Rapidly identifying the geographical origin of Lilium bulbs by nano-effect excitation-emission matrix fluorescence combined with chemometrics

Lilium bulbs (LB) are a highly nutritious food, and their quality and price are influenced by origin. The present study proposed a nano-effect excitation-emission matrix fluorescence (EEMF) combined with chemometrics strategy for rapidly identifying the geographical origin of LB. Nano-effect EEMF spectra of 280 LB samples from different origins were collected after reaction with bovine serum albumin-modified gold and silver nanoclusters (BSA-AuAgNCs). Further, partial least squares-discrimination analysis (PLS-DA) and principal component analysis-linear discriminant analysis (PCA-LDA) were used to establish classification models for identifying the geographical origin of LB based on the obtained nano-effect EEMF spectra. The result showed that PCA-LDA model gained the optimal performance, and the classification accuracy of the training set and the prediction set was 95.9% and 90.5%, respectively. The nano-effect EEMF spectra was based on the reaction of BSA-AuAgNCs with the components, such as phenolic acids, in LB through hydrogen bonding, which amplified the spectral difference. This study demonstrated that the proposed strategy is effective for identifying the geographical origins of LB, which provides a new idea for the geographic traceability of other foods.