Sensors for better data
PROFITABILITY per hectare will now be included in the Merino Lifetime Productivity project, adding the bottom line to data already being collected.
New wearable sensors and the latest carcass measurement scanners will be used to measure feed intake, body composition and productivity on sheep within the $13 million, four year MLP project.
These measurements can then be used to establish feed conversion and per hectare profitability.
Australian Wool Innovation Genetics and Animal Welfare Advocacy program manager Geoff Lindon said the new feed intake and body composition assessment tools, along with the existence of the MLP F1 ewes and wethers, had created an opportunity to make significant improvements to the economic evaluation of genetic bench marking.
The 2016 and 2017 drop first-cross wethers from 29 artificial insemination sires at the Pingelly MLP site in Western Australia will be assessed both under both animal house and normal grazing conditions, and the observations will extend to the ewes in the project if successful.
Mr Linden, speaking at the MerinoLink MLP field day at Temora, in southern NSW, last week, said the MLP project would also expand the collection of adult data, which was crucial.
“Industry has a higher percentage of breeding ewes and are not carrying the wethers we once did,’’ he said.
“The Merino is changing — body weight is increasing and there is a focus on wool and lamb, welfare traits and resilience, combined with a move from dollars per head to dollars per hectare.
“The advice from geneticists is one set of adult data is required, but industry isn’t necessarily collecting adult data. It’s collecting a large amount of yearling data and a little hogget data.’’
Mr Lindon said the MLP would look at the impact of high growth or low wrinkle on wool cut and quality, if ewes with more fat and muscle have more lambs and lower lamb mortality; if the current indexes are well correlated to lifetime productivity, does productivity changes as they age, and what is the best mix of visual and objective selection.