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Bulls that are likely to go on to be used as stud sires across a number of herds are identified for use by AI. Known/identified commercial cows are AI’ed and the resulting calves are recorded for birth date, birth weight and calving ease. Calves are grown out with management group details being recorded and then ultimately have carcase details recorded from effective sized contemporary groups.

, our people work ha r d to know livestock best. W e’ve been in the business e than 150 years and we’ r e committed to p r ovide the best s why you can rely on Landmark.

Herefords Australia’s newly formed R&D Advisory Group will be exploring opportunities to get more leverage from this approach to continue to build the reference population.

HAL supports the co-operator herds through the funding of genotypes, data and sample collection costs at slaughter, and in-kind support via the coordination of data at slaughter, grading, sample collection and analysis.

Victorian stud and commercial breeder Tim Hayes said genomic EBVs ‘speed up’ the process of genetic advancement for traits such as ease of calving and carcase characteristics, along with raw data and recording.

Tim and his family run Tarcombe Hereford stud at Ruffy, one of two Herefords Australia co-operator herds contributing to CONTINUED PAGE 24 in business more than 150 years and we’re committed to provide the best marketing options for every season. s why you can rely on Landmark. the BREEDPLAN reference population with a particular focus on building the data for carcase traits and fertility.

Mr Hayes has DNA profiles for all the Tarcombe sires and around 60-70 per cent of the cow herd of 300 registered females and 150 commercial breeders.

“Genomics is certainly making our information more accurate, especially on hard to measure factors such as raw carcase traits, and this will help us make more informed breeding and management decisions in the long run,” Mr Hayes said.

“Genetically I’m seeing a big improvement in marbling and other carcase traits, yield has improved a fair bit and I’ve seen a massive difference in calving ease.”

Mr Hayes runs a herd of females that are AI’ed to specially selected sires, with all participating animals DNA sire and dam verified.

Their calves are comprehensively performance recorded, with factors such as DNA, birth weights and calving ease entered on BREEDPLAN.

The steer portion of the Tarcombe progeny, around 70 animals, are finished on feed and processed as a group, with carcase data on fat depth, muscle, marbling and yield collected through the abattoir. Tissue samples are taken for shear force, tenderness and eating quality analysis.

Tarcombe’s 2022 cohort recorded an average liveweight of 572kg, 100 per cent compliance rate, average hot standard carcase weight of 309kg, rib fat 8mm, eye muscle area of 80sqcm, marble score one and MSA Index of 62.6.

“Our fellow co-operator, Andrew Bell of Red Gum Herefords at Millicent, slaughters around 200 steers. We see a lot of sires change just on the back of this important data. They would change anyway, it just happens faster through GEBVs,” Mr Hayes said.

“We try to select genetically different sires and commonly used sires as much as we can, but we’re very strict on data, the EBVs have to be right for calving traits etc.”

The Hayes family were one of the foundation herds in the Beef Information Nucleus (BIN) and Young Sire Progeny Test Project co-funded by MLA in the early 2000s, and Mr Hayes says he and Mr Bell are clear about the BREEDPLAN ranking of the sires they select.

“Calving ease in the top 20 per cent of the breed, 400-day weight in the top 20 per cent of breed, EMA top 10 per cent, IMF top 5 per cent and we’ll use the Southern Self Replacing Index that HAL has developed, which is a ranking in the top 5 per cent,” Mr Hayes said.

“The benefits of recording and having this data is not only in the genomics, it’s all the other information that we identify through DNA, such as poll testing. Raw data and recording are also very important.

“Instead of just one trait we’re measuring a whole range to support the data and build a background to each animal.”