A cutting-edge machine learning model has been developed to predict soil organic carbon (SOC) levels, a critical factor for soil health and crop productivity. The innovative approach utilizes hyperspectral data to identify key spectral bands, offering a more precise and efficient method for assessing soil quality and supporting sustainable agricultural practices. A cutting-edge machine learning model has been developed to predict soil organic carbon (SOC) levels, a critical factor for soil health and crop productivity. The innovative approach utilizes hyperspectral data to identify key spectral bands, offering a more precise and efficient method for assessing soil quality and supporting sustainable agricultural practices. Molecular & Computational biology Agriculture Phys.org – latest science and technology news stories
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