Assessment of Optical Properties and Monte Carlo Multilayered Simulation of Light Propagation in Cherries for SSC and...

Nondestructive detection technology for cherry quality is a critical demand in the field of agricultural product processing, whereas existing studies lack a systematic exploration of the optical properties of cherries. This study investigated the optical properties (OPs) of cherry tissues and the light propagation using Monte Carlo multilayered (MCML) simulations. Moreover, the relationships between the OPs with internal qualities were explored. The results showed that skin tissues had significant absorption in 400-600 nm, while decreasing in 650-1050 nm. The reduced scattering coefficient of flesh tissues has significant differences in 400-1050 nm. Microscopic images revealed that the differences in OPs were caused by the broken cellular structure, and the bruising had no significant effect on soluble solids content (SSC) and moisture content (MC). MCML simulations indicated that photon energy distribution was dominated by diffuse reflectance due to the high reflectance of the kernel. Therefore, the reflectance model is more effective for detecting internal qualities. The PLSR models for the prediction of SSC and MC built on the absorption coefficient spectra had the best prediction performance, with a coefficient of determination of 0.935 and 0.839, and root mean square error of 0.254 and 0.008, respectively. The results indicate that the absorption characteristics of cherry tissue are primarily influenced by SSC and MC, and the use of the absorption coefficient enables more accurate prediction of its internal quality. This work offers guidance for nondestructive assessment methods targeting cherry internal quality. PRACTICAL APPLICATIONS: The reflectance model is more effective for detecting internal qualities, and the internal quality can be predicted better based on the absorption coefficient. This work offers guidance for nondestructive assessment methods targeting cherry internal quality.