Monte Carlo Simulation of Light Propagation in Orah Mandarin Tissues and Optimization of Spectral Detection in Diffuse Reflection Mode

Visible light/near-infrared (Vis/NIR) spectroscopy serves as an effective method for quality assessment of orah mandarin. However, as a multi-layered thick-skinned fruit, the optical properties (OPs) of different tissue layers in orah mandarin affect quality evaluation, resulting in weak signals and difficulties in extracting pulp information when applying Vis/NIR spectroscopy in practical applications. This research utilizes Monte Carlo methods to reveal the light propagation mechanism within the multi-layered tissues of orah mandarin, clarify the optical properties of each tissue layer and their contributions to detection signals, and provide theoretical basis and technical support for optimizing spectral detection systems under diffuse reflectance mode.

Orah mandarin was selected as the research material. The optical parameters of its oil sac layer, albedo layer, and pulp tissue were measured in the 500~1050 nm band using a single integrating sphere system combined with the Inverse Adding-Doubling method (Integrating Sphere-Inverse Adding-Doubling method, IS-IAD). Based on the optical parameters of different tissue layers, a three-layer concentric sphere model (oil sac layer, albedo layer, and pulp tissue) was established. The voxel-based Monte Carlo eXtreme (MCX) method was employed to study the transmission patterns of simulated photons in orah mandarin under diffuse reflectance mode, in order to optimize the configuration of detection devices.

The experimental results demonstrated that throughout the entire wavelength range, the oil sac layer and albedo layer exhibited identical variation trends in average absorption coefficient and average reduced scattering coefficient. The oil sac layer, rich in liposoluble pigments such as carotenoids, resulted in a peak absorption coefficient at 500 nm, while the porous structure of the albedo layer led to a higher reduced scattering coefficient, and the pulp tissue exhibited the lowest reduced scattering coefficient due to its translucent structure. Light penetration depth analysis revealed that in the 500~620 nm band, the light penetration depth of the oil sac layer was higher than that of the albedo layer, while at 980 nm, due to water molecule absorption, the light penetration depth of the pulp tissue showed a significant valley. Monte Carlo simulation results indicated that light was primarily absorbed within orah mandarin tissue, with transmitted photons accounting for less than 4.2%. As the source-detector distance increased, the average optical path and light attenuation in orah mandarin tissue showed an upward trend, while the contribution rates of the oil sac layer, albedo layer, and pulp tissue to the detected signal showed decreasing, decreasing, and increasing trends, respectively. Additionally, the optical diffuse reflectance decreased significantly with increasing source-detector distance. Based on the simulation results, it was recommended that the source-detector distance for orah mandarin quality detection devices should be set in the range of 13~15 mm. This configuration could maintain a high signal contribution rate from pulp tissue while obtaining sufficient diffuse reflectance signal strength, thereby improving detection accuracy and reliability.

The combination of Vis/NIR spectroscopy and Monte Carlo simulation methods systematically reveals the light propagation patterns and energy distribution within orah mandarin tissue, providing important theoretical basis and methodological support for non-destructive detection of orah mandarin. By employing a single integrating sphere system with the Inverse Adding-Doubling method to obtain optical parameters of each tissue layer and utilizing voxel-based Monte Carlo simulation to thoroughly investigate photon propagation patterns within the fruit, this research accurately quantifies the contribution rates of different tissue layers to diffuse reflectance signals and effectively optimizes key parameters of the detection system. These findings provide important references for developing more precise non-destructive detection methods and equipment for orah mandarin.