By Lisa Lock
Scientists at the Royal Botanic Gardens, Kew, World Forest ID, University of Sheffield and international collaborators have developed a new technique that can identify where soybeans—the third largest driver of tropical deforestation—are grown to within roughly 200 kilometers, a breakthrough that could transform efforts to stop deforestation linked to global food supply chains.
The study, published in Communications Earth and Environment, combines chemical fingerprinting of soybeans with advanced geospatial machine learning to estimate where crops were harvested across South America. Researchers say the method could help regulators, scientists and companies verify the origins of commodities that are often traded through complex international supply chains.
Agricultural expansion remains the biggest driver of tropical forest loss, with 3.7 million hectares of tropical forest lost in 2023 alone, while 71.6 million hectares were lost between 2001 and 2015. Soy, primarily produced for pig and poultry feed, accounts for about 11.5% of commodity-driven deforestation, particularly in South America where production is rapidly expanding to meet global demand. The crop is the third-largest driver of tropical deforestation, behind cattle and oil palm, yet tracing where soy was grown is difficult because shipments are often mixed and traded across multiple countries.
The new study shows it is possible to estimate soybean harvest origin far more precisely than previous methods, which could only classify by country or broad region. By analyzing stable isotope ratios and trace elements across 267 soybean samples collected throughout South America, and combining them with environmental data, scientists have developed a machine-learning model that predicts crop origin to within 192.52 (±23.51) km from the harvest location. This is significant as deforestation risk varies dramatically over short distances, sometimes even between neighboring farms.
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