Fabrication of a Sensor Array Based on Quartz Crystal Microbalance and the Application in Egg Shelf Life Evaluation

Abstract

Abstract In this study, a QCM sensor array with four different surface modified QCM sensors (i.e., multi-walled carbon nanotubes, graphene, copper oxide and polyaniline) was fabricated and was applied to evaluate the shelf life of eggs by sensing the volatiles. The morphologies of the sensitive materials on electrodes were analyzed by field-emission scanning electron microscope (FE-SEM), and sensor responses were monitored by a self-made frequency measurement system. Particularly, these four sensors exhibited relatively good sensitivity, reversibility, repeatability and long-term stability. Then, the sensor array was applied to detect volatiles of eggs with different shelf life. The result of linear discriminant analysis (LDA) outperformed principal component analysis (PCA), and exhibited excellent classification accuracy. Partial least square regression (PLSR) was employed to predict the shelf life of eggs and the fitting coefficient of determination (R2) of PLSR increased from 0.8474 to 0.9547 after kernel principal component analysis (KPCA) introduced, which showed satisfactory prediction performance. It could be concluded that the QCM sensor array is effective for the detection of eggs with different shelf life, offering an alternative strategy to estimate the freshness of eggs.