Residual Feed Intake Is a Profitable Trait for Selection

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Source: Dairy Research and Extension Consortium of Alberta, Dr. Zhiquan Wang, University of Alberta

DRECA Dairy Research Summary

Why is this important?

Feed costs represent a large proportion of the variable costs in a dairy production operation and genetic improvement programs for production efficiency should include traits related to feed utilization. The limited use of feed efficiency measures from national dairy breeding objectives is mostly due to a lack of information on which to make selection decisions. Residual feed intake (RFI) is a liveweight and production-corrected measurement of feed utilization. It is recognized as a robust measurement of feed efficiency in livestock. Residual feed intake is defined as the difference between the actual feed intake and that predicted on the basis of mean requirements for body weight maintenance and level of production (Figure 1).

Methods for evaluating RFI for meat producing animals during growth have been well studied in beef, swine and poultry. However, evaluating RFI for lactating dairy cows while accounting for multi-functional energy requirements (growth, pregnancy, and milk production) is complex. Therefore, to develop an equation to predict cows RFI while accounting for multi -functional energy requirements properly are the key to the success for improving feed efficiency through reducing the feed cost but maintaining the production level in the production system.

What did we do?

We use daily individual feed intake, monthly energy (fat, protein and lactose) correct milk yield, monthly live body weight and body condition score of 293 lactating dairy cows with a total of 524 complete (287 fi rst, 175 second and 69 third) lactation records to develop individual dairy cow RFI predict equation while accounting for the multi -functional energy requirements. The prediction equation has been published in Journal of Dairy Science in December 2013.

What did we find?

Individual RFI for the 293 cows at the Dairy Research and Technology Center (DRTC) of the University of Alberta was evaluated using the developed prediction equation. The variations of individual RFI among the 293 cows were examined.

A sufficient RFI variation (Figure 2) was found among individual cows in the studied dairy population and the estimated heritability of RFI is about 0.20.

What does this mean?

Since feed costs represent a large proportion of the variable costs in dairy production, reducing feed costs associated with milk production has major implications for improving profitability of the dairy industry.

Our results indicated that RFI is heritable, and a sufficient variation of RFI exists among individual dairy cows. Genetic improvement for feed efficiency for dairy can be achieved through selection for lower RFI in individuals to improve the dairy production system efficiency. Selection for lower RFI individuals in a herd should result in reduction of feed intake while maintaining level of milk production and weight gain. Obviously, this will lead to improving the production efficiency and profitability of the dairy operation.

DRECA: Dairy Research and Extension Consortium of Alberta Alberta Agriculture and Rural Development, Alberta Milk, the University of Alberta, and the University of Calgary A partnership in dairy research, extension and education activities agric.gov.ab.ca albertamilk.com afns.ualberta.ca vet.ucalgary.ca

The author gratefully acknowledges Dr Ghader Manafiazar, the PhD student who worked on this project and Drs. Erasmus Okine, Laki Goonewardene and Thomas McFadden, who were Ghader’s supervisory committee members. The experimental support from the DRTC, especially Dr. Reza Khorasani and Harold Lehman should also be acknowledged. The funding support from NSERC discovery and DairyGen/NSERC CRD grants are greatly acknowledged. This research summary is based on a paper published in the Journal of Dairy Science (Manafi azar et al. 2013. J Dairy Sci. 96: 7991-8001). For further information please contact Dr. Zhiquan Wang at zhiquan.wang@ualberta.ca