Hyperspectral Sensing in Detecting Asymptomatic Basal Stem Rot Infection in Oil Palm, vol 12

Dr. Siti Khairunniza-Bejo

in Regional Professorial Chair Lecture from Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA)

Abstract: This issue of the monograph series emphasizes the importance of hyperspectral sensing as a contemporary tool for detecting Ganoderma boninense, a fungal pathogen that causes basal stem rot (BSR) disease in oil palm trees. Hyperspectral sensing detects early infections faster and more accurately than traditional methods, which can be labor-intensive to cover a large plantation area. Unlike traditional methods that primarily depend on analyzing spatial features, it utilizes sophisticated algorithms to capture spectral similarities and identify specific differences associated with various diseases.

Keywords: Ganoderma boninense; oil palm; basal stem rot; hyperspectral sensing (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:sag:serpcl:2025:607

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