ASAP-MS combined with mass spectrum similarity and binary code for rapid and intelligent authentication of 78 edible flowers

Abstract

This is the first report to use Atmospheric Pressure Solids Analysis Probe (ASAP) for rapid and intelligent authentication of 78 edible flowers. Mass spectra of 451 batches were collected, with each run for 1-2 min. Experimental raw data was automatically extracted and aligned to create a MS database, based on which flowers were identified by MS similarity scores and rankings. To avoid background interference, top 25 ions of each flower were screened and gathered into an m/z pool containing 292 ions (+) and 399 ions (-). Binary sequence IDs were then generated by automatically assigning "1″ for presence and "0″ for absence, resulting in 78 binary codes. Binary code similarity with 78 IDs was used for authentication. Above two approaches were automatically performed by MATLAB, and compared to k-nearest neighbor model, and samples were all successfully identified (100 %). The proposed method provides a high-throughput authentication approach for large-scale food samples.

Keywords: ASAP; Authentication; Flowers; MATLAB.