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Introduction Public health nutrition is the promotion of nutrition-related health of populations. Food composition databases have an essential role in the assessment, analyses and action phases of public health nutrition. The food composition database provides comprehensive information on the content of energy and various nutrients and other bioactive constituents in food products, including those obtained from agriculture, fisheries, and livestock. The country-specific food composition databases are developed with food composition data of foods consumed by the population and represent essential tools for assessing national nutritional status, thus being critical to advance nutritional research and policy. The management of food composition programmes includes the maintenance and continuous updating of food composition information foods and is a useful tool for estimating nutrient intake at national, regional and/or certain population levels. Accurate, country-specific food composition databases that reflect the national food supply are essential for estimating nutrient intake and conducting reliable dietary assessments, thereby serving as a critical tool for evaluating and monitoring diets.Accurate Country-specific databases, reflecting the national food supply, for improving the quality of food supply, contribute to determine nutrient intake and hence nutritional intake assessment, then representing a dietary assessment tool for measuring and assessing diets. Indeed, the food composition databases are utilised to accomplish the supply and demand of agricultural products, for assessing the quality of export products in international trade, in public health campaigns, in nutrition programmes and strategies, and to boost the innovations in the food industry. Food composition databases provide reliable data on nutrient composition and bioactive profiles, supporting diverse applications such as clinical nutrition, epidemiological research, health surveys, diet therapy and planning, dietary guidelines, nutrition policies, food development, nutrition recommendations, nutrition education, and food labeling regulations. Food composition databases are utilized by providing reliable data on the nutritional composition and bioactive profile, in different areas, i.e. clinical nutrition, epidemiological research, health surveys, diet treatments, diet planning, dietary guidelines, nutrition policies, food development, nutrition recommendations, nutrition education, food labeling regulations. Therefore, the food composition databases are fundamental for a broad type of user, i.e. researchers, dietitians, clinical dietitians and other health professionals, government policy makers, consumers, marketing professionals, and policymakers. These databases are therefore used also in a wide variety of organisations – from academia to various industries – including food businesses and IT providers, and governments. The integration and harmonization of food composition data and modern omic technologies is an ongoing challenge. Beyond the macro-and micronutrient information provided by national databases, resources for food composition data are increasingly focused on high-resolution analyses aimed at capturing the full spectrum of small, potentially bioactive molecules present in foods. Resources for food composition data, in addition to the macro-and micronutrients given by national databases, in order to meet the great chemical diversity of food components, are now directed towards high-resolution food composition data with the aim of capturing all small molecules with potential bioactivity. The availability of standardized, harmonized and integrated large-scale food composition data and mass spectra resources will be fundamental for future directions in the perspective of data integration and interoperability. Quality control of analytical procedures is a key element for the accuracy, precision, and reliability of data for inclusion in the Food Composition Databases. Safe food represents a key aspect of food security, and consequently food traceability along the supply chain represents a fundamental component. Data traceability starts from data collection to analysis results, and it has the role to ensure the data reproducibility along the food chain, from raw material production, transportation, toand logistics. The usefulness of analytical data and the development of a food safety assessment system produce useful information and represent key elements to obtain an effective traceability system and guarantee efficiency in the management of the entire supply chain. Emerging technologies such as cloud computing, digital platforms, mobile tools, and artificial intelligence offer new opportunities to build smart food traceability systems that integrate across the agri-food supply chain. These systems can monitor food supply and population-level dietary data, thereby improving data quality and safety while supporting the development of integrated food data infrastructures.The emerging advanced technologies, i.e. cloud computing, digital technologies, mobile ones, and artificial intelligence, represent new opportunities to develop a smart food traceability system integrated into the various food supply chain and applications in agri-foods, monitoring the food supply and population level dietary data and therefore improving the safety and quality of data and promote the construction of integrated food data system. Particularly, the use of artificial intelligence is currently emerging as a key part of the management of food composition databases. There is a need for improving the international harmonisation of food composition databases to meet expectations for international research and comparisons. The classification and harmonization of foods is essential in the development of connectable database systems. The growing availability of standardized data facilitates integration across sources, as future analyses increasingly rely on data harmonization and interoperability. A key current challenge is linking environmental and food composition databases, connecting nutritional and environmental entries in order to identify more sustainable food options. The increasing availability of more standardized facilitates the interlinkage of data: the incorporation of more interlinked data from different sources into future analyses is based on data standardization and harmonization. As instance, nowadays a new challenge is represented by the interlinking and connection of environmental and food composition databases, connecting the different type of entries (nutritional and environmental ones), that allow identification of different sustainable food options. Furthermore, there is a need for additional data also regarding food waste and by-products, and consequently of databases including information on chemical composition, origin, and quantities of by-products from the agri-food sector. The availability of branded food databases also brings new opportunities and challenges. By providing detailed and up-to-date nutritional information specific to branded products, these databases improve the reliability of data for applications such as nutrient intake assessment and food reformulation monitoring. In this context, the present Special Section, Databases and Nutrition – Volume III, brings together nine contributions that address these themes from different perspectives.The availability of branded food databases also provides new opportunities and challenges. The use of detailed and updated nutritional information specific to branded foods makes more reliable data for several applications, including measurement of nutrient intakes and monitoring food reformulation. Nine works are published in the Research Topic "Databases and Nutrition – Volume III". Concerning the development of automatic procedure in database management, the study of Westenbrink et al. (https://doi.org/10.3389/fnut.2024.1366083) addressed to the development of an automated approach to identify fortified foods in the Dutch branded food database LEDA. An automated procedure, based on a stepwise approach conforming with European food labeling legislation, using a list of rules and search terms, was developed and resulted in identifying 1,817 foods, fortified with one or more of the selected nutrients in the LEDA dataset (0.94%) (Westenbrink et al. https://doi.org/10.3389/fnut.2024.1366083). The study of Bardon et al. (https://doi.org/10.3389/fnut.2025.1519401) describeds the development and evaluation of the FNS-Cloud data quality assessment tool for dietary intake datasets. The study of Valenčič et al. (https://doi.org/10.3389/fnut.2024.1503389) presented NutriBase, a novel data-and knowledge base management system designed to advance the science of food composition through improvements in harmonisation, data quality, reduction of missing data, and interoperability. Regarding uses and applications of databases, the study of Fazzino et al. (https://doi.org/10.3389/fnut.2024.1364695) quantified the prevalence of hyper-palatable food (HPF) in the Italian food system and compared the hyper-palatability of similar foods across Italy and the United States, which has wide HPF saturation: HPF comprise less than one third of the Italian food system, indicating the Italian food system may confer protection from HPF exposure. Findings also revealed key differences in HPF products between Italy vs the US, with HPF from Italy tending to have lower palatability-inducing nutrients and higher satiety promoting nutrients, relative to comparable US products (Fazzino et al. https://doi.org/10.3389/fnut.2024.1364695). Moreover, authors highlighted that food companies in Italy and the US should consider reducing the sodium, refined carbohydrates, and fat in salty snacks, frozen pizzas, industrial breads, and protein/cereal bars, to reduce the hyper-palatability of these commonly consumed foods in Italy and the US. Wang X. et al. (https://doi.org/10.3389/fnut.2025.1527771) investigated the association between plain water intake (PWI) and the risk of osteoporosis among middle-aged and elderly people in the United States by a cross-sectional study: results suggested that among middle-aged and elderly people, a greater PWI was connected with a moderately lower osteoporosis risk. Study of Wang Y. et al. is focused into the application of food composition data; their work was focused into exploration of the links between consumption of Sugar-sweetened beverages (SSB) and specific health-related outcomes and lifestyle parameters (https://doi.org/10.3389/fnut.2024.1418393). Kraemer et al. (https://doi.org/10.3389/fnut.2025.1568089) have discussed methodological evolution and challenges of in-store census methods for assessing the composition of branded foods, and characterised a Brazilian food label database. Terro et al. (https://doi.org/10.3389/fnut.2025.1516521) present the IsoFoodTrack database - a comprehensive, scalable, and flexible platform designed to manage isotopic and elemental composition data for a wide range of food commodities. Brinkley et al. (https://doi.org/10.3389/fnut.2025.1552367) conducted an integrative review of 35 data attributes across 101 FCDBs from 110 countries, highlighting emerging opportunities and recommendations. Contributions in Volume III of Databases and Nutrition showcase cutting‑edge efforts to develop and update comprehensive and dedicated food databases, emphasizing rigorous standardisation, harmonisation, and interoperability across data sources—from analytical measurements to literature‑derived values, labeling, and calculated data. The adoption of robust quality evaluation indices, consistent food description systems, and semi‑automated matching and alignment procedures reflects the growing maturity and sophistication of nutritional data infrastructures. These resources serve not only to support food composition research but also to underpin interdisciplinary applications spanning health, environmental science, policy, and beyond.