Grain germination begins in the interior embryo, the early germination is difficult to be detected, which is a bottleneck restricting the safety of grain storage. The biological process of wheat grain germination mainly translates the starch into maltose for growth. In this paper, Terahertz(THz)imaging technology is used to investigate the image characteristics of maltose with different concentration. A THz spectrum is extracted from each pixel of the sample area in the image, and an average spectrum is obtained by averaging. The cumulative variance contribution rate of the first 5 principal components is over 98% according to the Principal Component Analysis(PCA) method, then the support vector machine (SVM) quantitative analysis regression model based on radial basis function is constructed by using the first 5 principal components score matrix. The comparison showed that THz imaging technology combined with chemometrics method is efficient and feasible for identifying maltose of different concentration and also indicated that the SVM obtains the best prediction results, which provides the theoretical basis for the detection of the state of germinated grain, guarantees the quality of stored grain and enhances the level of national storage technology.