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Support vector machine was used to invert nitrogen content of processing tomato early blight leaves in Xinjiang. The spectrum characteristic of processing tomato of difference disease level was analyzed. Then nitrogen content was found to be strong correlation with the spectral reflectivity on 218~357nm, 384~587nm, 1033~1141nm,1499~2500nm, because the correlation coefficients were more than 0.8. The vegetation index, SR705, ND705, GMI-2, RI-half, and PTEBc were chosen through K-CV cross validation, and SVM model was used to invert the nitrogen content with the vegetation index. The results show that the precision the SVM model of radial basis function kernel was the highest in linear kernel, polynomial kernel, radial basis function kernel and Sigmoid kernel. The value of MSE was 0.0124. The value of R was 85.916%. The value of average relative error was 0.175. SVM model with multi-vegetation index improved the precision of inverting nitrogen content of processing tomato early blight leaves.