Toward harmonizing protein data in food composition databases: evaluating perspectives, methods and implications

Protein content in foods has historically been estimated by multiplying measured nitrogen content with a universal nitrogen-to-protein conversion factor (NCF) of 6.25. Despite scientific consensus that this approach leads to systematic overestimations due to variations in amino acid composition and non-protein nitrogen (NPN) content, no universally accepted revision has been implemented. This review critically examines diverse perspectives on protein quantification and their implications for Food Composition Databases (FCDBs). A structured definition of protein for FCDBs is proposed, including amino acid residues, free amino acids and small peptides, while explicitly excluding NPN and prosthetic groups. Furthermore, analytical methods and NCF calculations are evaluated in order to provide more accurate assessments of protein content across a range of food matrices. The review highlights the importance of selecting food-specific NCFs to reduce overestimations, ensuring both scientific accuracy and practical feasibility. By addressing methodological shortcomings and proposing a refined protein quantification framework, this work aims to facilitate the transition toward more precise and harmonized protein values in FCDBs, benefiting nutritional research, dietary guidelines, and food labeling regulations.