Detection of salmon meat freshness using QCM gas sensor array combined with physicochemical method

Abstract

Salmon meat is easy to be spoiled during transportation and storage due to its abundant protein and fatty acids. During the spoilage process, the released volatile organic compounds (VOCs) may vary significantly, mainly including trimethylamine (TMA), dimethylamine (DMA), formaldehyde (HCHO), ammonia (NH3). Herein, a gas sensor array based on quartz crystal microbalance (QCM) modified with four carbon-based nanomaterials such as graphene oxide (GO), Mxenes (Ti3C2TX), hydroxylated multi-walled carbon nanotubes (MWCNTs), and graphite oxide alkyne (GOP) was established to detect TMA, DMA, HCHO and NH3 in salmon meat, respectively. Carbon-based materials have the advantages of high specific surface area and high stability, so they have great potential in gas adsorption. It was observed that the QCM sensors modified with four sensing carbon-based materials presented good sensitivity, selectivity and repeatability towards corresponding target gases. Finally, the sensor array composed by aforementioned four sensors were used to analyze freshness of salmon samples. The response matrix was processed by principal component analysis (PCA) for visualization. Further discrimination model was established by quadratic support vector machine (QSVM) and the classification accuracy was 100%. To demonstrate the feasibility of discriminating salmon freshness by gas sensor array, the identification results were correlated with the amount of total volatile base nitrogen (TVB-N) measured by semimicro-Kjeldahl method.