Sanya Institute of Nanjing Agricultural University, Sanya, Hainan 572024, China; College of Food Science and Technology, Nanjing Agricultural University, No. 1 Weigang Road, Nanjing 210095, China.
College of Food Science and Technology, Nanjing Agricultural University, No. 1 Weigang Road, Nanjing 210095, China.
Food Res Int. 2024 Sep;192:114787. doi: 10.1016/j.foodres.2024.114787. Epub 2024 Jul 18.
This original work investigated the optical properties and Monte-Carlo (MC) based simulation of light propagation in the flavedo of Nanfeng tangerine (NF) and Gannan navel orange (GN) infected by Penicillium italicum. The increase of absorption coefficient (μ) at around 482 nm and the decrease at around 675 nm were both observed in infected NF and GN during storage, indicating the accumulation of carotenoids and loss of chlorophyll. Particularly, the μ in NF varied more intensively than GN, but the limited differences of reduced scattering coefficient (μ') were detected while postharvest infection. Besides, MC simulation of light propagation indicated that the photon packets weight and penetration depth at 482 nm in NF were reduced more than in GN flavedo, while there were almost no changes at the relatively low absorption wavelength of 926 nm. The simulated absorption energy at 482 nm in NF and GN presented more changes than those at 675 nm during infection, thus could provide better detection of citrus diseases. Furthermore, PLS-DA models can discriminate healthy and infected citrus, with the accuracy of 95.24 % for NF and 98.67 % for GN, respectively. Consequently, these results can provide theoretical fundamentals to improve modelling prediction robustness and accuracy.
本研究旨在探讨受意大利青霉感染的南丰蜜橘和赣南脐橙果皮的光学特性及光在其中的传播的蒙特卡罗（MC）模拟。在贮藏过程中，我们观察到感染的 NF 和 GN 的吸收系数（μ）在 482nm 左右增加，在 675nm 左右下降，这表明类胡萝卜素的积累和叶绿素的损失。特别是，NF 中的 μ 变化比 GN 更为剧烈，但在采后感染期间，探测到的散射系数（μ'）的差异有限。此外，光在 NF 和 GN 果皮中的传播的 MC 模拟表明，在 NF 果皮中，482nm 处的光子包权重和穿透深度的降低比 GN 更为明显，而在相对吸收波长 926nm 处几乎没有变化。在 NF 和 GN 中，模拟的 482nm 处吸收能量在感染期间的变化比 675nm 处更为明显，因此可以更好地检测柑橘病害。此外，PLS-DA 模型可以区分健康和感染的柑橘，NF 的准确率为 95.24%，GN 的准确率为 98.67%。因此，这些结果可以为提高建模预测的稳健性和准确性提供理论基础。
