To reduce greenhouse gas and produce better-tasting beef, a cattle federation tests blockchain paid Oracle
to trace individual cuts of meat back to the cows from which they came, and then share that data with consumers in exchange for their feedback about the taste.
In addition to Oracle technology, ICBF is also writing custom code in R, using mixed-model equations, and creating machine-learning algorithms that can evaluate the range of traits that lead to superior genetics in cattle. Then, the models assign an economic value to those traits, which ultimately helps farmers determine the overall profitability of their herds.
Still, the size of the cow, the amount of methane it emits, and the meat it produces are only some of the components of the overall value equation, says Andrew Cromie, technical director for ICBF. “We’re also looking at how quickly those cows are finished and taken to market,” he says. By isolating genotypes that determine fast-growing traits, Cromie claims he is helping farmers get their cattle to market 100 days faster than the average 700 days.
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