Rapid identification of biochar traceability is of importance to the reasonable development and application of biochar. In this experiment, 14 kinds of biochar are taken as the research samples. The measured spectral data and principal components are compressed and extracted respectively by using the principal component analysis (PCA). The two dimensional distribution profile derived with the first and second principal components exhibits the distribution characteristics of different biochar samples. The linear identification model formed by the first three principal components has the best prediction effectiveness and the fewest error for the validation set. The experimental result shows that the spectroscopy combined with PCA can be used for the rapid identification and diagnosis of biochar.