholesterol (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65.03ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.81a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.41b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.82ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Proteins (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.37a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.91a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.14a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.10a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.67a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.70a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.49a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.38a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmino acids (\u0026micro;L/mL plasma)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.26a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.53a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.31a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.65a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrea (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.50a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.52a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.71a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.03a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSEM - Standard Error of the Mean. Means followed by different letters in the lines differ significantly according to the Tukey test (p\u0026thinsp;\u0026le;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003ePlasma cholesterol levels were significantly lower (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in animals exposed to the sun without concentrate supplementation compared to those in the shade with concentrate. The other metabolites (total protein, albumin, free amino acids, and urea) did not show significant differences (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in response to the environmental and feeding conditions assessed.\u003c/p\u003e \u003cp\u003eIn the hematological parameters of the red blood cell series, animals in the shade with concentrate supplementation had higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) red blood cell concentrations but lower hemoglobin, hematocrit, mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH) levels compared to those in the shade without concentrate (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The mean corpuscular hemoglobin concentration (MCHC) did not differ significantly (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) between treatments.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHematimetric parameters of the blood of cows exposed to shade and sun, with and without concentrate supplementation in the diet.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eWith concentrate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eWithout concentrate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFull sun\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShade\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFull sun\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eShade\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRed blood cells (million/mm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.91b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.65a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.75b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.83b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.54ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.99a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.53ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.15b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematocrit (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.63ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.00a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.60ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.46b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorpuscular volume (fL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.78ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.27ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.82a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.32b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorpuscular hemoglobin (pg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.52ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.08ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.58a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.41b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHC (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.32a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.32a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.32a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.31a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSEM - Standard Error of the Mean; CHC - Corpuscular Hemoglobin Concentration. Means followed by different letters in the lines differ significantly according to the Tukey test (p\u0026thinsp;\u0026le;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eDepending on the treatments, no significant differences (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) were observed in the total leukocyte count, band neutrophils, or segmented neutrophils in the animals\u0026rsquo; blood. On the other hand, animals exposed to the sun with concentrate supplementation showed the lowest values (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) for lymphocytes, monocytes, and platelets. The highest percentage (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) of eosinophils was observed in animals exposed to the sun with available concentrate (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLeukogram and platelet count in the blood of cows exposed to shade and sun, with and without concentrate supplementation in the diet.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eWith concentrate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eWithout concentrate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFull sun\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShade\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFull sun\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eShade\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukocytes (mil/mm\u0026sup3;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.905a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.745a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.272a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.046a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRods (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.75a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.25a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.50a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSegmented (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.00a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.75a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.25a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.50a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEosinophils (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.75a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.50c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.50b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.50b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocytes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.00b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.25a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.25ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.00ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocytes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.00ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.50a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.75ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelets (mil/mm\u0026sup3;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e159.25b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e432.75a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e417.50a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e276.50ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e68.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSEM - Standard Error of the Mean. Means followed by different letters in the lines differ significantly according to the Tukey test (p\u0026thinsp;\u0026le;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eAll temperature values in both conditions (sun and shade) exceeded the comfort zone limits for Holstein cattle, which range from 1\u0026deg;C to 16\u0026deg;C (Pilatti et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Maximum temperatures above 35\u0026deg;C were recorded, approximately 20\u0026deg;C above the normal comfort limit, causing physiological changes (Sammad et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) in these animals and impairing milk production and reproductive functions (Bhimte et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This maximum temperature is also at the upper limit of the comfort range for Zebu cattle (Rohleder et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), indicating that even animals considered tolerant are susceptible to heat stress in semi-arid regions.\u003c/p\u003e \u003cp\u003eIn conditions of low relative humidity (RH), animals may experience dehydration, as well as irritation of the skin and mucous membranes (Zero et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Conversely, under high RH conditions, thermoregulatory mechanisms can be compromised, impairing heat loss and increasing heat load, which ultimately leads to heat stress (Chauhan et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe THI values indicate that under sunny conditions, the animals were subjected to a critical environmental situation (71 to 78) as early as 8:00 a.m. However, the environment became dangerous at 12:00 p.m. and 4:00 p.m. (79 to 83). Animal comfort does not depend exclusively on air temperature (AT) or relative humidity (RH) but rather on a combination of these climatic elements. In situations of high RH and AT, animal comfort is significantly impaired because heat loss through evaporation, primarily via panting and perspiration, becomes less effective (Becker et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Therefore, the temperature-humidity index (THI) is used to predict the level of discomfort in these situations.\u003c/p\u003e \u003cp\u003eAccording to Hahn (1985), even under shaded conditions, the environment is classified as critical at both times, with values approaching the danger threshold at 4:00 p.m. For the maximum THI data under sunny conditions, the environment is in a critical state in the morning (8:00 a.m.), with danger values at 12:00 p.m. and 4:00 p.m. Pereira (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) states that THI values above 82 already indicate emergency conditions for animals. A similar pattern of increasing maximum values is observed under shaded conditions, where the environment transitions from a critical state at 8:00 a.m. and 12:00 p.m. to an emergency condition at 4:00 p.m.\u003c/p\u003e \u003cp\u003eThe average and maximum THI values recorded for the sunny period at 8:00 a.m. are classified as mild environmental conditions (72\u0026ndash;79), while for the other times, they are considered moderate environmental stress (80\u0026ndash;89). Under shaded conditions, the average THI values for all studied times were classified as mild, while only the average value at 4:00 p.m. was moderate, according to the Johnson scale (Johnson \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). These findings indicate that animals are exposed to stressful environmental conditions, even in shaded conditions when kept in semi-arid climates (Reis et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), directly affecting milk production, reproduction, and overall well-being (Tao et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, the physiological responses of the animals will ultimately determine their tolerance to specific environmental conditions (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe normal rectal temperature (RT) for dairy animals ranges between 38\u0026deg;C and 39.3\u0026deg;C (Preez \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). The average RT values recorded under sun, shade, shade with concentrate supplementation, and sun with concentrate supplementation conditions were within this normal range. However, when analyzing the maximum RT values, Diniz \u003cem\u003eet al\u003c/em\u003e. (Diniz et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) reported that animals experience heat stress (RT above 39.3\u0026deg;C) during midday in sunny conditions (12:00 p.m. and 4:00 p.m.). These findings align with those of Patbandha et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), who observed that RT is higher in the afternoon than in the morning. According to Bianca\u0026rsquo;s classification (Bianca \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1961\u003c/span\u003e), the average RT values in the shaded environment indicate mild stress, as thermoregulatory mechanisms, particularly respiratory frequency, effectively maintained body temperature within the normal range. Conversely, in the sunny afternoon, animals experienced moderate stress, where thermoregulatory mechanisms were intensified to maintain homeothermy, albeit at a higher RT level. Wang et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) highlighted that increased body temperature negatively affects feed intake and other physiological responses, such as fertility.\u003c/p\u003e \u003cp\u003eThe respiratory frequency (RF) values obtained were outside the normal range for cattle, which is between 10 and 30 bpm (Cunningham \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), except in the shade treatment without concentrate supplementation. According to Di\u0026szlig;mann et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the average RF for cattle ranges between 24 and 36 bpm, indicating that the RF values in the shaded environment fall within the normal range. In contrast, under sunny conditions, the animals showed significantly altered average RF values at 12:00 p.m. and 4:00 p.m., with maximum values reaching 100 bpm. The sun treatment with concentrate supplementation presented the highest RF values, likely due to the additional heat generated by the supply of concentrate in the diet.\u003c/p\u003e \u003cp\u003eAn animal is considered tolerant when it can maintain homeothermy under high-temperature conditions, as assessed by RT and RF values (Rocha et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In the present study, animals kept under sunny conditions exhibited lower heat tolerance (the farther from a value of 2, the less tolerant the animal) compared to those kept in the shade. When evaluating the average data, animals kept in the sun and fed concentrate showed the worst heat tolerance levels in the afternoon (4.0 and 3.7), with maximum values reaching 5.4, reflecting their low adaptability to hot weather. These findings are consistent with those reported by Hahn (1985), Rocha et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and Mylostyvyi et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), who observed that Holstein cattle exhibit lower heat tolerance in the afternoon.\u003c/p\u003e \u003cp\u003eThe weight loss observed in the animals in this study may be associated with heat stress (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and the physiological strain on the animals, as evidenced by their hematological and biochemical profiles. Both animals exposed to the full sun and those in the shade without concentrate supplementation experienced weight loss, likely reflecting increased caloric expenditure required to maintain homeothermy under adverse environmental conditions (Joy et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). It is estimated that during heat stress, energy expenditure to sustain respiratory frequency and dissipate heat increases energy requirements by up to 25% in dairy cattle (Garner et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHeat stress significantly affects feed intake, leading to a higher proportion of concentrate consumption compared to forage intake (Uyeno et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Additionally, the efficiency of microbial metabolism is directly related to heat generation in the rumen, which can be indirectly estimated through bacterial growth efficiency (Kim et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). According to Meneses et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), heat stress affects body temperature indices and causes significant damage to the thermal homeostasis mechanisms in cows. This raises the hypothesis that providing concentrate to animals under heat stress may mitigate the effects of the heat increment from the digestion process, thereby enhancing weight gain and milk production in cows.\u003c/p\u003e \u003cp\u003eIn high-temperature environments, sensible heat loss mechanisms are insufficient to maintain animals within the thermoneutral zone, making skin evaporation the primary route for heat dissipation (Yan et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consequently, animal weight can be negatively affected by temperature, as animals kept in shaded environments exhibit higher productivity compared to those raised in unshaded environments (De Lemos et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), likely due to reduced energy expenditure for respiration and heat dissipation processes, as observed in this study.\u003c/p\u003e \u003cp\u003eThe reduction in blood glucose observed in animals exposed to higher environmental temperatures and lower relative humidity under sunny conditions can be attributed to the increased energy demand required for thermoregulation. Despite the lower concentrations, they remain within the normal range for cattle (Fa\u0026ccedil;anha et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). When an animal is exposed to an unsuitable environment, its initial response involves activation of the hypothalamic-pituitary-adrenal axis, triggering the release of glucocorticoids. This process makes glucose available to vital tissues, thereby maintaining homeostasis (Fa\u0026ccedil;anha et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Vasconcelos et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Energy is diverted to thermoregulation mechanisms, which involve the activation of physiological responses (Ortega and Szab\u0026oacute; \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTriglycerides, along with fatty acids, are utilized in the formation of ketone bodies (acetone, acetoacetate, and β-hydroxybutyrate). Their reduction is also associated with decreased plasma glucose levels (Fletcher et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), which can predispose animals to ketosis. Ketosis occurs when an animal experiences a negative energy balance, often linked to poor nutritional management, where the energy provided by the diet is insufficient to meet the animal\u0026rsquo;s demands (Castro et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) or due to prolonged stress. The reduction in cholesterol levels may be related to lower nutrient availability, as the groups exposed to the sun exhibited greater weight losses.\u003c/p\u003e \u003cp\u003eThe hematological variations shown in this study are probably to compensate for losses in the body. Changes in red blood cells are due to their key role in transporting gases, transporting oxygen from the lungs to the tissues (Gomes et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Changes in hematocrit concentrations occur in animals subjected to heat stress because as the temperature rises, the animals lose fluids through the respiratory system. There is an increase in the concentration of hematocrit in regulating body temperature that the animal conducts through respiration (evaporation) due to the significant loss of liquid through the respiratory system, which reduces blood plasma volume (Mattosinho et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe increase in red blood cells during heat stress may result from the heightened oxygen demand of tissues (Teja et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), enabling their physiological needs to be met. This response leads to an elevation in erythrocyte levels, as heat stress induces dehydration in animals, resulting in hemoconcentration.\u003c/p\u003e \u003cp\u003eThe changes observed in the white blood cell series can be attributed to heat stress caused by environmental conditions and the caloric increase from the feed provided, as seen in animals exposed to the sun with concentrate supplementation (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Greater variations in the analyzed parameters were expected in animals exposed to the sun without concentrate. However, when concentrates were provided to the group in the sun, thermoregulatory parameters in these animals may have been more intensely affected due to the combined effects of heat stress and the caloric increase. Hematological changes are associated with heat stress, which can impact leukocyte, erythrocyte, and hemoglobin levels (Morar et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Thus, different weather and management conditions significantly influence the constituent elements of the blood count (Carvalho et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition to the heat stress caused by the environment, the caloric increase from concentrate supplementation can intensify hematological responses. According to Dal M\u0026aacute;s et al. (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), animals grazing on low-nutritional-quality grass tend to reduce their dry matter intake, as this process generates greater heat during the ruminal degradation of fiber. Therefore, careful attention must be given to the nutrients provided in the feed, as those with a higher caloric increase during metabolism, such as protein and fiber, can elevate the animal\u0026rsquo;s internal temperature and impair its performance (Valentim et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Attention must be given to feed management during conditions of thermal stress, including feeding frequency and scheduling meals during cooler periods of the day. As demonstrated in the present study, increasing the concentrate ratio in the diet can improve biochemical and hematological parameters in animals, as well as mitigate the decline in milk production (Yu et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Diets containing more than 27% ground corn have been shown to reduce the effects of thermal stress (Calamari et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). For instance, observed lower rectal temperatures in animals, which aligns with the findings of the present study.\u003c/p\u003e \u003cp\u003eThe increased caloric intake and stress from sun exposure also explain the reduction in lymphocytes and monocytes, as well as the increase in eosinophils observed in cows exposed to the sun with concentrate supplementation. During heat stress, cortisol production increases, affecting physiological responses, including a reduction in lymphocyte proliferation, particularly T lymphocytes, which are suppressed in cases of acute heat stress (Park et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Animals under severe stress exhibit a reduction in immune system cells and are more susceptible to pathogens. In this context, Eosinophils play a role in defense mechanisms against parasites and allergic reactions (Hooper et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe reduction in platelet levels can be attributed to the heat stress experienced by the animals as the body attempts to maintain homeostasis. This change was more pronounced in the group exposed to the sun with concentrate supplementation, suggesting a higher level of stress in these animals. The tested environmental and feeding conditions induced hematological variations in specific white blood cells and platelets, as previously described. Total leukocyte levels, hematocrits, and red blood cell counts are known to be influenced by seasonal changes (Moura et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThus, animals possess a relative morphophysiological capacity to dissipate heat, which depends on factors such as the duration of exposure, the type of feed consumed, the energy expended to sustain cellular processes, and their physiological functions. However, they require an environment with natural or artificial shading to shield them from direct solar radiation, particularly in tropical regions (Hooper et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eIt was concluded that Holstein cows kept under sunny conditions exhibited lower heat tolerance. Cows exposed to the sun, even when fed concentrate, were significantly influenced by the environment, resulting in weight loss and alterations in glucose, triglyceride, and plasma cholesterol concentrations. Animals kept in the sun and fed concentrate showed reduced levels of monocytes, lymphocytes, and platelets, along with increased eosinophil counts. Holstein cattle demonstrated better metabolic and hematological responses when provided with shade and concentrate supplementation in their diet.\u003c/p\u003e \u003cp\u003eThe harmful effects of heat stress in tropical conditions, particularly in semi-arid climates, are a significant concern, especially when using temperate-climate animals such as Holstein cattle. The thermal comfort range for these animals is much lower than the air temperature values typically found in tropical regions. Therefore, future research focused on selecting animals with heat resistance genes is necessary to enhance the full genetic potential of these animals in tropical conditions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Methodology, D.R.R., J.F.B.M. and S.A.U.; investigation, D.R.S.O., H.D.R.C.R., A.B.G.C. and F.P.T.C.; writing\u0026mdash;original draft preparation, A.E.C.M.C. and A.S.R.; writing\u0026mdash;review and editing, D.R.R. and J.V.E.N.; supervision, D.R.R. and F.N.L.; funding acquisition, D.R.R. and J.V.E.N. All authors have read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u003c/strong\u003e Data will be made available on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This study was financed in part by the Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior - Brasil (CAPES) - Finance Code 001. Additionally, this work received support from the following Brazilian research agencies: FACEPE and CNPq.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors have no competing interests to declare that are relevant to the content of this article\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMascarenhas, N.M.H.; Furtado, D.A.; Souza, B.B. de; Sousa, O.B. de; Costa, A.N.L. da; Feitosa, J.V.; Silva, M.R. da; Batista, L.F.; Dornelas, K.C. Morphology of Coat and Skin of Small Ruminants Reared in the Brazilian Semi-Arid Region. \u003cem\u003eJ Therm Biol\u003c/em\u003e \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e112\u003c/em\u003e, 103418, doi:10.1016/J.JTHERBIO.2022.103418.\u003c/li\u003e\n\u003cli\u003eAra\u0026uacute;jo do Nascimento, A.P.; Martins Castro, M.S.; de Sousa Oliveira, D.; Freitas Silveira, R.M.; Ortiz Vega, W.H.; Medeiros Nobre, M.E.; Andrioli, A.; Maria de Vasconcelos, A. Environmental Enrichment in Dairy Goats in a Semi-Arid Region: Thermoregulatory and Behavioral Responses. \u003cem\u003eJ Therm Biol\u003c/em\u003e \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e106\u003c/em\u003e, 103248, doi:10.1016/J.JTHERBIO.2022.103248.\u003c/li\u003e\n\u003cli\u003eHabeeb, A.A.; Osman, S.F.; Teama, F.E.I.; Gad, A.E. The Detrimental Impact of High Environmental Temperature on Physiological Response, Growth, Milk Production, and Reproductive Efficiency of Ruminants. \u003cem\u003eTrop Anim Health Prod\u003c/em\u003e \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e55\u003c/em\u003e, 1\u0026ndash;15, doi:10.1007/S11250-023-03805-Y/FIGURES/1.\u003c/li\u003e\n\u003cli\u003eUyeno, Y.; Sekiguchi, Y.; Tajima, K.; Takenaka, A.; Kurihara, M.; Kamagata, Y. An rRNA-based analysis for evaluating the effect of heat stress on the rumen microbial composition of Holstein heifers. \u003cem\u003eAnaerobe\u003c/em\u003e, \u003cstrong\u003e2010\u003c/strong\u003e, 16, 27\u0026ndash;33. doi: 10.1016/j.anaerobe.2009.04.006\u003c/li\u003e\n\u003cli\u003eKim, D.H.; Kim, M.H., Kim, S.B.; Son, J.K.; Lee, J.H.; Joo, S.S.; et al. Differential dynamics of the ruminal microbiome of jersey cows in a heat stress environment. \u003cem\u003eAnimals\u003c/em\u003e, \u003cstrong\u003e2020\u003c/strong\u003e, 10, 1127. doi: 10.3390/ani10071127.\u003c/li\u003e\n\u003cli\u003eSejian, V.; Bhatta, R.; Gaughan, J.B.; Dunshea, F.R.; Lacetera, N. Review: Adaptation of Animals to Heat Stress. \u003cem\u003eAnimal\u003c/em\u003e \u003cstrong\u003e2018\u003c/strong\u003e, \u003cem\u003e12\u003c/em\u003e, s431\u0026ndash;s444, doi:10.1017/S1751731118001945.\u003c/li\u003e\n\u003cli\u003eVieira, R.; Louvandini, H.; Barcellos, J.; Martins, C.F.; McManus, C. Path and Logistic Analysis for Heat Tolerance in Adapted Breeds of Cattle in Brazil. \u003cem\u003eLivest Sci\u003c/em\u003e \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e258\u003c/em\u003e, 104888, doi:10.1016/J.LIVSCI.2022.104888.\u003c/li\u003e\n\u003cli\u003eJo, J.H.; Nejad, J.G.; Peng, D.Q.; Kim, H.R.; Kim, S.H.; Lee, H.G. Characterization of Short-Term Heat Stress in Holstein Dairy Cows Using Altered Indicators of Metabolomics, Blood Parameters, Milk MicroRNA-216 and Characteristics. \u003cem\u003eAnimals \u003c/em\u003e\u003cstrong\u003e2021\u003c/strong\u003e, Vol. 11, Page 722, 2021, 11, 722, doi:10.3390/ANI11030722.\u003c/li\u003e\n\u003cli\u003eMonteiro, A.C.B.; Iano, Y.; Fran\u0026ccedil;a, R.P.; Arthur, R. Development of a Laboratory Medical Algorithm for Simultaneous Detection and Counting of Erythrocytes and Leukocytes in Digital Images of a Blood Smear. \u003cem\u003eDeep Learning Techniques for Biomedical and Health Informatics\u003c/em\u003e \u003cstrong\u003e2020\u003c/strong\u003e, 165\u0026ndash;186, doi:10.1016/B978-0-12-819061-6.00007-0.\u003c/li\u003e\n\u003cli\u003eCon\u0026ccedil;ei\u0026ccedil;\u0026atilde;o, W.L.F.; Brito, D.R.B.; Rocha, T.G.; Da Silva, D.G.; Chaves, D.P.; Fagliari, J.J. Serum Biochemical Profile of Nellore and Girolando Cows Raised in State of Maranh\u0026atilde;o. \u003cem\u003eCiencia Animal Brasileira\u003c/em\u003e \u003cstrong\u003e2019\u003c/strong\u003e, 20, doi:10.1590/1089-6891V20E-33796.\u003c/li\u003e\n\u003cli\u003eBagath, M.; Krishnan, G.; Devaraj, C.; Rashamol, V.P.; Pragna, P.; Lees, A.M.; Sejian, V. The Impact of Heat Stress on the Immune System in Dairy Cattle: A Review. \u003cem\u003eRes Vet Sci\u003c/em\u003e \u003cstrong\u003e2019\u003c/strong\u003e, \u003cem\u003e126\u003c/em\u003e, 94\u0026ndash;102, doi:10.1016/J.RVSC.2019.08.011.\u003c/li\u003e\n\u003cli\u003eMylostyvyi, R.; Lesnovskay, O.; Karlova, L.; Khmeleva, O.; Kalinichenko, O.; Orishchuk, O.; Tsap, S.; Begma, N.; Cherniy, N.; Gutyj, B.; et al. Brown Swiss Cows Are More Heat Resistant than Holstein Cows under Hot Summer Conditions of the Continental Climate of Ukraine. \u003cem\u003eJ. Anim. Behav. Biometeorol.\u003c/em\u003e \u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e9\u003c/em\u003e, 0\u0026ndash;0, doi:10.31893/JABB.21034/PDF/JABBNET-9-4-2134.PDF.\u003c/li\u003e\n\u003cli\u003eMartins Neto, T.; Silva, C.B.; Ruas, J.R.M.; Silva, E.A.; Queiroz, D.S.; Costa, M.D.; Gomes, V.M.; Santos, L.H.T. Economic Viability F1 Holstein x Zebu Cows of Dairy from Different Maternal Bases and Birth Orders. \u003cem\u003eArq Bras Med Vet Zootec\u003c/em\u003e \u003cstrong\u003e2018\u003c/strong\u003e, \u003cem\u003e70\u003c/em\u003e, 1959\u0026ndash;1969, doi:10.1590/1678-4162-10054.\u003c/li\u003e\n\u003cli\u003eTeixeira, A.H. C. Informa\u0026ccedil;\u0026otilde;es Agrometeorol\u0026oacute;gicas Do Polo Petrolina, PE/Juazeiro, BA - 1963 a 2009. \u003cstrong\u003e2011\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eNational Academies of Sciences, Engineering, and Medicine (NASEM). \u003cstrong\u003e2021\u003c/strong\u003e. \u003cem\u003eNutrient Requirements of Dairy Cattle: Eighth Revised Edition\u003c/em\u003e. Washington, DC: The National Academies Press. https://doi.org/10.17226/25806\u003c/li\u003e\n\u003cli\u003eMader T.L., Davis M.S., Brown-Brandl T. Environmental Factors Influencing Heat Stress in Feedlot Cattle. \u003cem\u003eJ. Anim. Sci\u003c/em\u003e. \u003cstrong\u003e2006\u003c/strong\u003e; 84:712\u0026ndash;719. doi: 10.2527/2006.843712x.\u003c/li\u003e\n\u003cli\u003eRocha, D.R.; Salles, M.G.F.; Moura, A.A.A.N.; Ara\u0026uacute;jo, A.A. \u0026Iacute;ndices de toler\u0026acirc;ncia ao calor de vacas leiteiras no per\u0026iacute;odo chuvoso e seco no cear\u0026aacute;. \u003cem\u003eRev. Acad. Ci\u0026ecirc;nc. Anim. \u003c/em\u003e\u003cstrong\u003e2012\u003c/strong\u003e, \u003cem\u003e10\u003c/em\u003e, 335\u0026ndash;343, doi:10.7213/academica.7739.\u003c/li\u003e\n\u003cli\u003eCosta, A.N.; Feitosa, J.V.; J\u0026uacute;nior, P.A.; Souza, P.T.; Ara\u0026uacute;jo, A.A. Hormonal profiles, physiological parameters, and productive and reproductive performances of Girolando cows in the state of Cear\u0026aacute;-Brazil. \u003cem\u003eInt J Biometeorol\u003c/em\u003e, \u003cstrong\u003e2015, \u003c/strong\u003e59(2), 231-6. doi:10.1007/s00484-014-0838-0.\u003c/li\u003e\n\u003cli\u003eCopley, N.G. \u003cem\u003eAlloxan and Ninhydrin Test\u003c/em\u003e; Analyst 66.; \u003cstrong\u003e1941\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eNatt, M.P.; Herrick, C.A. A New Blood Diluent for Counting the Erythrocytes and Leucocytes of the Chicken. \u003cem\u003ePoult Sci\u003c/em\u003e \u003cstrong\u003e1952\u003c/strong\u003e, \u003cem\u003e31\u003c/em\u003e, 735\u0026ndash;738, doi:10.3382/PS.0310735.\u003c/li\u003e\n\u003cli\u003eSchalm, O.W.; Jain, N.C.; Carrroll, E.J. \u003cem\u003eHematología Veterinaria\u003c/em\u003e; Hemisferio Sur: Buenos Aires, \u003cstrong\u003e1981\u003c/strong\u003e; ISBN 9789500042116.\u003c/li\u003e\n\u003cli\u003eSampaio, I.B.M., \u003cstrong\u003e2002\u003c/strong\u003e. Estat\u0026iacute;stica aplicada \u0026agrave; experimenta\u0026ccedil;\u0026atilde;o animal. FEP MVZ Editora, Belo Horizonte-MG\u003c/li\u003e\n\u003cli\u003ePilatti, J.A.; Vieira, F.M.C.; Pilatti, J.A.; Vieira, F.M.C. Environment, Behavior and Welfare Aspects of Dairy Cows Reared in Compost Bedded Pack Barns System. \u003cem\u003eJ. Anim. Behav. Biometeorol. \u003c/em\u003e\u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e5\u003c/em\u003e, 97\u0026ndash;105, doi:10.31893/2318-1265JABB.V5N3P97-105.\u003c/li\u003e\n\u003cli\u003eSammad, A.; Wang, Y.J.; Umer, S.; Lirong, H.; Khan, I.; Khan, A.; Ahmad, B.; Wang, Y. Nutritional Physiology and Biochemistry of Dairy Cattle under the Influence of Heat Stress: Consequences and Opportunities. \u003cem\u003eAnimals (Basel)\u003c/em\u003e \u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e10\u003c/em\u003e, doi:10.3390/ANI10050793.\u003c/li\u003e\n\u003cli\u003eBhimte, A.; Thakur, N.; Lakhani, N.; Yadav, V.; Khare, A.; Lakhani, P. Endocrine Changes in Livestock during Heat and Cold Stress. \u003cem\u003eJ Pharmacogn Phytochem\u003c/em\u003e \u003cstrong\u003e2018\u003c/strong\u003e, \u003cem\u003e7\u003c/em\u003e, 127\u0026ndash;132.\u003c/li\u003e\n\u003cli\u003eRohleder, L.A.S.; Querino, C.A.S.; Alves, P.V.; Querino, J.K.A. da S.; Pedreira Junior, A.L.; Vaz, M.A.B. Evaluation of Environmental Parameters in a Microregion in Southern Amazonas State, Brazil, and Their Relationship with Heat Stress in Dairy Cattle. \u003cem\u003eCi\u0026ecirc;ncia Animal Brasileira\u003c/em\u003e \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e23\u003c/em\u003e, e71625, doi:10.1590/1809-6891V23E-71625E.\u003c/li\u003e\n\u003cli\u003eZero, R.C.; Cano, L.M. da S.; Carneiro, L.G.; Lima, B.B. Fatores ambientais na resposta fisiologica e comportamental de vacas leiteiras. \u003cem\u003eNucleus Animalium\u003c/em\u003e \u003cstrong\u003e2015\u003c/strong\u003e, \u003cem\u003e7\u003c/em\u003e, 93\u0026ndash;103, doi:10.3738/1982.2278.1508.\u003c/li\u003e\n\u003cli\u003eChauhan, S.S.; Rashamol, V.P.; Bagath, M.; Sejian, V.; Dunshea, F.R. Impacts of Heat Stress on Immune Responses and Oxidative Stress in Farm Animals and Nutritional Strategies for Amelioration. \u003cem\u003eInt J Biometeorol\u003c/em\u003e \u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e65\u003c/em\u003e, 1231\u0026ndash;1244, doi:10.1007/S00484-021-02083-3.\u003c/li\u003e\n\u003cli\u003eBecker, C.A.; Collier, R.J.; Stone, A.E. Invited Review: Physiological and Behavioral Effects of Heat Stress in Dairy Cows. \u003cem\u003eJ Dairy Sci\u003c/em\u003e \u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e103\u003c/em\u003e, 6751\u0026ndash;6770, doi:10.3168/JDS.2019-17929.\u003c/li\u003e\n\u003cli\u003eHahn, G. L. Compensatory performance in livestock: Influence on environmental criteria. In: YOUSEF, M. K. (ed.). Stress physiology in livestock \u003cstrong\u003e1985\u003c/strong\u003e. Boca Raton: CRC Press, v.2, p.52-145.\u003c/li\u003e\n\u003cli\u003ePereira, J.C.C. Fundamentos de Bioclimatologia Aplicados À Produção Animal\u003cem\u003e.\u003c/em\u003e; \u003cem\u003eFEPMVZ\u003c/em\u003e: Belo Horizonte, \u003cstrong\u003e2005\u003c/strong\u003e; ISBN 8587144197.\u003c/li\u003e\n\u003cli\u003eJohnson, H.D. \u003cem\u003eBioclimatology and the Adaptation of Livestock\u003c/em\u003e; Elsevier, \u003cstrong\u003e1987\u003c/strong\u003e; ISBN 0444426906.\u003c/li\u003e\n\u003cli\u003eReis, N.S.; Ferreira, I.C.; Mazocco, L.A.; Souza, A.C.B.; Pinho, G.A.S.; Neto, \u0026Aacute;.M. da F.; Malaquias, J. V.; Macena, F.A.; Muller, A.G.; Martins, C.F.; et al. Shade Modifies Behavioral and Physiological Responses of Low to Medium Production Dairy Cows at Pasture in an Integrated Crop-Livestock-Forest System. \u003cem\u003eAnimals \u003c/em\u003e\u003cstrong\u003e2021\u003c/strong\u003e\u003cem\u003e, 11, e2411.\u003c/em\u003e doi:10.3390/ANI11082411.\u003c/li\u003e\n\u003cli\u003eTao, S.; Orellana Rivas, R.M.; Marins, T.N.; Chen, Y.C.; Gao, J.; Bernard, J.K. Impact of Heat Stress on Lactational Performance of Dairy Cows. \u003cem\u003eTheriogenology\u003c/em\u003e \u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e150\u003c/em\u003e, 437\u0026ndash;444, doi:10.1016/J.THERIOGENOLOGY.2020.02.048.\u003c/li\u003e\n\u003cli\u003ePreez, J. Du Parameters for the Determination and Evaluation of Heat Stress in Dairy Cattle in South Africa. \u003cem\u003eOnderstepoort j. vet. res.\u003c/em\u003e \u003cstrong\u003e2000\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eDiniz, T.A.; Carvalho, C.C.S.; Ruas, J.R.M.; Santos, H.P.; Mon\u0026ccedil;\u0026atilde;o, F.P.; Silva, E.A.; Costa, M.D.; Rocha J\u0026uacute;nior, V.R. An\u0026aacute;lise Termogr\u0026aacute;fica Aplicada Na Produ\u0026ccedil;\u0026atilde;o de Calor Corporal de Vacas F1 HxZ Manejadas Em Diferentes Microclimas. \u003cem\u003eArq Bras Med Vet Zootec\u003c/em\u003e \u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e72\u003c/em\u003e, 545\u0026ndash;552, doi:10.1590/1678-4162-11107.\u003c/li\u003e\n\u003cli\u003ePatbandha, T.K.; Mohanty, T.K.; Baithalu, R.K.; Kumaresan, A.; Bhakat, M.; Golher, D.; Lathwal, S.S.; Pathak, R. Evaluation of Rectal Temperature during the Post-Parturient Period in Crossbred Cows Reared under the Subtropical Climate. \u003cem\u003eIndian J Anim Res\u003c/em\u003e \u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e54\u003c/em\u003e, 110\u0026ndash;115, doi:10.18805/IJAR.B-3734.\u003c/li\u003e\n\u003cli\u003eBianca, W. Heat Tolerance in Cattle-Its Concept, Measurement and Dependence on Modifying Factors. \u003cem\u003eInt J Biometeorol\u003c/em\u003e \u003cstrong\u003e1961\u003c/strong\u003e, \u003cem\u003e5\u003c/em\u003e, 5\u0026ndash;30, doi:10.1007/BF02186917.\u003c/li\u003e\n\u003cli\u003eWang, N.; Zhou, C.; Basang, W.; Zhu, Y.; Wang, X.; Li, C.; Chen, L.; Zhou, X. Mechanisms by Which Mastitis Affects Reproduction in Dairy Cow: A Review. \u003cem\u003eReprod. Domest. Anim. \u003c/em\u003e\u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e56\u003c/em\u003e, 1165\u0026ndash;1175.\u003c/li\u003e\n\u003cli\u003eCunningham, J.G. Tratado de fisiologia veterin\u0026aacute;ria 2.ed. Rio de Janeiro: Guanabara Koogan, \u003cstrong\u003e1999\u003c/strong\u003e. 454p.\u003c/li\u003e\n\u003cli\u003eDi\u0026szlig;mann, L.; Heinicke, J.; Jensen, K.C.; Amon, T.; Hoffmann, G. How Should the Respiration Rate Be Counted in Cattle? \u003cem\u003eVet Res Commun\u003c/em\u003e \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e46\u003c/em\u003e, 1221\u0026ndash;1225, doi:10.1007/s11259-022-09984-7.\u003c/li\u003e\n\u003cli\u003eJoy, A.; Dunshea, F.R.; Leury, B.J.; Clarke, I.J.; Digiacomo, K.; Chauhan, S.S. Resilience of Small Ruminants to Climate Change and Increased Environmental Temperature: A Review. \u003cem\u003eAnimals\u003c/em\u003e \u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e10\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eGarner, J.B.; Douglas, M.L.; Williams, S.R.O.; Wales, W.J.; Marett, L.C.; Nguyen, T.T.T.; Reich, C.M.; Hayes, B.J. Genomic Selection Improves Heat Tolerance in Dairy Cattle. \u003cem\u003eSci Rep\u003c/em\u003e \u003cstrong\u003e2016\u003c/strong\u003e, \u003cem\u003e6\u003c/em\u003e, doi:10.1038/srep34114.\u003c/li\u003e\n\u003cli\u003eMeneses, J. A. M., Lopes de S\u0026aacute;, O. A. A., Coelho, C. F., Pereira, R. N., Batista, E. D., Ladeira, M. M., et al.. Effect of heat stress on ingestive, digestive, ruminal and physiological parameters of Nellore cattle feeding low- or high-energy diets. \u003cem\u003eLivest. Sci.\u003c/em\u003e \u003cstrong\u003e2021, \u003c/strong\u003e252, 104676. doi: 10.1016/j.livsci.2021.104676\u003c/li\u003e\n\u003cli\u003eYan, G.; Liu, K.; Hao, Z.; Li, H.; Shi, Z. Development and Evaluation of Thermal Models for Predicting Skin Temperature of Dairy Cattle. \u003cem\u003eComput Electron Agric\u003c/em\u003e \u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e188\u003c/em\u003e, doi:10.1016/j.compag.2021.106363.\u003c/li\u003e\n\u003cli\u003eLemos, M.J.; Braga, T.V.S.; Leite, D.K.V.H.; Galindo, E.L. O. Efeito Clim\u0026aacute;tico Sobre a Produ\u0026ccedil;\u0026atilde;o de Leite de Vacas Guzer\u0026aacute; Criadas Em Dois Ambientes Diferentes. \u003cem\u003eBraz. J. Anim. Environ. Res\u003c/em\u003e, \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e6\u003c/em\u003e, 1721\u0026ndash;1726, doi:10.34188/bjaerv6n2-062.\u003c/li\u003e\n\u003cli\u003eFontes, P.M.A.; Souza Junior, A. de; Carvalho, E.B. de; Gomes, L.P. de M.; Roier, E.C.R.; Moraes, R.F.F. de Compara\u0026ccedil;\u0026atilde;o Do Perfil Hematol\u0026oacute;gico e Bioqu\u0026iacute;mico de Novilhas Da Ra\u0026ccedil;a Girolando No Primeiro Ter\u0026ccedil;o de Gesta\u0026ccedil;\u0026atilde;o Com o Per\u0026iacute;odo de Anestro. \u003cem\u003eRev Fluminense de Extens\u0026atilde;o Universit\u0026aacute;ria\u003c/em\u003e \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e13\u003c/em\u003e, 06\u0026ndash;11.\u003c/li\u003e\n\u003cli\u003eFa\u0026ccedil;anha, D.A.E.; Chaves, D.F.; Morais, J.H.G.; Vasconcelos, \u0026Acirc;.M.; Costa, W.P.; Guilhermino, M.M. Methodological Tendencies of Adaptability Evaluation to Tropical Environment; \u003cstrong\u003e2013\u003c/strong\u003e;\u003c/li\u003e\n\u003cli\u003eVasconcelos, A.M. de; Albuquerque, C.C. de; Carvalho, J.F. de; Fa\u0026ccedil;anha, D.A.E.; Lima, F.R.G.; Silveira, R.M.F.; Ferreira, J. Adaptive Profile of Dairy Cows in a Tropical Region. \u003cem\u003eInt J Biometeorol\u003c/em\u003e \u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e64\u003c/em\u003e, 105\u0026ndash;113, doi:10.1007/s00484-019-01797-9.\u003c/li\u003e\n\u003cli\u003eOrtega, A.D.S.V.; Szab\u0026oacute;, C. \u003cem\u003eMetabolism and Endocrine Alterations in Growing and Finishing Pigs under Different Duration of Heat Stress-a Review\u003c/em\u003e; \u003cstrong\u003e2023\u003c/strong\u003e; Vol. 41;.\u003c/li\u003e\n\u003cli\u003eFletcher, G.F.; Balady, G.J.; Amsterdam, E.A.; Chaitman, B.; Eckel, R.; Fleg, J.; Froelicher, V.F.; Leon, A.S.; Pi\u0026ntilde;a, I.L.; Rodney, R.; et al. Exercise Standards for Testing and Training. \u003cem\u003eCirculation\u003c/em\u003e \u003cstrong\u003e2001\u003c/strong\u003e, \u003cem\u003e104\u003c/em\u003e, 1694\u0026ndash;1740, doi:10.1161/HC3901.095960.\u003c/li\u003e\n\u003cli\u003eCastro, B.A.D. de; Pires, I.M.; Andrade, L.S. de Cetose Subcl\u0026iacute;nica e Seu Impacto No Desempenho Reprodutivo de Vacas Leiteiras: Revis\u0026atilde;o de Literatura. \u003cem\u003eRev. Educ. Contin. Med. Vet. Zootec. CRMV-SP \u003c/em\u003e\u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e21\u003c/em\u003e, 2023, doi:10.36440/RECMVZ.V21.38359.\u003c/li\u003e\n\u003cli\u003eGomes, L.G.O.; Fodra, J.D.; Massabni, A.C. Hematologia Dos Vertebrados: A S\u0026eacute;rie Vermelha Do Sangue. \u003cem\u003eRevista Brasileira Multidisciplinar\u003c/em\u003e \u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e24\u003c/em\u003e, 226\u0026ndash;243.\u003c/li\u003e\n\u003cli\u003eMattosinho, R.; De Oliveira1; Sampaio, A.J.; Savioli De Almeida1, ; Balarin, M.; Regina, S.; Fiorato, C.; Andr\u0026eacute;2, ; Vasques, G.M.; Benedetti3, ; et al. Altera\u0026ccedil;\u0026otilde;es Hematol\u0026oacute;gicas e Bioqu\u0026iacute;mica S\u0026eacute;rica de Equinos Atletas. \u003cem\u003eRev. Ci\u0026ecirc;nc. Vet. Sa\u0026uacute;de P\u0026uacute;blica. \u003c/em\u003e\u003cstrong\u003e2017\u003c/strong\u003e, \u003cem\u003e4\u003c/em\u003e, 082\u0026ndash;091, doi:10.4025/REVCIVET.V4I1.35706.\u003c/li\u003e\n\u003cli\u003eTeja, K.V.; Sreedhar, S.; Chakravarthi, M.K. A Study on the Effect of Housing on Haematological Parameters of Nellore Lambs. \u003cem\u003eIndian Journal of Animal Production and Management\u003c/em\u003e \u003cstrong\u003e2024\u003c/strong\u003e, \u003cem\u003e37\u003c/em\u003e, 342\u0026ndash;349, doi:10.48165/ijapm.2023.37.4.13.\u003c/li\u003e\n\u003cli\u003eMorar, D.; Ciulan, V.; Simiz, F.; Moț, T. Effect of Heat Stress on Haematological Parameters in Dairy Cows. \u003cem\u003eLucrări ştiinţifice medicină veterinară\u003c/em\u003e \u003cstrong\u003e2018\u003c/strong\u003e, \u003cem\u003e61 (2)\u003c/em\u003e, 65\u0026ndash;70, doi:10.13140/RG.2.2.36806.22081.\u003c/li\u003e\n\u003cli\u003eCarvalho, A. de B.; Figueiredo, J.R.D.O.; Silva, N.I.S. da; Leite, R.F.; Ben\u0026iacute;cio, T.M.A.; Silva1, M.R. Da; Mascarenhas, N.M.H.; Fernandes, D.L.; Silva, J.A.P. da C.; Souza, B.B. de \u003cem\u003eInflu\u0026ecirc;ncia Dos Elementos Clim\u0026aacute;ticos Na Produ\u0026ccedil;\u0026atilde;o Animal Nos Tr\u0026oacute;picos\u003c/em\u003e; \u003cstrong\u003e2023\u003c/strong\u003e;\u003c/li\u003e\n\u003cli\u003eDal M\u0026aacute;s, F.E.; Debiage, R.R.; Schuh, B.R.F.; Guirro, E.C.B.D.P. \u003cem\u003eEstresse T\u0026eacute;rmico Em Bovinos Leiteiros-Impactos, Avalia\u0026ccedil;\u0026atilde;o e Medidas de Controle\u003c/em\u003e; \u003cstrong\u003e2020\u003c/strong\u003e;\u003c/li\u003e\n\u003cli\u003eValentim, J.K.; Bittencourt, T.M.; D\u0026rsquo;\u0026Aacute;villa Lima, H.J.; Moraleco, D.D.; Del Solar Velarde, J.M.; da Cruz, M.S.; Proc\u0026oacute;pio, D.P.; Lopes, Y.G.; Garcia, R.G. Thermoregulation of Broilers Fed with Diets Containing Dried Distillers Grain Levels. \u003cem\u003eRev. Acad. Ci\u0026ecirc;nc. \u003c/em\u003e\u003cem\u003eAnim.l\u003c/em\u003e \u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e18\u003c/em\u003e, doi:10.7213/2596-2868.2020.18002.\u003c/li\u003e\n\u003cli\u003eYu, M.F.; Zhao, X.M,; Cai, H; Yi, J.M.; Hua G.H. Dihydropyridine enhances the antioxidant capacities of lactating dairy cows under heat stress condition. \u003cem\u003eAnimals\u003c/em\u003e. \u003cstrong\u003e2020\u003c/strong\u003e, 10(10), e1812. doi: 10.3390/ani10101812\u003c/li\u003e\n\u003cli\u003eCalamari, L.; Lombardi, G.; Maianti, M.G.; Calegari, F.; Stefanini, L. Effect of energy supplementation and protein source on milk production of dairy cows in warm season. In:Proceeding XIV \u003cem\u003eASPA National Congress.\u003c/em\u003e \u003cstrong\u003e2001\u003c/strong\u003e, 123\u0026ndash;125.\u003c/li\u003e\n\u003cli\u003ePark, D.S.; Gu, B.-H.; Park, Y.J.; Joo, S.S.; Lee, S.-S.; Kim, S.-H.; Kim, E.T.; Kim, D.H.; Lee, S.S.; Lee, S.J.; et al. Dynamic Changes in Blood Immune Cell Composition and Function in Holstein and Jersey Steers in Response to Heat Stress. \u003cem\u003eCell Stress Chaperones\u003c/em\u003e \u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e26\u003c/em\u003e, 705\u0026ndash;720, doi:10.1007/s12192-021-01216-2/Published.\u003c/li\u003e\n\u003cli\u003eHooper, H.B.; Pieruzzi, P.A.P.; Lima, J.H.V. de; Anobi, B.T.; Ferreira, K.N.A.; Silva, R.R. da; Gurtler, G.D.; Santarosa, B.P.; Silva, P. dos S. Cromoterapia Associada \u0026agrave; Fitoterapia: Sa\u0026uacute;de Global e Controle de Parasitos de Bezerros de Aptid\u0026atilde;o Leiteira. \u003cem\u003eRevista Brasileira de Pr\u0026aacute;ticas Integrativas e Complementares em Sa\u0026uacute;de\u003c/em\u003e \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e2\u003c/em\u003e, 26\u0026ndash;43.\u003c/li\u003e\n\u003cli\u003eMoura, D.M.F. de; Santos, N.S.; Silva, J.C. de S.; Oliveira, A.R.N. de; Abdalla, A.L. Efeito Do Ambiente Sobre as Respostas Fisiol\u0026oacute;gicas de Caprinos Criados Em Clima Quente Recebendo Diferentes Fontes de Volumoso. \u003cem\u003eResearch, Society and Development\u003c/em\u003e \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e12\u003c/em\u003e, e16412842657, doi:10.33448/rsd-v12i8.42657.\u003c/li\u003e\n\u003cli\u003eHooper, H.B.; dos Santos Silva, P.; de Oliveira, S.A.; Merighe, G.K.F.; Negr\u0026atilde;o, J.A. Acute Heat Stress Induces Changes in Physiological and Cellular Responses in Saanen Goats. \u003cem\u003eInt J Biometeorol.\u003c/em\u003e \u003cstrong\u003e2018\u003c/strong\u003e, \u003cem\u003e62\u003c/em\u003e, 2257\u0026ndash;2265, doi:10.1007/s00484-018-1630-3.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Ambience, high temperatures, dairy cattle, heat stress","lastPublishedDoi":"10.21203/rs.3.rs-5932595/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5932595/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study evaluated heat tolerance and changes in biochemical and blood parameters in dairy cows under varying environmental and dietary conditions. Sixteen adult Holstein cows were used in four treatments: full sun with or without concentrate in the diet and shade with or without concentrate. Environmental parameters assessed included air temperature, relative humidity, and temperature-humidity index (THI). The cows' rectal temperature, respiratory rate, heat tolerance index, and blood parameters were also evaluated. Results showed that the cows experienced mild to severe heat stress, with the highest air temperature, humidity, and THI recorded in full sun during the afternoon (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Rectal temperature and heat tolerance index were also higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in full sun conditions, particularly in the afternoon. In shaded conditions with concentrate, respiratory rate did not differ between morning and afternoon (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Weight loss was greater (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in cows exposed to full sun. Cows in the sun with concentrate exhibited altered plasma glucose, triglyceride, and cholesterol levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Shaded cows had higher red blood cell counts but lower hemoglobin, hematocrit, mean corpuscular volume, and mean corpuscular hemoglobin levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Sun-exposed cows with concentrate had fewer monocytes, lymphocytes, and platelets but increased eosinophils (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Overall, cows kept in shade with concentrate demonstrated better heat tolerance and metabolic and hematological profiles.\u003c/p\u003e","manuscriptTitle":"Heat tolerance, biochemical, and hematological responses of Holstein cows under different feeding and environmental conditions in the semi-arid region of Brazil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-31 13:18:21","doi":"10.21203/rs.3.rs-5932595/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b484209c-2f56-44f3-b829-5532643b79d3","owner":[],"postedDate":"March 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-09T22:00:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-31 13:18:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5932595","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5932595","identity":"rs-5932595","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}