Researchers from the University of Arkansas and the Ohio State University have developed a next-gen machine-learning model that maps animal feeding operations and monitors their environmental impacts.
According to an Arkansas news release, knowing the locations of livestock facilities is important for effective environmental management and the development of mapping tools. However, many operations are undocumented because of differences in federal and state laws, leaving gaps in the data.
Becca Muenich, an associate professor of engineering at Arkansas, set out to create a mapping tool to better predict livestock facility locations.
Knowing where farm animals are raised is important because animal feeding facilities produce large amounts of manure, which can pose "significant ecological harm," according to Muenich. If animal waste isn't handled properly, it can contaminate water sources and contribute to algal blooms when excess nitrogen and phosphorus enter waterways through runoff.
"We can't really address something if we don't know where the problem is," said Muenich, who is also a researcher for the University of Arkansas System Division of Agriculture.
"We don't have a good nationwide — even at many state levels — understanding of where livestock are in the landscape, which really hinders our ability to do some of the studies that I was interested in," she added.
Rapid population growth and an increasing demand for animal products are fueling the expansion of animal feeding operations in the United States, making it necessary to develop accurate mapping tools.
Muenich's team developed a machine-learning-based model that incorporates factors such as surrounding vegetation, land surface temperatures, and phosphorus levels, which are strong indicators of a livestock facility in the area. This type of model removes some of the barriers associated with aerial image-based strategies since livestock facilities differ widely between states, which can lead to inaccuracies in data from aerial imagery.
According to a study on the machine-learning model published in the journal Science of the Total Environment, the improved mapping tool predicted the location of known animal feeding operations with 87% accuracy.
Being able to track livestock more closely without using time-consuming, expensive methods could lead to improvements in the environmental management of animals and "provide economic opportunities for farmers through the scaling up of technologies aimed at combating animal waste," Muenich explained.
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Grocery stores 🛒 The mapping technology could also help nearby communities, as more sustainable agricultural practices would lead to less pollution being released into the air and waterways, reducing the risk of waste contaminating groundwater and leaching into drinking supplies.
Another team of scientists developed a unique system to monitor cattle feed consumption, attaching tags equipped with a radio frequency mechanism that triggers machines to release specialized feed. Controlling the amount of food that cattle eat could help reduce pollution, a major problem in animal agriculture. Ranchers are also trialing a red algae diet for cows, which scientists found could reduce methane in their burps by 80%.
Eating plant-based foods, even as a replacement for one or two meals a week, can also make a big difference in reducing the environmental impact of the meat industry.
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