MEAT & Livestock Australia (MLA) and Australian Wool Innovation (AWI) have released a range of new resources to help producers scan and manage pregnant ewes.<\/p>\n
The new resources are the result of a multi-year co-investment between MLA and AWI aimed at improving lamb survival and reproductive rates in the Australian sheep flock through better adoption of pregnancy scanning.<\/p>\n
The background research was completed by The University of Adelaide and included many industry consultants in the project team.<\/p>\n
In 2018, an MLA-funded survey of Australian sheep producers determined that 69 per cent of respondents did not pregnancy scan their ewe flocks for litter size.<\/p>\n
According to project manager for sheep and goat productivity at MLA, Dr Daniel Forwood, this limits a producer’s capacity to maximise lamb and ewe survival.<\/p>\n
“Pregnancy scanning is a vital tool for improving sheep reproductive performance \u2013 it enables identification of litter size early in pregnancy, so that multiple-bearing ewes can be differentially managed to meet recommended condition score targets and increase survival,” Dr Forwood said. Research shows pregnancy scanning in sheep provides an average increase in profit of $5.55 for each ewe scanned.<\/p>\n
By customising ewe nutrition during pregnancy and lactation according to whether ewes are carrying singles or multiples, producers can help to reduce lamb and ewe mortality.<\/p>\n
As part of the project, AWI general Manager for Research, Bridget Peachey, said that AWI and MLA conducted an extensive benefit\/cost analysis on the value of scanning across a range of sheep producing regions and enterprise types.<\/p>\n
“In addition, the two organisations undertook a series of grower interviews and surveys to create a better understanding of the barriers to adoption of pregnancy scanning, then develop solutions to overcome these barriers,” Ms Peachey said.<\/p>\n
“Important to increasing producer adoption is having a detailed business case for pregnancy scanning which is applicable to different production environments and enterprise types, producer needs and resource availability.”<\/p>\n