Patterns of heat tolerance in different sheep breeds in Brazil

Patterns of heat tolerance in different sheep breeds in Brazil

Accepted Manuscript Title: Patterns of heat tolerance in different sheep breeds in Brazil Author: Concepta McManus Bruno St´efano Lima Dallago Carla L...

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Accepted Manuscript Title: Patterns of heat tolerance in different sheep breeds in Brazil Author: Concepta McManus Bruno St´efano Lima Dallago Carla Lehugeur Luiz Alberto Ribeiro Potira Hermuche Renato Fontes Guimar˜aes Osmar Carvalho J´unior Samuel Rezende Paiva PII: DOI: Reference:

S0921-4488(16)30271-1 http://dx.doi.org/doi:10.1016/j.smallrumres.2016.10.004 RUMIN 5308

To appear in:

Small Ruminant Research

Received date: Revised date: Accepted date:

30-6-2016 2-10-2016 3-10-2016

Please cite this article as: {http://dx.doi.org/ This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Patterns of heat tolerance in different sheep breeds in Brazil

Concepta McManus1,5, Bruno Stéfano Lima Dallago 1,5*, Carla Lehugeur2, Luiz Alberto Ribeiro 2, Potira Hermuche3, Renato Fontes Guimarães3, Osmar Carvalho Júnior3, Samuel Rezende Paiva4 1

Faculdade de Agronomia e Medicina Veterinária, Universidade de Brasília – UnB, Campus Universitário Darcy Ribeiro, ICC-SUL, Brasília/DF, CEP: 70910-900, Brazil. E-mail: [email protected]; [email protected]

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Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul – UFRGS, Av. Bento Gonçalves 9090, Porto Alegre/RS, CEP: 91.540-000, Brazil. E-mail: [email protected]; [email protected];

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LSIE - Laboratório de Sistemas de Informações Espaciais, Departamento de Geografia, Universidade de Brasília - UnB, Campus Darcy Ribeiro, ICC-Norte, Brasília/DF, CEP: 70910-900, Brazil. E-mail: [email protected]; [email protected]; [email protected]

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Laboratório de Genética Animal, Embrapa Recursos Genéticos e Biotecnologia - CENARGEN, SAIN PqEB, Final Av. W5 Norte, Brasília/DF, CEP: 70770-917, Brazil. E-mail: [email protected]

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Instituto Nacional de Ciência e Tecnologia – Informação Genético-Sanitária da Pecuária Brasileira (CNPq/INCT/IGSPB), Belo Horizonte/MG, Brazil.

*Corresponding author. Fone: 55 61 3107-7122. E-mail: [email protected] 1

Graphical abstract

Highlights 1. We used broken line regression to determine physiological limits by breed; 2. Inflexion points were used to determine regions suitable for sheep rearing by breed; 3. Clear boundaries were found for sheep breeds; 4. Not all breeds are indicated to be reared in all areas of the country; 5. Some regions are unsuitable for any breed.

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Abstract Respiration rate and eye temperature were collected on 80 sheep from 11 breeds (Australian Merino, Polwarth/Ideal, Corriedale, Romney Marsh, Crioula, Hampshire Down, Texel, Ile de France, Suffolk, Santa Inês and Dorper) during 5 days, giving a total of 1071 observations. All sheep were adult and non-lactating. Data were analysed using SAS® procedure NLIN, using broken line regression to determine temperature humidity index (THI), air temperature and relative humidity limits by breed for respiration rate and eye temperature. These inflexion points were then used to determine regions suitable for sheep rearing by breed, using mean THI by municipality which were then plotted using ARCGIS v.9.3. Clear boundaries were found for sheep breeds, with wool breeds mainly limited to the south and southeast as well as coastal areas. Not all breeds are indicated to be reared in all areas of the country and some regions are unsuitable for any breed. Breed adaptation is in line with their natural history of territorially occupation.

Keywords: broke line regression; temperature humidity index; eye temperature; rearing regions.

1.Introduction

The maintenance of body temperature within physiological limits is necessary for the animal to remain healthy and maintain its productivity and longevity (Marai et al., 2007). Thus, animals should cope with their environment in order to produce more and better. Farmers can positively influence this relationship between the animal and environment by selecting animals able to produce efficiently in these environments (Starling et al., 2002), but heat stress impairs 3

their performance (Silanikove, 2000). Severity of heat stress can be measured using both ambient temperature and relative humidity, termed as the temperature–humidity index (THI) (LPHSI, 1990; Marai et al., 2001). Tropical regions can be characterized by higher levels of solar radiation and temperature compared with temperate zones (McManus et al., 2009a), often vastly different from the local of the origin of the breed (McManus et al., 2011). Breed differences have been seen for responses to environmental stressors. An animal is considered to be stressed when it has to alter its physiology and behavior to adapt to adverse environmental and management conditions (Marai et al., 2007). Quesada et al. (2001) showed that it was necessary to know the tolerance and adaptive capacity of various breeds as a technical basis for sheep exploration in a certain region, including direction of crossbreeding programs. Heat tolerance is generally measured based on respiration rate and rectal temperature among others traits (Castanheira et al., 2010; Correa et al., 2012). However, these measurements require direct intervention with the animals, which may influence their physiological responses. Overcoming this obstacle, Paim et al. (2013) studied the use of infrared thermography to measure heat tolerance in lambs of different genetic groups and found the method to be efficient in differentiating between them. Other way to minimize the stress caused by stressful landscape factors is, based in descriptors, to determine regions more suitable to rear one or other breed. Both wool and hair sheep are found in Brazil. Sheep arrived in Brazil from the Iberian Peninsula and African continent with the settlers in the late 15 th century (Primo, 2004). The possible Iberian breeds which came to Brazil early on include Merino, Manchega, Ojalado, Talayerana, Bordalera and Churra. Hair sheep were registered as early as 1640 (Villela et al., 2005). British Lincoln and Romney Marsh breeds were used to the end of the 19 th century for 4

mutton production for the European market. In the 1930s the decreasing demand for sheep meat and increasing wool prices led to the use Australian Merinos, Polwarths and Corriedales, imported from Australia and New Zealand (Cardellino, 2000) as well as Hampshire Down, in the south of the Country as well as Uruguay and Argentina. The importation of meat breeds (Ile-deFrance, Suffolk and Texel) increased in the 1990s. It is known that wool sheep were mainly concentrated in the south and hair sheep remained in the northeast (Hermuche et al., 2012; McManus et al., 2014) of Brazil. The northeastern hair breeds were mainly reared in harsh environments by subsistence farmers, undergoing little selection, while commercial wool and meat sheep tended to be reared in the South. This led to different adaption traits of these breeds. Physiological mechanisms which limit and adjust cold and heat tolerance are regaining interest due to global warming. Shifts in the geographical distribution of animals have also stimulated actions within the Food and Agricultural Organization of the United Nations (Pilling et al., 2008) to attempt to standardize descriptors for animals and their environments. However, farmers are increasingly using terminal sire breeds in diverse environments without taking their adaptation into account. This study aimed to determine differing regions of Brazil that could be more favorable for sheep breeds based in differences in heat adaptation.

2.Material and Methods

Data from eye temperature (Teye ) and respiration rate (RR) were collected on 80 sheep from 11 breeds (ranging from 3 to 8 animals/breed) during 5 days, using a total of 1071 observations (not all sheep were collected at all times). Breeds included Australian Merino (ME), Polwarth/Ideal (ID), Corriedale (COR), Romney Marsh (RM) and Crioula (CRI) for wool 5

sheep. Semi wool sheep included Hampshire Down (HD), Texel (TX), Ile de France (IL) and Suffolk (SU), while hair sheep included Santa Inês (SI) and Dorper (DR). All sheep were adult males (2 to 5 years old). Teye were taken using a FLIR série-I Infrared InfraCAM™ (Wilsonville, USA). The recorded temperature corresponding to the point of maximum temperature observed in the eyeball. The temperature was measured in both eyes and average temperature calculated. The respiratory rate (RR) was assessed by remote inspection of animals by movement of the chest wall and abdomen during breathing and the movements performed in one minute counted. During the evaluation, the animals were at rest and were not sniffing, feeding or ruminating. The air temperature (Tair) and relative humidity (RH) of the shed housing the animals were evaluated at several points at the same time using a digital thermo-hygrometer Incoterm® (Porto Alegre, Brazil). Measurements of the shed conditions - Tair and RH - and the physiological parameters of animals - Teye and RR - were taken concomitant and in three times a day: in the morning between 7 and 9; afternoon between 13 and 15 and night between 18 and 20 hours. For data collection there was no interference in the behavior and physiological responses of animals, the sheep were not handled or disturbed during the experiment. Measurements of respiratory rate and temperature of the surface of the eye were held at a distance of 1m to 1.5m from each animal. Two formulae were used to calculate temperature humidity index of shed house, called THIt (temperature-humidity index by Thom (1959)) and THIm (temperature-humidity index by Marai et al. (2001)):

i)

THIt  0.8  Tair  [( RH / 100)  (Tair  14.3)]  46.4 according to (Thom, 1959) 6

ii) THI m  Tair  [(0.31  0.31 RH / 100)  (Tair  14.4)] according to (Marai et al., 2001)

Where: Tair is the air temperature (ºC); RH is the relative humidity (RH).

Data were analysed using SAS® (v.9.3 Cary, NC, USA) procedure NLIN, using broken line regression to determine THIt, THIm, Tair and RH limits by breed for RR and Teye. The model used was:

yi   0  1 xi   2 xi  x    i   i

Where: yi is the response variable (RR and Teye); β is the regression components; xi are the environmental (Tair, RH, THIt and THIm) observations recorded concomitantly to Teye and RR parameters for each animal at that time; x is the inflexion point of the independent variable (Tair, RH, THIt and THIm); δi = 1 if xi > x and 0 if xi < x; εi = error term for each observation.

Inflexion points calculated for THIm were then used to determine regions suitable for sheep rearing by breed, using mean THI by municipality (here called regional THI or THIr), which were then plotted using ARCGIS v.9.3. The THIr use temperature and humidity previously acquired by remote sensing and data from National Institute of Meteorology 7

(INMET) respectively, and the explanation about this process is in the next paragraph below. Then, this temperature and humidity were applied in the following equation according to McManus et al. (2014) :

THI r  Tair  (0.36  T0 )  41.5

Where: Tair is the air temperature (ºC) T0 is the temperature of the dew point (ºC)

Air temperatures used to calculate THIr were acquired as surface temperature data by remote sensing. The surface temperature data are images from MODIS (Moderate Resolution Imaging Spectro-radiometer) product mod11, which represents the average monthly surface temperature. Relative humidity data used to calculate THIr were from INMET and are the result of the average of a range of approximately 30 years of observations of 283 weather stations distributed throughout the Brazilian territory. Details about the methodology used to establish Tair and RH used to calculate THIr are in McManus et al. (2014). According to Andersen (1997) and Salisbury and Daria (1992), remote sensing is an important tool to obtain surface temperature data (ST) as it works with thermal behaviour of materials, enabling the measurement of radiation energy (Jensen, 2007). This is possible as objects with temperature higher than absolute zero (0 K or -273 ºC) produce and emit electromagnetic energy by particle movements, which is known as “kinetic heat”. There is a high positive correlation between kinetic heat from object and the radiation flow emitted by it (OREGON-DEC, 2003). Thus, the use of remote sensing for these purposes is completely 8

justified. In addition, some works as Prihodko and Goward (1997) and Yan et al. (2009) corroborate with the use of remote sensing as the data measured by weather stations present high positive correlation (reaching, sometimes, 90%) with data estimated by remote sensing. Furthermore, it is worth noting that weather stations present only punctual measurements with limitations in spatial and temporal coverage.

3.Results

Shed environmental conditions (Table 1) presented values outside the comfort zones for sheep as maximum values are too far from that preconized by WMO (1989) as ideal for sheep production.

TABLE 1

According to Marai et al. (2001) the values for THIm indicate the following in Table 2:

TABLE 2

The inflexion point for RR indicates the point (THI t, THIm, Tair or RH) that the animal changes its respiration to compensate for environment changes, while Teye inflexion point is the value where physiological mechanisms no longer can maintain the core temperature under control. Different inflexion points were seen for each independent variable and breed (Table 3), with those for wool sheep generally being lower than for hair sheep, indicating poor adaptation. 9

The hair breeds tended to have faster reactions to increases in THI (both, THIt and THIm) and Tair, as expected. Variation in responses for Dorper, Santa Ines and Ile de France were more varied and in general lower. Inflexion points for Teye were highest in Romney, Merino, Ideal and Suffolk, while Crioula showed lower inflexion points for Teye, although it used respiration at a lower temperature managed to maintain Teye at a low level (Table 3).

TABLE 3

In general, inflexion points of RR and Teye presented ratio lower than 1 for Tair, THIt and THIm. In opposite, inflexion points of RR and T eye for RH presented ratio higher than 1 (Table 4). In addition, correlations between THIt and THIm were significant (P < 0.05) with R² = 0.99.

TABLE 4

Tair, and mainly, the THI have great importance in determining the animal response to heat stress (Figures 1, 2, 3 and 4). This is better seen at higher values, where the response lines are, in general, vertical, showing that few variation in X axis (T air or THIm – according to the figure) modify greatly the Z axis (RR or Teye), instead at lower values where some horizontal variation can be seem. In relation to Teye, no indication exists in the literature as to what T eye is considered “normal”.

FIGURE 1

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FIGURE 2

FIGURE 3

FIGURE 4

There is a band of municipalities running form the midwest to the northeast of the country where many sheep breeds would be under stress on an average day (Figures 5, 6, 7 and 8). A large portion of the northern region is covered by forest and therefore, although adequate environmental conditions exist, is not used for sheep production.

FIGURE 5

FIGURE 6

FIGURE 7

FIGURE 8

4.Discussion

The desire for higher production per animal has led to an increase in the use of terminal breeds to increase lamb weight and carcass quality. Little is known about the adaptation of these 11

breeds for Brazilian conditions, especially where the environment requires higher heat tolerance. The adaptation of sheep breeds to new environments may be either a matter of chance or trial and error - owing to variability of the environment and breed reaction to factors like terrain (Hafez, 1987). Marai et al. (2007) suggested predicting breed adaptation by constructing climographs and comparing similarities in position, shape and area of the patterns formed. However, other factors such as disease and parasite criteria, feed availability, prices of inputs and products and the market situation, have to be considered. Heat tolerance is due to several factors (Marai et al., 2007; McManus et al., 2009b), including genetic composition of the animal, feeding regime and physiological status. Respiration rate can be an indicator of heat stress (Habeeb et al., 1992). Average respiratory rate here were higher than the suggested parameters for sheep in thermoneutral conditions by Marek and Mócsy (1965) and Hales and Webster (1967). The breed of the animals was an important factor in the variation of physiological parameters evaluated. The main mechanisms of heat exchange with the environment used by sheep are by sweating and evaporation through the respiratory tract (Marai et al., 2001), which explains the increase in respiratory rate in periods of high heat. In addition, the difficulty of body heat dissipation has been identified as a major cause of stress in animal production (Silanikove, 2000). Evaporation is the most important avenue for heat dissipation, since sweating in sheep is much less important than respiratory evaporation due to the presence of a wool coat (Marai et al., 2007). The temperature of the surface of the eye (Teye) has a high positive correlation with the animal rectal temperature (Johnson et al., 2011), so the increase in Teye indicates an increase of the internal body temperature. For Tair, THIt and THIm, inflexion points to RR are lower than those for Teye (ratio RR/Teye less than 1 – Table 4), showing that animals use respiratory 12

mechanisms to dissipate this heat increment before core temperature changes. However, for these parameters, Texel showed lower inflexion points for Teye than for RR. This suggests higher sensibility to heat stress as, in thesis, the core temperature begin to increase before changes in physiological mechanisms to alleviate it. On the other hand, the ratio, in general, inverts (ratio RR/T eye greater than 1 – Table 4) for RH. This is usually because relative humidity is lower at higher temperatures, an intrinsec characteristic of part of Brazil where climates is tropical (high temperatures most part of year) but is dry, with low relative humidity. When is wet, the temperature are not so high and the animal does not need to improve their RR to dissipate heat. In turn, this tropical dry climates and the inflexion points to RH just reinforce and highlight the importance of THI in determinig the animal physiological response to heat stress as shown in Figure 1. McManus et al. (2014) pointed that each breed in Brazil has distinct regions where it is reared. The wool breeds are mostly seen in the south and southeast whereas hair breeds are seen in the northeast and midwest. As shown by these authors, each regions has its specific climatic conditions. Breed history can explain the adaptation seen here. Breeds such as Hampshire, Suffolk and Romney are British breeds, selected for cooler climates, while Texel and Ile de France came from continental Europe, with slightly higher adaptation for warmer climates. Corriedale, Merino and Ideal were selected in Australia and New Zealand, for wool production but in harsher environments. Dorper and Santa Ines were developed in South Africa and Brazil respectively, to be resistant to stressful conditions. Nevertheless, these are not suitable for all regions of Brazil. From these, responses areas of the country can be delimited, not only for sheep rearing on general, but also by breed. The Southern region is the region most suitable for all breeds of 13

sheep (Figure 2 and 4). As can be seen some municipalities in the Southern Region are unsuitable even for rearing Suffolk or Texel breeds, while the Santa Ines can be reared in almost all environments. However, there are some regions where sheep cannot be reared. According to Madalena et al. (2002) in the Southern cone of Latin-America, where most of the sheep population is concentrated, an initial period of grading up the local breed (Crioula) to Merino type breeds at the end of the 19th century was followed by a strong predominance of Lincoln and Romney crosses for export mutton meat at the beginning of the 20th century. Then, there was a subsequent period of alternated crossbreeding with Merino or Lincoln and Romney rams, depending on market trends for wool or mutton meat. In the 1930s and 1940s, a process of grading-up to pure breeds was initiated, the Merino, Romney, Corriedale and Polwarth being preferred in different sub-regions, which led to the disappearance of the local types and the present predominance of the wool or dual-purpose breeds. During the 20th Century, breeds for wool and double purpose breeds such as Australian Merino, Ideal (Polwarth), Corriedale and Romney Marsh were imported from their countries of origin and from Uruguay and Argentina, replacing by repeated back crossing the original Creole sheep populations (Cardellino, 2000). The first meat breed to be imported was Hampshire Down, followed by Texel, Suffolk and Ilede-France, and most recently limited numbers of Poll Dorset, Polypay and Laucane. Indigenous livestock that have evolved over the centuries in the diverse, often stressful tropical environments, have a range of unique adaptive traits (e.g. disease resistance, heat resistance, water tolerance, ability to cope with poor quality feed, etc.) which enable them to survive and be productive in these environments (Fitzhugh and Bradford, 1983; Devendra, 1987; Baker and Rege, 1994). A detailed assessment of breed adaptability is not available, and “adaptability” is inferred by measuring total flock productivity, efficiency or net benefits of different breeds (Fitzhugh and Bradford, 1983; Bosman et al., 1997; Ayalew et al., 2003). 14

Most indigenous sheep in the tropics are thought to be well adapted to their stressful environments but farmers see them as unproductive because of their small size and slow growth rates. This led to importation of exotic breeds, which are assumed to be more productive based on their performances in their temperate environments of origin which are generally less stressful. Often they cannot even survive in the tropical environments into which they are introduced. Although some development agencies are now appreciating the importance of an integrated systems approach to livestock improvement in the tropics (e.g. Ayalew et al. (2003)) this has been the exception rather than the rule. Obviously THI is not the only factor which limits the use of a breed in a certain situation. Other questions such as feed availability and quality, shelter, precipitation, disease challenges market demands, work force availability among others need to be taken into account. Nevertheless this is a first attempt to zone sheep production by breed in Brazil.

5.Conclusions There is need to re-evaluate thermal limits for sheep breeding in Brazil, especially hair sheep. A validation test in field would be interesting to confirm the results showed here, especially due the other factors involved in field conditions as for example, disease challenges and feed availability.

Acknowledgements INCT – Pecuária for scholarships and CNPq for financing and scholarships. To professor David Ayron Assen and to DVM João Paulo Barbosa and DVM José Jivago Rolo for cooperation with final figures.

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Figure Captions

Figure 1. Effect of Tair (air temperature) and RH (relative humidity) on RR (respiration rate) in sheep reared in Brazil by breed.

Figure 2. Effect of Tair (air temperature) and RH (relative humidity) on Teye (eye temperature) in sheep reared in Brazil by breed.

Figure 3. Effect of THIm (temperature-humidity index) and RH (relative humidity) on RR in sheep reared in Brazil by breed.

Figure 4. Effect of THIm (temperature-humidity index) and RH (relative humidity) on Teye (eye temperature) in sheep reared in Brazil by breed.

Figure 5. Cartograms of Brazil (with State boundaries) presenting the limits by breed for RR (respiration rate). SU – Suffolk; RM – Romney; HD – Hampshire; CRI – Crioula; IL – Ile de France; TX – Texel; COR – Corriedale; ID – Ideal; ME – Merino; DR – Dorper; SI – Santa Inês.

Figure 6. Concatenated cartogram of Brazil (with State boundaries) presenting the limits by breed for RR (respiration rate). Colors indicate limits by breed - lowest tolerance to highest tolerance according to “cold” to “hot” colors. For example: white regions indicate that there is 21

no breed tolerant to those regions. Most intense red regions indicate that only SI sheep are tolerant to those regions but SI are still tolerante to “colder” coloured regions. SU – Suffolk; RM – Romney; HD – Hampshire; CRI – Crioula; IL – Ile de France; TX – Texel; COR – Corriedale; ID – Ideal; ME – Merino; DR – Dorper; SI – Santa Inês.

Figure 7. Cartograms of Brazil (with State boundaries) presenting the limits by breed for Teye (temperature of eye). SU – Suffolk; RM – Romney; HD – Hampshire; CRI – Crioula; IL – Ile de France; TX – Texel; COR – Corriedale; ID – Ideal; ME – Merino; DR – Dorper; SI – Santa Inês.

Figure 8. Concatenated cartogram of Brazil (with State boundaries) presenting the limits by breed for Teye (temperature of eye). Colors indicate limitations by breed - lowest tolerance to highest tolerance according to “cold” to “hot” colors. For example: blue regions indicate the boundarie regions where Romney (the breed with the lowest tolerance) tolerates the climatic conditions according to calculated limits for T eye. Most intense red regions indicate that only SI sheep are tolerant to those regions but SI are still tolerante to “colder” coloured regions. SU – Suffolk; RM – Romney; HD – Hampshire; CRI – Crioula; IL – Ile de France; TX – Texel; COR – Corriedale; ID – Ideal; ME – Merino; DR – Dorper; SI – Santa Inês.

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Figure 8

Table 1. Mean, standard deviation (SD), minimum and maximum values of environment into the shed housing. Parameters Mean SD Minimum Maximum Tair (ºC) 21.75 5.73 14.00 35.10 RH (%) 58.21 13.51 40.50 81.00 THIm 20.65 4.71 14.02 31.44 THIt 67.68 7.04 57.36 83.42 Tair – air temperature; RH – relative humidity; THIm – temperature-humidity index according to Marai et al. (2001); THIt – temperature-humidity index according to Thom (1959); SD – standard deviation. Table 2. Temperature limits for stress according to Marai et al. (2001). Temperature (ºC) Heat Stress < 22.2 Absent 22.2 to < 23.3 Moderate 23.2 to < 25.6 Severe ≥ 25.6 Extreme severe

Table 3. Inflexion points for Tair, RH, THIt and THIm of broken line analysis for RR and Teye by sheep breed. RR

Teye Tair RH THIt THIm Tair RH THIt THIm Corriedale Wool 23.50 60.00 70.57 22.37 24.24 56.28 71.40 22.91 Crioulo Wool 22.82 62.50 69.99 21.84 23.68 55.12 70.51 22.39 Dorper Hair 24.51 62.50 72.48 23.33 25.55 59.92 73.58 24.16 Hampshire Semi wool 22.47 61.41 69.40 21.50 23.85 57.06 70.93 22.59 Ideal Wool 23.52 63.00 71.01 22.47 25.21 54.23 72.48 23.68 Ile de France Semi wool 23.17 60.00 70.28 22.08 24.50 58.61 71.99 23.20 Merino Wool 24.19 60.00 71.89 22.98 24.59 66.93 72.96 23.55 Romney Wool 22.15 61.76 68.96 21.23 22.54 58.54 69.26 21.49 Santa Inês Hair 25.21 61.97 73.36 23.94 26.45 57.42 74.52 24.86 Suffolk Semi wool 21.79 62.50 68.67 20.93 22.89 56.07 69.53 21.73 Texel Semi wool 23.25 60.87 70.43 22.18 23.11 57.42 69.94 21.96 Overall 23.33 61.50 70.64 22.26 24.24 57.96 71.55 22.96 RR – relative humidity; Teye – eye temperature; Tair – air temperature; RH – relative humidity; THIt – temperature-humidity index according to Thom (1959); THIm – temperature-humidity index according to Marai et al. (2001); Breed

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Table 4. Ratio between RR and Teye by sheep breed. RR/Teye Tair RH THIt THIm Corriedale Wool 0.969 1.066 0.988 0.976 Crioulo Wool 0.963 1.133 0.992 0.975 Dorper Hair 0.959 1.043 0.985 0.965 Hampshire Semi wool 0.942 1.076 0.978 0.951 Ideal Wool 0.932 1.161 0.979 0.948 Ile de France Semi wool 0.945 1.023 0.976 0.951 Merino Wool 0.983 0.896 0.985 0.975 Romney Wool 0.982 1.055 0.995 0.987 Santa Inês Hair 0.953 1.079 0.984 0.962 Suffolk Semi wool 0.951 1.114 0.987 0.963 Texel Semi wool 1.006 1.060 1.007 1.010 Overall 0.962 1.061 0.987 0.969 RR – relative humidity; Teye – eye temperature; Tair – air temperature; RH – relative humidity; THIt – temperature-humidity index according to Thom (1959); THIm – temperature-humidity index according to Marai et al. (2001); Breed

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