Ovotransferrin (OVT), a major iron binding glycoprotein in egg white, is increasingly studied as a multifunctional ingredient for food preservation, mineral delivery, and colloidal design. This review critically evaluates how native structure, iron saturation, thermal history, glycation, phosphorylation, fibrillation, and interactions with proteins, polysaccharides, polyphenols, and lipid interfaces influence or determine OVT behavior during processing and gastrointestinal digestion. Rather than defining digestive stability simply as resistance to proteolysis, the review compares how processing routes reshape protease accessibility, peptide release, residual allergenic risk, and the persistence of antimicrobial or antioxidant functions. Particular emphasis is placed on cross-matrix interactions because OVT rarely acts as an isolated purified protein in practical formulations; its performance depends on pH, ionic strength, competing ligands, and the architecture of emulsified, coated, or liquid food systems. The available literature indicates that the most mature application space is multifunctional food system design, including preservation-oriented coatings, Pickering-type emulsions, oleogel-associated systems, and liquid food delivery platforms. Broader industrial applications will require standardized reporting of apo/holo state, processing history, digestion models, real food validation, sensory consequences, and allergenicity. To reduce overinterpretation, the present synthesis prioritizes primary studies and weighs model food or real food validation more heavily than mechanistic or preclinical evidence when discussing application readiness. Overall, OVT should be regarded as a promising but context-dependent protein platform whose value lies in coupling bioactivity with techno-functionality rather than in any single universal health claim. Methodological transparency is further supported by explicit database sources, reproducible search blocks, inclusion/exclusion rules, and a structured quality-appraisal and evidence tiering framework.
Zhang et al. (2026) studied this question.