Oct 2026· Journal of food process engineering· Vol 49· 0 citations· 27 references
Abstract
Visible/near‐infrared (Vis/NIR) spectroscopy offers a promising non‐destructive technique for assessing round eggplant (
Solanum melongena
var.
esculentum
) quality. For the purple‐black round eggplant samples examined here, however, dark pericarp coloration and multi‐layered tissue structure limit light penetration and accurate internal evaluation. To clarify how light penetrates round eggplant tissues, this study measured two key optical parameters. These were the absorption coefficient () and reduced scattering coefficient (), which describe tissue light absorption and scattering, respectively. The and values of the pericarp, pulp, and seed cavity were determined across 400–1050 nm using a single integrating sphere system combined with the inverse adding‐doubling method. Results revealed high in the pericarp (up to 8.93 mm
−1
) at 400–700 nm, which impeded light penetration. Beyond 700 nm, decreased to near zero and stabilized at approximately 0.6 mm
−1
, facilitating deeper transmission. The measured optical properties were then used in Monte Carlo eXtreme (MCX) simulations to examine light propagation and penetration through the tissues. Simulations showed that as source‐detector angles increased, average path lengths and attenuations stabilized between 120° and 165°. Seed cavity absorbance contributions increased with angle, whereas pericarp and pulp contributions declined, with the overall contribution pattern stabilizing near 135°. Optimal source‐detector angles of 105°–135° were identified to maximize tissue information extraction and signal stability. This study systematically characterized the optical properties of purple‐black round eggplant tissues and performed MCX simulations based on the measured parameters. Although the simulation model treated tissue layers as homogeneous media, the results revealed light propagation and penetration patterns within round eggplant tissues. These findings provide a theoretical foundation for developing Vis/NIR spectroscopy‐based non‐destructive monitoring and detection systems for round eggplant quality.
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