Crop spectrum characteristic analysis plays an important role in growth condition monitoring and nutrition diagnosis for precision management. It is also the theoretical basis of remote sensing data analysis. In order to predict the nutrient content of crop nondestructively and quickly, a spectrum detection system for summer corn was developed to measure the reflectance of 350~820nm. The system had three parts, i.e., optical sensor, data storage and transmission module and controller. And spectral information collection software included three modules, i. e., acquisition parameters, acquisition control and data management. Calibration experiment was carried out to test the performance of spectrum analyzing system. The correlation with ASD Field Spec Hand Held 2 was analyzed. The result showed that the average determination coefficient was 0.94. It was used to detect the chlorophyll and moisture contents of corn leaves. The relationships were analyzed based on the one and twodimensional correlations, respectively. Firstly, the chlorophyll content detecting model was established based on firstorder differential and Kvalue clustering method by using 548nm,594nm and 652nm with determination coefficients of 0.43 and 0.36. Then, the response relationships between moisture content and chlorophyll content in corn leaves were discussed and the model was revised by wavelengths at 480nm, 594nm, 652nm and 819nm. The revised chlorophyll content detecting model was established with determination coefficients of 0.47 and 0.34.