Do RFI ratings predict cattle performance on pasture?

In a word, no

Grazing behaviour checked by GPS and pedometers did not differ significantly for high- and low-RFI females in this trial.

Producers often wonder if genetic markers for feed efficiency based on drylot tests reflect feed efficiency on pasture where terrain, water sources and plant diversity are very different from a pen setting.

Genetic markers for residual feed intake (RFI) have been identified that correlate well with actual RFI determined during the standard trials in pens with GrowSafe bunks to measure individual animal feed intake on silage-grain rations. Animals that eat less than expected for their weight, production and maintenance needs will have RFI scores below zero, indicating that they are more feed efficient than animals that eat more than expected and have RFI scores above zero.

The problem is that there isn’t a practical way to test for feed efficiency in a pasture setting where each animal picks and chooses what it eats and amounts can’t be precisely measured. To further complicate matters, energy expended while grazing can be quite variable among animals.

University of Alberta masters candidates with doctors Edward Bork and Graham Plastow took on the challenge of trying to determine whether and how genetic markers for RFI predict cattle performance on pasture.

RFI, performance and emissions

Nicky Lansink. photo: Supplied

Nicky Lansink’s research involved 450 commercial cows from the Gemstone Cattle herd that had already been genotyped to determine molecular breeding values (MBV) for RFI. This is the predicted RFI based on genetic markers alone. The cows weren’t tested to determine actual RFI.

The pairs spent the 2015 grazing season on native range at the University of Alberta Rangeland Research Institute’s Mattheis Research Ranch north of Brooks, Alta., where Lansink tracked weights, back fat and pregnancy status relative to each cow’s MBV score for RFI.

When breed composition was included in the statistical models, it became clear that breed composition had a significant effect on calf growth whereas RFI did not, Lansink says.

There wasn’t a marked difference between the low- and high-RFI cows’ weight gain and back fat accumulation during the grazing season, although the low-RFI cows did put on a bit more back fat overall. This trend for the low-RFI cows was particularly apparent for cows five years and older, suggesting genetic influences may be more likely to express themselves once cattle reach maturity and settle into their normal genetic production potential. The role of cow age may need further study.

Nor was there any significant differences between low- and high-RFI cows in the percentages conceiving on the first and second breeding cycles, or open at the end of breeding season.

For the most part, Lansink says the findings were in line with her expectations because, technically, RFI is independent of an animal’s gain, growth and production.

After weaning, heifer calves from the 30 cows with the lowest MBVs for RFI and from the 30 cows with the highest MBVs for RFI went into an RFI test in drylot pens at Lacombe Research Centre. Individual dry-matter (DM) intake and individual methane emissions were determined with the use of GrowSafe and GreenFeed technologies, respectively.

Methane is an expense for cattle because it represents wasted energy that otherwise would go toward growth, Lansink explains, adding that methane is also associated with climate change.

Simply measuring the amount of methane released doesn’t tell the whole story though because the amount an animal eats also comes into play. The methane yield calculation adjusts for feed consumption and is given as the grams of methane produced per kilogram of DM intake.

Low-RFI heifers had significantly lower DM intakes, but absolute methane production per head didn’t differ between the high- and low-RFI groups. However, the low-RFI heifers had significantly greater methane yields because they ate less but produced the same amount of methane as the high-RFI heifers.

Carbon dioxide production was significantly higher for the high-RFI heifers, while carbon dioxide yields were greater for the low-RFI heifers.

Lansink suspects this trend toward higher emission yields for low-RFI animals could be because of greater digestion rates and rumen retention times compared to high-RFI heifers. For example, low-RFI animals may have fundamentally different digestion processes that favour enhanced food breakdown, but also generate more methane and carbon dioxide per unit of feed consumed. More research will definitely be needed to understand the mechanisms behind methane emissions from cattle, she adds.

Some of the heifers from the feedlot RFI test were part of Lansink’s 2016 study on individual DM intake and group methane emissions that took place on a forage-oat pasture at the Mattheis ranch.

DM intake was evaluated by individually grazing fresh forage-oat pasture and fecal sampling eight high-RFI heifers and eight low-RFI heifers twice a day for six days. Each animal was dosed with alkane feed pellets as a tracer to assess intake.

For the methane emissions study, an open-path Fourier infrared spectrometry system run by Dr. Tom Flesch of the U of A was placed between the two adjoining paddocks. The low-RFI heifers were moved daily from strip to strip running crossways down one paddock, while the high-RFI heifers were managed the same way in the opposite paddock.

Lansink explains that the laser sends a beam of infrared energy down the full length of the paddock to bounce off the mirror at the other end and return to the laser where the device uses WindTrax software to record the methane concentration. Methane absorbs infrared energy, therefore, the more methane in the beam’s path, the less infrared energy returns to the laser.

To account for wind direction, the laser rotates to send a beam across the paddock to deflect off a mirror at that corner and travel down the full length on the other side, then bounce back to the corner mirror to deflect into the laser.

The laser then rotates to capture the same information from the opposite paddock. The pattern repeated 24 hours a day for six days straight during Lansink’s trial.

Overall, actual methane emissions, methane yield, and DM intake of the two groups didn’t differ, although the high-RFI heifers did produce a bit more methane.

“Wild storms interrupted some of the data collection and we may have seen more differences had the test been longer. We did notice a strong daily pattern, though. Most methane was released shortly after the heifers were let out on a new strip and the concentration went down during the day and was lowest at night,” Lansink reports.

Summing it up, she says cow MBV for RFI wasn’t a major factor in regulating cow or calf performance on pasture, or subsequent calf performance in the drylot. Without more research, it’s difficult to know whether selection for RFI would be beneficial for reducing methane emissions.

RFI and grazing behaviour

Carly Moore. photo: Supplied

Carly Moore looked into whether pasture use differs between low- and high-RFI groups and whether genetics (RFI), environmental variables (forage quality, distance to water), or a combination of the two would best predict cattle performance on pasture.

Fifteen cows with the lowest MBVs for RFI and 15 cows with the highest MBVs for RFI from the 450 cows at Mattheis ranch in 2015 were fitted with GPS collars and pedometers to monitor the herd’s grazing patterns.

In lieu of feed intake measurements, Moore collected forage samples and ground-cover information to estimate forage quality and quantity throughout the grazing season.

She then created a file with GPS points for the sampled locations and GPS information from the collared cows to link the cows’ locations to forage characteristics at the time of grazing each of the 14 pastures.

She also collected fecal samples from the collared cows in July when forage quality was at its best, and in October when forage quality had tapered off. The samples were sent to Washington State University’s Wildlife Habitat Lab to analyze diet composition.

In the end, she didn’t detect any clear differences in pasture-use patterns between RFI groups, although pasture size was a consistent factor influencing the amount of time cattle spent moving about and lying down during the grazing season. A possible explanation for the lack of differences may be that subtle variation in RFI score in a commercial cattle herd simply does not translate into detectable behavioural differences in the field, which is further masked by high environmental variation.

“Even if there isn’t a difference in habitat use between low- and high-RFI animals, this may be a good thing. Producers selecting cattle for feed efficiency shouldn’t see their cattle using pasture any differently than before,” Moore comments. Had there been differences, they may have led to more variable use of pasture resources, and potentially facilitated localized degradation.

As for environmental variables, it turned out that grazing distance from water didn’t differ between the high- and low-RFI groups. Instead, cows from both groups had lower back-fat gain the more time they spent close to water, likely because they were not venturing out in search of higher-quality forage across the pasture.

Season of grazing did strongly influence forage quality and cattle movement rate.

The movement rate and number of times the cows got up and down was highest in spring.

It was as if they were searching out high-quality forage to meet the post-calving demand for energy and protein because the movement rate slowed when forage quality was at its peak, she explains.

Surprisingly, the slowest movement rate was in fall when she had expected to see it pick up again thinking that the cows would be searching out what remained of the best-quality forage. Instead, they seemed to be looking for a quick fill, she says, just hanging out in one area and eating whatever was in front of them before moving on.

The fecal results supported the movement-rate pattern. The July samples contained mainly grasses, whereas there was a greater variety of plants, including forbs and sedges, identified in the October samples, suggesting that cattle were becoming less picky and more opportunistic to keep their rumens full.

“So the diet changed over the grazing season. When forages were high quality, they stuck to preferred grasses and when forages were not so high quality, they chose more diverse diets. This result supports past research findings showing how the diversity of native range may help optimize what cattle eat for overall performance. There is a large number of species and they are at their best at different times of the year, so cattle are getting better-quality forage for longer than, for example, on tame pastures with relatively few species in the mix,” she explains.

The fecal analysis did reveal differences between RFI groups. In summer, high-RFI cows tended to eat fewer non-native species, such as Kentucky bluegrass, while low-RFI cows had fewer species in their diets. Both groups had similar diets in fall.

“We are thinking that feed efficient animals may be more flexible in their diets as forage quality changes. Choosing less-diverse diets in summer, when most forage is high-quality anyway, to reduce time looking for feed could potentially make them more efficient,” Moore sums up.

Overall, her results reinforce that monitoring the forage base, coupled with pasture management considerations, such as placement of water, minerals and fencing, are extremely important for managing cattle for the best performance.

About the author



Stories from our other publications