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Assessment of Optical Properties and Monte Carlo-Based Simulation of Light Propagation in Blackhearted Potatoes

文献类型： 外文期刊

作者： Guo, Yalin 1 ; He, Yakai 2 ; Li, Xilong 1 ; Guo, Zhiming 3 ; Zhang, Mengyao 1 ; Huang, Xiaomei 4 ; Zhu, Zhiyou 4 ; Jian, Huabin 1 ; Du, Zhilong 2 ; Lv, Huangzhen 1 ;

作者机构： 1.Chinese Acad Agr Mechanizat Sci Grp Co Ltd, Beijing 100083, Peoples R China

2.China Natl Packaging & Food Machinery Corp, Beijing 100083, Peoples R China

3.Jiangsu Univ, Sch Food & Biol Engn, Zhenjiang 212013, Peoples R China

4.Minist Agr & Rural Affairs China, Key Lab Agroprod Primary Proc, Beijing 100083, Peoples R China

关键词： blackhearted potatoes; Vis-NIR spectroscopy; optical properties; light propagation; Monte Carlo simulation

期刊名称：SENSORS （ 影响因子：3.5； 五年影响因子：3.7 ）

ISSN：

年卷期： 2025 年 25 卷 12 期

页码：

收录情况： SCI

摘要： This study investigated the optical properties (OPs) and Monte Carlo (MC) simulations of light propagation in Healthy Group (HG) and Blackhearted Group (BG) potatoes. The MC simulation of light propagation indicated that both the photon packet weight and the penetration depth were significantly lower in blackhearted tissues than in healthy tissues. The simulation revealed deeper light penetration in healthy tissues than in the blackhearted tissues, approximately 6.73 mm at 805 nm, whereas the penetration depth in blackhearted tissues was much shallower (1.30 mm at 805 nm). Additionally, the simulated absorption energy at both 490 nm and 805 nm was higher in blackhearted tissues, suggesting that these wavelengths effectively detect blackheart in potatoes. The absorption (mu a) and reduced scattering (mu's) coefficients were obtained using Vis-NIR spectroscopy, which represented a notable increase in mu a in BH tissues, particularly around 550-850 nm, and an increase in mu's across the Vis-NIR region. Based on transmittance (Tt), mu a and mu's, Support Vector Machine Discriminant Analysis (SVM-DA) models demonstrated exceptional performance, achieving 95.83-100.00% accuracy in Cross-Validation sets, thereby confirming the robustness and reliability of the optical features for accurate blackheart detection. These findings provide valuable theoretical insights into the accuracy and robustness of predictive models for detecting blackhearted potatoes.

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