Assessment of Optical Properties and Monte Carlo-Based Simulation of Light Propagation in Blackhearted Potatoes
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 lowe...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/12/3713 |
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| Summary: | 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 (<i>μ</i><sub>a</sub>) and reduced scattering (<i>μ</i>’<sub>s</sub>) coefficients were obtained using Vis-NIR spectroscopy, which represented a notable increase in <i>μ</i><sub>a</sub> in BH tissues, particularly around 550–850 nm, and an increase in <i>μ</i>’<sub>s</sub> across the Vis-NIR region. Based on transmittance (<i>T</i>t), <i>μ</i><sub>a</sub> and <i>μ</i>’<sub>s</sub>, 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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| ISSN: | 1424-8220 |