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Near-Infrared Spectroscopy for Ganoderma Boninense Detection: An Outlook

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Recent Trends in Mechatronics Towards Industry 4.0

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 730))

Abstract

Ganoderma boninense (G. boninense) infection reduces the productivity of oil palms and causing a serious threat to the palm oil industry. This catastrophic disease ultimately destructs the basal tissues of oil palm that causing the eventual death of the palm. Early detection of G. boninense is vital since there is no effective treatment to stop the continuing spread of the disease. This mini-review describes past and future prospects of integrated research of near-infrared spectroscopy (NIRS) towards early G. boninense detection system. This effort could reduce the cost of plantation management and avoid production losses. Remarkably, (i) spectroscopy techniques are more reliable than other detection techniques such as serological, molecular, biomarker-based sensor and hyperspectral in reacting with organic tissues, (ii) NIR spectrum is more precise and sensitive to particular diseases include G. boninense compared to visible light, (iii) hand-held NIRS for in situ measurement is to explore the efficacy for early detection system in real-time using machine learning (ML) classifier algorithms and predictive analytics model. This non-destructive, environmentally friendly (no chemical involved), mobile and sensitive leads the integrated hand-held NIRS with ML, and predictive analytics has significant potential as a platform towards early detection of G. boninense in the future.

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Acknowledgements

This project is supported in part by CREST T14C2-16/006, FRGS/1/2019/STG02/UMP/01/1, UIC200814 and RDU202803

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Authors and Affiliations

  1. College of Engineering, Universiti Malaysia Pahang, 26300, Kuantan, Malaysia

    Mas Ira Syafila Mohd Hilmi Tan, Mohd Faizal Jamlos & Fatimah Dzaharudin

  2. Universiti Sains Malaysia, 11800, Gelugor, Penang, Malaysia

    Ahmad Fairuz Omar & Mohd Noor Ahmad

  3. Universiti Kuala Lumpur, 53100, Kuala Lumpur, Gombak, Malaysia

    Mohd Azraie Mohd Azmi

  4. Advanced Communication Engineering Centre (ACE), Universiti Malaysia Perlis, 01000, Kangar, Malaysia

    Nur Akmal Abd. Rahman

  5. VAT Manufacturing, Industrial Zone, 14100, Batu Kawan, Penang, Malaysia

    Khairil Anuar Khairi

Authors
  1. Mas Ira Syafila Mohd Hilmi Tan
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Correspondence to Mohd Faizal Jamlos .

Editor information

Editors and Affiliations

  1. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, Pekan, Malaysia

    Ahmad Fakhri Ab. Nasir

  2. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, Pekan, Malaysia

    Ahmad Najmuddin Ibrahim

  3. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, Pekan, Malaysia

    Ismayuzri Ishak

  4. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, Pekan, Malaysia

    Nafrizuan Mat Yahya

  5. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, Pekan, Malaysia

    Muhammad Aizzat Zakaria

  6. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, Pekan, Malaysia

    Anwar P. P. Abdul Majeed

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Tan, M.I.S.M.H. et al. (2022). Near-Infrared Spectroscopy for Ganoderma Boninense Detection: An Outlook. In: Ab. Nasir, A.F., Ibrahim, A.N., Ishak, I., Mat Yahya, N., Zakaria, M.A., P. P. Abdul Majeed, A. (eds) Recent Trends in Mechatronics Towards Industry 4.0. Lecture Notes in Electrical Engineering, vol 730. Springer, Singapore. https://doi.org/10.1007/978-981-33-4597-3_12

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