The expected increase this year in beef animals born into the dairy herd has not yet materialised. In fact, according to the ICBF the total number of beef calves registered up to last Friday is actually less than 2016 at 145,300 calves, while there were 163,401 calves registered in the same period last year.

But this reduction is in line with fewer registrations overall so far this year as herds seem to have calved that bit later. Last year, there was a 6% increase in the use of AI beef straws in the dairy herd, while there was only a 4.8% increase in dairy AI used on the dairy herd.

The background to the increased use of beef was low milk prices in 2016 and a sluggish calf trade. Farmers made a decision to breed for fewer dairy replacement stock and use more beef AI to deliver a higher value and more saleable calf. The view among many farmers was that with milk prices low and no signs of recovery there will not be a big demand for surplus dairy stock.

That was the rationale and for many farmers it was and will continue to be the right thing to do, with the proviso that the beef bulls used must be easy calving and have short gestation. Of course, using any beef bull increases the risk of a harder calving, so when picking beef bulls make sure and use only proven easy calving bulls with as short a gestation length as possible.

But should herd genetics play a part in the decision process? A number of weeks ago we featured Oisin Gill in the Irish Farmers Journal (2 March 2017). Oisin’s herd had a very low EBI of €38 and despite doing a good job of managing grass and feeding them well his milk solids output was low and calving pattern was spread out.

He made the decision to sell all of his young stock and the most infertile cows, which was about 30% of the cows and instead he bought in high-EBI heifers. He felt that breeding from his own cows would take too long to get the herd up to the standard he required.

Oisin’s predicament is something dairy consultant Matt Ryan regularly comes across.

Massive gap

“There is a massive gap between what the top herds are achieving when it comes to fat and protein percent and what the average herd is doing. Many of the better herds are now averaging fat of 5% and protein of 3.9% over the lactation while the national average is 4.16% fat and 3.49% protein. If a cow produces 5,300l the difference in milk value between the two is about €290 per year,” Ryan said.

“With the best will in the world it would still take 10 to 15 years for the average herd to catch up to the top herd and of course the top herds are continuously improving also.”

By their nature, most of the high-EBI herds are compact calving and will breed enough dairy replacements for their own use in the first two or three weeks of breeding. This means that they only really need to use dairy AI for the first three weeks or so and thereafter they could use beef AI or introduce clean-up bulls.

Matt Ryan suggests that the price of surplus heifer calves from these herds are undervalued at present and it is leading to more and more of these farmers using beef bulls when their replacement needs are met. Remember, for every dairy heifer calf there is a dairy bull calf which can have a very low value. But beef calves have much higher value, regardless of their sex. So Matt reckons the farmers with the low-EBI cows should be the ones using the beef bulls across their herd and to enter into a sort of a contract mating agreement with a high EBI farmer to buy his surplus replacements at an agreed price which is more reflective of their value.

The long-term benefits to the industry from such an initiative would be immense. The farmer buying the stock would benefit from rapidly increasing the genetic potential of his herd and also have higher calf sales from using beef bulls on his cows. The farmer selling the high EBI heifers would be guaranteed a price reflective of their value as cows, which would be their incentive to breed to dairy AI for longer. But all calves destined as replacements should be born before mid-March.

Read more

Special focus: spring AI 2017