Triterpenic acids are abundant in Loquat leaves, which present a relatively high medicinal value. The relative relationship between hyperspectral signal and triterpenic acid content was established and the distribution of triterpenic acids in loquat leaves was measured using hyperspectral images, as they contain the spectral signal for each pixel. Synergy interval partial least squares (siPLS) was used to establish an analytical model of triterpenic acid content in loquat leaves. The results showed that the optimal model was obtained by the siPLS spectral region screening method, which separated the whole spectrum into 11 intervals and combined four intervals, including intervals 1, 5, 6, and 7, and had a factor number of 4. The model achieved a correlation coefficient of 0.8449 and root mean square error of cross validation (RMSECV) of 3.392 mg/g in the calibration set and a correlation coefficient of 0.8223 and root mean square error of prediction (RMSEP) of 3.73 mg/g in the prediction set. Every pixel in the hyperspectral image was computed and the triterpenic acid content of each pixel was obtained according to the siPLS model, followed by the creation of a pseudo-color map to describe the distribution of triterpenic acids in loquat leaves. Overall, the results sufficiently demonstrate that it is feasible to employ hyperspectral imaging technology to measure the content of triterpenic acid and its distribution in loquat leaves.