Post by CSIRO

A competition with thousands of entries has advanced the use of AI in agriculture. 🐄 In partnership with Google Australia and Meat & Livestock Australia, we've launched a global challenge to help farmers determine when and how to graze their livestock. Using Kaggle, a data science competition platform, participants were tasked with training machine learning models to estimate pasture biomass directly from images, using data collected across different Australian regions, seasons, and pasture types. The winners of the Image2Biomass Prediction Competition have now been announced, with Team 卷不动了 from China securing first place for an approach that improved accuracy by adapting to changing conditions. The winning teams demonstrated that advanced models can learn to extract meaningful information from images, such as the amount of plant material, including grass and other vegetation available for livestock to graze, and do so reliably across changing conditions. This approach supports a shift from broad monitoring to targeted, site-specific management that pinpoints exactly where fertiliser or other interventions are needed. With a US$75,000 prize pool, the competition attracted nearly 100,000 model submissions from approximately 14,000 registrations across 109 countries. Read more about this new AI tool: https://lnkd.in/gXEhjgvk