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Volume 55
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Proceeding Paper

Near-Infrared Wavelength Selection and Optimizing Detector Location for Apple Quality Assessment Using Molecular Optical Simulation Environment (MOSE) Software †

by
Quy Tan Ha
1,
Thao Nguyen Dang Thi
1,
Ngoc Tuyet Le Nguyen
1,
Hoang Nhut Huynh
1,
Anh Tu Tran
2,
Hong Duyen Trinh Tran
1 and
Trung Nghia Tran
1,*
1
Laboratory of Laser Technology, Faculty of Applied Science, Ho Chi Minh City University of Technology (HCMUT), VNUHCM, 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City 72506, Vietnam
2
Laboratory of General Physics, Faculty of Applied Science, Ho Chi Minh City University of Technology (HCMUT), VNUHCM, 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City 72506, Vietnam
*
Author to whom correspondence should be addressed.
†
Presented at the IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability, Tainan, Taiwan, 2–4 June 2023.
Eng. Proc. 2023, 55(1), 29; https://doi.org/10.3390/engproc2023055029
Published: 29 November 2023
(This article belongs to the Proceedings of 2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability)
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Abstract

As an alternate non-destructive analytical modality for monitoring from pre-harvest to post-storage, optical imaging with near-infrared wavelength is used to forecast the quality of numerous fruits. In the near-infrared spectrum, bio-chemicals are identified and measured with light by penetrating deeply into food components. In addition, apples and other fruits with a high water content benefit from water absorption capabilities. The optical approaches are efficient, inexpensive, and environmentally beneficial. This study is performed to examine the setup of reflection imaging to pick the near-infrared wavelength and optimize the distance between the detector and the light source. Molecular Optical Simulation Environment (MOSE) and Monte Carlo multi-layered programs (MCML) were used to simulate the light propagation in a model of apple tissue to select the appropriate wavelength for evaluating food quality in experiments and optimize the position of the reflected signal receiver. As a consequence, the 700–900 nm wavelength has great promise for use in assessing food quality, particularly apple quality. One centimeter is the optimal distance between the detector and the light source. The data may be used to organize an experiment and create an evaluation tool for determining the quality of fruits using optical methods, particularly apples.
Keywords: optical imaging; light propagation; near-infrared; Monte Carlo; MOSE; MCML optical imaging; light propagation; near-infrared; Monte Carlo; MOSE; MCML

Share and Cite

MDPI and ACS Style

Ha, Q.T.; Thi, T.N.D.; Le Nguyen, N.T.; Huynh, H.N.; Tran, A.T.; Tran, H.D.T.; Tran, T.N. Near-Infrared Wavelength Selection and Optimizing Detector Location for Apple Quality Assessment Using Molecular Optical Simulation Environment (MOSE) Software. Eng. Proc. 2023, 55, 29. https://doi.org/10.3390/engproc2023055029

AMA Style

Ha QT, Thi TND, Le Nguyen NT, Huynh HN, Tran AT, Tran HDT, Tran TN. Near-Infrared Wavelength Selection and Optimizing Detector Location for Apple Quality Assessment Using Molecular Optical Simulation Environment (MOSE) Software. Engineering Proceedings. 2023; 55(1):29. https://doi.org/10.3390/engproc2023055029

Chicago/Turabian Style

Ha, Quy Tan, Thao Nguyen Dang Thi, Ngoc Tuyet Le Nguyen, Hoang Nhut Huynh, Anh Tu Tran, Hong Duyen Trinh Tran, and Trung Nghia Tran. 2023. "Near-Infrared Wavelength Selection and Optimizing Detector Location for Apple Quality Assessment Using Molecular Optical Simulation Environment (MOSE) Software" Engineering Proceedings 55, no. 1: 29. https://doi.org/10.3390/engproc2023055029

APA Style

Ha, Q. T., Thi, T. N. D., Le Nguyen, N. T., Huynh, H. N., Tran, A. T., Tran, H. D. T., & Tran, T. N. (2023). Near-Infrared Wavelength Selection and Optimizing Detector Location for Apple Quality Assessment Using Molecular Optical Simulation Environment (MOSE) Software. Engineering Proceedings, 55(1), 29. https://doi.org/10.3390/engproc2023055029

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