This is a significant step
change, and the most measurable improvement to the animal evaluation system
since the introduction of BW in 1996. From an LIC perspective, the
incorporation of genomic information will further enhance MINDA outputs and deliver
further value.
To align with the announced change from NZAEL, LIC will release its own animal genetic evaluation enhancements which will not only contribute significantly to the base model changes at industry level (NZAEL) but also deliver further benefit by incorporating our own latest development in the fast moving, high impacting area of genomic technology. This new model known as the Single Step Animal Model (SSAM) will come into effect from 22 February and will be visible throughout the MINDA product suite.
LIC has spent the past six months collaborating with NZAEL to ensure the enhancements our people have identified and developed, can be leveraged for the wider industry. This has resulted in NZAEL implementing our latest software into their animal evaluation.
While the enhancements will result in some re-ranking between animals, the overall benefit to farmers is improved accuracy in the prediction of an animal’s true genetic merit enabling improvements in overall herd performance and greater rates of genetic gain.
LIC has invested considerable resources into genomic evaluation of animals and the selection system it uses to predict an animal’s performance based on its DNA profile. Our enhancements are a result of LIC’s $70 million investment in research and development over several decades. SSAM has been validated using the latest cohorts of bulls who now have daughter proofs to confirm its accuracy.
Importantly, it was also reviewed by internationally renowned geneticists who have commended LIC on our genomics work. NZAEL’s Scientific Advisory Committee has also reviewed and support our latest model.
Read more about the changes on the DairyNZ website.
https://www.dairynz.co.nz/animal/animal-evaluation/interpreting-the-info/breeding-values/?fbclid=IwAR3qHTn9GnR70LGwsPCY4ibJr4waCi1zi5dYSlHXvpbmwjqZF69iJunEHwI
