Mention genomics to a scientist, and the eyes light up with thoughts of recombination, microarrays and polymorphisms. For a beef producer, those terms make their eyes glaze over, but one word is sure to grab their interest: profit. It’s a word that plays a leading role in the Genome Alberta project using genomics to improve feed efficiency and carcass quality in beef cattle, and a key part of the project is development of a feedlot profit index.
“Using commercial animals, we have gathered information on a number of traits including average daily gain, residual feed intake, backfat thickness, marbling and carcass weight,” said Dr. Tiago Valente, PhD in Animal Breeding and Genetics from the Faculty of Agricultural and Veterinarian Sciences – São Paulo State University (UNESP). He is also a postdoctoral fellow at Livestock Gentec at the University of Alberta, working on this Genome Alberta project.
Worth the weight
Combining the trait data with carcass values and input costs, researchers are creating a profitability index that considers all traits and assigns each one an economic weight or value. Because they are using genotypes (an organism's full hereditary information) as well as phenotypes (an organism's actual observed properties, such as development or behavior), they can calculate the molecular breeding value (MBV) of each animal before sending it to the feedlot.
“Instead of waiting for an animal to be slaughtered and then gathering information from the plant, we can predict in advance the likelihood of that animal being profitable in terms of feed efficiency and carcass traits.”
Prospects for success
The goal is to provide producers who have genotyped their animals with an index they can use to improve profitability. Now that genotyping costs are decreasing, cattle farmers will know early on, at minimal expense, the prospects for each animal and act accordingly.
As the cost of keeping animals at the feedlot continues to rise, producers can choose to spend less on low profitability cows. The index will also aid decisions on which animals should be shipped to the feedlot, and help select bulls that can produce more profitable offspring.
“I’m happy with the progress so far, as we are substantially improving the accuracy of MBV’s and, in the process, building a very good selection index. We are now working to increase the number of individuals phenotyped for feed efficiency and carcass traits so we can make the selection index even stronger. As we do, we are developing the index and validating it with part of our cattle population to see if our values are correct based on actual phenotypes.”
Any scientist can attest that some research projects are more applicable to the real world than others, and this one is definitely in the “more” category.
“It’s exciting to be part of giving producers a decision-making tool that will be useful to them and their businesses. As researchers, we want to do our best in finding ways to improve the market, and producers want to produce better animals and better meat. If science can support them in that effort and allow them to change their herds or their systems as needed, we’ve done our job.”
Ultimately, it’s about enabling producers to spend money where it will earn them the best return. Nothing against microarrays and recombination, but the most relevant term at day’s end is something far more tangible for industry: ROI.