Abstract: Spring corn leaf blight with different grades was induced by artificial inoculation of pathogenic bacteria, the hyperspectral data of spring corn canopies in both healthy planting area and different infected planting areas were measured at different growth stages. To effectively monitor and control the effects of spring corn leaf blight, this study proposed a new remote sensing monitoring index which was the product of the sum total of the first derivative within green edge core area and the sum total of the first derivative within red edge core area. Finally, the results of correlation analysis between the proposed monitoring index and degrees of disease showed that the proposed index had significant linear correlation with the degrees of disease, and the correlation coefficient was 0.9711, which was better than the results of other traditional remote sensing monitoring index. The proposed index could be used for recognition of healthy spring corn and infected spring corn, and also could be used for spring corn classification of different disease grades. Therefore, hyperspectral remote sensing method could be used for disease monitoring of spring corn, and has great reference for improving grain output and ensuring grain security.