Assessing the heat tolerance of 17 beef cattle genotypes

作者:Gaughan J B*; Mader T L; Holt S M; Sullivan M L; Hahn G L
来源:International Journal of Biometeorology, 2010, 54(6): 617-627.
DOI:10.1007/s00484-009-0233-4

摘要

Cattle production plays a significant role in terms of world food production. Nearly 82% of the world's 1.2 billion cattle can be found in developing countries. An increasing demand for meat in developing countries has seen an increase in intensification of animal industries, and a move to cross-bred animals. Heat tolerance is considered to be one of the most important adaptive aspects for cattle, and the lack of thermally-tolerant breeds is a major constraint on cattle production in many countries. There is a need to not only identify heat tolerant breeds, but also heat tolerant animals within a non-tolerant breed. Identification of heat tolerant animals is not easy under field conditions. In this study, panting score (0 to 4.5 scale where 0 = no stress and 4.5 = extreme stress) and the heat load index (HLI) [HLI(BG < 25A degrees C) = 10.66 + 0.28 x rh + 1.30 x BG - WS; and, HLI (BG > 25A degrees C) = 8.62 + 0.38 x rh + 1.55 x BG - 0.5 x WS + e((2.4 - WS)), where BG = black globe temperature ((o)C), rh = relative humidity (decimal form), WS = wind speed (m/s) and e is the base of the natural logarithm] were used to assess the heat tolerance of 17 genotypes (12,757 steers) within 13 Australian feedlots over three summers. The cattle were assessed under natural climatic conditions in which HLI ranged from thermonuetral (HLI < 70) to extreme (HLI > 96; black globe temperature = 40.2A degrees C, relative humidity = 64%, wind speed = 1.58 m/s). When HLI > 96 a greater number (P < 0.001) of pure bred Bos taurus and crosses of Bos taurus cattle had a panting score a parts per thousand yenaEuro parts per thousand 2 compared to Brahman cattle, and Brahman-cross cattle. The heat tolerance of the assessed breeds was verified using panting scores and the HLI. Heat tolerance of cattle can be assessed under field conditions by using panting score and HLI.

  • 出版日期2010-11