• 1 Advanced Biotechnology and Breeding Centre (ABBC), Malaysian Palm Oil Board (MPOB), No. 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor, Malaysia
  • 2 Faculty of Chemical Engineering, Universiti Teknologi MARA (UiTM) 40450 Shah Alam, Selangor, Malaysia
  • 3 Institute for Mathematical Research, Universiti Putra Malaysia, 43400 UPM Serdang Selangor, Malaysia
Heliyon, 2021 Feb;7(2):e06048.
PMID: 33553773 DOI: 10.1016/j.heliyon.2021.e06048


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-P+, 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.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.