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Foodomics is an emerging multidisciplinary field that applies omics technologies such as genomics, proteomics, metabolomics, transcriptomics, and nutrigenomics to improve the understanding of food composition, quality, safety, and traceability. This review highlights recent advances in analytical methods for assessing nutrient profiles, identifying contaminants, and verifying food authenticity. Case studies demonstrate the practical impact of Foodomics, including metabolomics for authenticating horse milk adulteration, proteomic profiling for tracing seafood species and dairy product origins, and transcriptomic approaches for monitoring flavonoid biosynthesis in seeds and nitrogen stress responses in apple plants. In cereal and fruit-based products, Foodomics has also been employed to assess processing impacts through volatile fingerprinting and enzyme activity profiling. Despite these successes, widespread adoption is limited by high costs, data complexity, and the need for advanced bioinformatics and technical expertise. The variability of food matrices and dynamic processing environments presents further analytical challenges. A more balanced view of the field is necessary, including critical evaluation of methodological limitations and reproducibility concerns. Future directions involve integrating omics data with technologies such as machine learning and blockchain to enhance predictive modeling and supply chain transparency. Advancements in portable and affordable platforms along with standardization of protocols will be essential for broader implementation, particularly in developing countries. Collaboration among researchers, industry, and regulators will be vital to establish clear regulatory frameworks and realize the full potential of Foodomics in improving food safety and public health outcomes.
Yohannis et al. (Sat,) studied this question.