SciELO - Scientific Electronic Library Online

vol.46 issue4Blood profiles of indigenous Pedi goats fed varying levels of Vachellia karroo leaf meal in Setaria verticillata hay-based dietEffect of taurine and bile acid supplementation and their interaction on performance, serum components, ileal viscosity and carcass characteristics of broiler chickens author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand



Related links

  • On index processCited by Google
  • On index processSimilars in Google


South African Journal of Animal Science

On-line version ISSN 2221-4062
Print version ISSN 0375-1589


WILLIAMS, R.; SCHOLTZ, M. M.  and  NESER, F. W. C.. Geographical influence of heat stress on milk production of Holstein dairy cattle on pasture in South Africa under current and future climatic conditions. S. Afr. j. anim. sci. [online]. 2016, vol.46, n.4, pp.441-447. ISSN 2221-4062.

Heat stress, as a consequence of global warming, can have a profound effect on dairy cattle in South Africa. In this paper, current milk production data of Holstein dairy herds on pasture in South Africa, together with climate variables related to heat stress, were used to model and identify geographical areas for optimal milk production under current and future climatic conditions. To model the influence of heat stress on milk production of Holstein dairy herds on pasture in South Africa, the maximum entropy (Maxent) modelling technique was used in a novel approach to model and map optimal milk-producing areas. Geographical locations of farms with top milk-producing Holstein herds on pasture were used as presence-only data points. Only three of a possible eight climate variables that made significant contributions to the model were included, namely evaporation rate, relative humidity and mean annual temperature. The modelling technique showed good capability to capture the geographical influence of heat stress on milk production of Holstein dairy cattle and to reconstruct this relationship in sites where no data were available. The method performed well with low test omission rates, an area under curve (AUC) value of 0.929, and mean training data predictive rate of 0.66 (SD = 0.13). The modelled map indicated optimal milk production areas in the eastern parts of South Africa, which correlates well with the geographical influence of heat stress as represented by the temperature humidity index for the country. Future climate change projections (2046-2065) were used to predict optimal milk-producing areas for the future, indicating progressive shrinking of currently suitable areas and a geographical shift towards the southern parts of the east coast of South Africa. Possible long-term viable alternatives are suggested, including changes in nutrition and replacing existing breeds with more heat tolerant genotypes.

Keywords : climate change; climate variables; Maxent modelling; temperature-humidity index.

        · text in English     · English ( pdf )


Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License