A major goal of tomato metabolomics is to elucidate genes and biosynthetic pathways that can be exploited for crop improvement in productivity and quality. Tomato productivity involves net accumulation of photosynthetically synthesized compounds such as sugars and amino acids, and polymeric compounds derived from them, e.g., cellulose and starch. Fruit quality is determined by a complex blend of traits including taste, fragrance, and color. These traits are mostly attributed to metabolite composition. For example, accumulated sugars, amino acids, lipids, and various secondary metabolites affect fruit taste. Lipid, sugar, alcohol, aldehyde, and isoprenoid contents affect fruit flavor. Levels of carotenoids and flavonoids influence fruit color. Thus, "productivity" and "quality" can be defined in terms of metabolic profiles.

Recent development of chromatography-coupled MS technologies has facilitated the simultaneous detection of thousands of metabolite-derived mass peaks. Comprehensive acquisition of tomato metabolite data followed by high-throughput analysis has allowed an integrated approach (genomics, transcriptomics, metabolomics) to tomato research. This approach has the potential to identify priority target genes conferring tomato phenotypes (Carrari etal. 2006; Schauer etal. 2006). The application of MS technology has also revealed that tomato contains a large number of metabolites that have not yet been identified. Characterization of these unknown metabolites has become one of the major challenges in understanding the complexityoftomato metabolism.

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