The production environment is known to have a large influence on extensively managed beef cows. A better understanding of the relationship between the beef cow and her environment should be useful in the pursuit of improving beef cow efficiency. The influence of the production environment on the efficiency of extensively managed Bonsmara cows was investigated through a series of research objectives. It was found that VEGMAP’s bioregion classification system can be used to describe the South African beef production regions. The environmental characteristics with the potential to influence beef cow efficiency were identified as temperature, rainfall, cation exchange capacity, soil pH, soil organic carbon, soil P and grazing capacity. A dataset was created that contains the historical cow production records for every Bonsmara breeder. GIS tools were then used to link the cow production records with the production region in which the farm is located, as well as the environmental characteristics for that specific location. The combined dataset was then statistically analysed to investigate the research objectives. The influence of the geographic location, production region and breeder on Bonsmara production traits was investigated by cluster analysis and ANOVA. Results from ANOVA indicate that production region has a statistically significant (p < 0.05) influence on production traits. The influence of the breeders on the same production traits was, however, statistically much larger (p < 0.0001) than production region. Bonsmara production traits are therefore influenced to a greater extent by the breeders rather than production environment. Stepwise regression analysis was used to determine the influence of the combined environment on production traits. The combined environment has a statistically significant (p < 0.0001) influence on all the production traits. The results indicate that the extent of the influence of the environment on production change through the growth curve. The environment’s influence was the greatest at weaning (9%) and yearling age (10%). Bonsmara weaning and yearling weights therefore show the largest potential for manipulation through management. The influence of individual environmental characteristics on all the Bonsmara cow production traits was then investigated by the same stepwise regression analysis. Most of the environmental characteristics were found to have a statistically significant (p < 0.0001) influence on the production traits. Rainfall and temperature had the largest influence on Bonsmara production traits. The negative influence of rainfall was attributed to the influence of rainfall on the quality of the grazing. The influence of temperature on production traits was small. The small negative influence of temperature could indicate that Bonsmara cows are well adapted to the main South African beef production regions. Finally, the relationship between Bonsmara cow size and reproduction was investigated by linear regression analysis. Results indicate that larger Bonsmara cows are to some extent more reproductive than smaller cows. The study confirmed that production environment influences beef cow efficiency. Bonsmara breeders however have a much larger influence on the efficiency of their cows through the implementation of management practices and breeding objectives. / Dissertation (MSc(Agric))--University of Pretoria, 2012. / Animal and Wildlife Sciences / unrestricted
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:up/oai:repository.up.ac.za:2263/24963 |
Date | 24 May 2013 |
Creators | Visagie, Pieter Cornelis |
Contributors | Van der Westhuizen, Japie, Webb, E.C. (Edward Cottington), pietervisagie@gmail.com |
Publisher | University of Pretoria |
Source Sets | South African National ETD Portal |
Detected Language | English |
Type | Dissertation |
Rights | © 2012 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria |
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