Multiplex Detection of Biogenic Amines for Meat Freshness Monitoring Using Nanoplasmonic Colorimetric Sensor Array

Biogenic amines (BAs) were presented as significant markers for the evaluation of the spoilage of meat and meat products. In this work, a colorimetric sensor array was developed for the discrimination and detection of spermine (SP), spermidine (SD), histamine (HS), and tryptamine (TP) as important BAs in food assessment. For this aim, two important spherical plasmonic nanoparticles, namely gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs), were utilized as the sensing elements of the probes. The cross-reactive interaction of the target biogenic amines and the plasmonic nanoparticles caused the aggregation-induced UV-Vis spectra changes, which were accompanied by visual color variation in the solution. The collected responses were analyzed by principal component analysis-linear discrimination analysis (PCA-LDA) to classify the four BAs. This colorimetric sensor array can also discriminate between the individual BAs and their mixture accurately. Partial least squares regression (PLS-R) was also utilized for quantitative analysis of the BAs. The wide linear concentration ranges of 0.1-10.0 mu M for the four BAs and desirable figures of merits (FOMs) showed the potential of the developed sensor for quantitative detection of the BAs. Finally, the practical ability of the developed probe was studied by the determination of the BAs in the meat samples, which successfully proved the potential of the colorimetric sensor array in a food sample.

Automated summary

In this study, a colorimetric sensor array was developed to discriminate and detect important biogenic amines (BAs) in food assessment. Utilizing gold and silver nanoparticles as sensing elements, the cross-reactive interaction of the target BAs and nanoparticles caused changes in UV-Vis spectra and visual color variation. Principal component analysis-linear discrimination analysis (PCA-LDA) was used to classify the BAs, and partial least squares regression (PLS-R) was utilized for quantitative analysis. The developed sensor array showed potential for quantitative detection of BAs and successfully detected BAs in meat samples.