The internal qualities of apple were detected using spectral imaging. The spectral imaging in wavelength of 632 nm, 650 nm, 670 nm, 780 nm, 850 nm and 900 nm were captured. The Lorentzian distribution (LD), Gaussian distribution (GD) and Exponential distribution (ED) with three parameters were used to fit scattering profiles for all wavelengths. LD was found to be the best function for fitting gray distribution of imaging. The multi-linear regression model relating Lorentzian parameters to fruit sugar content were development using best single wavelength, double wavelengths, three wavelengths and four wavelengths. The best model with four wavelengths was able to predict apple sugar content with r=0.831. Results show that the multi-spectral scattering imaging is nondestructive, fast and easy to implement, and it can provide a nondestructive means for measuring fruit internal quality.