This research uses remote sensing technologies and environmental data to optimize “farming practices” affected by climate change.
The study, published in the journal Frontiers in Plant Science, highlights the benefits of UAVs and hyperspectral cameras in collecting comprehensive phenotypic data, significantly reducing time-consuming manual methods. By combining genetic markers, environmental data and remote sensing information, the team developed a neural network that could more accurately predict complex corn yield traits.
The AI model is one of the first to combine plant genetics with yield predictions over large areas and over several years, allowing breeders to select traits for more resilient corn varieties, the researchers said.
Source: Ferra
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