Food Science and Technology Department


Date of this Version



A THESIS Presented to the Faculty of The Graduate College of 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 Professor Joseph L. Baumert. Lincoln, Nebraska: August 2016

Copyright (c) 2016 Charlene Gan


Macadamia nut is considered a priority food allergen and undeclared macadamia nut residues pose a potential food safety risk to individuals with macadamia nut allergies. To date, there are a limited number of immunochemical methods that are available for detection of processed macadamia nut residues. Therefore, the aim of this study was to develop a reliable and robust sandwich ELISA for detection of macadamia nut residues. Raw and roasted macadamia nuts were used for immunization in three different species of animals (sheep, goat, and rabbits). Macadamia nut specific IgG antibodies produced by each animal were tested for their specificity and monitored by determining their titer values. Rabbit antiserum was used as the capture reagent while goat antiserum was used as the detector reagent in the optimized sandwich ELISA. These antisera recognized both raw and roasted macadamia protein equivalently. Potential matrix interference was evaluated in sugar cookies, vanilla ice cream, and dark chocolate to assess the overall sensitivity of the ELISA. The cookie and ice cream matrices did not significantly affect the sensitivity of the developed ELISA (p<0.05). The dark chocolate matrix decreased macadamia nut protein extraction and overall ELISA sensitivity; however, the addition of NFDM or fish gelatin into the extraction buffer enhanced the extraction efficiency which allowed for an estimated limit of quantification of 1 ppm macadamia nut in three matrices. Potential cross-reactivity was assessed in 86 food ingredients. Pure extracts from a few ingredients (all-spice, cinnamon, cloves, paprika, Brazil nut, poppy seeds, oregano, nutmeg, and cherries) showed low level binding but would not significantly affect the accuracy of the ELISA. The sensitivity and efficiency of the developed ELISA was evaluated further through macadamia incurred sugar cookies and vanilla ice cream. The overall high percentage recovery of macadamia nut residues in both model foods shows that the developed ELISA can sufficiently and reliably detect macadamia nut proteins in processed foods, and will provide a useful tool to support the validation of allergen control procedures within food companies or regulatory compliance.

Advisor: Joseph L. Baumert