[Study on a method for fast selecting feature wavelengths from the spectral information of crop nitrogen]

Research on a method for fast selecting feature wavelengths from the nitrogen spectral information is necessary, which can determine the nitrogen content of crops. Based on the uniformity of uniform design, the present paper proposed an improved particle swarm optimization (PSO) method. The method can choose the initial particle swarm uniformly and describe the optimization space well by fewer sample points, which is helpful to avoiding the local optimum and accelerate the convergence. Then, the method was applied to fast select the nitrogen spectral wavelengths of soybean, cotton and maize. Calibration models based on the partial least square (PLS) method and selected wavelengths were constructed. The results illustrate that compared with the original wavelengths, the number of selected wavelengths decreases about 93%, which means the computation is simplified. Also, the precision of PLS prediction mode based on the selected wavelengths improves by 34% at least, and the prediction ability of calibration model increases greatly. Therefore, the proposed method is both correct and effective.