We’ve all known animals we call "easy-keepers" – memorable cows that always seem to hold their own or even gain weight on overgrazed pastures of rocks and cactus, or they breeze through a rough winter in good body condition while all their herdmates appear to have joined a weight-loss program.
We’ve known cows that routinely come off rough pastures nicely fleshed every year. And most horse owners have known mares that get fat by just looking at good pasture, or so it seems. These easy-keepers inevitably stand out in a herd – how can you miss them – and ranchers everywhere want more of them because they save feed and do well even under tough conditions.
But from my scientist point of view, easy-keepers represent an uncomfortable conundrum. They are undeniable evidence that individual animals can differ from the herd average. That even when fed the same diet, some animals retain their body condition and some don’t. These individuals seem to march to the beat of a different drummer. They seem to laugh at the reference tables that list the nutritional requirements for each type of animal and each level of production. What is going on?
In science, we describe data with a mathematical "model." A model is an equation that lists all the factors we think influence that data point. For example, let’s say we measure something – average daily gain (ADG) or body condition score (BCS) or whatever – and call this response X. The model is simply an equation that states the value of X is due to the effects of factor A plus the effects of factor B plus the effects of factor C, etc., where factor A could be the sex of the animal, factor B could be the diet, etc. You get the idea. These models can contain lots of factors, and the interrelationships between these factors can get very complex.
But here’s the thing: Every model ends with a strange-looking term on the extreme right side of the equation. Scientists call this term epsilon. (Scientists like Greek letters.) But this term, also known as the "error term," really stands for unexplained variation – namely, the random part of X we can’t quite predict. In other words, once we add up all the known factors to get a predictable response, there is still an extra weirdness variation we cannot explain. In our example above, once we know the sex of an animal and its environment and the quality of its feed and its feed intake, we can predict its growth rate. More or less. That more or less is the unexplained variation. In science, we strive to minimize this unexplained variation. We want to find explanations for it so we can predict things better.
Utilizing residual feed intake
Which brings us back to easy-keepers. These animals are living testimonials to the “more or less” factor. If we could explain the phenomenon of easy-keepers, we could run our experiments more efficiently. And cattle producers could use this knowledge to select and manage animals more profitably.
But two lines of intriguing research recently caught my eye. These are wildly disparate topics, but as I studied the reports, I began thinking about our easy-keepers. So, if you’ll bear with me, I’d like to do a bit of speculation – about metabolism, cattle, unexplained variation and possible explanations.
The first line of research is on the topic of “residual feed intake” (RFI). Never heard of it? Well, the RFI concept was developed a few years ago when researchers began using computerized feeding equipment to measure individual feed intake, even for animals housed in group pens. This allowed nutritionists to develop sophisticated mathematical models to predict intake. But as the data accumulated, researchers noticed an interesting thing: Animals didn’t eat exactly what was predicted. Some ate more and some ate less, even when they all gained weight at the same rate – which meant some animals were more efficient at using nutrients than others. The difference between actual feed intake and predicted feed intake was called residual feed intake. Animals with negative RFI (values below 0) had better feed efficiency than animals with positive RFI (values above 0). Researchers also found that RFI is repeatable over time in the same animal and that RFI is, at least in part, genetically controlled. They also identified some metabolic differences between animals with low RFIs and high RFIs. It seems that RFI may have a real basis in metabolism and genetics. How interesting.
Currently, RFI is a very active topic of livestock research on all types of livestock. Google Scholar lists more than 7,000 research articles on RFI since 2014. In all fairness, there are some controversies about RFI and some of the mathematics behind those predictions, but let’s not get into the weeds. But here is one critical takeaway message from RFI research: Animals genuinely differ in their individual feed intakes and feed efficiencies. Which means that, in any herd, some cattle are more efficient at using nutrients than others.
Brown fat research
Let’s switch gears to the second line of research: the topic of fat, specifically “brown fat.” Everyone is familiar with white fat, of course, which is the ubiquitous storage tissue critical for finishing cattle. But brown fat is different – it’s designed to use energy, not store it. The brown color is due to its high population of mitochondria, which house the cellular machinery that converts fat and glucose to heat. Brown fat uses nutrients to create heat. We’ve long known newborn animals – calves, lambs, foals and even human babies – contain quite a bit of brown fat at birth, which certainly makes sense for newborns trying to survive in a harsh world. Brown fat and warm colostrum help newborns stay alive. We’ve also long known adults don’t have brown fat because the newborns use it up soon after birth.
At least that was the accepted doctrine until 2007, when Swedish researchers published indisputable evidence to the contrary. They used a sophisticated, expensive medical technology called “positron emission tomography” (PET) to scan healthy adult humans and found, to their surprise, numerous small depots of brown fat. Whoa. This was a real breakthrough. It has since triggered scores of investigations on human brown fat and its potential effects on obesity and health.
Although this brown fat research is genuinely exciting, my perspective is slightly different. What about adult livestock? The human research is new, and so far, there are no reports about corresponding PET scans of cows. Frankly, we don’t know if adult livestock actually contain functional depots of brown fat.
So here’s my speculation: If adult humans have brown fat, it logically follows that adult livestock would also have it. We don’t know much about this yet – namely, if and how much brown fat is present in adult livestock, how it develops during adult life, when it gets turned on, what turns it on or if any of this is governed by genetics. But the ramifications for livestock nutrition are enormous.
Sure, this research is expensive; PET scans don’t come cheap. But, in a way, we may already have some indirect evidence for adult brown fat: those RFI experiments demonstrating differences in feed efficiency. RFI has shown that some animals are clearly less efficient than others, and that this may be due to genetics. So, my thinking is: If some animals contain more brown fat than others, or if their brown fat were turned on more often, these animals would be less efficient because they would burn more nutrients to maintain themselves. It wouldn’t take much of a difference, maybe only 5% or so, which could be caused by a small amount of metabolically active brown fat. These animals would have high RFI values. Conversely, animals with low RFI values would have less brown fat, or maybe turn it on less often. And if this was governed by genetics, some of the unexplained variation we see in nutritional experiments could be explained by the presence of adult brown fat. The most efficient cattle would have less brown fat. And these would be our easy-keepers.
Now we’ve come full circle. Easy-keepers … feed efficiency … residual feed intake … PET scans … brown fat … lower maintenance requirements … easy-keepers.
It looks like we may have some interesting research ahead of us. We can dream, can’t we?
