20 October 2008

5 minute read

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These new programme's depend primarily on cutting-edge research of feed intake and feed efficiency combined with a new appreciation of the roles that genetics and physiological processes have to play. Currently, the majority of research is based on beef, but there is also a growing trend in dairy research that seems set for further increase.

The problem forseen for producers of the future is that they will have approximately the same area of land available, but will be challenged to produce 25 per cent more produce from it by 2025.

Demand will be set soaring by predicted population and economic increases across the globe, whilst the challenge posed by a new generation of bioenergy crops will compete for land, preventing expansion.

Speaking at the 42nd University of Nottingham Feed Conference, Donagh Berry, of the Moorepark Dairy Production Research Centre, explained that in order to meet this challenge producers must minimise input costs with no negative repercussions on economic efficiency. Essentially the farmer must produce more for less.

There is clear significance in this message. According to Dr Berry, 80 per cent of variable costs are feed related, due to last year's food price boom. For producers to succeed in this volatile marketplace, they must strivce for greater efficiency.  

In order to understand how feed efficiency works, it is necessary to understand what it is. According to Dr Berry, there is a "plethora of different definitions of feed efficiency". Amongst the most common are:

Dr Berry says that RFI is the current measure of choice. He says that the term, 'residual feed intake' has increased in popularity in recent years, mainly in the area of animal breeding since it is independent of the performance traits adjusted for such things as live-weight and daily gain in beef cattle and live-weight and milk production in dairy cattle.

Expected energy intake can be estimated using the observed performance of the animal and standard feed tables, or by using least squares regression to estimate the energy requirements for each of the regressors based on the sample population under investigation.

"From an animal breeding perspective defining RFI using phenotypic regression does not guarantee genetic independence with the regressor traits although genetic regression may also be undertaken; this has not advantage over inclusion of all traits in a multi-trait selection index.", he said.

The advantage of RFI is that it is independent, either phenotypically or genetically, from the regressor traits. However, the disadvantages of RFI are that it is more difficult to compute and can be more difficult to explain.

Figure 1. A graphical illustration of how RFI is calculated
Example of actual (square dots) and predicted (continuous line) dry matter intake for a series of individuals. Dots above the predicted DM intake line have positive RFI values (less efficient) while individuals below the predicted DM intake line have negative RFI values (more efficient).

According to research by Richardson and Herd (2004)different results among animals in RFI could be attributable to differences in body composition (5%), activity (10%), ability to digest a given diet (10%), heat increment from fermentation (9%), feeding behaviour (2%), protein turnover, stress and metabolism (37%). Despite of these conclusions the researchers were unable to attribute the remaining 27% of the variation in RFI.

Dr Berry explained that differences in maintenance efficiency undoubtedly play a large role in differences in RFI. He says that this is because, although protein synthesis requires less energy than fat synthesis, protein is continually degraded and resynthesised resulting in lower maintenance efficiency than fat.

"Nonetheless, differences in body composition do not account for all differences in maintenance requirements among animals. Energy expenditure by the main visceral organs also contributes to the energy required for basal metabolism; therefore size and activity of these organs is also likely to contribute to differences in energy for maintenance among animals.

"Where RFI is calculated using the regressor daily gain, differences among animals may be attributable to the difference in the composition of the live-weight gain similar to why differences exist in maintenance efficiency due to differences in body composition. Similarly, in lactating dairy cattle, differences among animals in RFI may be due to differences in the composition of the milk. Therefore, it is important that milk solids or milk solids corrected milk are used in the calculations."

He pointed out several studies which have investigated the presence of genetic variation in feed efficiency related measures in both dairy and beef cattle. Narrow sense heritability is a statistic which describes the proportion of phenotypic differences among individual attributable to differences in additive genes.

He said: "Heritability estimates of RFI in lactating dairy cattle vary from 0.12 to 0.38 although it does vary over lactation. In direct contrast some studies have reported no genetic variation in RFI in lactating dairy cattle. There appears to be currently no apparent limitations to the response to selection on RFI.

"Current gaps in knowledge relate to how to accurately quantify RFI in lactating dairy cattle taking conscience of their cyclic body tissue mobilisation patterns. Little is also known on the association between RFI measured in growing juveniles and subsequent RFI in adult cattle especially reproductive and health performance in lactating adult cattle."

Dr Berry concluded his speech by identifying future areas of research. According to him, scientists will look more closely at dairy, specifically focusing on cyclic trends. The use of biotechnology will also play a large role, when combined with marker assisted selection, and social science will be much more significant, discovering why people do not take up this new research. This new research will forge an advance in molecular genetics and statistics.