This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: In beef cattle production, determining the ideal time to sell makes all the difference in a producer's costs. This is because, once an animal reaches its natural growth limit, it stops gaining weight significantly.
From that point on, every additional day in a feedlot means spending money on feed without gaining meat in return. To identify this optimal window without having to weigh every animal in the herd on a scale—a time-consuming and stressful process for the cattle—a group of researchers has developed a noninvasive solution. They created a system that combines drones and artificial intelligence to map the growth of Nelore cattle, allowing for precise monitoring of fattening and slaughter decisions based on aerial images.
The technology is described in an article published in the journal Computers and Electronics in Agriculture. The details were presented by Jayme Garcia Arnal Barbedo, a researcher at Embrapa Digital Agriculture—one of the decentralized units of the Brazilian Agricultural Research Corporation (EMBRAPA)—in a presentation given on Oct. 28 during FAPESP Week Netherlands. "We're very close to obtaining a complete, functional prototype of the system.
The next crucial step will be to establish partnerships with companies in the sector or agtechs, startups in the agricultural sector, to transform that research into a commercially available product for ranchers," Barbedo said. The innovation uses aerial images captured by drones flying at a height of 15 meters (49 feet). Using advanced deep learning algorithms, the system segments the animals' bodies and extracts morphological metrics to map the fattening curve in real time.
The results demonstrated that the optimal time for sale can be determined up to a week earlier than predicted by conventional methods. "The weight gain curve of a group of animals intended for slaughter has a characteristic shape of an 'S': it starts slowly during the adaptation phase, enters a period of very accelerated gain and then slows down in the final stage. From that point on, no matter how much feed you provide, the animal will no longer convert feed into meat at the same rate," Barbedo explained.
"Sometimes, a one-day difference in the decision to slaughter or in the sale of the herd can increase that operation's profit by 5% to 10%," he emphasized. The system's computational architecture combines two state-of-the-art artificial intelligence models. The first, for object detection, was fine-tuned to individually locate each Nelore steer in the feedlot, achieving 95.56% accuracy.
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