Effects of Breed, Diet and Sex on Thermo-physiology of Nigerian Goats

Effects of Breed, Diet and Sex on Thermo-physiology of Nigerian Goats | 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 Effects of Breed, Diet and Sex on Thermo-physiology of Nigerian Goats Iliya Mallam, Abdulmojeed Yakubu, Maikano Mohammed Ari, Ibrahim Suleiman Ari, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5746207/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 The understanding of complex interplay between breed, diet and sex on thermo-physiology is crucial for developing effective strategies to manage heat stress in Nigerian goat production. This experiment was conducted to study the effects of breed, diet, sex and their interactions on thermo-physiology response of Nigerian goats. A total of 36 weaner goats of two breeds (West African dwarf, n = 18; 9 males + 9 females) and Red Sokoto goats, n = 18; 9 males + 9 females) of about 3–4 months of age were used for the experiment. A 2×3×2 factorial experiment comprising 2 breeds, 3 diets groups and 2 sexes in a completely randomized design. Data collected were the rectal temperature, pulse rate, respiratory rate, maximum and minimum ambient temperature (°C) and relative humidity (%) and the average values were used to calculate temperature-humidity index and the heat stress index was also calculated. The fixed and interaction effects of data collected were analysed using Statistix Analytical software version 8.0 while excel package was used for graphical representation of the temperature-humidity index and significant means were separated using Duncan’s Multiple Range Test. The effect of breed on thermo-physiological indices of goats revealed that breed had significant (P < 0.05) effect on pulse rate and respiratory rate. Diet showed significant (P < 0.05) effect on rectal temperature (RT), pulse rate and respiratory rate. Male goats had higher (P < 0.05) thermo-physiology indices compared to females. It can be concluded that the experimental goats experienced little or moderate heat stress, which is crucial for maintaining productivity, growth, and overall well-being. Breed diet sex thermo-physiology Nigerian goats Figures Figure 1 INTRODUCTION Goat is one of the important farm animals that provide abundant meat, milk and income to the local people (Nguluma et al. 2022 ). Breed, diet, and sex effects on the thermo-physiology of Nigerian goats are crucial for optimizing their management and productivity, especially in the context of a changing climate. Physical therapy is important to prevent hyperthermia and maintain normal body temperature. When exposed to thermal stress, physiological parameters such as heart rate, respiration and rectal temperature respond immediately (Helal et al. 2010 ; Sanusi et al. 2011 ). Thermo-physiological parameters can help in monitoring the health status of goats, allowing for timely interventions when necessary (Mallam et al. 2024 ). Goats are integral to the livelihoods of many Nigerian farmers, examining thermal comfort, physiological responses can provide insights into their health (Mallam et al. 2024 ). Changes in respiration, heart rate and abdominal pressure have been widely used as markers of physiological adaptation to stress in small ruminants (Sharma et al. 2013). The circulatory system responds to changes in temperature and is an important function of the body's response to challenges (Ribeiro et al. 2018 ). Nigerian goats, particularly the West African Dwarf (WAD) and Red Sokoto (RS) breeds, exhibit distinct physiological responses to environmental stressors, which can significantly influence their health and productivity. Research indicates that breed differences play a pivotal role in thermo-physiological responses. WAD goats have been observed to maintain higher rectal temperatures and pulse rates compared to RS goats, suggesting a greater vulnerability to heat stress despite no significant differences in heat stress indices between the two breeds (Timveh et al. 2022 ). Additionally, sex-related variations have been noted, with male goats generally exhibiting more stress than females under similar conditions. This disparity may be attributed to hormonal differences, as female goats often show higher levels of thyroid stimulating hormone (TSH), which can affect their physiological responses to heat (Habibu et al. 2021 ). The broad objective of the study was to determine the effects of breed, diet and sex on thermo-physiology of Nigerian goats. MATERIALS AND METHODS The Study Area This experiment was carried out at the Livestock Teaching and Research Farm of the Animal Science Department, Faculty of Agriculture, Shabu-Lafia Campus, Nasarawa State University, Keffi. Lafia is located on latitude 08 0 35˝ and longitude 08 0 33˝ (Ovimap, 2023 ). It is geographically located in the Guinea Savanna Zone of North Central Nigeria. It has mean maximum monthly temperature of 35.06°C and mean minimum monthly temperature of 20.16°C with a mean monthly relative humidity of 74% and the annual rainfall is about 168.90 mm (NiMet, 2023). Sources of Experimental Materials The grass ( Digitaria smutsii ) was sourced from the National Animal Production Research Institute (NAPRI)/Ahmadu Bello University, Shika, Zaria, Nigeria while the two legumes (groundnut haulms and cowpea husk) were sourced from farms after harvest in Lafia, Nasarawa State. After collection, the haulms were brought to the Faculty Livestock Farm, where they were shade-dried and debris was removed before being fed to the experimental goats. Experimental Diets The diet groups included 100% Digitaria smutsii (diet 1), 50% Digitaria smutsii + 50% groundnut haulms (diet 2) and 50% Digitaria + 50% cowpea husk (diet 3). Experimental Design A 2×3×2 factorial experiment comprising 2 breeds West African dwarf (WAD) and Red Sokoto (RS) goats, 3 diets groups (100% Digitaria smutsii , 50% Digitaria smutsii + 50% groundnut haulms and 50% Digitaria smutsii + 50% cowpea husk) and 2 sexes (Male and Female) in a Completely Randomized Design (CRD) was used. There were six treatments (T1 = WAD100% Digitaria smutsii , T2 = WAD50% Digitaria smutsii + 50% groundnut haulms, T3 = WAD50% Digitaria smutsii + 50% cowpea husk, T4 = RS100% Digitaria smutsii , T5 = RS50% Digitaria smutsii + 50% groundnut haulms, T6 = RS50% Digitaria + 50% cowpea husk) which were replicated three times with two goats (male and female) in each replicate. Experimental Goats and Management Physically sound goats were randomly sourced from reputable local farms in Lafia, Nasarawa State. A total of 36 weaner goats of two breeds (West African dwarf, n = 18; 9 males + 9 females) and Red Sokoto goats, n = 18; 9 males + 9 females) of about 3–4 months of age were sourced from farmers for the experiment. Upon arrival, the experimental goats were allowed to acclimatize for a period of 2 weeks during which they were dewormed against parasites and vaccinated against Peste des petits ruminants (PPR). The experimental goats were randomly allotted into the six treatments groups. Diets and water were given ad-libitum and any goat with any sign of disease was treated by a professional (Veterinarian). Other routine management practices were adopted throughout the experimental period according to (Timveh et al. 2022 ). In conduct of the research, there was a strict adherence to the International Ethical Guidelines for Biomedical research (CIOMS, 2002 ) involving Human Subjects and the Global code of conduct for research in resource-poor settings following the Convention on Biological and Declaration of Helsinki. The Research also follows Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines as described by du Sert et al. ( 2018 ). Data Collection and Measurements Proximate analysis of the experimental materials Proximate analysis of the experimental materials was conducted at the Biochemistry Laboratory, National Animal Production Research Institute (NAPRI)/Ahmadu Bello University, Zaria, Nigeria using the methods proposed by (AOAC 2008 ) for the determination of their nutrients’ composition. Table 1 Proximate composition of the experimental materials Experimental materials %DM %Ash %EE %CF %CP %NDF %ADF DS 94.08 6.76 1.10 34.08 13.06 63.46 34.67 GH 92.16 8.38 6.71 20.94 25.19 38.09 31.18 CH 93.88 6.36 19.18 25.50 23.13 36.92 15.89 DS = Digitaria smutsii , GH = Groundnut haulm, CH = Cowpea husk, DM = Dry matter, EE = Ether extract, CF = Crude fibre, CP = Crude protein, NDF = Neutral detergent fibre, ADF = Acid detergent fibre. Meteorological Parameters The meteorological data collected were maximum and minimum ambient temperature (°C) and relative humidity (%) and the average values were used for analysis. The records were obtained from the Meteorological Unit of the Nigerian Meteorological Agency, Lafia, located about 200 meters away from the site of the experiment. The temperature humidity index (THI) was used to evaluate the level of heat stress induced by the environment and was calculated using the equation reported by (Ravagnolo et al. 2000 ) as follows: THI = (1.8 × T + 32) - {(0.55–0.0055 × RH) × (1.8 × T − 26)} Where; T– ambient temperature (°C); RH– relative humidity (%). Thermo-physiology Data Collected The thermo-physiology data collected were rectal temperature (RT), pulse rate (PR) and respiratory rate (RR) while the heat stress index (HSI) was calculated. A digital thermometer was used to take each animal's rectal temperature. After disinfecting the sensory tip of the digital thermometer, it was placed into the rectum. This was taken out following the alarm signal and the displayed body temperature was recorded. Pulse rate was determined by counting the beats of the heart using a stethoscope per unit time, and expressed in number of beats per minute. This was achieved by positioning the stethoscope on the left side of the chest. The respiratory rate was done by counting the flanks' movements around the lower back area per minute using a stopwatch. The RT, PR, and RR were taken between the hours of 6:30 am and 9:30 am in the morning and 1:00 pm and 3:00 pm in the afternoon every day. Heat stress index (HSI) was calculated as: HSI = RR/PR × NP/NR Where; RR = actual respiratory rate; PR = actual pulse rate; NP = normal pulse rate; NR = normal respiratory rate. In both goat breeds, the basal reference value for NR was 30 breaths/minute while that of NP was 90 beats/minute (Yakubu et al. 2017b ). Statistical Analysis Data collected were subjected to analysis of variance (ANOVA) to test the fixed effect of breed, diet and sex as well as their interactions on thermo-physiology response. Significant differences between treatments were compared using the Duncan multiple range test option of Statistix Analytical software, file version 8.0 while excel package was used for graphical representation of the temperature-humidity index (Fig. 1 .) The mathematical model employed was: Y ijkl = µ + A i + B j +C k + (AB) ij + (AC) ik + (BC) jk +(ABC) ijk + e ijkl Where; Y ijkl = individual observation, µ = general or overall mean, A i = effect of factor A (breed) (A i =WAD, RS) B j = effect of factor B (diet) (j = 100% DS , 50%DS + 50%GH, 50%DS + 50%CH) C k = effect of factor C (sex) (k = Male, Female) (AB) ij = effect of interaction between A i and B j, (AC) ik = effect of interaction between A i and C k (BC) jk = effect of interaction between be B j and C k (ABC) ijk =effect of interaction between A i , B j and C k e ijkl = experimental error. RESULTS Temperature-Humidity Index (THI) During the Study Period Temperature-Humidity Index (THI) during the study period is presented in Fig. 1 . The results showed that higher THI value (71.04) was observed in December and the least value (70.07) was observed in January. Effect of breed on thermo-physiology indices of goats The effect of breed on thermo-physiology indices of goats (WAD) and (RS) goats is presented in Table 2 . The results revealed that breed had significant (P 0.05) different in terms of rectal temperature (RT) and heat stress index (HSI). The PR and RR were higher in Red Sokoto (RS) goats than their West African dwarf (WAD) counterparts. Effect of diet on thermo-physiology indices of goats Table 3 presents the effect of diet on thermo-physiology indices of goats. The results showed that diet had significant (P 0.05) influence on heat stress index (HSI). The RT was higher in goats fed 50%DS + 50GH diet group but statistically similar to goats fed 100%DS. For PR and RR, goats fed 100%DS had significantly (P < 0.05) higher values than those fed 50%DS + 50%GH and 50%DS + 50%CH. The least value for PR was observed in goats fed 50%DS + 50CH but statistically similar to those fed 50%DS + 50%GH while the least value for RR was found in goats fed 50%DS + 50%GH though statistically similar to goats fed 50%DS + 50%CH. Meanwhile, the diet had no significant (P > 0.05) effect on heat stress index (HSI) but higher numerical value was observed in goats fed 50%DS + 50%CH and the HSI ranged from 1.24 ± 0.01 to 1.26 ± 0.03. Effect of sex on thermo-physiology indices of goats Table 4 shows the effect of sex on thermo-physiology indices of goats. The results observed revealed that sex had significant (P < 0.05) effect in all the thermo-physiology indices of goats. The results showed that male goats had significantly (P < 0.05) higher values than their female counterparts in all the parameters. The rectal temperature (RT), pulse rate (PR), respiratory rate (RR) and heat stress index (HSI) ranges from 37.50 ± 0.05–38.29 ± 0.04, 76.53 ± 0.39–78.46 ± 0.34, 31.40 ± 0.19–32.90 ± 0.15 and 1.24 ± 0.03–1.26 ± 0.02, respectively. Table 2 Effect of breed on thermo-physiology indices of goats Parameters Breed WAD RS P-value Ref. RT ( o C) 37.88 ± 0.05 37.96 ± 0.04 0.2133 * 38–41 (Bello et al., 2016 ) PR (beats/minute) 75.86 ± 0.38 b 79.40 ± 0.34 a 0.0000 * 70–102 (Bello et al., 2016 ) RR(breaths/minute) 31.42 ± 0.18 b 33.04 ± 0.15 a 0.0000 * 15–30 (Bello et al., 2016 ) HSI 1.24 ± 0.03 1.25 ± 0.03 0.4324 NS NA ab Means in the same row bearing different superscripts differ significantly (P < 0.05), WAD = West African dwarf, RS = Red Sokoto, RT = Rectal temperature, PR = Pulse rate, RR = Respiratory rate, HSI = Heat stress index, NA = Not available, WAD = West African dwarf, RS = Red Sokoto, *= Significant at 0.05, NS = Not significant, o C = Degree Celsius, Ref.= Reference values from literature Table 3 Effect of diet on thermo-physiology indices of goats Parameters Diet 100%DS 50%DS + 50 % GH 50%DS + 50 % CH P-value Ref. RT( o C) 37.98 ± 0.06 a 38.06 ± 0.05 a 37.71 ± 0.07 b 0.0001 * 38–41 (Bello et al., 2016 ) PR(beats/minute) 78.49 ± 0.44 a 77.09 ± 0.51 b 76.96 ± 0.43 b 0.0276 * 70–102 (Bello et al., 2016 ) RR (breaths/minute) 32.63 ± 0.21 a 31.77 ± 0.23 b 32.14 ± 0.18 ab 0.0142 * 15–30 (Bello et al., 2016 ) HSI 1.25 ± 0.03 1.24 ± 0.01 1.26 ± 0.03 0.1889 NS NA ab Means in the same row bearing different superscripts differ significantly (P < 0.05),WAD = West African dwarf, RS = Red Sokoto, DS = Digitaria smutsii, GH = Groundnut haulm, CH = Cowpea husk, RT = Rectal temperature, PR = Pulse rate, RR = Respiratory rate, HSI = Heat stress index, o C = Degree Celsius, *= Significant at 0.05, NS = Not significant, Ref.= Reference values from literature Table 4 Effect of sex on thermo-physiology indices of goats Parameters Sex Male Female P-value Ref. RT ( o C) 38.29 ± 0.04 a 37.50 ± 0.05 b 0.0000 * 38–41 (Bello et al., 2016 ) PR (beats/minute) 78.46 ± 0.34 a 76.53 ± 0.39 b 0.0002 * 70–102 (Bello et al., 2016 ) RR (breaths/minute) 32.90 ± 0.15 a 31.40 ± 0.19 b 0.0000 * 15–30 (Bello et al., 2016 ) HSI 1.26 ± 0.03 a 1.24 ± 0.03 b 0.0004 * NA ab Means in the same row bearing different superscripts differ significantly (P < 0.05), o C= Degree Celsius, *= Significant at 0.05, RT = Rectal temperature, PR = Pulse rate, RR = Respiratory rate, HSI = Heat stress index, NA = Not available, Ref.= Reference values from literature Interactions effect between breed × diet on thermo-physiology indices of goats Interactions effect between breed × diet on thermo-physiology indices of goats are presented in Table 5 . The results observed revealed that breed × diet interactive effect had significant (P < 0.05) effect in all the thermo-physiological parameters. For rectal temperature (RT), WAD×50%DS + 50%GH had significantly (P < 0.05) higher value (38.29 ± 0.08 o C) followed by RS×50%DS + 50%CH (38.06 ± 0.09 o C) but statistically similar to RS×100%DS (38.01 ± 0.08 o C) and the least was observed in WAD×50%DS + 50%CH (37.44 ± 0.08 o C). For pulse rate (PR), the RS×100%DS had significantly ((P < 0.05) higher value (83.11 ± 0.59 beats/minute) followed by RS×50%DS + 50%CH (77.97 ± 0.67 beats/minute) but similar to WAD×50%DS + 50%GH (77.81 ± 0.62 beats/minute), WAD×50%DS + 50%CH (76.36 ± 0.63 beats/minute) and RS ×50%DS + 50%GH (76.36 ± 0.63 beats/minute) and the least was found in WAD×100%DS (73.71 ± 0.59 beats/minute) and similar trend was observed for respiratory rate (RR). The heat stress index in WAD ×100%DS and RS×50%DS + 50%GH were statistically same and the least heat stress index was found in WAD ×50%DS + 50%GH. Interactions effect between breed × sex on thermo-physiology indices of goats Interactions effect between breed × sex on thermo-physiology indices of goats on thermo-physiological indices of goats is shown in Table 6. The results revealed that breed × sex had significant (P < 0.05) effect on rectal temperature (RT) with WAD × male had significantly (P 0.05) effect on pulse rate (PR), respiratory rate (RR) and heat stress index (HSI). However, the highest numerical value for PR, RR and HSI were found in RS× male and the least was found in WAD ×female for PR and RR while the least for HSI was found in RS ×female. Interactions effect between diet × sex on thermo-physiology indices of goats Table 7 indicates the interactions effect between diet × sex on thermo-physiology indices of goats. The observed results obtained indicated that diet × sex had significant (P < 0.05) effect in all the thermo-physiological parameters. For rectal temperature, 50%DS + 50%GH × male had significantly (P < 0.05) higher value but statistically to 100%DS × male and 50%DS + 50%CH × male and the least value was observed in 50%DS + 50%CH × female though statistical to with 100%DS × female and 50%DS + 50%GH × female. For pulse rate (PR), the 100%DS × male had significantly (P < 0.05) higher value (80.94 ± 0.55 beats/minute) followed by 50%DS + 50%CH × female (77.50 ± 0.55 beats/minute) but statistically similar to 50%DS + 50%GH × male 50%DS + 50%GH × female and 50%DS + 50%CH × male and the least PR was found in 100%DS × female. The respiratory rate (RR) followed the same trend with PR. The heat stress index (HSI) was found to be significantly (P < 0.05) higher in 100%DS ×male which was statistically similar to 100%DS ×female, 50%DS + 50%GH × male, 50%DS + 50%CH ×male and, 50%DS + 50%CH ×female and the least HSI was found in 50%DS + 50%GH ×female (1.20 ± 0.01). Interactions effect between breed × diet ×sex on thermo-physiology indices of goats Interactions effect between breed × diet × sex interactive on thermo-physiology indices of goats is represented in Table 8 . The results of breed × diet × sex had no significant (P < 0.05) effect in all the thermo-physiology parameters of goats. However, the highest numerical value for rectal temperature (RT), pulse rate (PR), respiratory rate (RR) and heat stress index (HSI) were obtained in RS×50%DS + 50%CH×female, RS×100%DS ×female, RS×100%DS ×male, RS×50%DS + 50%GH×male, respectively and the least were found in WAD ×50%DS + 50%CH×female, WAD×100%DS× female, WAD ×100%DS×female and WAD×50%DS + 50%GH×female, respectively. Table 5 Interaction effect between breed × diet on thermo-physiology indices of goats Parameters WAD RS 100%DS 50%DS + 50 % GH 50%DS + 50 % CH 100%DS 50%DS + 50 % GH 50%DS + 50 % CH P-value Ref. RT( o C) 37.95 ± 0.08 b 38.29 ± 0.08 a 37.44 ± 0.08 c 38.01 ± 0.08 ab 37.82 ± 0.09 b 38.06 ± 0.09 ab 0.0000 * 38–41 (Bello et al., 2016 ) PR(beats/min) 73.71 ± 0.59 c 77.81 ± 0.62 b 76.36 ± 0.63 b 83.11 ± 0.59 a 76.36 ± 0.63 b 77.97 ± 0.67 b 0.0000 * 70–102 (Bello et al., 2016 ) RR(breaths/min) 31.11 ± 0.28 c 31.34 ± 0.29 c 31.79 ± 0.27 bc 34.09 ± 0.32 a 32.23 ± 0.30 bc 32.58 ± 0.32 b 0.0001 * 15–30 (Bello et al., 2016 ) HIS 1.27 ± 0.01 a 1.21 ± 0.01 c 1.26 ± 0.01 ab 1.23 ± 0.01 bc 1.27 ± 0.01 a 1.26 ± 0.01 ab 0.0000 * NA abc Means in the same row bearing different superscripts differ significantly (P < 0.05),WAD = West African dwarf, RS = Red Sokoto, DS = Digitaria smutsii, GH = Groundnut haulm, CH = Cowpea husk, RT = Rectal temperature, PR = Pulse rate, RR = Respiratory rate, HSI = Heat stress index, NA = Not available, Ref.= Reference values from literature, o C = Degree Celsius, *= Significant at 0.05, NS = Not significant Table 6: Interaction effect between breed × sex on thermo-physiology indices of goats Parameters WAD RS Male Female Male Female P-value Ref. RT( o C) 38.45 ± 0.06 a 37.33 ± 0.06 d 38.14 ± 0.06 b 37.72 ± 0.07 c 0.0000 * 38–41(Bello et al., 2016 ) PR(beats/min) 77.11 ± 0.51 74.66 ± 0.50 79.72 ± 0.49 78.98 ± 0.57 0.2978 NS 70–102 (Bello et al., 2016 ) RR(breaths/min) 32.20 ± 0.23 30.67 ± 0.23 33.56 ± 0.22 32.35 ± 0.26 0.4914 NS 15–30 (Bello et al., 2016 ) HSI 1.26 ± 0.03 1.24 ± 0.01 1.27 ± 0.03 1.23 ± 0.02 0.2117 NS NA abcd Means in the same row bearing different superscripts differ significantly (P < 0.05),WAD = West African dwarf, RS = Red Sokoto, RT = Rectal temperature, PR = Pulse rate, RR = Respiratory rate, HSI = Heat stress index, NA = Not available,, o C= Degree Celsius, *= Significant at 0.05, NS = Not significant, Ref.= Reference values from literature. Table 7 Interaction effect between diet × sex on thermo-physiology indices of goats Parameters 100%DS 50%DS + 50%GH 50%DS + 50%CH Male Female Male Female Male Female P-value Ref. RT( o C) 38.18 ± 0.07 a 37.67 ± 0.09 b 38.38 ± 0.07 a 37.44 ± 0.09 b 38.32 ± 0.10 a 37.41 ± 0.07 b 0.0013 * 38–41(Bello et al., 2016 ) PR(beats/min) 80.94 ± 0.55 a 74.73 ± 0.68 c 77.19 ± 0.56 bc 76.93 ± 0.78 bc 75.84 ± 0.79 bc 77.50 ± 0.55 b 0.0000 * 70–102 (Bello et al., 2016 ) RR(breaths/min) 34.05 ± 0.25 a 30.45 ± 0.31 c 32.32 ± 0.26 b 30.74 ± 0.35 c 31.70 ± 0.36 bc 32.34 ± 0.25 b 0.0000 * 15–30 (Bello et al., 2016 ) HIS 1.27 ± 0.01 a 1.23 ± 0.01 ab 1.26 ± 0.01 a 1.20 ± 0.01 b 1.26 ± 0.01 a 1.26 ± 0.01 a 0.0086 * NA abc Means in the same row bearing different superscripts differ significantly (P < 0.05), DS = Digitaria smutsii , GH = Groundnut haulm, CH = Cowpea husk, RT = Rectal temperature, PR = Pulse rate, RR = Respiratory rate, HSI = Heat stress index, NA = Not available, o C = Degree Celsius,*= Significant at 0.05, Ref.= Reference values from literature. Table 8 Interaction effect between breed × diet × sex on thermo-physiology indices of goats Parameters Breed Diet Sex RT( o C) PR(beats/min) RR(breaths/min) HSI WAD 100%DS M 38.29 ± 0.11 7 6.73 ± 0.08 32.92 ± 0.37 1.29 ± 0.01 F 37.55 ± 11 70.26 ± 0.86 29.04 ± 0.39 1.25 ± 0.01 50%DS + 50%GH M 38.75 ± 0.10 77.80 ± 0.76 31.77 ± 0.35 1.23 ± 0.01 F 37.48 ± 0.13 77.83 ± 1.02 30.56 ± 0.48 1.17 ± 0.01 50%DS + 50%CH M 38.15 ± 0.13 76.49 ± 1.02 31.82 ± 0.47 1.25 ± 0.02 F 37.11 ± 0.09 76.07 ± 0.69 31.79 ± 0.33 1.26 ± 0.01 RS 100%DS M 38.09 ± 0.09 84.18 ± 0.70 34.91 ± 0.33 1.25 ± 0.01 F 37.84 ± 0.13 80.89 ± 1.01 32.41 ± 0.47 1.20 ± 0.02 50%DS + 50%GH M 38.02 ± 0.10 76.58 ± 1.02 32.86 ± 0.35 1.30 ± 0.01 F 37.40 ± 0.14 75.93 ± 1.08 30.94 ± 0.50 1.23 ± 0.02 50%DS + 50%CH M 38.54 ± 0.14 75.02 ± 1.14 31.55 ± 0.53 1.27 ± 0.02 F 37.83 ± 0.11 79.46 ± 0.81 33.11 ± 0.38 1.25 ± 0.01 P-value 0.6428 NS 0.0919 NS 0.1059 NS 0.8636 Ref. 38–41(Bello et al., 2016 ) 70–102 (Bello et al., 2016 ) 15–30 (Bello et al., 2016 ) NA WAD = West African dwarf, RS = Red Sokoto, DS = Digitaria smutsii , GH = Groundnut haulm, CH = Cowpea husk, RT = Rectal temperature, PR = Pulse rate, RR = Respiratory rate, HSI = Heat stress index, NA = Not available, o C= Degree Celsius, M = Male, F = Female, *= Significant at 0.05, NS = Not significant, Ref. = Reference values from literature DISCUSSION In this study, THI in December and January were lower than those reported by (Timveh et al. 2022 ) who reported 79.68 in March, 81.31 in April and 80.07 in May. The variation could be due to differences in month and year as thes affect the THI value. The heat stress range for goats, based on the temperature humidity index (THI), is as follows: comfortable conditions are when the THI is less than or equal to 72; mild stress occurs when the THI ranges from 73 to 78; and severe stress is experienced when the THI is greater than or equal to 80. THI values exceeding 80 are categorized as moderate heat stress (MHS) for goats (Koluman-Darcan et al. 2017 ). This means the goats used in this study were within their comfort zone during the experiment. The values observed in the study for rectal temperature across the breeds were within the range reported by (Timveh et al. 2022 ) who reported 38.93 ± 0.10 o C for West African dwarf and 38.59 ± 0.10 o C for Red Sokoto goats and that breed had no effect on heat stress index as observed in the present study. However, the pulse rates observed in this study were higher than the values reported by (Timveh et al. 2022 ) but reported higher respiratory rate than the one observed in this study. This may be due to changes in the age of the animals, season, and other environmental factors during the study. Parturition had no significant effect on rectal temperature, similar to the findings of (Yousif 2019 ) who reported no significant difference in rectal temperature in the Nubian goat. The increased pressure in the RS goats may be due to increased blood flow from the core to the skin surface, allowing more heat to pass through the skin. The similar temperature profiles found in the WAD and RS goats support studies that show that domestic goats are one of the best adapted to extreme climates compared to other ruminant species. Respiratory rate serves as a dependable measure of heat load and is an indicator of thermal stress (Alam et al. 2011 ). The basal reference respiratory rate is 15–30 breaths/minute in goats Robertshaw and Dmi'el ( 1983 ). So, measuring the rate of breathing and determining if an animal is panting, along with assessing the level of heat stress based on the panting rate (breaths per minute) in different climates (low: 40–60, medium: 60–80, high: 80–120, and severe heat stress: >200) appears to be the most accessible and easiest method for evaluating the impact of heat stress on animals under extreme conditions. Therefore, the values in this study showed that they were slightly above the normal range and little heat stress. The rectal temperature values obtained in this study were within the range of 38.40 ± 0.36 0 C to 39.30 ± 0.67 0 C as earlier reported by (Ajayi et al. 2010 ; Sanusi et al. 2011 ) for WAD goats. The higher temperatures observed for animals on diets 50%DS + 50%GH and 100%D led to increase in temperature may be a result of the heat generated during the breakdown of the feeds. This is in agreement with the finding of (Hicks et al. 2001 ) who earlier reported that the rumen temperature is the effect of body temperature and may be used to predict diseases or heat stress. Increased respiration in goats fed 100% DS is a clear indication that respiration increases with temperature (environment) and weight during the goat maturation cycle to establish homeostasis (Singh et al. 2002 ). However, the findings were previously reported by (Sanusi et al. 2011 ) for WAD goats. Pulse rate was significantly affected by dietary intake (P < 0.05) of 100%DS (78.49 ± 0.42 beats/minute) compared to diets 50%DS + 50%GH (77.09 ± 0.51 beats/min) and 50%DS + 50%CH (76.96 ± 0.43 beats/min). This heart rate change was reported by (Ogebe et al.1996) that speed at which the heart pumps blood throughout the body, hence the pumping rate of blood in goats on 100% DS diet was higher than diets 50%DS + 50%GH and 50%DS + 50%CH. Thermal stress index values ​​of goats fed 100% DS, 50% DS + 50%GH and 50%DS + 50%CH diets were found to be 1.25 ± 0.03, 1.24 ± 0.01 and 1.26 ± 0.03, respectively. The highest heat stress value was obtained when fed 50% DS + 50% CH diet, though not significantly different with others, the results were in line with (Okoruwa et al. 2013 ), who found that temperature and pulse rate are utilized in assessing the physiological condition and adaptability of domestic animals in challenging situations. The influence of sex on thermo-physiology indices in the present study is in agreement with the findings of (Timveh et al. 2022 ) who reported that sex affected pulse rate and heat stress index. The authors reported that pulse rate was higher in a female (54.70 ± 0.24 versus 53.73 ± 0.24) which varies from the present study in which pulse rate in male was higher than their female counterparts in the study. Meanwhile, the higher heat stress index in male in the present study is similar with the finding of (Timveh et al. 2022 ) who reported higher heat stress index in males (2.35 ± 0.03) than female goats (2.26 ± 0.03). The male goats had higher rectal temperature, pulse rate, respiratory rate and male goats showed to be more stressed based on heat stress index. This agrees with the finding of (Facanha et al. 2012 ) who reported that goats subjected to heat stress were found to have an increased respiratory rate, which is a dependable indicator of heat load and thermal stress (Okoruwa et al. 2013 ). Female small ruminants seem to handle heat stress better than their male counterparts, even though both sexes are affected by it as reported by (Schoenian 2019 ). According to (Helal et al. 2010 ; Sanusi et al. 2011 ) have indicated that in harsh environments, rectal temperature, respiratory rate, and blood indices are the most effective thermo-physiological parameters for objectively monitoring animal welfare. As observed in the present study, the highest rectal temperature in WAD×50%DS + 50%GH could signify the presence of diseases such as Peste des Petits Ruminants (PPR) or other infectious diseases prevalent in Nigeria. These diseases can cause fever as one of the primary symptoms. The significantly high pulse rate (PR) and respiratory rate (RR) in RS×100%DS over others could mean that the Red Sokoto goats fed 100% Digitaria smutsii may have different nutritional content compared to cowpea and groundnut husk and if it lacks essential nutrients or is imbalanced, goats may experience physiological stress, leading to increased heart and breathing rates. Other possible reason could be that the digestibility of Digitaria smutsii might be lower than that of cowpea and groundnut husk (Wulandari et al. 2020 ). Poor digestibility can result in longer retention time in the digestive system, leading to discomfort and increased metabolic activity, which can manifest as higher pulse and respiratory rates as observed in the present study. Furthermore, Digitaria smutsii may have higher fibre content, which could lead to increased fermentation in the rumen (Sani et al. 2023 ). This fermentation process produces gases and heat as by-products, which can increase metabolic activity and subsequently raise pulse and respiratory rates. The breed × sex relationship in this study is similar to the relationship suggested by (Timveh et al. 2022 ) who reported that there was no significant difference in rectal temperature, pulse rate, respiratory rate, and body temperature between animals and gender. In contrast, the current study found that breed × sex had an effect on rectal temperature, with WAD males experiencing the highest rectal temperature. This suggests that the animal will experience discomfort and distress, which will have an impact on their overall well-being, behaviour, and productivity in terms of growth, reproduction, or performance. The no significant difference in the present study in PR, RR and HSI implies that both male and female goats across different breeds have similar thermoregulatory capabilities. This uniformity in adaptation can be advantageous in environments with fluctuating temperatures as it ensures that goats of different breeds and sexes can cope similarly with heat or cold stress. Also, the lack of significant differences may indicate that thermoregulatory mechanisms are highly conserved among different goat breeds and sexes. This suggests a level of genetic resilience within the goat population, enabling them to maintain stable body temperature regardless of breed or sex differences (Daramola et al. 2021 ). The significantly higher rectal temperature, pulse rate, respiratory rate (RR) and heat stress index in 100%DS ×male over others could mean that the male goats fed 100% Digitaria smutsii may have different nutritional content compared to cowpea and groundnut husk and if it lacks essential nutrients or is imbalanced, goats may experience physiological stress, leading to increased heart and breathing rates as well as heat stress. Also, it could be that the digestibility of Digitaria smutsii might be lower than that of cowpea and groundnut husk (Wulandari et al. 2020 ). Poor digestibility can result in longer retention time in the digestive system, leading to discomfort and increased metabolic activity, which can manifest as higher pulse and respiratory rates as observed in the present study. Furthermore, Digitaria smutsii may have higher fibre content, which could lead to increased fermentation in the rumen (Sani et al. 2023 ). This fermentation process produces gases and heat as by-products, which can increase metabolic activity and subsequently raise pulse rate, rectal temperature, and respiratory rates and heat stress as observed in the present study. However, the lower heat stress index in 50%DS + 50%GH × female could be that groundnut haulms may contain components that have a calming or stress-reducing effect which in turn can lead to lower heat stress index (Chimmad et al. 2022 ). The no difference could be that thermoregulatory mechanisms are highly conserved among different goat breeds fed different diets and of different sexes. This suggests a level of genetic resilience within the goat population, enabling them to maintain stable body temperature regardless of breed, diet and sex differences (Daramola et al. 2021 ). The breed × diet ×sex interaction effect in the present study showed no significant effect in all the thermo-physiology indices and this is same to the finding of (Timveh et al. 2022 ) who reported no significant difference between breed × sex on rectal temperature, pulse rate, respiratory rate and heat stress index. The possible reason for no variation controlled environmental conditions where factors such as temperature, humidity, and ventilation were consistent for all the breeds, diets and both sexes of goats. When environmental conditions are standardized, it can minimize the impact of external factors on physiological parameters. Also, all the goats in the study received similar diets. Therefore, breed or sex, there may not have been significant differences in physiological responses. Also, sometimes, even if there are differences between groups, the sample size might not be large enough to detect those differences statistically. CONCLUSION AND RECOMMENDATIONS It can be concluded that the goats are effectively managing their thermal environment and are likely in good health and the goats experienced little or moderate heat stress, which is crucial for maintaining productivity, growth, and overall well-being. When considering management strategies or interventions related to pulse rate and respiratory rate, factors such as breed and diet should be taken into account. Any of the breeds and diets is recommended since the two factors were not influenced by heat stress index (HSI). However, regards sex, female goats had ability to handle heat stress than their male counterparts and are therefore recommended. Declarations Authors’ contribution Conceptualization and design of the experiment: Mallam, Iliya; Yakubu, Abdulmojeed;Ari, Maikano Mohammed; Musa, Ibrahim Suleiman and Achi, Neyu Patrick Material preparation: Mallam, Iliya; Yakubu, Abdulmojeed;Ari, Maikano Mohammed; Musa, Ibrahim Suleiman and Achi, Neyu Patrick Data collection and analysis: Mallam, Iliya and Yakubu, Abdulmojeed The first draft of the manuscript was written by: Mallam, Iliya and Yakubu, Abdulmojeed All authors read and approved the final manuscript. Acknowledgments The authors sincerely thank the Tertiary Education Trust Funds (TETFund), Nigeria through local Ph.D. grant awarded by the Kaduna State University, Kaduna for the fund. Data availability Data will be made available on request. Funding This project was funded by the TETFund, Nigeria through local Ph.D. grant awarded by the Kaduna State University, Kaduna. Ethics declarations Animal ethics statement with an approval number This research work was carried out according to the ethical guideline and obtained ethics approval from the Committee for Ethical and Responsible Conduct of Research (ABUACAUC/2017/004) of National Animal Production Research Institute (NAPRI), Zaria. Consent to participate Not applicable. Consent for publication Not applicable. Conflict of interest The authors declare that they have no competing interests. Electronic supplementary material This will be made available on request. References Ajayi DA, Adewumi MK, Okunlola OO (2010) Physiological response of WAD sheep to ambient environmental temperature changes in humid tropics of South West Nigeria. Proceedings of 35th Conference of Nigeria Society for Animal Production , University of Ibadan Nigeria Pp. 110–112 Alam MM, Hashem MA, Rahman MM, Hossain MM, Haque MR, Sobhan Z, Islam MS (2011) Effect of heat stress on behavior, physiological and blood parameters of goat. 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J Environ Ecol 37:634–639 CIOMS (2002) International Ethical Guidelines for Biomedical Research Involving Human Subjects prepared by the Council for International Organizations of Medical Sciences (CIOMS) in Collaboration with the World Health Organization (WHO), Geneva p.62 Daramola JO, Abioja MO, Iyasere OS, Oke OE, Majekodunmi BC, Logunleko MO, Adekunle EO, Nwosu EU, Smith OF, James IJ, Williams TJ, Abiona JA (2021) The resilience of dwarf goats to environmental stress: A review . Small Ruminant Res 205:106534. https://doi.org/10.1016/j.smallrumres.2021.106534 du Sert NP, Hurst V, Ahluwalia A, Alam S, Altman DG, Avey MT, Baker M, Browne W, Clark A, Cuthill IC, Dirnagl U, Emerson M, Garner P, Howells DW, Karp NA, MacCallum CJ, Macleod M, Petersen O, Rawle F, Reynolds P, Rooney K, Sena ES, Silberberg SD, Steckler T, Würbel H, Holgate ST (2018) Revision of the ARRIVE guidelines: rationale and scope. Br Med J Open Sci 2(1):e000002. 10.1136/bmjos-2018-000002 Facanha DAE, Sammichelli L, Bozzi R, Silva WST, Morais JHG, Lucena RMO, Escossia PP, Costa WP (2012) Performance of Brazilian native goats submitted to a mix supply under thermal stress conditions, Proceedings of XI International Conference on Goats , Gran Canaria, Spain Pp.23–27 Habibu B, Kawu MU, Aluwong T, Makun HJ, Yaqub LS, Buhari HU, Saleh A (2021) Endogenous and seasonal factors influencing circulating thyrotropin concentration in Red Sokoto and Sahel goats. Sokoto J Veterinary Sci 19(4):150–159. 10.4314/sokjvs.v19i4.1 Helal A, Hashem ALS, Abde–Fattah MS, El-Shaer HM (2010) Effects of heat stress on coat characteristics and physiological responses of Balady and Damascus goats in Sinai, Egypt. American-Eurasian J Agricultural Environ Sci 7:60–69 Hicks LC, Hicks RA, Bucklin JK, Shearer DR, Bray PS, Carvalho V (2001) Comparison of methods of measuring deep body temperature of dairy cows. 6th International Symposium, Animal Society of Agricultural Engineering , Louis Ville. Ky. Pp. 432–438 Koluman-Darcan N, Koluman A, Arsoy D (2017) Heat stress effects on water metabolism of goats in harsh environments. Sustainable Goat Prod Adverse Environ 1:429–438. 10.1007/978-3-319-71855-2_24 Mallam I, Yakubu A, Ari MM, Musa IS, Achi NP (2024) Pearson’s Correlation Coefficient Among Thermo-Physiological and Haematological Parameters of Nigerian Goats. J Anim Husb Dairy Sci 8(1):13–16 Nguluma A, Kyallo M, Tarekegn GM, Loina R, Nziku Z, Chenyambuga S, Pelle R (2022) Typology and characteristics of indigenous goats and production systems in different agroecological zones of Tanzania. Trop Anim Health Prod 54(1):70. 10.1007/s11250-022-03074-1 Nigerian Meteorological Agency (NiMet) (2023) Nigerian Meteorological Agency, Lafia, Nasarawa State, Nigeria. Proceedings: In Geographic Perspective on Nasarawa Company Keffi, Nasarawa State. Ogebe PO, Ogunmodede BK, McDowell LR (1996) Behavioural and physiological response of Nigeria, Dwarf goats to seasonal changes of the humind tropics. Small Ruminants Resource 22(3):213–217 Okoruwa MI, Adewumi MK, Igene FU (2013) Thermophysiological Responses of West African Dwarf (WAD) Bucks Fed Pennisetum purpureum and Unripe Plantain Peels. Nigerian J Anim Sci 15:168–178 Ovimap (2023) Ovi map location: Ovi earth imagery. Accessed on: 4th July 2023 ( latitude.to/satellitemap/ng/nigeria/135458/Lafia ) Percie du Sert N, Hurst V, Ahluwalia A (2020) The ARRIVE guidelines 2.0: Updated Guidelines for Reporting Animal Research. Br J Pharmacol 177:3617–3624. https://doi.org/10.1111/bph.15193 Ravagnolo O, Misztal I, Hoogenboom G (2000) Genetic component of heat stress in dairy cattle, development of heat index function. J Dairy Sci 83:2120–2125. 10.3168/jds.S0022-0302(00)75094-6 Ribeiro MN, Ribeiro NL, Bozzi R, Costa R (2018) Physiological and biochemical blood variables of goats subjected to heat stress – a review. J Appl Anim Res 46(1):1036–1041. https://doi.org/10.1080/09712119.2018.1456439 Robertshaw D, Dmi'el R (1983) The effect of dehydration on the control of panting and sweating in the black Bedouin goat. J Physiological Zool 56:412–418. https://www.jstor.org/stable/30152606 Sani RT, Lamidi OS, Achi NP, Idowu W, Ishiaku YM, Ahmed SA, Lawal HB (2023) Effects of feeding diet containing raw or parboiled rice offal on rumen metabolite of Bunaji bulls. FUDMA J Sci 7(1):84–90. https://doi.org/10.33003/fjs-2023-0701-1246 Sanusi AO, Peters SO, Sonibare AO, Ozojie MO (2011) Effects of coat colour on heat stress among West African dwarf sheep. Nigerian J Anim Prod 38:28–36. 10.51791/njap.v38i1.710 Schoenian S (2019) Heat Stress in Small Ruminants. https://u.osu.edu/sheep/2019/05/21/heat-stress-in-smallruminants/ , Accessed on 30th April, 2024 Singh AS, Pal DT, Mandal BC, Singh P, Pathak NN (2002) Studies on changes in some of blood constituentsof adult cross-bred cattle fed different levels of extracted rice bran. Pakistan J Nutr 1(2):95–98. 10.3923/pjn.2002.95.98 Timveh JT, Yakubu A, Alu SE (2022) Effects of breed and sex on the adaptive profile of tropical goat. Acta Fytotechnica et Zootechnica 25(1):24–33. http://www.acta.fapz.uniag.sk Wulandari WBP, Noviandi CT, Agus A (2020) In vitro digestibility and ruminal fermentation profile of pangola grass ( Digitaria decumbens ) supplemented with crude palm oil protected by sodium hydroxide. Livestock Research for Rural Development, Volumem32,Article#102. Retrieved April30,2024, fromhttp://www.lrrd.org/lrrd32/7/wulan32102.html Yakubu A, Salako AE, De Donato M, Peters SO, Takeet MI, Wheto M, Okpeku M (2017b) Association of SNP variants in MHC-Class II DRB gene with thermo-physiological indices in tropical goats. Trop Anim Health Prod 49(2):323–336. http://dx.doi.org/10.1007/s11250-016-1196-1 Yousif HS (2019) Some Physiological Responses in Nubian Goats Exposed to Heat load. Int J Sci Eng Sci 3(2):6–9. http://ijses.com/wp-content/uploads/2019/03/75-IJSES-V3N2.pdf 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-5746207","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":423224709,"identity":"8daa4be6-1369-485b-a863-f3075ca8cca1","order_by":0,"name":"Iliya Mallam","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIiWNgGAWjYFAC5sYDDAwSMmwMDIwPEgwk5EBiBx7g1cLYANLCA9TCbPChwMIYrCWBsBYGHiBmk5zxoSKxASSIT4tu+8GGAz9zLHj4JJIfSPMYSKTPDzv8EGiLnZxuA3YtZmcSGw72bgM6TCLNwBioJXfj7TQDoJZkY7MDOLQcSGw4wAvWkmCQDNYyOwGk5UDiNlxazj9sOPgXrCX9w2GQwwxnp3/Ar+VGYsNhiC05ho0zDCQS5KVzCNhy42HDYVmQFp43xQwfDCQMN0jnFBwAOhK3X84nH3z4dludnHx7+vYfCX/q5OVnp2/+8KHCTg6XFgQQSIDQBmCVBoSUgwA/1FD5BmJUj4JRMApGwUgCACrGZSy1TGA+AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-4265-9589","institution":"Kaduna State University","correspondingAuthor":true,"prefix":"","firstName":"Iliya","middleName":"","lastName":"Mallam","suffix":""},{"id":423224710,"identity":"99e07433-ea81-4850-b029-de7bfffa7fcd","order_by":1,"name":"Abdulmojeed Yakubu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Abdulmojeed","middleName":"","lastName":"Yakubu","suffix":""},{"id":423224711,"identity":"3b9f035d-ea90-4e67-a960-14326d7e801e","order_by":2,"name":"Maikano Mohammed Ari","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Maikano","middleName":"Mohammed","lastName":"Ari","suffix":""},{"id":423224712,"identity":"7334829f-e31b-4344-bb35-3bc96fa14052","order_by":3,"name":"Ibrahim Suleiman Ari","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Ibrahim","middleName":"Suleiman","lastName":"Ari","suffix":""},{"id":423224713,"identity":"810396c7-55fe-498e-b5ec-ce5e7e320b14","order_by":4,"name":"Neyu Patrick Achi","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Neyu","middleName":"Patrick","lastName":"Achi","suffix":""}],"badges":[],"createdAt":"2025-01-01 12:45:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5746207/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5746207/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":77796395,"identity":"c4193f9c-5d93-45d2-b411-843afd50bbb6","added_by":"auto","created_at":"2025-03-05 15:31:55","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":85512,"visible":true,"origin":"","legend":"\u003cp\u003eTemperature-Humidity Index during the study period.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5746207/v1/f7d5d5775d6c6fa0e592a746.jpg"},{"id":88701943,"identity":"bf4b57cf-6574-49dd-956c-587ff0ee2e00","added_by":"auto","created_at":"2025-08-09 22:32:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1564926,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5746207/v1/3181f355-685b-477a-9e57-829db12441a9.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eEffects of Breed, Diet and Sex on Thermo-physiology of Nigerian Goats\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003e Goat is one of the important farm animals that provide abundant meat, milk and income to the local people (Nguluma et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Breed, diet, and sex effects on the thermo-physiology of Nigerian goats are crucial for optimizing their management and productivity, especially in the context of a changing climate. Physical therapy is important to prevent hyperthermia and maintain normal body temperature. When exposed to thermal stress, physiological parameters such as heart rate, respiration and rectal temperature respond immediately (Helal et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Sanusi et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Thermo-physiological parameters can help in monitoring the health status of goats, allowing for timely interventions when necessary (Mallam et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Goats are integral to the livelihoods of many Nigerian farmers, examining thermal comfort, physiological responses can provide insights into their health (Mallam et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Changes in respiration, heart rate and abdominal pressure have been widely used as markers of physiological adaptation to stress in small ruminants (Sharma et al. 2013). The circulatory system responds to changes in temperature and is an important function of the body's response to challenges (Ribeiro et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Nigerian goats, particularly the West African Dwarf (WAD) and Red Sokoto (RS) breeds, exhibit distinct physiological responses to environmental stressors, which can significantly influence their health and productivity. Research indicates that breed differences play a pivotal role in thermo-physiological responses. WAD goats have been observed to maintain higher rectal temperatures and pulse rates compared to RS goats, suggesting a greater vulnerability to heat stress despite no significant differences in heat stress indices between the two breeds (Timveh et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, sex-related variations have been noted, with male goats generally exhibiting more stress than females under similar conditions. This disparity may be attributed to hormonal differences, as female goats often show higher levels of thyroid stimulating hormone (TSH), which can affect their physiological responses to heat (Habibu et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The broad objective of the study was to determine the effects of breed, diet and sex on thermo-physiology of Nigerian goats.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eThe Study Area\u003c/h2\u003e \u003cp\u003eThis experiment was carried out at the Livestock Teaching and Research Farm of the Animal Science Department, Faculty of Agriculture, Shabu-Lafia Campus, Nasarawa State University, Keffi. Lafia is located on latitude 08\u003csup\u003e0\u003c/sup\u003e 35˝ and longitude 08\u003csup\u003e0\u003c/sup\u003e 33˝ (Ovimap, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). It is geographically located in the Guinea Savanna Zone of North Central Nigeria. It has mean maximum monthly temperature of 35.06\u0026deg;C and mean minimum monthly temperature of 20.16\u0026deg;C with a mean monthly relative humidity of 74% and the annual rainfall is about 168.90 mm (NiMet, 2023).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSources of Experimental Materials\u003c/h3\u003e\n\u003cp\u003eThe grass (\u003cem\u003eDigitaria smutsii\u003c/em\u003e) was sourced from the National Animal Production Research Institute (NAPRI)/Ahmadu Bello University, Shika, Zaria, Nigeria while the two legumes (groundnut haulms and cowpea husk) were sourced from farms after harvest in Lafia, Nasarawa State. After collection, the haulms were brought to the Faculty Livestock Farm, where they were shade-dried and debris was removed before being fed to the experimental goats.\u003c/p\u003e\n\u003ch3\u003eExperimental Diets\u003c/h3\u003e\n\u003cp\u003eThe diet groups included 100% \u003cem\u003eDigitaria smutsii\u003c/em\u003e (diet 1), 50% \u003cem\u003eDigitaria smutsii\u003c/em\u003e\u0026thinsp;+\u0026thinsp;50% groundnut haulms (diet 2) and 50% \u003cem\u003eDigitaria\u003c/em\u003e\u0026thinsp;+\u0026thinsp;50% cowpea husk (diet 3).\u003c/p\u003e\n\u003ch3\u003eExperimental Design\u003c/h3\u003e\n\u003cp\u003eA 2\u0026times;3\u0026times;2 factorial experiment comprising 2 breeds West African dwarf (WAD) and Red Sokoto (RS) goats, 3 diets groups (100% \u003cem\u003eDigitaria smutsii\u003c/em\u003e, 50% \u003cem\u003eDigitaria smutsii\u003c/em\u003e\u0026thinsp;+\u0026thinsp;50% groundnut haulms and 50% \u003cem\u003eDigitaria smutsii\u003c/em\u003e\u0026thinsp;+\u0026thinsp;50% cowpea husk) and 2 sexes (Male and Female) in a Completely Randomized Design (CRD) was used. There were six treatments (T1\u0026thinsp;=\u0026thinsp;WAD100% \u003cem\u003eDigitaria smutsii\u003c/em\u003e, T2\u0026thinsp;=\u0026thinsp;WAD50% \u003cem\u003eDigitaria smutsii\u003c/em\u003e\u0026thinsp;+\u0026thinsp;50% groundnut haulms, T3\u0026thinsp;=\u0026thinsp;WAD50% \u003cem\u003eDigitaria smutsii\u003c/em\u003e\u0026thinsp;+\u0026thinsp;50% cowpea husk, T4\u0026thinsp;=\u0026thinsp;RS100% \u003cem\u003eDigitaria smutsii\u003c/em\u003e, T5\u0026thinsp;=\u0026thinsp;RS50% \u003cem\u003eDigitaria smutsii\u003c/em\u003e\u0026thinsp;+\u0026thinsp;50% groundnut haulms, T6\u0026thinsp;=\u0026thinsp;RS50% \u003cem\u003eDigitaria\u003c/em\u003e\u0026thinsp;+\u0026thinsp;50% cowpea husk) which were replicated three times with two goats (male and female) in each replicate.\u003c/p\u003e\n\u003ch3\u003eExperimental Goats and Management\u003c/h3\u003e\n\u003cp\u003ePhysically sound goats were randomly sourced from reputable local farms in Lafia, Nasarawa State. A total of 36 weaner goats of two breeds (West African dwarf, n\u0026thinsp;=\u0026thinsp;18; 9 males\u0026thinsp;+\u0026thinsp;9 females) and Red Sokoto goats, n\u0026thinsp;=\u0026thinsp;18; 9 males\u0026thinsp;+\u0026thinsp;9 females) of about 3\u0026ndash;4 months of age were sourced from farmers for the experiment. Upon arrival, the experimental goats were allowed to acclimatize for a period of 2 weeks during which they were dewormed against parasites and vaccinated against \u003cem\u003ePeste des petits ruminants\u003c/em\u003e (PPR). The experimental goats were randomly allotted into the six treatments groups. Diets and water were given \u003cem\u003ead-libitum\u003c/em\u003e and any goat with any sign of disease was treated by a professional (Veterinarian). Other routine management practices were adopted throughout the experimental period according to (Timveh et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn conduct of the research, there was a strict adherence to the International Ethical Guidelines for Biomedical research (CIOMS, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) involving Human Subjects and the Global code of conduct for research in resource-poor settings following the Convention on Biological and Declaration of Helsinki. The Research also follows Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines as described by du Sert et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Collection and Measurements\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eProximate analysis of the experimental materials\u003c/h2\u003e \u003cp\u003eProximate analysis of the experimental materials was conducted at the Biochemistry Laboratory, National Animal Production Research Institute (NAPRI)/Ahmadu Bello University, Zaria, Nigeria using the methods proposed by (AOAC \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) for the determination of their nutrients\u0026rsquo; composition.\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\u003eProximate composition of the experimental materials\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExperimental materials\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%DM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%Ash\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%EE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%CF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e%CP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e%NDF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e%ADF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e94.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e63.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e34.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e25.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e38.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e31.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e36.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e15.89\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\u003eDS\u0026thinsp;=\u0026thinsp;\u003cem\u003eDigitaria smutsii\u003c/em\u003e, GH\u0026thinsp;=\u0026thinsp;Groundnut haulm, CH\u0026thinsp;=\u0026thinsp;Cowpea husk, DM\u0026thinsp;=\u0026thinsp;Dry matter, EE\u0026thinsp;=\u0026thinsp;Ether extract, CF\u0026thinsp;=\u0026thinsp;Crude fibre, CP\u0026thinsp;=\u0026thinsp;Crude protein, NDF\u0026thinsp;=\u0026thinsp;Neutral detergent fibre, ADF\u0026thinsp;=\u0026thinsp;Acid detergent fibre.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eMeteorological Parameters\u003c/h3\u003e\n\u003cp\u003eThe meteorological data collected were maximum and minimum ambient temperature (\u0026deg;C) and relative humidity (%) and the average values were used for analysis. The records were obtained from the Meteorological Unit of the Nigerian Meteorological Agency, Lafia, located about 200 meters away from the site of the experiment. The temperature humidity index (THI) was used to evaluate the level of heat stress induced by the environment and was calculated using the equation reported by (Ravagnolo et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) as follows:\u003c/p\u003e \u003cp\u003eTHI = (1.8 \u0026times; T\u0026thinsp;+\u0026thinsp;32) - {(0.55\u0026ndash;0.0055 \u0026times; RH) \u0026times; (1.8 \u0026times; T \u0026minus;\u0026thinsp;26)}\u003c/p\u003e \u003cp\u003eWhere; T\u0026ndash; ambient temperature (\u0026deg;C); RH\u0026ndash; relative humidity (%).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eThermo-physiology Data Collected\u003c/h2\u003e \u003cp\u003eThe thermo-physiology data collected were rectal temperature (RT), pulse rate (PR) and respiratory rate (RR) while the heat stress index (HSI) was calculated. A digital thermometer was used to take each animal's rectal temperature. After disinfecting the sensory tip of the digital thermometer, it was placed into the rectum. This was taken out following the alarm signal and the displayed body temperature was recorded. Pulse rate was determined by counting the beats of the heart using a stethoscope per unit time, and expressed in number of beats per minute. This was achieved by positioning the stethoscope on the left side of the chest. The respiratory rate was done by counting the flanks' movements around the lower back area per minute using a stopwatch. The RT, PR, and RR were taken between the hours of 6:30 am and 9:30 am in the morning and 1:00 pm and 3:00 pm in the afternoon every day.\u003c/p\u003e \u003cp\u003eHeat stress index (HSI) was calculated as:\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eHSI\u0026thinsp;=\u0026thinsp;RR/PR \u0026times; NP/NR\u003c/h2\u003e \u003cp\u003eWhere; RR\u0026thinsp;=\u0026thinsp;actual respiratory rate; PR\u0026thinsp;=\u0026thinsp;actual pulse rate; NP\u0026thinsp;=\u0026thinsp;normal pulse rate; NR\u0026thinsp;=\u0026thinsp;normal respiratory rate. In both goat breeds, the basal reference value for NR was 30 breaths/minute while that of NP was 90 beats/minute (Yakubu et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017b\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData collected were subjected to analysis of variance (ANOVA) to test the fixed effect of breed, diet and sex as well as their interactions on thermo-physiology response. Significant differences between treatments were compared using the Duncan multiple range test option of Statistix Analytical software, file version 8.0 while excel package was used for graphical representation of the temperature-humidity index (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.)\u003c/p\u003e \u003cp\u003eThe mathematical model employed was:\u003c/p\u003e \u003cp\u003eY\u003csub\u003eijkl\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u0026micro;\u0026thinsp;+\u0026thinsp;A\u003csub\u003ei\u003c/sub\u003e + B\u003csub\u003ej\u003c/sub\u003e +C\u003csub\u003ek\u003c/sub\u003e+ (AB)\u003csub\u003eij\u003c/sub\u003e+ (AC)\u003csub\u003eik\u003c/sub\u003e + (BC)\u003csub\u003ejk\u003c/sub\u003e +(ABC)\u003csub\u003eijk\u003c/sub\u003e + e\u003csub\u003eijkl\u003c/sub\u003e\u003c/p\u003e \u003cp\u003eWhere;\u003c/p\u003e \u003cp\u003eY\u003csub\u003eijkl\u003c/sub\u003e = individual observation,\u003c/p\u003e \u003cp\u003e\u0026micro;\u0026thinsp;=\u0026thinsp;general or overall mean,\u003c/p\u003e \u003cp\u003eA\u003csub\u003ei\u003c/sub\u003e = effect of factor A (breed) (A\u003csub\u003ei\u003c/sub\u003e =WAD, RS)\u003c/p\u003e \u003cp\u003eB\u003csub\u003ej\u003c/sub\u003e = effect of factor B (diet) (j\u0026thinsp;=\u0026thinsp;100%\u003cem\u003eDS\u003c/em\u003e, 50%DS\u0026thinsp;+\u0026thinsp;50%GH, 50%DS\u0026thinsp;+\u0026thinsp;50%CH)\u003c/p\u003e \u003cp\u003eC\u003csub\u003ek\u003c/sub\u003e = effect of factor C (sex) (k\u0026thinsp;=\u0026thinsp;Male, Female)\u003c/p\u003e \u003cp\u003e(AB)\u003csub\u003eij\u003c/sub\u003e = effect of interaction between A\u003csub\u003ei\u003c/sub\u003e and B\u003csub\u003ej,\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(AC)\u003csub\u003eik\u003c/sub\u003e = effect of interaction between A\u003csub\u003ei\u003c/sub\u003e and C\u003csub\u003ek\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(BC)\u003csub\u003ejk\u003c/sub\u003e = effect of interaction between be B\u003csub\u003ej\u003c/sub\u003e and C\u003csub\u003ek\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(ABC)\u003csub\u003eijk\u003c/sub\u003e =effect of interaction between A\u003csub\u003ei\u003c/sub\u003e, B\u003csub\u003ej\u003c/sub\u003e and C\u003csub\u003ek\u003c/sub\u003e\u003c/p\u003e \u003cp\u003ee\u003csub\u003eijkl\u003c/sub\u003e = experimental error.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eTemperature-Humidity Index (THI) During the Study Period\u003c/h2\u003e \u003cp\u003eTemperature-Humidity Index (THI) during the study period is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The results showed that higher THI value (71.04) was observed in December and the least value (70.07) was observed in January.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eEffect of breed on thermo-physiology indices of goats\u003c/h2\u003e \u003cp\u003eThe effect of breed on thermo-physiology indices of goats (WAD) and (RS) goats is presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The results revealed that breed had significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) effect on pulse rate (PR) and respiratory rate (RR). However, breed was not significantly (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) different in terms of rectal temperature (RT) and heat stress index (HSI). The PR and RR were higher in Red Sokoto (RS) goats than their West African dwarf (WAD) counterparts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eEffect of diet on thermo-physiology indices of goats\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the effect of diet on thermo-physiology indices of goats. The results showed that diet had significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) effect on rectal temperature (RT), pulse rate (PR) and respiratory rate (RR). However, diet had no significant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) influence on heat stress index (HSI). The RT was higher in goats fed 50%DS\u0026thinsp;+\u0026thinsp;50GH diet group but statistically similar to goats fed 100%DS. For PR and RR, goats fed 100%DS had significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) higher values than those fed 50%DS\u0026thinsp;+\u0026thinsp;50%GH and 50%DS\u0026thinsp;+\u0026thinsp;50%CH. The least value for PR was observed in goats fed 50%DS\u0026thinsp;+\u0026thinsp;50CH but statistically similar to those fed 50%DS\u0026thinsp;+\u0026thinsp;50%GH while the least value for RR was found in goats fed 50%DS\u0026thinsp;+\u0026thinsp;50%GH though statistically similar to goats fed 50%DS\u0026thinsp;+\u0026thinsp;50%CH. Meanwhile, the diet had no significant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) effect on heat stress index (HSI) but higher numerical value was observed in goats fed 50%DS\u0026thinsp;+\u0026thinsp;50%CH and the HSI ranged from 1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 to 1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eEffect of sex on thermo-physiology indices of goats\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the effect of sex on thermo-physiology indices of goats. The results observed revealed that sex had significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) effect in all the thermo-physiology indices of goats. The results showed that male goats had significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) higher values than their female counterparts in all the parameters. The rectal temperature (RT), pulse rate (PR), respiratory rate (RR) and heat stress index (HSI) ranges from 37.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u0026ndash;38.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04, 76.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u0026ndash;78.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34, 31.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u0026ndash;32.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15 and 1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u0026ndash;1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02, respectively.\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\u003eEffect of breed on thermo-physiology indices of goats\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBreed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWAD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRT (\u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2133\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38\u0026ndash;41 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR (beats/minute)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70\u0026ndash;102 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRR(breaths/minute)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u0026ndash;30 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4324\u003csup\u003eNS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003eab\u003c/sup\u003eMeans in the same row bearing different superscripts differ significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), WAD\u0026thinsp;=\u0026thinsp;West African dwarf, RS\u0026thinsp;=\u0026thinsp;Red Sokoto, RT\u0026thinsp;=\u0026thinsp;Rectal temperature, PR\u0026thinsp;=\u0026thinsp;Pulse rate, RR\u0026thinsp;=\u0026thinsp;Respiratory rate, HSI\u0026thinsp;=\u0026thinsp;Heat stress index, NA\u0026thinsp;=\u0026thinsp;Not available, WAD\u0026thinsp;=\u0026thinsp;West African dwarf, RS\u0026thinsp;=\u0026thinsp;Red Sokoto, *= Significant at 0.05, NS\u0026thinsp;=\u0026thinsp;Not significant, \u003csup\u003eo\u003c/sup\u003eC = Degree Celsius, Ref.= Reference values from literature\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\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\u003eEffect of diet on thermo-physiology indices of goats\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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eDiet\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e100%DS\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e50%DS\u0026thinsp;+\u0026thinsp;50\u003c/b\u003e%\u003cb\u003eGH\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e50%DS\u0026thinsp;+\u0026thinsp;50\u003c/b\u003e%\u003cb\u003eCH\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eP-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRT(\u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38\u0026ndash;41 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR(beats/minute)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0276\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70\u0026ndash;102 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRR (breaths/minute)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0142\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u0026ndash;30 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1889\u003csup\u003eNS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003eab\u003c/sup\u003eMeans in the same row bearing different superscripts differ significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05),WAD\u0026thinsp;=\u0026thinsp;West African dwarf, RS\u0026thinsp;=\u0026thinsp;Red Sokoto, DS\u0026thinsp;=\u0026thinsp;Digitaria smutsii, GH\u0026thinsp;=\u0026thinsp;Groundnut haulm, CH\u0026thinsp;=\u0026thinsp;Cowpea husk, RT\u0026thinsp;=\u0026thinsp;Rectal temperature, PR\u0026thinsp;=\u0026thinsp;Pulse rate, RR\u0026thinsp;=\u0026thinsp;Respiratory rate, HSI\u0026thinsp;=\u0026thinsp;Heat stress index, \u003csup\u003eo\u003c/sup\u003eC = Degree Celsius, *= Significant at 0.05, NS\u0026thinsp;=\u0026thinsp;Not significant, Ref.= Reference values from literature\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \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\u003eEffect of sex on thermo-physiology indices of goats\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRT (\u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38\u0026ndash;41 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR (beats/minute)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0002\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70\u0026ndash;102 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRR (breaths/minute)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u0026ndash;30 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0004\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003eab\u003c/sup\u003eMeans in the same row bearing different superscripts differ significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), \u003csup\u003eo\u003c/sup\u003eC= Degree Celsius, *= Significant at 0.05, RT\u0026thinsp;=\u0026thinsp;Rectal temperature, PR\u0026thinsp;=\u0026thinsp;Pulse rate, RR\u0026thinsp;=\u0026thinsp;Respiratory rate, HSI\u0026thinsp;=\u0026thinsp;Heat stress index, NA\u0026thinsp;=\u0026thinsp;Not available, Ref.= Reference values from literature\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eInteractions effect between breed \u0026times; diet on thermo-physiology indices of goats\u003c/h2\u003e \u003cp\u003eInteractions effect between breed \u0026times; diet on thermo-physiology indices of goats are presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The results observed revealed that breed \u0026times; diet interactive effect had significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) effect in all the thermo-physiological parameters. For rectal temperature (RT), WAD\u0026times;50%DS\u0026thinsp;+\u0026thinsp;50%GH had significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) higher value (38.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 \u003csup\u003eo\u003c/sup\u003eC) followed by RS\u0026times;50%DS\u0026thinsp;+\u0026thinsp;50%CH (38.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09 \u003csup\u003eo\u003c/sup\u003eC) but statistically similar to RS\u0026times;100%DS (38.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 \u003csup\u003eo\u003c/sup\u003eC) and the least was observed in WAD\u0026times;50%DS\u0026thinsp;+\u0026thinsp;50%CH (37.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 \u003csup\u003eo\u003c/sup\u003eC). For pulse rate (PR), the RS\u0026times;100%DS had significantly ((P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) higher value (83.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59 beats/minute) followed by RS\u0026times;50%DS\u0026thinsp;+\u0026thinsp;50%CH (77.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67 beats/minute) but similar to WAD\u0026times;50%DS\u0026thinsp;+\u0026thinsp;50%GH (77.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62 beats/minute), WAD\u0026times;50%DS\u0026thinsp;+\u0026thinsp;50%CH (76.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63 beats/minute) and RS \u0026times;50%DS\u0026thinsp;+\u0026thinsp;50%GH (76.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63 beats/minute) and the least was found in WAD\u0026times;100%DS (73.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59 beats/minute) and similar trend was observed for respiratory rate (RR). The heat stress index in WAD \u0026times;100%DS and RS\u0026times;50%DS\u0026thinsp;+\u0026thinsp;50%GH were statistically same and the least heat stress index was found in WAD \u0026times;50%DS\u0026thinsp;+\u0026thinsp;50%GH.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eInteractions effect between breed \u0026times; sex on thermo-physiology indices of goats\u003c/h2\u003e \u003cp\u003eInteractions effect between breed \u0026times; sex on thermo-physiology indices of goats on thermo-physiological indices of goats is shown in Table\u0026nbsp;6. The results revealed that breed \u0026times; sex had significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) effect on rectal temperature (RT) with WAD \u0026times; male had significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) higher value (38.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 \u003csup\u003eo\u003c/sup\u003eC) followed by RS \u0026times; male (38.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 \u003csup\u003eo\u003c/sup\u003eC) and the least was found in WAD \u0026times;female (37.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 \u003csup\u003eo\u003c/sup\u003eC). The breed \u0026times; sex interactive effect had no significant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) effect on pulse rate (PR), respiratory rate (RR) and heat stress index (HSI). However, the highest numerical value for PR, RR and HSI were found in RS\u0026times; male and the least was found in WAD \u0026times;female for PR and RR while the least for HSI was found in RS \u0026times;female.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eInteractions effect between diet \u0026times; sex on thermo-physiology indices of goats\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e7\u003c/span\u003e indicates the interactions effect between diet \u0026times; sex on thermo-physiology indices of goats. The observed results obtained indicated that diet \u0026times; sex had significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) effect in all the thermo-physiological parameters. For rectal temperature, 50%DS\u0026thinsp;+\u0026thinsp;50%GH \u0026times; male had significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) higher value but statistically to 100%DS \u0026times; male and 50%DS\u0026thinsp;+\u0026thinsp;50%CH \u0026times; male and the least value was observed in 50%DS\u0026thinsp;+\u0026thinsp;50%CH \u0026times; female though statistical to with 100%DS \u0026times; female and 50%DS\u0026thinsp;+\u0026thinsp;50%GH \u0026times; female. For pulse rate (PR), the 100%DS \u0026times; male had significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) higher value (80.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55 beats/minute) followed by 50%DS\u0026thinsp;+\u0026thinsp;50%CH \u0026times; female (77.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55 beats/minute) but statistically similar to 50%DS\u0026thinsp;+\u0026thinsp;50%GH \u0026times; male 50%DS\u0026thinsp;+\u0026thinsp;50%GH \u0026times; female and 50%DS\u0026thinsp;+\u0026thinsp;50%CH \u0026times; male and the least PR was found in 100%DS \u0026times; female. The respiratory rate (RR) followed the same trend with PR. The heat stress index (HSI) was found to be significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) higher in 100%DS \u0026times;male which was statistically similar to 100%DS \u0026times;female, 50%DS\u0026thinsp;+\u0026thinsp;50%GH \u0026times; male, 50%DS\u0026thinsp;+\u0026thinsp;50%CH \u0026times;male and, 50%DS\u0026thinsp;+\u0026thinsp;50%CH \u0026times;female and the least HSI was found in 50%DS\u0026thinsp;+\u0026thinsp;50%GH \u0026times;female (1.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eInteractions effect between breed \u0026times; diet \u0026times;sex on thermo-physiology indices of goats\u003c/h2\u003e \u003cp\u003eInteractions effect between breed \u0026times; diet \u0026times; sex interactive on thermo-physiology indices of goats is represented in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e8\u003c/span\u003e. The results of breed \u0026times; diet \u0026times; sex had no significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) effect in all the thermo-physiology parameters of goats. However, the highest numerical value for rectal temperature (RT), pulse rate (PR), respiratory rate (RR) and heat stress index (HSI) were obtained in RS\u0026times;50%DS\u0026thinsp;+\u0026thinsp;50%CH\u0026times;female, RS\u0026times;100%DS \u0026times;female, RS\u0026times;100%DS \u0026times;male, RS\u0026times;50%DS\u0026thinsp;+\u0026thinsp;50%GH\u0026times;male, respectively and the least were found in WAD \u0026times;50%DS\u0026thinsp;+\u0026thinsp;50%CH\u0026times;female, WAD\u0026times;100%DS\u0026times; female, WAD \u0026times;100%DS\u0026times;female and WAD\u0026times;50%DS\u0026thinsp;+\u0026thinsp;50%GH\u0026times;female, respectively.\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\u003eInteraction effect between breed \u0026times; diet on thermo-physiology indices of goats\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eWAD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eRS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e100%DS\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e50%DS\u0026thinsp;+\u0026thinsp;50\u003c/b\u003e%\u003cb\u003eGH\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e50%DS\u0026thinsp;+\u0026thinsp;50\u003c/b\u003e%\u003cb\u003eCH\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e100%DS\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e50%DS\u0026thinsp;+\u0026thinsp;50\u003c/b\u003e%\u003cb\u003eGH\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e50%DS\u0026thinsp;+\u0026thinsp;50\u003c/b\u003e%\u003cb\u003eCH\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eP-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRT(\u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.0000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e38\u0026ndash;41 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR(beats/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e76.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e77.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.0000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e70\u0026ndash;102 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRR(breaths/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.0001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e15\u0026ndash;30 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.0000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003csup\u003eabc\u003c/sup\u003e Means in the same row bearing different superscripts differ significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05),WAD\u0026thinsp;=\u0026thinsp;West African dwarf, RS\u0026thinsp;=\u0026thinsp;Red Sokoto, DS\u0026thinsp;=\u0026thinsp;Digitaria smutsii, GH\u0026thinsp;=\u0026thinsp;Groundnut haulm, CH\u0026thinsp;=\u0026thinsp;Cowpea husk, RT\u0026thinsp;=\u0026thinsp;Rectal temperature, PR\u0026thinsp;=\u0026thinsp;Pulse rate, RR\u0026thinsp;=\u0026thinsp;Respiratory rate, HSI\u0026thinsp;=\u0026thinsp;Heat stress index, NA\u0026thinsp;=\u0026thinsp;Not available, Ref.= Reference values from literature, \u003csup\u003eo\u003c/sup\u003eC = Degree Celsius, *= Significant at 0.05, NS\u0026thinsp;=\u0026thinsp;Not significant\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e\u003cb\u003eTable\u0026nbsp;6: Interaction effect between breed \u0026times; sex on thermo-physiology indices of goats\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eWAD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eRS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRT(\u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38\u0026ndash;41(Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR(beats/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2978\u003csup\u003eNS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e70\u0026ndash;102 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRR(breaths/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.4914\u003csup\u003eNS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u0026ndash;30 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2117\u003csup\u003eNS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\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\u003e \u003csup\u003eabcd\u003c/sup\u003eMeans in the same row bearing different superscripts differ significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05),WAD\u0026thinsp;=\u0026thinsp;West African dwarf, RS\u0026thinsp;=\u0026thinsp;Red Sokoto, RT\u0026thinsp;=\u0026thinsp;Rectal temperature, PR\u0026thinsp;=\u0026thinsp;Pulse rate, RR\u0026thinsp;=\u0026thinsp;Respiratory rate, HSI\u0026thinsp;=\u0026thinsp;Heat stress index, NA\u0026thinsp;=\u0026thinsp;Not available,, \u003csup\u003eo\u003c/sup\u003eC= Degree Celsius, *= Significant at 0.05, NS\u0026thinsp;=\u0026thinsp;Not significant, Ref.= Reference values from literature.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInteraction effect between diet \u0026times; sex on thermo-physiology indices of goats\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e100%DS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e50%DS\u0026thinsp;+\u0026thinsp;50%GH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e50%DS\u0026thinsp;+\u0026thinsp;50%CH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRT(\u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e37.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.0013\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e38\u0026ndash;41(Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR(beats/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e75.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e77.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.0000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e70\u0026ndash;102 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRR(breaths/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.0000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e15\u0026ndash;30 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.0086\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNA\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\u003e \u003csup\u003eabc\u003c/sup\u003eMeans in the same row bearing different superscripts differ significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), DS\u0026thinsp;=\u0026thinsp;\u003cem\u003eDigitaria smutsii\u003c/em\u003e, GH\u0026thinsp;=\u0026thinsp;Groundnut haulm, CH\u0026thinsp;=\u0026thinsp;Cowpea husk, RT\u0026thinsp;=\u0026thinsp;Rectal temperature, PR\u0026thinsp;=\u0026thinsp;Pulse rate, RR\u0026thinsp;=\u0026thinsp;Respiratory rate, HSI\u0026thinsp;=\u0026thinsp;Heat stress index, NA\u0026thinsp;=\u0026thinsp;Not available, \u003csup\u003eo\u003c/sup\u003eC = Degree Celsius,*= Significant at 0.05, Ref.= Reference values from literature.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInteraction effect between breed \u0026times; diet \u0026times; sex on thermo-physiology indices of goats\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiet\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRT(\u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePR(beats/min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRR(breaths/min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHSI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100%DS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e6.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.55\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50%DS\u0026thinsp;+\u0026thinsp;50%GH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50%DS\u0026thinsp;+\u0026thinsp;50%CH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100%DS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80.89\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50%DS\u0026thinsp;+\u0026thinsp;50%GH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50%DS\u0026thinsp;+\u0026thinsp;50%CH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.02\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eP-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6428\u003csup\u003eNS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0919\u003csup\u003eNS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1059\u003csup\u003eNS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8636\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38\u0026ndash;41(Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70\u0026ndash;102 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u0026ndash;30 (Bello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eWAD\u0026thinsp;=\u0026thinsp;West African dwarf, RS\u0026thinsp;=\u0026thinsp;Red Sokoto, DS\u0026thinsp;=\u0026thinsp;\u003cem\u003eDigitaria smutsii\u003c/em\u003e, GH\u0026thinsp;=\u0026thinsp;Groundnut haulm, CH\u0026thinsp;=\u0026thinsp;Cowpea husk, RT\u0026thinsp;=\u0026thinsp;Rectal temperature, PR\u0026thinsp;=\u0026thinsp;Pulse rate, RR\u0026thinsp;=\u0026thinsp;Respiratory rate, HSI\u0026thinsp;=\u0026thinsp;Heat stress index, NA\u0026thinsp;=\u0026thinsp;Not available, \u003csup\u003eo\u003c/sup\u003eC= Degree Celsius, M\u0026thinsp;=\u0026thinsp;Male, F\u0026thinsp;=\u0026thinsp;Female, *= Significant at 0.05, NS\u0026thinsp;=\u0026thinsp;Not significant, Ref. = Reference values from literature\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this study, THI in December and January were lower than those reported by (Timveh et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) who reported 79.68 in March, 81.31 in April and 80.07 in May. The variation could be due to differences in month and year as thes affect the THI value. The heat stress range for goats, based on the temperature humidity index (THI), is as follows: comfortable conditions are when the THI is less than or equal to 72; mild stress occurs when the THI ranges from 73 to 78; and severe stress is experienced when the THI is greater than or equal to 80. THI values exceeding 80 are categorized as moderate heat stress (MHS) for goats (Koluman-Darcan et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This means the goats used in this study were within their comfort zone during the experiment. The values observed in the study for rectal temperature across the breeds were within the range reported by (Timveh et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) who reported 38.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10 \u003csup\u003eo\u003c/sup\u003eC for West African dwarf and 38.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10 \u003csup\u003eo\u003c/sup\u003eC for Red Sokoto goats and that breed had no effect on heat stress index as observed in the present study. However, the pulse rates observed in this study were higher than the values reported by (Timveh et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) but reported higher respiratory rate than the one observed in this study. This may be due to changes in the age of the animals, season, and other environmental factors during the study. Parturition had no significant effect on rectal temperature, similar to the findings of (Yousif \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) who reported no significant difference in rectal temperature in the Nubian goat. The increased pressure in the RS goats may be due to increased blood flow from the core to the skin surface, allowing more heat to pass through the skin. The similar temperature profiles found in the WAD and RS goats support studies that show that domestic goats are one of the best adapted to extreme climates compared to other ruminant species. Respiratory rate serves as a dependable measure of heat load and is an indicator of thermal stress (Alam et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The basal reference respiratory rate is 15\u0026ndash;30 breaths/minute in goats Robertshaw and Dmi'el (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1983\u003c/span\u003e). So, measuring the rate of breathing and determining if an animal is panting, along with assessing the level of heat stress based on the panting rate (breaths per minute) in different climates (low: 40\u0026ndash;60, medium: 60\u0026ndash;80, high: 80\u0026ndash;120, and severe heat stress: \u0026gt;200) appears to be the most accessible and easiest method for evaluating the impact of heat stress on animals under extreme conditions. Therefore, the values in this study showed that they were slightly above the normal range and little heat stress.\u003c/p\u003e \u003cp\u003eThe rectal temperature values obtained in this study were within the range of 38.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36 \u003csup\u003e0\u003c/sup\u003eC to 39.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67 \u003csup\u003e0\u003c/sup\u003eC as earlier reported by (Ajayi et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Sanusi et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) for WAD goats. The higher temperatures observed for animals on diets 50%DS\u0026thinsp;+\u0026thinsp;50%GH and 100%D led to increase in temperature may be a result of the heat generated during the breakdown of the feeds. This is in agreement with the finding of (Hicks et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) who earlier reported that the rumen temperature is the effect of body temperature and may be used to predict diseases or heat stress. Increased respiration in goats fed 100% DS is a clear indication that respiration increases with temperature (environment) and weight during the goat maturation cycle to establish homeostasis (Singh et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). However, the findings were previously reported by (Sanusi et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) for WAD goats. Pulse rate was significantly affected by dietary intake (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) of 100%DS (78.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42 beats/minute) compared to diets 50%DS\u0026thinsp;+\u0026thinsp;50%GH (77.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51 beats/min) and 50%DS\u0026thinsp;+\u0026thinsp;50%CH (76.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43 beats/min). This heart rate change was reported by (Ogebe et al.1996) that speed at which the heart pumps blood throughout the body, hence the pumping rate of blood in goats on 100% DS diet was higher than diets 50%DS\u0026thinsp;+\u0026thinsp;50%GH and 50%DS\u0026thinsp;+\u0026thinsp;50%CH. Thermal stress index values ​​of goats fed 100% DS, 50% DS\u0026thinsp;+\u0026thinsp;50%GH and 50%DS\u0026thinsp;+\u0026thinsp;50%CH diets were found to be 1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03, 1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 and 1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03, respectively. The highest heat stress value was obtained when fed 50% DS\u0026thinsp;+\u0026thinsp;50% CH diet, though not significantly different with others, the results were in line with (Okoruwa et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), who found that temperature and pulse rate are utilized in assessing the physiological condition and adaptability of domestic animals in challenging situations.\u003c/p\u003e \u003cp\u003eThe influence of sex on thermo-physiology indices in the present study is in agreement with the findings of (Timveh et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) who reported that sex affected pulse rate and heat stress index. The authors reported that pulse rate was higher in a female (54.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24 versus 53.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24) which varies from the present study in which pulse rate in male was higher than their female counterparts in the study. Meanwhile, the higher heat stress index in male in the present study is similar with the finding of (Timveh et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) who reported higher heat stress index in males (2.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03) than female goats (2.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03). The male goats had higher rectal temperature, pulse rate, respiratory rate and male goats showed to be more stressed based on heat stress index. This agrees with the finding of (Facanha et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) who reported that goats subjected to heat stress were found to have an increased respiratory rate, which is a dependable indicator of heat load and thermal stress (Okoruwa et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Female small ruminants seem to handle heat stress better than their male counterparts, even though both sexes are affected by it as reported by (Schoenian \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to (Helal et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Sanusi et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) have indicated that in harsh environments, rectal temperature, respiratory rate, and blood indices are the most effective thermo-physiological parameters for objectively monitoring animal welfare. As observed in the present study, the highest rectal temperature in WAD\u0026times;50%DS\u0026thinsp;+\u0026thinsp;50%GH could signify the presence of diseases such as \u003cem\u003ePeste des Petits Ruminants\u003c/em\u003e (PPR) or other infectious diseases prevalent in Nigeria. These diseases can cause fever as one of the primary symptoms. The significantly high pulse rate (PR) and respiratory rate (RR) in RS\u0026times;100%DS over others could mean that the Red Sokoto goats fed 100% \u003cem\u003eDigitaria smutsii\u003c/em\u003e may have different nutritional content compared to cowpea and groundnut husk and if it lacks essential nutrients or is imbalanced, goats may experience physiological stress, leading to increased heart and breathing rates. Other possible reason could be that the digestibility of \u003cem\u003eDigitaria smutsii\u003c/em\u003e might be lower than that of cowpea and groundnut husk (Wulandari et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Poor digestibility can result in longer retention time in the digestive system, leading to discomfort and increased metabolic activity, which can manifest as higher pulse and respiratory rates as observed in the present study. Furthermore, \u003cem\u003eDigitaria smutsii\u003c/em\u003e may have higher fibre content, which could lead to increased fermentation in the rumen (Sani et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This fermentation process produces gases and heat as by-products, which can increase metabolic activity and subsequently raise pulse and respiratory rates.\u003c/p\u003e \u003cp\u003eThe breed \u0026times; sex relationship in this study is similar to the relationship suggested by (Timveh et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) who reported that there was no significant difference in rectal temperature, pulse rate, respiratory rate, and body temperature between animals and gender. In contrast, the current study found that breed \u0026times; sex had an effect on rectal temperature, with WAD males experiencing the highest rectal temperature. This suggests that the animal will experience discomfort and distress, which will have an impact on their overall well-being, behaviour, and productivity in terms of growth, reproduction, or performance. The no significant difference in the present study in PR, RR and HSI implies that both male and female goats across different breeds have similar thermoregulatory capabilities. This uniformity in adaptation can be advantageous in environments with fluctuating temperatures as it ensures that goats of different breeds and sexes can cope similarly with heat or cold stress. Also, the lack of significant differences may indicate that thermoregulatory mechanisms are highly conserved among different goat breeds and sexes. This suggests a level of genetic resilience within the goat population, enabling them to maintain stable body temperature regardless of breed or sex differences (Daramola et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe significantly higher rectal temperature, pulse rate, respiratory rate (RR) and heat stress index in 100%DS \u0026times;male over others could mean that the male goats fed 100% \u003cem\u003eDigitaria smutsii\u003c/em\u003e may have different nutritional content compared to cowpea and groundnut husk and if it lacks essential nutrients or is imbalanced, goats may experience physiological stress, leading to increased heart and breathing rates as well as heat stress. Also, it could be that the digestibility of \u003cem\u003eDigitaria smutsii\u003c/em\u003e might be lower than that of cowpea and groundnut husk (Wulandari et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Poor digestibility can result in longer retention time in the digestive system, leading to discomfort and increased metabolic activity, which can manifest as higher pulse and respiratory rates as observed in the present study. Furthermore, \u003cem\u003eDigitaria smutsii\u003c/em\u003e may have higher fibre content, which could lead to increased fermentation in the rumen (Sani et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This fermentation process produces gases and heat as by-products, which can increase metabolic activity and subsequently raise pulse rate, rectal temperature, and respiratory rates and heat stress as observed in the present study. However, the lower heat stress index in 50%DS\u0026thinsp;+\u0026thinsp;50%GH \u0026times; female could be that groundnut haulms may contain components that have a calming or stress-reducing effect which in turn can lead to lower heat stress index (Chimmad et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe no difference could be that thermoregulatory mechanisms are highly conserved among different goat breeds fed different diets and of different sexes. This suggests a level of genetic resilience within the goat population, enabling them to maintain stable body temperature regardless of breed, diet and sex differences (Daramola et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The breed \u0026times; diet \u0026times;sex interaction effect in the present study showed no significant effect in all the thermo-physiology indices and this is same to the finding of (Timveh et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) who reported no significant difference between breed \u0026times; sex on rectal temperature, pulse rate, respiratory rate and heat stress index. The possible reason for no variation controlled environmental conditions where factors such as temperature, humidity, and ventilation were consistent for all the breeds, diets and both sexes of goats. When environmental conditions are standardized, it can minimize the impact of external factors on physiological parameters. Also, all the goats in the study received similar diets. Therefore, breed or sex, there may not have been significant differences in physiological responses. Also, sometimes, even if there are differences between groups, the sample size might not be large enough to detect those differences statistically.\u003c/p\u003e"},{"header":"CONCLUSION AND RECOMMENDATIONS","content":" \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003cp\u003eIt can be concluded that the goats are effectively managing their thermal environment and are likely in good health and the goats experienced little or moderate heat stress, which is crucial for maintaining productivity, growth, and overall well-being. When considering management strategies or interventions related to pulse rate and respiratory rate, factors such as breed and diet should be taken into account. Any of the breeds and diets is recommended since the two factors were not influenced by heat stress index (HSI). However, regards sex, female goats had ability to handle heat stress than their male counterparts and are therefore recommended.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors’ contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConceptualization and design of the experiment:\u0026nbsp;\u003c/strong\u003eMallam, Iliya; Yakubu, Abdulmojeed;Ari, Maikano Mohammed; Musa, Ibrahim Suleiman and Achi, Neyu Patrick\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterial preparation:\u0026nbsp;\u003c/strong\u003eMallam, Iliya; Yakubu, Abdulmojeed;Ari, Maikano Mohammed; Musa, Ibrahim Suleiman and Achi, Neyu Patrick\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Data collection and analysis:\u0026nbsp;\u003c/strong\u003eMallam, Iliya and Yakubu, Abdulmojeed\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe first draft of the manuscript was written by:\u0026nbsp;\u003c/strong\u003eMallam, Iliya and Yakubu, Abdulmojeed\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAll authors read and approved the final manuscript.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors sincerely thank the Tertiary Education Trust Funds (TETFund), Nigeria through local Ph.D. grant awarded by the Kaduna State University, Kaduna for the fund.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was funded by the TETFund, Nigeria through local Ph.D. grant awarded by the Kaduna State University, Kaduna.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimal ethics statement with an approval number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research work was carried out according to the ethical guideline and obtained ethics approval from the Committee for Ethical and Responsible Conduct of Research (ABUACAUC/2017/004) of National Animal Production Research Institute (NAPRI), Zaria.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eElectronic supplementary material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis will be made available on request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAjayi DA, Adewumi MK, Okunlola OO (2010) Physiological response of WAD sheep to ambient environmental temperature changes in humid tropics of South West Nigeria. \u003cem\u003eProceedings of 35th Conference of Nigeria Society for Animal Production\u003c/em\u003e, University of Ibadan Nigeria Pp. 110\u0026ndash;112\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlam MM, Hashem MA, Rahman MM, Hossain MM, Haque MR, Sobhan Z, Islam MS (2011) Effect of heat stress on behavior, physiological and blood parameters of goat. 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Int J Sci Eng Sci 3(2):6\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ijses.com/wp-content/uploads/2019/03/75-IJSES-V3N2.pdf\u003c/span\u003e\u003cspan address=\"http://ijses.com/wp-content/uploads/2019/03/75-IJSES-V3N2.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"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":"Breed, diet, sex, thermo-physiology, Nigerian goats","lastPublishedDoi":"10.21203/rs.3.rs-5746207/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5746207/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe understanding of complex interplay between breed, diet and sex on thermo-physiology is crucial for developing effective strategies to manage heat stress in Nigerian goat production. This experiment was conducted to study the effects of breed, diet, sex and their interactions on thermo-physiology response of Nigerian goats. A total of 36 weaner goats of two breeds (West African dwarf, n\u0026thinsp;=\u0026thinsp;18; 9 males\u0026thinsp;+\u0026thinsp;9 females) and Red Sokoto goats, n\u0026thinsp;=\u0026thinsp;18; 9 males\u0026thinsp;+\u0026thinsp;9 females) of about 3\u0026ndash;4 months of age were used for the experiment. A 2\u0026times;3\u0026times;2 factorial experiment comprising 2 breeds, 3 diets groups and 2 sexes in a completely randomized design. Data collected were the rectal temperature, pulse rate, respiratory rate, maximum and minimum ambient temperature (\u0026deg;C) and relative humidity (%) and the average values were used to calculate temperature-humidity index and the heat stress index was also calculated. The fixed and interaction effects of data collected were analysed using Statistix Analytical software version 8.0 while excel package was used for graphical representation of the temperature-humidity index and significant means were separated using Duncan\u0026rsquo;s Multiple Range Test. The effect of breed on thermo-physiological indices of goats revealed that breed had significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) effect on pulse rate and respiratory rate. Diet showed significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) effect on rectal temperature (RT), pulse rate and respiratory rate. Male goats had higher (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) thermo-physiology indices compared to females. It can be concluded that the experimental goats experienced little or moderate heat stress, which is crucial for maintaining productivity, growth, and overall well-being.\u003c/p\u003e","manuscriptTitle":"Effects of Breed, Diet and Sex on Thermo-physiology of Nigerian Goats","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-05 15:31:50","doi":"10.21203/rs.3.rs-5746207/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":"be34264a-9c1d-4c68-8c45-4138596916a1","owner":[],"postedDate":"March 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-31T14:51:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-05 15:31:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5746207","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5746207","identity":"rs-5746207","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}