The article reviews the field of plant metabolomics, which involves the large-scale phytochemical analysis of plants in the context of functional genomics and systems biology. It provides a historical overview of the development of metabolite profiling and discusses the technologies used, including optical spectroscopy, nuclear magnetic resonance (NMR), and mass spectrometry. The critical role of bioinformatics and data visualization methods such as principal component analysis (PCA), hierarchical cluster analysis (HCA), and self-organizing maps (SOMs) is highlighted. The article also assesses the future role of metabolomics in plant science, noting its limitations and the need for comprehensive and integrated approaches to understand the complex metabolic networks of plants. The importance of databases for storing and analyzing metabolomic data is emphasized, along with the challenges of integrating metabolomic data with other biological data to infer gene function and understand metabolic pathways.The article reviews the field of plant metabolomics, which involves the large-scale phytochemical analysis of plants in the context of functional genomics and systems biology. It provides a historical overview of the development of metabolite profiling and discusses the technologies used, including optical spectroscopy, nuclear magnetic resonance (NMR), and mass spectrometry. The critical role of bioinformatics and data visualization methods such as principal component analysis (PCA), hierarchical cluster analysis (HCA), and self-organizing maps (SOMs) is highlighted. The article also assesses the future role of metabolomics in plant science, noting its limitations and the need for comprehensive and integrated approaches to understand the complex metabolic networks of plants. The importance of databases for storing and analyzing metabolomic data is emphasized, along with the challenges of integrating metabolomic data with other biological data to infer gene function and understand metabolic pathways.