When addressing milk quality concerns on-farm, short term management and health issues are often the focus. At NMC's 46th Annual Meeting, Dr. George Shook, University of Wisconsin-Madison, encouraged attendees to consider genetic selection for milk quality, too.
In particular, Dr. Shook recommends producers and their milk quality advisors to:
1) Use sire selection for as a long-term strategy to improve milk quality.
2) Sort sires first on a complete performance index, such as Net Merit or TPI.
3) Include SCS for criteria in making a "short list” of sires from that longer list. For example, producers should use sires with PTA-SCS of 3.2 or higher very sparingly and only if they excel at another economically viable trait.
4) Consider SCS as a selection tool, even if the herd does not have milk quality problems.
5) Use AI, as these sires are backed by a wealth of information about their superiority. Producers not able to manage an AI program should still gather as much information as possible about the genetic background of their herd sires.
The USDA has calculated Somatic Cell Score (SCS) indices for sires since 1994. The good news is that since Shook presented this topic in 2007, progress has been made! Today, only seven Holstein bulls out of 694 (about 1 percent) are at or above the 3.3 threshold. And, only 31 of the 694 bulls (about 4.5 percent) are above the 3.2 threshold. Just three years ago, 5 to 10 percent of the sires were above 3.2.
"SCS has progressively increased in the weightings of index formulas, such as Net Merit and TPI, and producers are more aware of the trait now and its relationship with mastitis and health in general,” says Ryan Starkenburg, ABS Global North American Sire Selection Manager. "Additionally, there are also more low SCS bulls are available today than in the past, as studs have selected for lower SCS.”
Starkenbrg agrees with Dr. Shook's recommendations, but points out that genetics alone cannot fix SCC problems as the heritability is only 12 percent. "The most important step in a mating program is selecting the right group of bulls. Typically, it is best to start with an overall index that puts emphasis on SCS, such as Net Merit or TPI. Once a group of bulls has been identified, if further emphasis is needed on SCS, the higher SCS bulls can be removed.”
Looking down the road, genomics is expected to improve the selection efficiency of SCS and other similar health traits but will not eliminate the need for data collection Starkenburg points out. "Genomics helps to avoid the higher SCS brothers from litters of bulls and helps select bulls with better overall chances for success. While that is certainly a step in the right direction, genomics alone cannot directly determine bulls with better milk quality or mastitis resistance. In order to directly monitor traits, we still need to collect and evaluate the data.”