Improving our sector’s overall herd reproductive performance is a pressing matter. The 6-week in-calf rate is a good overall measure of performance and is used as the national benchmark, with the target being 78%. However, our sector average is only 68%, while the top 25% of herds have a 6-week-in-calf rate of more than 73%1. To build more profitable and sustainable businesses, we need to get those rates higher.
DairyNZ’s The InCalf book2 outlines eight key management areas for improving herd reproductive performance (Figure 1). These components contribute at different times of the annual cycle, and genetics is one component that can be used when farmers are making bull selection decisions. Remember, the benefits of better genetic fertility are cumulative and compounding across each crop of replacements.
Improving genetics for fertility There’s a significant economic reward from improving genetic fertility. That’s why it’s recognised in the Breeding Worth (BW) index, which ranks cows and bulls on their expected ability to breed profitable and efficient replacements.
Key research findings
The Fertility BV is one of nine components contributing to BW. It provides an objective measure of an animal’s genetic merit for fertility. Before December 2021, the Fertility BV was estimated from whether an animal calved in the first 42 days of the herd’s calving period (scored as 1) or later (scored as 0), using data from the second, third and fourth calvings. Mating data is also included, with cows scored as 1 if the animal was bred in the first 21 days of the mating period during lactations one, two and three; or scored as 0 if bred later.
In December 2021, two key changes to the fertility BV were implemented. Firstly, an animal’s first calving (as a heifer) was included in her evaluation. Secondly, the old 1 or 0 scoring system was replaced with ‘calving season day’ (number of days between the herd’s planned start of calving and a cow’s calving date). This modification better rewards cows that calve earliest in the herd, while cows are more heavily penalised3 if they calve later, are culled for poor fertility, or do not calve in the next season.
Our national herd has struggled to become genetically more fertile. There was a downwards trend between 2000 and 2015, but the Fertility BV has gradually increased since 20154. Farmers can take advantage of this favourable trend by using sires with high BW and high Fertility BV. By doing so, you should expect to see better reproductive performance.
The sector needs to deliver continuous improvement of the Fertility BV, ensuring greater accuracy and a greater rate of gain. That’s why, in 2014, we worked with some of our sector experts (NZAEL, LIC, CRV, AbacusBio and AgResearch) and farmers to generate a unique research herd of about 550 heifers with positive (+5%) and negative (-5%) Fertility BV.
To put the Fertility BV of these groups into context, the national average Fertility BV was -1.6% (standard deviation of +3.5%) for heifers born in 2015 based on NZAEL3.0 evaluations3.
We didn’t expect to see marked differences in reproductive measures of positive (POS) and negative (NEG) heifers because the Fertility BV uses data only from lactating cows (i.e., calving records and submission to artificial breeding records). We were surprised that the POS heifers achieved puberty three weeks earlier and at a much lower percentage of mature live weight than the NEG heifers5:
Consequently, 94% of the POS heifers had ovulated by the start of breeding, compared with 82% of the NEG heifers. The 3-week and 6-week in-calf rates were 13% and 9% greater in the POS compared with NEG heifers, with the POS heifers conceiving 3-4 days earlier than the NEG heifers (13 vs 16.6 days after the start of mating).
Whether age at puberty and timing of pregnancy in heifers is a helpful measure for accelerating Fertility BV gain is a question we’re now addressing through large-scale studies.
Calving patterns in lactations one and two
In lactation one, the POS cows calved, on average, four days earlier than the NEG cows. By lactation two, the difference was 12 days earlier6. Hence, more POS animals calved within the first three weeks of seasonal calving during lactation one and two (Table 1). This is not surprising, as Fertility BV is based on cows’ ability to re-calve during the first six weeks of their second lactation.
In our research herd, submission rates were markedly different between the POS and NEG cows. The 3-week submission rates during lactations one and two were 87% and 88% in POS cows, compared with only 49% and 63% in NEG cows, respectively6.
Calving pattern in the first lactation was not the cause of the poor submission rates for NEG cows. Instead, the poor submission rates were due to 46% of the NEG cows not cycling (anoestrus) in the first six weeks of mating, compared with only 5% of the POS cows.
Furthermore, among the NEG cows that did cycle, their interval from calving to first oestrus was nine days longer than the POS cows that cycled. This delay in ovulation was seen in both lactations one and two.
The key finding here is that the ability of cows to resume cycling within a reasonable timeframe after calving (e.g., within six weeks) is likely to share a genetic link with the 6-week calving rate. So, measuring the time between a cow’s calving and first heat may help improve the accuracy of the Fertility BV. We’re currently investigating this possibility.
As we followed our research herd over the two seasons, we saw marked differences in the timing of conception and pregnancy rates between the POS and NEG animals. On average, the POS cows conceived 12 days earlier than the NEG cows. In lactations one and two, significantly more POS cows were pregnant by six weeks of artificial breeding6:
By the end of breeding in lactations one and two, there was a 10% to 14% difference in final in-calf rates between POS and NEG cows6. The high not-in-calf rates of the NEG cows resulted in a sizable percentage of this group being culled as nonpregnant each year (Figure 2).
These data support an argument for basing the Fertility BV on conception success as a more direct and earlier measure of fertility than re-calving data. Foetal-aged pregnancy testing is a routine practice on more than 4000 farms1, so there are enough industry records to use this trait in genetic evaluation.
Survivability of this trial herd through to the third calving (pregnant at the end of lactation two) was markedly different between the POS and NEG lines (Figure 2). Losses in the heifer groups were low, with 6% of the POS and 11% of the NEG heifers removed before their first calving.
However, only 25% of the NEG heifers survived to the point of being pregnant at the end of lactation two, compared with 61% of the POS heifers. The primary reason for culling was cows failing to conceive: the NEG cows had twice the removal rate of the POS cows (Figure 2).
The results of this long-term study clearly show that genetic selection for cow fertility results in tangible differences in herd reproductive performance.
Importantly, we discovered novel traits linked with genetic fertility. For example, a cow’s genetic merit for fertility affects her ability to start cycling post-calving and calve in the first six weeks of the next season. Also, earlier 'puberty' and better 'heifer reproductive outcomes' are associated with the Fertility BV and, therefore, are better and earlier predictors of cow fertility than current measures based upon mating and calving records during lactation.
Large-scale validation and development studies of the new fertility traits are currently underway. The findings are encouraging, although further work is required before we can include these traits (e.g., age at puberty) into routine evaluations.
Acknowledgements
This work was funded through the Pillars of a New Dairy System partnership between NZ dairy farmers through DairyNZ Inc. and the Ministry of Business, Innovation and Employment, with additional support from AgResearch, LIC and CRV.
References