No abstract

Adaptability can be evaluated by the ability of an animal to adjust to environmental conditions and is especially important in extreme weather conditions such as that found in tropical Brazil. A multivariate analysis using physical and physiological traits in exotic (Nellore and Holstein) and naturalized (Junqueira, Curraleira, Mocho Nacional, Crioula Lageana, and Pantaneira) cattle breeds was carried out in the Federal District of Brazil to test and determine which traits are important in the adaptation of animal to heat stress as well as the ability of these traits and statistical techniques to separate the breeds studied. Both physical and physiological traits were measured on three occasions and included body measurements, skin and hair thickness, hair number and length, pigmentation, sweat gland area as well as heart and breathing rates, rectal temperature, sweating rate, and blood parameters. The data underwent multivariate statistical analyses, including cluster, discriminate, and canonical procedures. The tree diagram showed clear distances between the groups studied, and canonical analysis was able to separate individuals in groups. Coat traits explained little variation in physiological parameters. The traits which had higher discriminatory power included packed cell volume, shoulder height, mean corpuscular volume, body length, and heart girth. Morphological and physiological traits were able to discriminate between the breeds tested, with blood and size traits being the most important. More than 80% of animals of all breeds were correctly classified in their genetic group.

Heat stress is considered a limiting factor for sheep production. We used information from physiological characteristics linked to heat tolerance to determine whether infrared thermography temperatures were able to separate groups of animals and determine the most important variables in this differentiation. Forty-eight four-month-old male lambs from eight genetic groups were used. Physiological (rectal temperature–RT, heart rate–HR, respiratory rate–RR) and blood traits, infrared thermography temperatures, heat tolerance indices, body measurements, weight and carcass traits were measured. Statistical analyses included variance, correlations, factor, discrimination and regression. Observing the correlations between physiological characteristics (RT, RR and HR) with temperatures measured by infrared thermography, regions for further studies should include the mean temperature of flank, nose and rump. Results show that there are strong relationships between thermograph measurements and RR, RT and HR in lambs, which are suggested to be directly correlated with heat tolerance capacity of the different genetic groups evaluated in this study. The assessment of body surface temperature measured by the thermograph could be used as a noninvasive tool to assess heat tolerance of the animals.

The animal and its environment make up an integrated system, where each acts on the other. Tropical regions are characterized by high levels of solar radiation and environmental temperature which may adversely affect animal production. This study carries out a multivariate analysis of physical and physiological traits in sheep in the Federal District of Brazil to test the ability to separate groups of animals and determine which traits are most important in the adaptation of animal to heat stress. The variables studied included coat thickness, number and length of hairs, pigmentation of the skin and coat, number of sweat glands as well as heart and respiratory rates, rectal and skin temperatures, sweating rate, and blood parameters. Five groups of ten animals were used depending on breed (Bergamasca, crossbred, or Santa Inês) or coat color (Santa Inês--brown, white, and black). The data underwent multivariate statistical analyses including cluster, discriminate, and canonical, using Statistical Analysis System--SAS®. The tree diagram showed clear distances between groups studied and canonical analysis was able to separate individuals in groups, especially Bergamasca and white Santa Inês. The canonical correlation redundancy analysis showed that coat reflectance as well as hair length and number of hairs per unit area were the most useful in explaining changes in physiological traits. Skin and coat traits such as hair length, coat reflectance, percentage of epithelial area occupied by sweat glands, skin reflectance and thickness, as well as heart and breathing rates were the most important in separating these groups.