Abstract: The available components of soil organic matter content is an important factor for spectral characteristics of soil，and it can provide important information for soil digital management and precise fertilization if available components of soil can be estimated accurately using hyperspectral technology. Although the traditional chemical method had a high precision，there were mainly shortcomings，such as high cost，time-consuming，so it was unable to meet the needs of modern precision agriculture fertilization technology. In order to predict the available kalium content of soil more quickly and accurately，and improve the precision and practicability of the soil available kalium estimation model by removing the noise of soil hyperspectral reflectance，this paper studied the inversion relationship between soil spectrum and soil available kalium content used wavelet analysis and based on hyperspectral technology. With 134 soil samples selected at Qitai County in Xinjiang，the first derivative spectrum of the soil sample logarithmic reflectance was decomposed to many layers by using 4 wavelet functions respectively，and PLSR was used to establish the prediction models respectively and test precision values. Through comparison analysis，the optimal wavelet decomposing resolution for extracting the characteristic spectrum of soil organic matter was ascertained，and the best forecasting model was established. The results show that：1-3 layers low-frequency coefficients of wavelet decomposition were better，while the rest were worse. In 6 layers of all function decomposition，the highest accuracy of inversion models construct by low-frequency coefficients were all ca2，with increased the decomposition layers，the precision and significance decreased significantly. In the same scale，there was little accuracy difference between inversion models constructed by 4 wavelet functions low-frequency coefficients，while Bior1.3 was optimal. The best inversion model was ca2 that built by Bior 1.3，with R² and RMSE were 0.964 and 8.19 mg·kg^-1 respectively，and reached to significant level. Transformed the first derivative spectrum of the soil sample logarithmic reflectance from the 350 nm to 2 500 nm by the experiment，reducing the spectral noise signal，using wavelet analysis and PLSR method to invert the soil available kalium content，it can eliminate effectively and reduce multi-linearity and randomness of the inter-band，and it can improve the accurary value and stability of inversion model. A series of experimental results show that，the wavelet analysis for obtaining wavelet coefficients can not only extract the soil hyperspectral information，but also compress data，which is feasible to forecast soil potassium content in combination with partial least squares regression method. It should be an important part in future researches that how to choose the right function types to analyze specific soil spectral data.

Key words: soil hyperspectral, available kalium, wavelet analysis, inversion model, Qitai County