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The rapid monitoring of soil organic matter content based on hyperspectral data is of great significance for evaluating soil fertility. The best spectral parameters for predicting soil organic matter content were tried to find and nondestructive monitoring of soil nutrients was achieved. ASD Field-Spec3 spectrometer was used to measure the indoor spectra of soil samples collected in the field, and the organic matter content of soil samples was measured by the potassium dichromate oxidation capacity method; the nitrogen planar component index (SOMCI/ND) was optimized by twoband optimization algorithm. Band optimization, screening the most sensitive spectral parameters of different spectral data (the original spectral reflectance and its corresponding four mathematical transformations), thus establishing a hyperspectral estimation model of soil organic matter content. The results showed that the correlations between soil organic matter content and the new algorithm (SOMCI/ND) optimized by the normalized spectral index (IND) and conceptual index (ICI) ratios were significantly improved. The raw data in the spectrum and its square root and reciprocal transformation form, the absolute value of correlation coefficient reached 0.82, and the sensitive combination bands were concentrated in 2220~2240nm and 2160~2195nm. The prediction model based on the square root band optimization had the best effect. The prediction accuracy was R2P of 0.84，RMSEP of 2.24g/kg and RPD of 2.89. Therefore, the appropriate mathematical transformation of the spectral data was conducive to optimizing the spectral index to better estimate the soil organic matter content, and further achieve highprecision dynamic monitoring of soil organic matter.