Food Science and Technology Department


First Advisor

Philip E. Johnson

Second Advisor

Melanie L. Downs

Date of this Version

Fall 11-2022


A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Food Science and Technology, Under the Supervision of Professors Philip E. Johnson and Melanie L. Downs. Lincoln, Nebraska: November 2022

Copyright © 2022 Sara K. Schlange


The unintentional presence of peanut in food products through allergen cross-contact is a considerable safety concern for peanut-allergic individuals. The food industry monitors for this contamination using immunoassays; however, these detection methods demonstrate issues with recovery and accurate quantification of allergenic protein when analyzing processed, complex food matrices. Of particular concern is the deficit in immunoassay-based detection and quantification of peanut in cookie and dark chocolate matrices, as the unintentional presence of peanut has been observed in these food products. A liquid chromatography with tandem mass spectrometry (LC-MS/MS) method for the detection and quantification of peanut protein in cookie and dark chocolate was developed to overcome the issues plaguing immunoassays in analysis of peanut in these matrices.

Peanut-incurred cookie and dark chocolate matrices were generated at various concentrations of peanut. Untargeted MS analysis of incurred matrices identified and quantified peanut peptides. Peptides were subjected to selection criteria, based on abundance and robustness in matrix, to determine 32 (cookie) and 67 (dark chocolate) candidate target peptides for the method. Candidate peptides were filtered to determine robust and sensitive target peptides in each matrix using iterative rounds of targeted MS. Six (cookie) and seven (dark chocolate) final peptides were determined. This resulted in nine unique peanut peptides for the method.

A quantitative strategy was developed based on stable isotope labeled (SIL) peptides and an external calibration to peanut flour (PF). Quantification was reported in parts per million (ppm) peanut protein. Optimization of various aspects of the method, including instrument parameters, LC, and sample preparation, improved the method’s sensitivity and variability. The LC-MS/MS method was evaluated with incurred matrices and demonstrated highly sensitive and reliable detection, even at low concentrations of peanut protein (1.24 ppm peanut protein in cookie and 2 ppm peanut protein in dark chocolate). This sensitivity is sufficient to detect peanut concentrations relevant for the most sensitive peanut-allergic individuals.

Advisors: Philip E. Johnson and Melanie L. Downs