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Soil organic matter (SOM) is crucial for carbon sequestration and sustainable agriculture, yet traditional quantification methods are challenging to apply at large scales. Hyperspectral technology combined with machine-learning offers promising prospects for rapid quantification. This study explores the impact of using VNIR-SWIR spectra on SOM quantification in regions characterized by distinctive
