Effectively Addressing Feed Efficiency

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Efficiency is a critical factor in modern agriculture. Nowhere is this more apparent than in the livestock industry, where optimising resource use is essential for economic and environmental sustainability. Feed efficiency is gaining more and more traction and for some cattle producers, it is now a central concern. The term refers to the amount of feed required to produce a given amount of beef. In other words, how effectively can cattle convert grass into beef? Thus, it can also be referred to as productivity which is maximising beef production from a given feed resource.

We think the critical question with regard to feed efficiency is; should the focus be on selecting for productive herds or feed efficient animals? There has been a lot of research done in this area and we will draw on that research to address this question and contribute to the industry discussion on the topic. In doing our research for this article, a Head Shepherd podcast interview with Professor Wayne Pitchford was very useful and we recommend it to readers. A list of published papers we used in preparation for this article is included at the end of the article.

Measuring feed efficiency

At an individual animal level, feed efficiency is expressed as residual feed intake (RFI) or net feed intake (NFI). It is calculated by measuring an animal’s actual feed intake and comparing it to its estimated intake, based on its physiological factors (size, growth rate, reproduction etc.). Animals with lower RFI values are considered to be more efficient because they consume less feed than expected for their level of production or growth. The inverse relationship between RFI or NFI and efficiency is potentially confusing but important to understand; animals with a lower RFI value are
more efficient and animals with a higher RFI value are less efficient. RFI can only be measured in controlled feeding experiments and not in the paddock.

At herd level, we measure productivity as kilograms of beef produced per animal unit (AE or DSE) per year, where the animal unit is based on energy demand and is a proxy for dry matter intake. Our analysis of beef herds has consistently found that kilograms of beef produced is the number one income driver for beef herds (assuming stock rate is optimised) and, therefore, one of the key profit drivers.

Selecting for individual animal feed efficiency

Research has found that RFI is moderately heritable and that there are antagonistic relationships with some fertility traits in both females and bulls. This means that targeting for low RFI (i.e. more efficient animals) may negatively impact herd fertility. A large-scale long-term study done in WA with selection for high and low RFI animals found that the low RFI animals, over time were larger, leaner, and later maturing.

The research indicates that when nutrition is not a limiting factor, the differences in RFI are greatest and, the low RFI animals are more efficient overall. However, when nutrition is lacking, the differences in RFI are much less and the higher RFI animals carry more fat reserves which benefits their ability to reproduce and delays when supplementation is required. One paper suggests that differences in residual feed intake are attributable to appetite and that those animals with greater appetite are more resilient in times when nutrition is limiting.

Given that nutrition is a limiting factor for most beef producing regions of Australia for significant periods of the year, it is animals’ performance under these conditions that is most important, rather than their performance in a controlled environment where nutrition is not limiting.

Selecting for low RFI, without consideration of fat and fertility genetics could therefore be detrimental to overall herd feed efficiency and productivity.

Selecting for herd feed efficiency

Our analysis has found that around three-quarters of the differences in herd productivity (kilograms of beef per animal unit) between herds can be explained by the following three key productivity drivers;

  • Weaning Rate
  • Mortality Rate
  • Sale Weight

Of these three, weaning rate is the most important measure. Small differences in each of these measures have a big influence on the productivity of herds. More productive herds have greater overall feed efficiency; generating more beef, and income, for every kilogram of grass eaten.

The below table shows the differences in productivity drivers, herd productivity, and income (gross profit) per animal unit between the average and Top 25% performers in northern and southern Australia over the last 12 years, from the Australian Beef Report 2023. This shows how small apparent differences in the productivity drivers have a large cumulative effect on herd productivity, with the Top 25% herds being 10% more productive in the north and 14% more productive in the south, meaning their feed efficiency is 10% and 14% better than average, respectively.

Top 25%
Top 25%
Weaning Rate
Mortality Rate
Sale Weight (kg LW)
Kg Beef/AE [/DSE]
91 [10.8]
100 [11.9]
127 [15.1]
145 [17.3]
Income/AE [/DSE]
$255 [$30]
$272 [$32]
$368 [$44]
$416 [$50]

Some context may be needed for the differences in productivity and income per animal unit between the north and south. On average;

  • the south has higher productivity resulting in higher income per animal unit than the north, but less operating scale resulting in higher operating costs per animal unit.
  • the north has lower productivity resulting in lower income per animal unit than the south, but more operating scale, resulting in lower operating costs per animal unit.
  • it is those businesses that can combine scale and productivity that generate healthy herd profits, irrespective of location. See the Australian Beef Report 2023 for more information.
What does this mean for commercial businesses?

Our interpretation is that commercial breeding businesses will do more to improve the feed efficiency of their system by selecting for traits that will improve overall herd productivity (fertility and growth) than by trying to select for animals that have better individual feed efficiency.

One of the big challenges in feed efficiency is that it cannot be measured in the paddock, meaning if you do select for feed efficiency then there is no reliable way of measuring improvements at paddock level. This, coupled with the potential for antagonistic effects on overall herd productivity through selecting for feed efficiency, poses serious challenges in achieving and measuring any benefits from selecting more feed efficient animals.

If you are selecting a terminal sire, breeding animals to retain ownership through a feedlot, or are in a production system where nutrition is never lacking, then there may be real benefits in selecting for feed efficiency. However, for commercial breeding businesses, selecting for feed efficiency will reduce the selection pressure that can be placed on the key productivity and profit drivers, for no measurable benefit.

An important tool in selecting for productive herds are the selection indices within BREEDPLAN, as they are a weighted measure of traits that drive the profitability of that production system, and they account for energy demand for production, as the animal unit calculations do. Interestingly, if you screen within BREEDPLAN for higher indexing (more profitable) animals within breeds that have a feed efficiency EBV, you will find these higher indexing animals will generally have lower feed efficiency, and vice versa. This relationship is evident in the Top Studs publication and demonstrates that BreedObject multi-trait selection indexes do head in the right direction.

In conclusion, select for efficient herds by focusing on productivity, rather than having too much emphasis on efficient animals; the difference is important to understand.


Arthur, P. F., Archer, J. A., & Herd, R. M. (2004). Feed intake and efficiency in beef cattle: overview of recent Australian research and challenges for the future. Australian Journal of Experimental Agriculture, 361-369.

Awda, B. J., Miller, S. P., Montanholi, Y. R., Vander Voort, G., Caldwell, T., Buhr, M. M., & Swanson, K. C. (2013). The relationship between feed efficiency traits and fertility in young beef bulls. Canadian Journal of Animal Science, 185-192.

Basarab, J. A., Beauchemin, K. A., Baron, V. S., Ominski, K. H., Guan, L. L., Miller, S. P., & Crowley, J. J. (2013). Reducing GHG emissions through genetic improvement for feed efficiency: effects on economically important traits and enteric methane production. Animal : an international journal of animal bioscience, 303–315.

Crowley, J. J., Evans, R. D., McHugh, N., Kenny, D. A., McGee, M., Crews, D. H., & Berry, D. P. (2011). Genetic relationships between feed efficiency in growing males and beef cow performance. Journal of Animal Science, 3372-3381.

Gonzalez-Recio, O., Pryce, J. E., Haile-Mariam, M., & Hayes, B. J. (2014). Incorporating heifer feed efficiency in the Australian selection index using genomic selection. Journal of Dairy Science, 3883-3893.

Jones F. M., Accioly J. M., Copping K. J., Deland M. P. B., Graham J. F., Hebart M. L., Herd R. M., Laurence M., Lee S. J., Speijers E. J., Pitchford W. S. (2018) Divergent breeding values for fatness or residual feed intake in Angus cattle. 1. Pregnancy rates of heifers differed between fat lines and were affected by weight and fat. Animal Production Science 58, 33-42.

Montanholi, Y. R., Fontoura, A. B., Diel de Amorim, M., Foster, R. A., Chenier, T., & Miller, S. P. (2016). Seminal plasma protein concentrations vary with feed efficiency and fertility-related measures in young beef bulls. Reproductive Biology, 147-156.

Mu, Y., Vander Voort, G., Abo-Ismail, M. K., Ventura, R., Jamrozik, J., & Miller, S. P. (2016). Genetic correlations between female fertility and postweaning growth and feed efficiency traits in multibreed beef cattle. Canadian Journal of Animal Science, 96(3): 448-455.

Pitchford, W. S. (2004). Genetic improvement of feed efficiency of beef cattle: what lessons can be learnt from other species? Australian Journal of Experimental Agriculture, 44(5): 371-382.

Pitchford, W. S., Lines, D. S., & Wilkes, M. J. (2018). Variation in residual feed intake depends on feed on offer. Animal Production Science, 1414-1422.

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