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Ganoderma boninense is a causal agent of basal stem rot (BSR) and is responsible for a significant portion of oil palm (Elaeis guineensis) losses, which can reach US$500 million a year in Southeast Asia. At the early stage of this disease, infected palms are symptomless, which imposes difficulties in detecting the disease. In spite of the availability of tissue and DNA sampling techniques, there is a particular need for replacing costly field data collection methods for detecting Ganoderma in its early stage with a technique derived from spectroscopic and imagery data. Therefore, this study was carried out to apply the artificial neural network (ANN) analysis technique for discriminating and classifying fungal infections in oil palm trees at an early stage using raw, first, and second derivative spectroradiometer datasets. These were acquired from 1,016 spectral signatures of foliar samples in four disease levels (T1: healthy, T2: mildly-infected, T3: moderately infected, and T4: severely infected). Most of the satisfactory results occurred in the visible range, especially in the green wavelength. The healthy oil palms and those which were infected by Ganoderma at an early stage (T2) were classified satisfactorily with an accuracy of 83.3%, and 100.0% in 540 to 550 nm, respectively, by ANN using first derivative spectral data. The results further indicated that the sensitive frond number modeled by ANN provided the highest accuracy of 100.0% for frond number 9 compared with frond 17. This study showed evidence that employment of ANN can predict the early infection of BSR disease on oil palm with a high degree of accuracy.

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Dual encapsulation of fungicides into the chitosan was synthesized and proven to prolong the release time and enhance the antifungal activity.

Basal stem rot (BSR) is a prominent plant disease caused by Ganoderma boninense fungus, which infects oil palm plantations leading to large economic losses in palm oil production. There is need for novel disease detection techniques that can be used to reduce the oil palm losses due to BSR. Thus, this paper investigated the feasibility of utilizing electrical properties such as impedance, capacitance, dielectric constant, and dissipation factor in early detection of BSR disease in oil palm tree. Leaf samples from different oil palm trees (healthy, mild, moderate, and severely-infected) were collected and measured using a solid test fixture (16451B, Keysight Technologies, Japan) connected to an impedance analyzer (4294A, Agilent Technologies, Japan) at a frequency range of 100 kHz-30 MHz with 300 spectral interval. Genetic algorithm (GA), random forest (RF), and support vector machine-feature selection (SVM-FS) were used to analyze the electrical properties of the dataset and the most significant frequencies were selected. Following the selection of significant frequencies, the features were evaluated using two classifiers, support vector machine (SVM) and artificial neural networks (ANN) to determine the overall and individual class classification accuracies. The selection model comparative feature analysis demonstrated that the best statistical indicators with overall accuracy (88.64%), kappa (0.8480) and low mean absolute error (0.1652) were obtained using significant frequencies produced by SVM-FS model. The results indicated that the SVM classifier shows better performance as compared to ANN classifier. The results also showed that the classes, features selection models, and the electrical properties were found to be significantly different (p < .1). The impedance values were highly classified by Ganoderma disease at different levels of severity with overall accuracies of more than 80%. Impedance can be considered as the best electrical properties that can be used to estimate the severity of BSR disease in oil palm using spectroscopy technique. As such, this study demonstrates the potentials of utilizing electrical properties for detection of Ganoderma diseases in oil palm.

Endophytic bacteria (Pseudomonas aeruginosa UPMP3 and Burkholderia cepacia UMPB3), isolated from within roots of oil palm (Elaeis guineensis Jacq.) were tested for their presymbiotic effects on two arbuscular mcorrhizal fungi, Glomus intraradices UT126 and Glomus clarum BR152B). These endophytic bacteria were also tested for antagonistic effects on Ganoderma boninense PER 71, a white wood rot fungal pathogen that causes a serious disease in oil palm. Spore germination and hyphal length of each arbuscular mycorrhizal fungal (AMF) pairing with endophytic bacteria was found to be significantly higher than spores plated in the absence of bacteria. Scanning electron microscopy (SEM) showed that the endophytic bacteria were scattered, resting or embedded on the surface hyaline layer or on the degraded walls of AMF spores, possibly feeding on the outer hyaline spore wall. The antagonistic effect of the endophytic bacteria was expressed as severe morphological abnormalities in the hyphal structures of G. boninense PER 71. The effects of the endophytic bacteria on G. boninense PER 71 hyphal structures were observed clearly under SEM. Severe inter-twisting, distortion, lysis and shriveling of the hyphal structures were observed. This study found that the effect of endophytic bacteria on G. intraradices UT126 and G. clarum BR152B resembled that of a mycorrhiza helper bacteria (MHB) association because the association significantly promoted AMF spore germination and hyphal length. However, the endophytic bacteria were extremely damaging to G. boninense PER 71.

Basal stem rot, caused by the basidiomycete fungus, Ganoderma boninense, is an economically devastating disease in Malaysia. Our study investigated the changes in lignin content and composition along with activity and expression of the phenylpropanoid pathway enzymes and genes in oil palm root tissues during G. boninense infection. We sampled control (non-inoculated) and infected (inoculated) seedlings at seven time points [1, 2, 3, 4, 8, and 12 weeks post-inoculation (wpi)] in a randomized design. The expression profiles of phenylalanine ammonia lyase (PAL), cinnamyl alcohol dehydrogenase (CAD), and peroxidase (POD) genes were monitored at 1, 2, and 3 wpi using real-time quantitative polymerase chain reaction. Seedlings at 4, 8, and 12 wpi were screened for lignin content, lignin composition, enzyme activities (PAL, CAD, and POD), growth (weight and height), and disease severity (DS). Gene expression analysis demonstrated up-regulation of PAL, CAD, and POD genes in the infected seedlings, relative to the control seedlings at 1, 2, and 3 wpi. At 2 and 3 wpi, CAD showed highest transcript levels compared to PAL and POD. DS increased progressively throughout sampling, with 5, 34, and 69% at 4, 8, and 12 wpi, respectively. Fresh weight and height of the infected seedlings were significantly lower compared to the control seedlings at 8 and 12 wpi. Lignin content of the infected seedlings at 4 wpi was significantly higher than the control seedlings, remained elicited with no change at 8 wpi, and then collapsed with a significant reduction at 12 wpi. The nitrobenzene oxidation products of oil palm root lignin yielded both syringyl and guaiacyl monomers. Accumulation of lignin in the infected seedlings was in parallel to increased syringyl monomers, at 4 and 8 wpi. The activities of PAL and CAD enzymes in the infected seedlings at DS = 5–34% were significantly higher than the control seedlings and thereafter collapsed at DS = 69%.

The effect of arbuscular mycorrhizal fungi (AMF) in combination with endophytic bacteria (EB) in reducing development of basal stem rot (BSR) disease in oil palm (Elaeis guineensis) was investigated. BSR caused by Ganoderma boninense leads to devastating economic loss and the oil palm industry is struggling to control the disease. The application of two AMF with two EB as biocontrol agents was assessed in the nursery and subsequently, repeated in the field using bait seedlings. Seedlings pre-inoculated with a combination of Glomus intraradices UT126, Glomus clarum BR152B and Pseudomonas aeruginosa UPMP3 significantly reduced disease development measured as the area under disease progression curve (AUDPC) and the epidemic rate (R L) of disease in the nursery. A 20-month field trial using similar treatments evaluated disease development in bait seedlings based on the rotting area/advancement assessed in cross-sections of the seedling base. Data show that application of Glomus intraradices UT126 singly reduced disease development of BSR, but that combination of the two AMF with P. aeruginosa UPMP3 significantly improved biocontrol efficacy in both nursery and fields reducing BSR disease to 57 and 80%, respectively. The successful use of bait seedlings in the natural environment to study BSR development represents a promising alternative to nursery trial testing in the field with shorter temporal assessment.