Digital Mapping of Central Asian Foods: Towards a Standardized Visual Atlas for Nutritional Research

Background/Objectives: Portion size estimation is important for dietary assessment and nutrition research, but has remained understudied in Central Asia, a region characterized by red meat-rich diets and high rates of diet-related noncommunicable diseases (NCDs). Therefore, this study aimed to develop a digital visual food atlas for Central Asian cuisine that would provide high-quality images of commonly consumed foods and beverages, while special focus was given to meat dishes that were not present in previous atlases. Methods: Foods were selected based on the Central Asian Food Dataset (CAFD) and Central Asian Food Scenes Dataset (CAFSD) and photographed in three portion sizes: small, average, and large. There were nine broad categories: main dishes, soups, meat dishes, salads, snacks, side dishes, bakery and bread, desserts, and beverages. Similar settings were preserved for each photograph: the 60° angle, sufficient lighting, and food setup (including reference objects like utensils, a ruler, and a neatly folded napkin). Results: The final digital visual food atlas comprised 115 items (95 food series, 20 beverage guides), with 12 meat-based dishes, reflecting the central role of meat in regional diets. Each entry included portion weights and names in both English and local languages, improving cultural and linguistic relevance. The digital format with clear labeling ensured accessibility on web and mobile platforms. Conclusions: This was the first digital visual food atlas developed for Central Asia, providing standardized portion-size references. The atlas offered a practical tool for dietary assessment, with applications in nutrition research, mobile health technologies, artificial intelligence (AI)-driven portion estimation, and policy development.