The objective of this paper is to identify disease and its severity of soybean by using single leaf spectral data in the field. The soybean spectral were measured in the Sutton Bonington Campus of University of Nottingham( 52.8°N, 1.2°W), which infected rust disease(RD) and common mosaic disease (CMD), respectively, and continuum removal method was used to process the original spectral data, and sensitive bands were selected for disease and disease severity, and vegetation index was designed for identifying RD and CMD of soybean. The result showed spectral reflectance of soybean under CMD stressed is more than that of health in the visible region. However, spectral reflectance of soybean under RD stressed will decrease in the green region and that will increase in the red region with disease severity increasing. According to the spectral changing features, a new index R500×R550/R680 was designed for identifying the disease of soybean. In order to test the index identifying disease ability, the J-M distances were calculated among health, RD and CMD. The result indicated index R500×R550/R680 can better identify RD and CMD, at the same time, the index has good ability for discriminating the disease severity of soybean. The research results of this paper has important theoretical value for crops disease monitoring and prevention and practical application meanings.