Metabolite profiling of Ganoderma-infected oil palm tree grown on ultisol and oxisol soil / Muhamad Fadhil Ahmad - Muhamad Fadhil , Ahmad (2020)
The oil palm industry is a pillar of the Malaysian economy and plays a pivotal role in feeding and fueling a growing global population. In 2018, oil palm contributed 37.9% or RM37.7 billion to the country's' Gross Domestic Products (GDP) of agriculture sector. Despite achieving significant achievements in the industry, Ganoderma sp. infection that cause basal stem rot (BSR) and upper stem rot (USR) disease are considered a threat. The palm oil industry is expected to experience significant losses, thereby affecting yield production and ultimately the dead of trees. Some factors have been reported to affect the occurrence of the disease such as the cultivation of the previous crop, replanting technique, age and number of individual palms per planted area, type of soil series, inoculum potential, shading and soil temperature, but research conducted on weathered tropical soils in Malaysia is still lacking. In Malaysia, Ultisol and Oxisol soil are very common which occupy about 72% of the country’s land area. This research is therefore conducted with the objective to determine soil physicochemical properties of Ultisol and Oxisol soil and profile metabolites of healthy and Ganoderma-infected oil palm grown on both soils. Biological samples were extracted using methanol and analyzed by using liquid chromatography time-of-flight mass spectrometry (LC-TOF-MS). Soil physicochemical properties analyzed using U-Mann Whitney revealed that Ultisol and Oxisol soil are different at pH and TC level but not for EC level. A chi-square test of independence classified Ultisol and Oxisol soil into sandy clay and clay respectively. For biological sample analysis, the initial Principal Component Analysis (PCA) model concluded that there was a difference between two main groups of metabolite profiles between healthy and Ganoderma-infected oil palm tree rachis samples. A strongly significant Partial Least Square-Discriminant Analysis (PLS-DA) model was acquired, indicating that the 12 biological variables indeed contained class separating information. The separation of the four classes was slightly superior compared with the previous PCA modelling attempts. This model also fits the criteria for validity in permutation test. From the model, 17 potential biomarker panels with variable importance in project (VIP) more than 2.00 and p-value of analysis of variance (ANOVA) less than 0.05 were identified. Among metabolite of interest putatively identified are choline phosphate, p-fluorophenylalanine, 2-oxoglutaramate, 4-oxoglutaramate, 4-amino-4-cyanobutanoic acid, 2-amino-4-cyanobutanoic acid, 5-aminolevulinate, L-allohydroxyproline and N-acetyl-beta-alanine. These findings are crucial for further study on the pathogenicity characteristic of BSR and USR disease in penetrating oil palm tree in the future.