GC–MS-Based Untargeted Metabolic Profiling of Oil Palm Stems Associated with Ganoderma boninense Infection

Basal stem rot, mainly caused by Ganoderma boninense, is a major disease affecting oil palm (Elaeis guineensis) and can lead to reduced productivity and plant mortality. This study characterized metabolic changes associated with different levels of G. boninense infection in oil palm stem tissue using untargeted gas chromatography–mass spectrometry metabolomics. Stem samples representing healthy, low, moderate, and high infection categories were analyzed, and the resulting metabolic features were processed using multivariate and univariate statistical approaches. A total of 14 features were retained after data processing and filtering. Principal component analysis and partial least squares discriminant analysis showed differences in the overall metabolic profiles among infection categories, while variable importance in projection analysis identified features contributing to group discrimination. However, permutation testing did not provide significant evidence for a classification model beyond chance (ANOVA p-value = 0.121), indicating that 121 of 1,000 permuted models achieved an accuracy at least as high as that of the observed model. None of the detected features remained significant after false discovery rate correction. Several fatty acid-related features, including methyl decanoate, methyl myristate, methyl oleate, methyl stearate, and methyl ricinoleate, were prioritized based on their multivariate contribution, abundance patterns, and library-based annotation. These compounds are therefore considered candidate metabolites associated with disease severity rather than validated biomarkers. The findings provide a preliminary view of metabolic variation in oil palm stems associated with G. boninense infection and identify candidate features for further validation using larger and independent sample sets.

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Publication Details

Journal
Periodica Polytechnica Chemical Engineering
Published
2026-11-10
DOI
https://doi.org/10.3311/ppch.44836
Primary Topic
Plant Pathogens and Fungal Diseases
Type
article
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article

GC–MS-Based Untargeted Metabolic Profiling of Oil Palm Stems Associated with Ganoderma boninense Infection

Susi Indriani, Adi Pancoro, Isdaryanti Isdaryanti, Andi Besse Poleuleng et al.
Periodica Polytechnica Chemical Engineering
Plant Pathogens and Fungal Diseases
article

GC–MS-Based Untargeted Metabolic Profiling of Oil Palm Stems Associated with Ganoderma boninense Infection

Susi Indriani, Adi Pancoro, Isdaryanti Isdaryanti, Andi Besse Poleuleng, Sitti Nur Ilmiah, Fitri Handayani
article en

Abstract

Basal stem rot, mainly caused by Ganoderma boninense, is a major disease affecting oil palm (Elaeis guineensis) and can lead to reduced productivity and plant mortality. This study characterized metabolic changes associated with different levels of G. boninense infection in oil palm stem tissue using untargeted gas chromatography–mass spectrometry metabolomics. Stem samples representing healthy, low, moderate, and high infection categories were analyzed, and the resulting metabolic features were processed using multivariate and univariate statistical approaches. A total of 14 features were retained after data processing and filtering. Principal component analysis and partial least squares discriminant analysis showed differences in the overall metabolic profiles among infection categories, while variable importance in projection analysis identified features contributing to group discrimination. However, permutation testing did not provide significant evidence for a classification model beyond chance (ANOVA p-value = 0.121), indicating that 121 of 1,000 permuted models achieved an accuracy at least as high as that of the observed model. None of the detected features remained significant after false discovery rate correction. Several fatty acid-related features, including methyl decanoate, methyl myristate, methyl oleate, methyl stearate, and methyl ricinoleate, were prioritized based on their multivariate contribution, abundance patterns, and library-based annotation. These compounds are therefore considered candidate metabolites associated with disease severity rather than validated biomarkers. The findings provide a preliminary view of metabolic variation in oil palm stems associated with G. boninense infection and identify candidate features for further validation using larger and independent sample sets.

Periodica Polytechnica Chemical Engineering
Bandung Institute of Technology (ID), Universitas Sulawesi Barat (ID), Politeknik Pertanian Negeri Pangkajene Kepulauan (ID), Universitas Billfath (ID), Institut Teknologi Bacharuddin Jusuf Habibie (ID)
Plant Pathogens and Fungal Diseases
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