dc.contributor.advisor |
Van Marle-Koster, Este |
|
dc.contributor.coadvisor |
Meissner, H.H. |
|
dc.contributor.postgraduate |
Gresse, Anton Ulendo |
|
dc.date.accessioned |
2019-07-08T09:46:55Z |
|
dc.date.available |
2019-07-08T09:46:55Z |
|
dc.date.created |
2019/04/17 |
|
dc.date.issued |
2018 |
|
dc.description |
Dissertation (MSc (Agric))--University of Pretoria, 2018. |
|
dc.description.abstract |
Globally, dairy producers are employing precision farming practices and incorporating computer software that enables producers to manage large herds at an individual animal level. South African dairy producers have been adopting similar strategies with a trend towards larger production units and the incorporation of automatic milking systems. The software employed in automatic systems record production, reproduction and health parameters on a daily basis. These systems record all variables and movements of individual animals, from the day of birth to the day the cow exits the herd. The majority of producers using automatic milking systems do not participate in national recording. The aim of this study was to perform a production analysis with the primary objective of constructing a template for extracting and analysing herd performance data from producers employing automatic management software in South Africa. Two large dairy herds, representing a TMR system, and a pasture-based production system participated in the study. Producers installed the AfiFarm herd management software from S.A.E Afikim, Kibbutz, Israel. By extracting animal records from multiple years, comprehensive data tables were constructed for different production analyses. Analyses included time-trend evaluation of herd numbers, mean production and reproduction performance at the heifer and cow level, distribution of exit reasons and assessing the relationship between the genetic merit of sires and the mean performance of their progeny. Findings from this study confirm that the AfiFarm herd management software permit extraction and analyses of multiple variables imperative to dairy management at the herd and cow level. The software has the potential to serve as a platform to add a vast number of dairy cow performance records for future analyses. |
|
dc.description.availability |
Unrestricted |
|
dc.description.degree |
MSc (Agric) |
|
dc.description.department |
Animal and Wildlife Sciences |
|
dc.identifier.citation |
Gresse, AU 2018, Alternative approaches for analyses of production performance from automatic milking systems in South Africa, MSc (Agric) Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/70581> |
|
dc.identifier.other |
A2019 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/70581 |
|
dc.language.iso |
en |
|
dc.publisher |
University of Pretoria |
|
dc.rights |
© 2019 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. |
|
dc.subject |
UCTD |
|
dc.title |
Alternative approaches for analyses of production performance from automatic milking systems in South Africa |
|
dc.type |
Dissertation |
|