What do pigs and snowflakes have in common? If you said they’re both pretty and fall from the sky, it’s time to quit the eggnog. The correct answer is that in both cases, no two are the same. That may sound simplistic, but it plays a key role in the complex task of applying genomics to improve disease resilience in the pork industry.
“There’s a strong focus on precision agriculture today, and it’s a concept that applies to our research as well,” said Austin Putz, graduate research assistant in the Department of Animal Science at Iowa State University. “The more precise we are in gathering data on individual pigs, the more accurate our phenotyping will be, leading to better results for the project.”
To that end, Putz is collecting individual feed intake information daily on 2200 pigs to identify trends.
Putting the “stock” in livestock
“Looking at feeding behavior for each pig is a lot like watching the stock market. Some pigs steadily increase their feed intake day-to-day, while others are very volatile, spiking one day and then crashing for a while. Studying feed patterns reveals that within the same group of animals, a number of them stay perfectly healthy while other pen-mates get sick. My goal is to summarize all of this data to phenotype pigs on a gradient of resilience, where higher values indicate a less resilient animal.”
After plotting feed intake from 70-180 days of age, Putz’s first approach to analyzing the data was simple regression, where he determined the total amount of variation from a straight line for each animal. Ones that followed the line closely – like a low volatility stock – were deemed more resilient. Conversely, a lot of deviation from the line equated to non-resilience. Though he found that on a genetic level, this method was 80-90 per cent correlated with mortality and about 70 per cent with treatment rate, he also explored alternatives.
“My next strategy centered on consecutive days below the line, or what I call ‘a run of depression’. Any run of 7 days or more is highly unlikely to occur by chance, so I can take that information and include it in my resilience calculations by boiling it down to a single number for every pig."
The entire process involved more statistical models and computations than one article can address. Suffice it to say that Putz’s work is moving the project closer to its ultimate goal of selecting for more resilient pigs, something the industry would welcome.
Rising to the challenge
“A study in 1998 divided pigs into two groups with either high or low levels of disease challenge and other stressors. It was a small sample size, but it estimated the value of the diseased pigs at about 70 per cent of the healthy ones. Working on this project and these traits, we want to limit productivity loss. A non-resilient pig that dies provides no revenue, so the aim here is minimizing the economic burden on producers and boosting the efficiency of the system. We do that by supporting the survival of pigs, and enabling those pigs to be more productive.”
Admittedly, the process of improving resilience and reducing death loss is a long one, yet it’s something that is gaining an ever greater following in the industry.
All things considered, the progress to date is worth toasting with some eggnog; just not too much.