Metabolome Analysis of Oil Palm Clone P325 of Different Planting Trials

Tahir, Noor Idayu

doi:10.21894/jopr.2016.2804.04

Cited by 6 publications

(4 citation statements)

References 10 publications

(11 reference statements)

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“…These revealed metabolites or signatory phytochemical markers (m/z ions) which are influential on the clusters as seen on the scores plot are unique for the two different planting sites. Identification of the metabolites using MS/MS (fragmentation of selected ions using collisioninduced dissociation (CID) in quadrupole-time-of-flight (Q-TOF) mass spectrometer and liquid chromatography t R comparison with commercial standards deduced the loadings point 1 as asparagine while metabolite of loadings point 2 was dopamine (Tahir et al, 2016). The identification of these phytochemicals fitted into Level 1 of identity confidence of the Metabolomics Standards Initiative (MSI) (Viant et al, 2017).…”

Section: Resultsmentioning

confidence: 99%

“…As part of our effort to streamline the ecometabolomics workflow for sustainable oil palm, the utilization of a rapid, straightforward and cost-effective method of field data interpretation is ideal. In this investigation, the raw LC-MS data set from an earlier published work (Tahir et al, 2016) was used for comparison of COVAIN toolbox, MetaboAnalyst, SIMCA-Pþ, and RIKEN Excel Macro statistical analysis tools. The real data set represents the individual biological palms of similar genetic background to put the genetic factor as a constant and to monitor the plants components such as the metabolome that responds to environmental stimuli in a metabolic homeostasis (Nagler et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

“…The general plant metabolomics workflow of oil palm tissue sampling up to data analysis and storage steps is schematised in Figure 1. LC-MS data was obtained from the metabolomics profiling of spear leaves from clonal oil palm planted on two different planting sites of Keratong and Teluk Intan of different soils as previously described by Tahir et al (2016).…”

Section: Sample Preparation Liquid Chromatography-mass Spectrometry (Lc-ms) Analysis Data Collection and Pre-processingmentioning

confidence: 99%

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Comparative analysis of statistical tools for oil palm phytochemical research

Ishak

Tahir

Sa'id

et al. 2021

Heliyon

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Recent advances in phytochemical analysis have allowed the accumulation of data for crop researchers due to its capacity to footprint and distinguish metabolites that are present within an organisms, tissues or cells. Apart from genotypic traits, slight changes either by biotic or abiotic stimuli will have significant impact on the metabolite abundances and will eventually be observed through physicochemical characteristics. Apposite data mining to interpret the mounds of phytochemical information from such a dynamic system is thus incumbent. In this investigation, several statistical software platforms ranging from exploratory and confirmatory technique of multivariate data analysis from four different statistical tools of COVAIN, SIMCA-Pþ, MetaboAnalyst and RIKEN Excel Macro were appraised using an oil palm phytochemical data set. As different software tool encompasses its own advantages and limitations, the insights gained from this assessment were documented to enlighten several aspects of functions and suitability for the adaptation of the tools into the oil palm phytochemistry pipeline. This comparative analysis will certainly provide scientists with salient notes on data assessment and data mining that will later allow the depiction of the overall oil palm status in-situ and ex-situ.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Sample Preparation Liquid Chromatography-mass Spectrometry (Lc-ms) Analysis Data Collection and Pre-processingmentioning

confidence: 99%

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Comparative analysis of statistical tools for oil palm phytochemical research

Ishak

Tahir

Sa'id

et al. 2021

Heliyon

Self Cite

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“…The concentration of sugars, especially fructose, increased from leaves 0-25 [152]. In developing clonal oil palm leaves, two amino acids, asparagine and dopamine, were found to vary based on whether the plants were planted on peat or mineral soils [153]. Phenolic compounds in olive leaves were used to differentiate varieties from a similar geographical location, as well as discriminate samples of a similar variety from different cultivar zones [154,155].…”

Section: Leaf Metabolomics Studiesmentioning

confidence: 99%

Review: Omics and Strategic Yield Improvement in Oil Crops

Teh

Neoh

Ithnin

et al. 2017

J Americ Oil Chem Soc

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Crop yield improvement is essential for feeding the growing world population without concomitant increases in land allocated to agriculture. Oil crops are critical components of food supply as well as non-food applications. Oil palm is of particular value due to its significantly higher yield per unit area of land as compared to other oil crops. In the context of sustainable production of edible oils, this review will discuss the role of biochemical-omics techniques, including metabolomics, transcriptomics and proteomics research for yield improvement through plant breeding; in particular, the unique challenges of the mesocarp-oil bearing perennial crop, oil palm, are specifically discussed along with perspectives on what is needed for future crop improvement. Future oil crop improvement will need to go beyond classical trait selection, and omics research needs to go beyond looking at oil biosynthesis and fruit development. We need to explore carbon supply and flux, plant stress response, nutrient uptake and water use through a combination of genetics, biochemistry, epigenetics and gene interaction coupled to more detailed and continuous phenotypic data analysis.

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