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[Objective] Estimating soil total potassium content quickly and accurately is very important to precision agriculture. [Method]Based on soil spectral data and soil total potassium content data obtained from laboratory analysis, the relationship between soil spectral and soil total potassium content was studied. The smooth spectral data of soil total potassium were treated with the first derivative, second derivative and reciprocal logarithmic to select the spectral indicators with the highest correlation with soil total potassium content. Finally, a model was established to predict soil total potassium content. [Result] Spectral variables based on first derivative are the best spectral index for estimating soil total potassium content. The predicted accuracy of hyperspectral inversion model(y=2E+06x2+11328x+16. 372) was the best with R2 of 0. 64 and RMSE of 4. 850 g/kg. [Conclusion] It is feasible to rapidly estimate the soil total potassium content of Guangdong Province by using this model. [ABSTRACT FROM AUTHOR]