By Steve Suther
The performance of healthy cattle on feed is “extremely predictable,” but you have to know what to expect and when to worry. That’s according to Richard Zinn, University of California-Davis animal scientist, who presented at the late summer Feeding Quality Forum in Omaha, Neb., and Garden City, Kan.
Large-scale cattle feeding is only practical because scientists learned what to expect and shared knowledge with the industry, he said. Over the years, rules of thumb as precise as slide rules moved from experiment stations to feedyard managers’ notebooks and computers.
“We have a sense of certainty from looking at millions of numbers, so if a number isn’t what we expect, there’s a problem, and we can look for areas of opportunity,” Zinn said. “It boils down to confidence. But there’s risk and that’s inversely proportional to confidence. The greater the risk [sickness, environment] the more we pay attention.”
The most predictable situations can be confused by assumptions like pencil shrink, poor weighing conditions or simple errors in recording data on the wrong line or wrong sex of the cattle.
“I look at tens of thousands of closeouts, but discharge 3% to 5% because the numbers aren’t just improbable—they’re impossible,” Zinn said.
There’s real variation that goes against the norms, he said, noting the main one is extreme weather at closeout. Space allowance per animal is another factor, with performance dropping off when that gets below his recommended 130 square feet. Differences in shade, shelter, feed additives and implants tweak expectations but can be factored in.
Changes in energy density of the ration affect feed efficiency as do shifts in starting weight and carcass weight.
“If you’re only looking at average daily gain and feed efficiency, you’re going to be misled in terms of how well the feedlot is actually performing,” Zinn said, suggesting a closer look at the energy component of dry matter intake. “The relationship between energy intake and growth performance is almost certainly the most reliable of nutritional concepts.”
That relationship is critical to profit as well. A model that accounts for gender, frame, quality, in-weight and energy value of the diet can reliably predict outcomes for average cattle.
“Deviations would be areas for the feedlot to look at why performance is not this number right here,” Zinn said, noting the predictability given accurate input to the model or formula. But what happens if energy intake varies?
One example showed the impact of a 2% increase in energy intake added $9 per head on the final close-out. Further implications support industry efforts to enhance that intake, and Zinn analyzed a feed additive example that came in 3.3% above average: 40% due to an increase in dry matter intake and the rest from improved energy utilization.
He closed with a mystery solved regarding varied results linked to specific pens within feedyards. He knew that pens encountering the most feed-truck traffic tend toward lower performance from that low-level stress. But a very large feedyard was dismayed that its new addition at the far end of the facility rarely beat average performance.
A study of daily feed logs and other factors showed those pens were always fed last, so every minor breakdown over a year of feeding came to bear on that area.
“If there was ever a problem with electricity going out or a storm, or whatever, performance in those cattle took the brunt of it,” Zinn said. “So we discussed some ways they could mollify that challenge. But it’s good to know all the potential sources of variation when you want to determine what to do.”