Detection of Six Commercially Processed Soy Ingredients in an Incurred Food Matrix Using Parallel Reaction Monitoring

Soybeans are one of the major allergenic foods in many countries. Soybeans are commonly processed into different types of soy ingredients to achieve the desired properties. The processing, however, may affect the protein profiles and protein structure, thus affecting the detection of soy proteins. Mass spectrometry (MS) is a potential alternative to the traditional immunoassays for the detection of soy-derived ingredients in foods. This study aims to develop a liquid chromatography-tandem MS method that uniformly detects different types of soy-derived ingredients. Target peptides applicable to the detection of six commercial soy ingredients were identified based on the results of MS label-free quantification and a set of selection criteria. The results indicated that soy ingredient processing can result in different protein profiles. A total of six soy ingredients were then individually incurred into cookie matrices at different levels. Sample preparation methods were optimized, and a distinct improvement in peptide performance was observed after optimization. Cookies and dough incurred with different soy ingredients at 100 ppm total soy protein showed a similar level of peptide recovery (90% mean signal relative to unroasted soy flour), demonstrating the ability of the MS method to detect processed soy ingredients in a uniform manner.