Ganoderma boninense (G. boninense) infection reduces the productivity of oil palms and causes a serious threat to the palm oil industry. This catastrophic disease ultimately destroys the basal tissues of oil palm, 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 review describes past and future prospects of integrated research of near-infrared spectroscopy (NIRS), machine learning classification for predictive analytics and signal processing towards an 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 imaging techniques in reactions with organic tissues, (ii) the NIR spectrum is more precise and sensitive to particular diseases, including G. boninense, compared to visible light and (iii) hand-held NIRS for in situ measurement is used to explore the efficacy of an early detection system in real time using ML classifier algorithms and a predictive analytics model. The non-destructive, environmentally friendly (no chemicals involved), mobile and sensitive leads the NIRS with ML and predictive analytics as a significant platform towards early detection of G. boninense in the future.
This paper aims to study a triple flat-type air coil inductive sensor that can identify two maturity stages of oil palm fruits, ripe and unripe, based on the resonance frequency and fruitlet capacitance changes. There are two types of triple structure that have been tested, namely Triple I and II. Triple I is a triple series coil with a fixed number of turns (n = 200) with different length, and Triple II is a coil with fixed length (l = 5 mm) and a different number of turns. The peak comparison between Triple I and II is using the coefficient of variation cv, which is defined as the ratio of the standard deviation to the mean to express the precision and repeatability of data. As the fruit ripens, the resonance frequency peaks from an inductance⁻frequency curve and shifts closer to the peak curve of the air, and the fruitlet capacitance decreases. The coefficient of the variation of the inductive oil palm fruit sensor shows that Triple I is smaller and more consistent in comparison with Triple II, for both resonance frequency and fruitlet capacitance. The development of this sensor proves the capability of an inductive element such as a coil, to be used as a sensor so as to determine the ripeness of the oil palm fresh fruit bunch sample.
Oil palm ripeness' main evaluation procedure is traditionally accomplished by human vision. However, the dependency on human evaluators to grade the ripeness of oil palm fresh fruit bunches (FFBs) by traditional means could lead to inaccuracy that can cause a reduction in oil palm fruit oil extraction rate (OER). This paper emphasizes the fruit battery method to distinguish oil palm fruit FFB ripeness stages by determining the value of load resistance voltage and its moisture content resolution. In addition, computer vision using a color feature is tested on the same samples to compare the accuracy score using support vector machine (SVM). The accuracy score results of the fruit battery, computer vision, and a combination of both methods' accuracy scores are evaluated and compared. When the ripe and unripe samples were tested for load resistance voltage ranging from 10 Ω to 10 kΩ, three resistance values were shortlisted and tested for moisture content resolution evaluation. A 1 kΩ load resistance showed the best moisture content resolution, and the results were used for accuracy score evaluation comparison with computer vision. From the results obtained, the accuracy scores for the combination method are the highest, followed by the fruit battery and computer vision methods.
The production of palm oil (PO) is highly profitable. The economies of the principal producers, Malaysia and Indonesia, and others, benefit considerably. Climate change (CC) will most likely have an impact on the distribution of oil palms (OP) (Elaeis guineensis). Here we present modelled CC projections with respect to the suitability of growing OP, in Malaysia and Indonesia. A process-oriented niche model of OP was developed using CLIMEX to estimate its potential distribution under current and future climate scenarios. Two Global Climate Models (GCMs), CSIRO-Mk3.0 and MIROC-H, were used to explore the impacts of CC under the A1B and A2 scenarios for 2030, 2070 and 2100. Decreases in climatic suitability for OP in the region were gradual by 2030 but became more pronounced by 2100. These projections imply that OP growth will be affected severely by CC, with obvious implications to the economies of (a) Indonesia and Malaysia and (b) the PO industry, but with potential benefits towards reducing CC. A possible remedial action is to concentrate research on development of new varieties of OP that are less vulnerable to CC.
GWAS in out-crossing perennial crops is typically limited by insufficient marker density to account for population diversity and effects of population structure resulting in high false positive rates. The perennial crop oil palm is the most productive oil crop. We performed GWAS for oil-to-dry-mesocarp content (O/DM) on 2,045 genotyped tenera palms using 200K SNPs that were selected based on the short-range linkage disequilibrium distance, which is inherent with long breeding cycles and heterogeneous breeding populations. Eighty loci were significantly associated with O/DM (p ≤ 10(-4)) and three key signals were found. We then evaluated the progeny of a Deli x AVROS breeding trial and a 4% higher O/DM was observed amongst those having the beneficial genotypes at two of the three key loci (p < 0.05). We have initiated MAS and large-scale planting of elite dura and pisifera parents to generate the new commercial tenera palms with higher O/DM potential.
Ground-based LiDAR also known as Terrestrial Laser Scanning (TLS) technology is an active remote sensing imaging method said to be one of the latest advances and innovations for plant phenotyping. Basal Stem Rot (BSR) is the most destructive disease of oil palm in Malaysia that is caused by white-rot fungus Ganoderma boninense, the symptoms of which include flattening and hanging-down of the canopy, shorter leaves, wilting green fronds and smaller crown size. Therefore, until now there is no critical investigation on the characterisation of canopy architecture related to this disease using TLS method was carried out. This study proposed a novel technique of BSR classification at the oil palm canopy analysis using the point clouds data taken from the TLS. A total of 40 samples of oil palm trees at the age of nine-years-old were selected and 10 trees for each health level were randomly taken from the same plot. The trees were categorised into four health levels - T0, T1, T2 and T3, which represents the healthy, mildly infected, moderately infected and severely infected, respectively. The TLS scanner was mounted at a height of 1 m and each palm was scanned at four scan positions around the tree to get a full 3D image. Five parameters were analysed: S200 (canopy strata at 200 cm from the top), S850 (canopy strata at 850 cm from the top), crown pixel (number of pixels inside the crown), frond angle (degree of angle between fronds) and frond number. The results taken from statistical analysis revealed that frond number was the best single parameter to detect BSR disease as early as T1. In classification models, a linear model with a combination of parameters, ABD - A (frond number), B (frond angle) and D (S200), delivered the highest average accuracy for classification of healthy-unhealthy trees with an accuracy of 86.67 per cent. It also can classify the four severity levels of infection with an accuracy of 80 per cent. This model performed better when compared to the severity classification using frond number. The novelty of this research is therefore on the development of new approach to detect and classify BSR using point clouds data of TLS.
Meiotic crossovers in outbred species, such as oil palm (Elaeis guineensis Jacq., 2n = 32) contribute to allelic re-assortment in the genome. Such genetic variation is usually exploited in breeding to combine positive alleles for trait superiority. A good quality reference genome is essential for identifying the genetic factors underlying traits of interest through linkage or association studies. At the moment, an AVROS pisifera genome is publicly available for oil palm. Distribution and frequency of crossovers throughout chromosomes in different origins of oil palm are still unclear. Hence, an ultrahigh-density genomic linkage map of a commercial Deli dura x AVROS pisifera family was constructed using the OP200K SNP array, to evaluate the genetic alignment with the genome assembly. A total of 27,890 linked SNP markers generated a total map length of 1,151.7 cM and an average mapping interval of 0.04 cM. Nineteen linkage groups represented 16 pseudo-chromosomes of oil palm, with 61.7% of the mapped SNPs present in the published genome. Meanwhile, the physical map was also successfully extended from 658 Mb to 969 Mb by assigning unplaced scaffolds to the pseudo-chromosomes. A genic linkage map with major representation of sugar and lipid biosynthesis pathways was subsequently built for future studies on oil related quantitative trait loci (QTL). This study improves the current physical genome of the commercial oil palm, and provides important insights into its recombination landscape, eventually unlocking the full potential genome sequence-enabled biology for oil palm.
Oil palm is an important crop for global vegetable oil production, and is widely grown in the humid tropical regions of Southeast Asia. Projected future climate change may well threaten palm oil production. However, oil palm plantations currently produce large amounts of unutilised biological waste. Oil palm stems - which comprise two-thirds of the waste - are especially relevant because they can contain high levels of non-structural carbohydrates (NSC) that can serve as feedstock for biorefineries. The NSC in stem are also considered a potent buffer to source-sink imbalances. In the present study, we monitored stem NSC levels and female reproductive growth. We then applied convergent cross mapping (CCM) to assess the causal relationship between the time-series. Mutual causal relationships between female reproductive growth and the stem NSC were detected, with the exception of a relationship between female reproductive organ growth and starch levels. The NSC levels were also influenced by long-term cumulative temperature, with the relationship showing a seven-month time lag. The dynamic between NSC levels and long-term cumulative rainfall showed a shorter time lag. The lower temperatures and higher cumulative rainfall observed from October to December identify this as a period with maximum stem NSC stocks.
Evaluation of transcriptome data in combination with QTL information has been applied in many crops to study the expression of genes responsible for specific phenotypes. In oil palm, the mesocarp oil extracted from E. oleifera × E. guineensis interspecific hybrids is known to have lower palmitic acid (C16:0) content compared to pure African palms. The present study demonstrates the effectiveness of transcriptome data in revealing the expression profiles of genes in the fatty acid (FA) and triacylglycerol (TAG) biosynthesis processes in interspecific hybrids. The transcriptome assembly yielded 43,920 putative genes of which a large proportion were homologous to known genes in the public databases. Most of the genes encoding key enzymes involved in the FA and TAG synthesis pathways were identified. Of these, 27, including two candidate genes located within the QTL associated with C16:0 content, showed differential expression between developmental stages, populations and/or palms with contrasting C16:0 content. Further evaluation using quantitative real-time PCR revealed that differentially expressed patterns are generally consistent with those observed in the transcriptome data. Our results also suggest that different isoforms are likely to be responsible for some of the variation observed in FA composition of interspecific hybrids.
The fundamental trait in selective breeding of oil palm (Eleais guineensis Jacq.) is the shell thickness surrounding the kernel. The monogenic shell thickness is inversely correlated to mesocarp thickness, where the crude palm oil accumulates. Commercial thin-shelled tenera derived from thick-shelled dura × shell-less pisifera generally contain 30% higher oil per bunch. Two mutations, sh MPOB (M1) and sh AVROS (M2) in the SHELL gene - a type II MADS-box transcription factor mainly present in AVROS and Nigerian origins, were reported to be responsible for different fruit forms. In this study, we have tested 1,339 samples maintained in Sime Darby Plantation using both mutations. Five genotype-phenotype discrepancies and eight controls were then re-tested with all five reported mutations (sh AVROS , sh MPOB , sh MPOB2 , sh MPOB3 and sh MPOB4 ) within the same gene. The integration of genotypic data, pedigree records and shell formation model further explained the haploinsufficiency effect on the SHELL gene with different number of functional copies. Some rare mutations were also identified, suggesting a need to further confirm the existence of cis-compound mutations in the gene. With this, the prediction accuracy of fruit forms can be further improved, especially in introgressive hybrids of oil palm. Understanding causative variant segregation is extremely important, even for monogenic traits such as shell thickness in oil palm.
The recent expansion of oil palm (OP, Elaeis guineensis) plantations into tropical forest peatlands has resulted in ecosystem carbon emissions. However, estimates of net carbon flux from biomass changes require accurate estimates of the above ground biomass (AGB) accumulation rate of OP on peat. We quantify the AGB stocks of an OP plantation on drained peat in Malaysia from 3 to 12 years after planting using destructive harvests supported by non-destructive surveys of a further 902 palms. Peat specific allometric equations for palm (R2 = 0.92) and frond biomass are developed and contrasted to existing allometries for OP on mineral soils. Allometries are used to upscale AGB estimates to the plantation block-level. Aboveground biomass stocks on peat accumulated at ~6.39 ± 1.12 Mg ha-1 per year in the first 12 years after planting, increasing to ~7.99 ± 0.95 Mg ha-1 yr-1 when a 'perfect' plantation was modelled. High inter-palm and inter-block AGB variability was observed in mature classes as a result of variations in palm leaning and mortality. Validation of the allometries defined and expansion of non-destructive inventories across alternative plantations and age classes on peat would further strengthen our understanding of peat OP AGB accumulation rates.
Excessive high fat dietary intake promotes risk of developing non-alcoholic fatty liver disease (NAFLD) and predisposed with oxidative stress. Palm based tocotrienol-rich fraction (TRF) has been reported able to ameliorate oxidative stress but exhibited poor bioavailability. Thus, we investigated whether an enhanced formulation of TRF in combination with palm kernel oil (medium-chain triglycerides) (ETRF) could ameliorate the effect of high-fat diet (HFD) on leptin-deficient male mice. All the animals were divided into HFD only (HFD group), HFD supplemented with ETRF (ETRF group) and HFD supplemented with TRF (TRF group) and HFD supplemented with PKO (PKO group). After 6 weeks, sera were collected for untargeted metabolite profiling using UHPLC-Orbitrap MS. Univariate analysis unveiled alternation in metabolites for bile acids, amino acids, fatty acids, sphingolipids, and alkaloids. Bile acids, lysine, arachidonic acid, and sphingolipids were downregulated while xanthine and hypoxanthine were upregulated in TRF and ETRF group. The regulation of these metabolites suggests that ETRF may promote better fatty acid oxidation, reduce oxidative stress and pro-inflammatory metabolites and acts as anti-inflammatory in fatty liver compared to TRF. Metabolites regulated by ETRF also provide insight of its role in fatty liver. However, further investigation is warranted to identify the mechanisms involved.
Nanoemulsion is a delivery system used to enhance bioavailability of plant-based compounds across the stratum corneum. Elaeis guineensis leaves are rich source of polyphenolic antioxidants, viz. gallic acid and catechin. The optimal E. guineensis leaves extract water-in-oil nanoemulsion was stable against coalescence, but it was under significant influence of Ostwald ripening over 90 days at 25 °C. The in-vitro permeability revealed a controlled and sustained release of the total phenolic compounds (TPC) of EgLE with a cumulative amount of 1935.0 ± 45.7 µgcm-2 after 8 h. The steady-state flux and permeation coefficient values were 241.9 ± 5.7 µgcm-2 h-1 and 1.15 ± 0.03 cm.h-1, respectively. The kinetic release mechanism for TPC of EgLE was best described by the Korsmeyer-Peppas model due to the highest linearity of R2 = 0.9961, indicating super case II transport mechanism. The in-silico molecular modelling predicted that the aquaporin-3 protein in the stratum corneum bonded preferably to catechin over gallic acid through hydrogen bonds due to the lowest binding energies of - 57.514 kcal/mol and - 8.553 kcal/mol, respectively. Thus, the in-silico study further verified that catechin could improve skin hydration. Therefore, the optimal nanoemulsion could be used topically as moisturizer to enhance skin hydration based on the in-silico prediction.
Neurodegenerative diseases, including Alzheimer's disease and Parkinson's disease, are becoming more prevalent and an increasing burden on society. Neurodegenerative diseases often arise in the milieu of neuro-inflammation of the brain. Reactive astrocytes are key regulators in the development of neuro-inflammation. This study describes the effects of Palm Fruit Bioactives (PFB) on the behavior of human astrocytes which have been activated by IL-1β. When activated, the astrocytes proliferate, release numerous cytokines/chemokines including TNFα, RANTES (CCL5), IP-10 (CXCL10), generate reactive oxygen species (ROS), and express specific cell surface biomarkers such as the Intercellular Adhesion Molecule (ICAM), Vascular Cellular Adhesion Molecule (VCAM) and the Neuronal Cellular Adhesion Molecule (NCAM). Interleukin 1-beta (IL-1β) causes activation of human astrocytes with marked upregulation of pro-inflammatory genes. We show significant inhibition of these pro-inflammatory processes when IL-1β-activated astrocytes are exposed to PFB. PFB causes a dose-dependent and time-dependent reduction in specific cytokines: TNFα, RANTES, and IP-10. We also show that PFB significantly reduces ROS production by IL-1β-activated astrocytes. Furthermore, PFB also reduces the expression of ICAM and VCAM, both in activated and naïve human astrocytes in vitro. Since reactive astrocytes play an essential role in the neuroinflammatory state preceding neurodegenerative diseases, this study suggests that PFB may have a potential role in their prevention and/or treatment.
The fructose-1,6-bisphosphate aldolase catalyzed glycolysis branch that forms dihydroxyacetone phosphate and glyceraldehyde-3-phosphate was identified as a key driver of increased oil synthesis in oil palm and was validated in Saccharomyces cerevisiae. Reduction in triose phosphate isomerase (TPI) activity in a yeast knockdown mutant resulted in 19% increase in lipid content, while yeast strains overexpressing oil palm fructose-1,6-bisphosphate aldolase (EgFBA) and glycerol-3-phosphate dehydrogenase (EgG3PDH) showed increased lipid content by 16% and 21%, respectively. Genetic association analysis on oil palm SNPs of EgTPI SD_SNP_000035801 and EgGAPDH SD_SNP_000041011 showed that palms harboring homozygous GG in EgTPI and heterozygous AG in EgGAPDH exhibited higher mesocarp oil content based on dry weight. In addition, AG genotype of the SNP of EgG3PDH SD_SNP_000008411 was associated with higher mean mesocarp oil content, whereas GG genotype of the EgFBA SNP SD_SNP_000007765 was favourable. Additive effects were observed with a combination of favourable alleles in TPI and FBA in Nigerian x AVROS population (family F7) with highest allele frequency GG.GG being associated with a mean increase of 3.77% (p value = 2.3E-16) oil content over the Family 1. An analogous effect was observed in yeast, where overexpressed EgFBA in TPI - resulted in a 30% oil increment. These results provide insights into flux balances in glycolysis leading to higher yield in mesocarp oil-producing fruit.
The production of oil palm (Elaeis guineensis) in Southeast Asia is vital to the economies of Indonesia and Malaysia. Both fertilisers and pesticides used in palm production can contain elevated concentrations of Trace Elements (TEs) which may accumulate in soils and leaf tissues of plants. We hypothesised that leaves from oil palms may be deficient in essential elements, while containing elevated concentrations of non-essential TEs commonly found in agrichemicals. Samples of plant materials (leaves and fruitlets) were collected from active and former plantations in Sumatra, Indonesia, and analysed for essential and non-essential elements. Indonesian palm oil samples were sourced in New Zealand and their elemental concentrations determined. Leaf materials from both active and abandoned production sites were deficient in N, K, S and Mo, while leaf materials from abandoned sites were deficient in P. These deficiencies may have been a contributing factor to the abandonment of production at these sites. Concentrations of non-essential elements were below or comparable to average plant concentrations and no evidence of contamination was found in plant tissues. Palm oil contained low concentrations of TEs, which did not pose any toxicity risks. However, Na and Al were present in concentrations of 1198 and 159 mg kg-1 respectively, which were higher than have been previously reported. Tropical oil palm production could benefit from the determination of bioaccumulation factors for fertiliser contaminants in E. guineensis, to limit the transfer of contaminants to plants and products if increased fertiliser applications were used to correct nutrient deficiencies.
New plantations can either cause deforestation by replacing natural forests or avoid this by using previously cleared areas. The extent of these two situations is contested in tropical biodiversity hotspots where objective data are limited. Here, we explore delays between deforestation and the establishment of industrial tree plantations on Borneo using satellite imagery. Between 1973 and 2015 an estimated 18.7 Mha of Borneo's old-growth forest were cleared (14.4 Mha and 4.2 Mha in Indonesian and Malaysian Borneo). Industrial plantations expanded by 9.1 Mha (7.8 Mha oil-palm; 1.3 Mha pulpwood). Approximately 7.0 Mha of the total plantation area in 2015 (9.2 Mha) were old-growth forest in 1973, of which 4.5-4.8 Mha (24-26% of Borneo-wide deforestation) were planted within five years of forest clearance (3.7-3.9 Mha oil-palm; 0.8-0.9 Mha pulpwood). This rapid within-five-year conversion has been greater in Malaysia than in Indonesia (57-60% versus 15-16%). In Indonesia, a higher proportion of oil-palm plantations was developed on already cleared degraded lands (a legacy of recurrent forest fires). However, rapid conversion of Indonesian forests to industrial plantations has increased steeply since 2005. We conclude that plantation industries have been the principle driver of deforestation in Malaysian Borneo over the last four decades. In contrast, their role in deforestation in Indonesian Borneo was less marked, but has been growing recently. We note caveats in interpreting these results and highlight the need for greater accountability in plantation development.
Human-induced habitat alterations globally threaten animal populations, often evoking complex behavioural responses in wildlife. This may be particularly dramatic when negatively affecting social behaviour, which fundamentally determines individual fitness and offspring survival in group-living animals. Here, we provide first evidence for significant behavioural modifications in sociality of southern pig-tailed macaques visiting Malaysian oil palm plantations in search of food despite elevated predation risk. Specifically, we found critical reductions of key positive social interactions but higher rates of aggression in the plantation interior compared to the plantation edge (i.e. plantation areas bordering the forest) and the forest. At the plantation edge, affiliation even increased compared to the forest, while central positions in the macaques' social network structure shifted from high-ranking adult females and immatures to low-ranking individuals. Further, plantations also affected mother-infant relationships, with macaque mothers being more protective in the open plantation environment. We suggest that although primates can temporarily persist in human-altered habitats, their ability to permanently adapt requires the presence of close-by forest and comes with a trade-off in sociality, potentially hampering individual fitness and infant survival. Studies like ours remain critical for understanding species' adaptability to anthropogenic landscapes, which may ultimately contribute to facilitating their coexistence with humans and preserving biodiversity.
Pseudomonas aeruginosa developed its biocontrol agent property through the production of antifungal derivatives, with the phenazine among them. In this study, the applications of crude phenazine synthesized by Pseudomonas aeruginosa UPMP3 and hexaconazole were comparatively evaluated for their effectiveness to suppress basal stem rot infection in artificially G. boninense-challenged oil palm seedlings. A glasshouse experiment under the randomized completely block design was set with the following treatments: non-inoculated seedlings, G. boninense inoculated seedlings, G. boninense inoculated seedlings with 1 mg/ml phenazine application, G. boninense inoculated seedlings with 2 mg/ml phenazine application and G. boninense inoculated seedlings with 0.048 mg/ml hexaconazole application. Seedlings were screened for disease parameters and plant vigour traits (plant height, plant fresh weight, root fresh, and dry weight, stem diameter, and total chlorophyll) at 1-to-4 month post-inoculation (mpi). The application of 2 mg/ml phenazine significantly reduced disease severity (DS) at 44% in comparison to fungicide application (DS = 67%). Plant vigour improved from 1 to 4 mpi and the rate of disease reduction in seedlings with phenazine application (2 mg/ml) was twofold greater than hexaconazole. At 4, 6 and 8 wpi, an up-regulation of chitinase and β-1,3 glucanase genes in seedlings treated with phenazine suggests the involvement of induced resistance in G. boninense-oil palm pathosystem.
In recent decades, global oil palm production has shown an abrupt increase, with almost 90% produced in Southeast Asia alone. To understand trends in oil palm plantation expansion and for landscape-level planning, accurate maps are needed. Although different oil palm maps have been produced using remote sensing in the past, here we use Sentinel 1 imagery to generate an oil palm plantation map for Indonesia, Malaysia and Thailand for the year 2017. In addition to location, the age of the oil palm plantation is critical for calculating yields. Here we have used a Landsat time series approach to determine the year in which the oil palm plantations are first detected, at which point they are 2 to 3 years of age. From this, the approximate age of the oil palm plantation in 2017 can be derived.