Please use this identifier to cite or link to this item:
Title: New ways of measuring intake, efficiency and behaviour of grazing livestock
Contributor(s): Greenwood, Paul (author); Valencia, Philip (author); Overs, Leslie (author); Paull, David R (author); Purvis, Ian W (author)
Publication Date: 2014
DOI: 10.1071/an14409
Handle Link:
Abstract: Wireless sensor networks (WSN) offer a novel method for measuring important livestock phenotypes in commercial grazing environments. This information can then be used to inform genetic parameter estimation and improve precision livestock management. Arguably, these technologies are well suited for such tasks due to their small, non-intrusive form, which does not constrain the animals from expressing the genetic drivers for traits of interest. There are many technical challenges to be met in developing WSN technologies that can function on animals in commercial grazing environments. This paper discusses the challenges of the software development required for the collection of data from multiple types of sensors, the management and analyses of the very large volumes of data, determination of which sensing modalities are sufficient and/or necessary, and the management of the constrained power source. Assuming such challenges can be met however, validation of the sensor accuracy against benchmark data for specific traits must be performed before such a sensor can be confidently adopted. To achieve this, a pasture intake research platform is being established to provide detailed estimates of pasture intake by individual animals through chemical markers and biomass disappearance, augmented with highly annotated video recordings of animal behaviours. This provides a benchmark against which any novel sensor can be validated, with a high degree of flexibility to allow experiments to be designed and conducted under continually differing environmental conditions. This paper also discusses issues underlying the need for new and novel phenotyping methods and in the establishment of the WSN and pasture intake research platforms to enable prediction of feed intake and feed efficiency of individual grazing animals.
Publication Type: Journal Article
Source of Publication: Animal Production Science, 54(10), p. 1796-1804
Publisher: CSIRO Publishing
Place of Publication: Australia
ISSN: 1836-5787
Field of Research (FOR): 070204 Animal Nutrition
070203 Animal Management
070201 Animal Breeding
Socio-Economic Outcome Codes: 970106 Expanding Knowledge in the Biological Sciences
830301 Beef Cattle
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Statistics to Oct 2018: Visitors: 284
Views: 712
Downloads: 1
Appears in Collections:Journal Article

Files in This Item:
2 files
File Description SizeFormat 
Show full item record


checked on Nov 30, 2018

Page view(s)

checked on May 2, 2019
Google Media

Google ScholarTM



Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.