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Abstract
Metabolomics, a rapidly evolving field, has revolutionized horticultural crop research by enabling comprehensive analysis of metabolites that influence plant yield, growth, quality and nutritional value. The integration of web-based resources, including databases, computational tools and analytical platforms has significantly enhanced metabolomics studies by facilitating data processing, metabolite identification and pathway analysis. Moreover, the application of machine learning algorithms to these web resources has further optimized data interpretation, enabling more accurate prediction of metabolic profiles. Publicly available reference libraries and bioinformatic tools support precision of breeding, postharvest quality assessment and ultimately improving crop yield and sustainability. In this mini-review, we explore the current status of the diverse range of plant metabolomics databases in horticultural crops, highlighting the synergy between machine learning and traditional bioinformatics methods, their applications, challenges and future prospects in advancing plant science and agricultural innovation.
Highlights
Metabolomics emerged at the end of the last century, with the term coined by analogy with genomics and transcriptomics to refer to the metabolite complement of the cell in a review of Stephen Oliver (Oliver et al 1998)
Given the sheer number of publications that have been published over the last quarter of a century, we feel that the time is ripe for a focused review only on metabolomics of horticultural crops
Over the last two decades, metabolomics has been utilized to address a wide range of important questions in plant biology, including pathway structure (Shen et al 2023), the influence of metabolism on growth (Meyer et al 2007; Sulpice et al 2009), plant ecology (Davey et al 2008), various aspects of plant genetics including evolution and the domestication syndrome (Alseekh et al 2021; Beleggia et al 2016; Kliebenstein 2009) and detailed characterizations of the metabolic response to biotic and abiotic stressors
Summary
Metabolomics emerged at the end of the last century, with the term coined by analogy with genomics and transcriptomics to refer to the metabolite complement of the cell in a review of Stephen Oliver (Oliver et al 1998). Keywords Metabolite databases, Bioinformatic tools, Plant metabolomics and horticultural crops These databases enable researchers to identify unknown metabolites, compare metabolic profiles across species and integrate data with omics approaches for a comprehensive understanding of plant metabolism.
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