Review of diagnostic technologies for monitoring feedlot animal health
The Review of diagnostic technologies for monitoring feedlot animal health project undertook a scoping study of current and emerging technologies and systems capable of remotely identifying shy-feeders and cattle with ill-health and their implementation in a feedlot operation.
Summary
The Australian feedlot industry has a production value of approximately AUD $2.7 billion annually, and employs approximately 2000 individuals directly and 7000 individuals indirectly. In a typical feedlot, cattle are monitored daily to identify under-performing animals (e.g. shy-feeders) and animals with ill-health. The high concentration of susceptible livestock in a feedlot and in individual pens provides ideal conditions for the spread of infectious diseases. Health management programs are used to detect illness and injuries, and maintain the health of feedlot cattle. Optimal early detection and transfer of affected cattle to hospital pens for treatment are important components of feedlot health management programs. Over the past 10 years, a number of new technologies have become available to allow animals in pain and animals with abnormal behaviour to be detected earlier without the need for intensive monitoring by highly trained personnel. If these technologies can be applied successfully in an intensive feedlot system, animal welfare and productivity will be improved because sick animals can be identified and treated promptly, and labour costs will be reduced because feedlot staff will no longer be required to carry out intensive daily inspections.
The objective of this review is to conduct a scoping study of current and emerging technologies and systems capable of remotely identifying shy-feeders and cattle with ill-health. It appraises technologies and systems in terms of practical implementation in a feedlot operation, including installation requirements, ability to cope with environmental conditions, proximity to cattle, data storage and processing requirements, relative benefits, and costs associated with their use and implementation. The following three main tasks are identified as important in relation to the implementation of remote diagnostic technologies: i) accurate detection of animals with ill-health, ii) identification (e.g. tag number or electronic ID) of animals with ill-health and iii) transfer of identified animals to the feedlot hospital. Each of these tasks requires different procedures and expertise.
When: 30 May 2014 to 15 May 2015
Contact: John Al-Alawneh, Ahmad R Rabiee, Tim Olchowy, Michael McGowan, Mark A Stevenson, Susanne Clay and Tim McCready
Collaborators: Kahne Limited NZ, University of Melbourne, CowSignals Australia, University of Queensland
More information
To learn about this research, please read the final report summary and download the final report (B.FLT.0240) (PDF, 4.0 MB) from the Meat & Livestock Australia website.