Soil total nitrogen prediction using sentinel-2 simulated bands and machine learning: a laboratory spectroscopy study in Hemerocallis citrina Baroni fields

Soil total nitrogen (STN) is a crucial indicator of crop productivity and soil health. Accurate monitoring of STN is essential for optimizing nitrogen management and achieving sustainable agricultural development. An adequate and timely STN supply serves as a key physiological basis for promoting effective tillering, flower stalk development, and continuous multibatch bud formation in Hemerocallis citrina Baroni. To address the challenges posed by the high-dimensionality of hyperspectral data an