Cross-validation and receiver operating characteristic analyses for oil palm leaf metabolome dataset

Nur Ain Ishak, . and Noor Idayu Tahir, . and Nurul Liyana Rozali, . and Zain Nurazah, . and Nur Raihan Abd Rahim, . and Abrizah Othman, . and Umi Salamah Ramli, . (2023) Cross-validation and receiver operating characteristic analyses for oil palm leaf metabolome dataset. Journal of Oil Palm Research (Malaysia), 35. pp. 376-384. ISSN 2811-4701

The advancement of systems biology research has emphasised the capabilities of statistical analysis tools in distinguishing many factors associated with oil palm including genetic vs. environment (GxE) components from omics data. The availability of an efficient and robust ecometabolomics workflow has a high potential in augmenting oil palm precision agriculture. In this study, we employed cross-validation (CV) and receiver operating characteristic (ROC) methodologies to evaluate the performance of an oil palm metabolome dataset linked to GxE factors for its predictive ability and integrity. The specificity and sensitivity of identified metabolite candidates contributing to the demarcation of the two oil palm groups in the dataset were found to be distinctive and were of discrimination quality. The dataset showed no overfitting and exhibited excellent predictive power. This work provides fundamental information and a guideline for universal metabolome data exploration toward oil palm phenotyping and precision agriculture.

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Abstract

The advancement of systems biology research has emphasised the capabilities of statistical analysis tools in distinguishing many factors associated with oil palm including genetic vs. environment (GxE) components from omics data. The availability of an efficient and robust ecometabolomics workflow has a high potential in augmenting oil palm precision agriculture. In this study, we employed cross-validation (CV) and receiver operating characteristic (ROC) methodologies to evaluate the performance of an oil palm metabolome dataset linked to GxE factors for its predictive ability and integrity. The specificity and sensitivity of identified metabolite candidates contributing to the demarcation of the two oil palm groups in the dataset were found to be distinctive and were of discrimination quality. The dataset showed no overfitting and exhibited excellent predictive power. This work provides fundamental information and a guideline for universal metabolome data exploration toward oil palm phenotyping and precision agriculture.

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Item Type:	Article
AGROVOC Term:	oil palms
AGROVOC Term:	leaves
AGROVOC Term:	metabolomics
AGROVOC Term:	tissue analysis
AGROVOC Term:	data analysis
AGROVOC Term:	statistical methods
AGROVOC Term:	scientists
AGROVOC Term:	metabolism
Geographical Term:	Malaysia
Depositing User:	Nor Hasnita Abdul Samat
Date Deposited:	04 Aug 2025 14:07
Last Modified:	04 Aug 2025 14:07
URI:	http://webagris.upm.edu.my/id/eprint/1015

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