Rapid identification of the authenticity of iron rod yam by in-situ mass spectrometry based on random forest algorithm
[Objective]To establish a fast and nondestructive analysis method for identifying iron rod yam.[Methods]Atmospheric pressure chemical ionization mass spectrometry(APCI-MS)was employed to detect the chemical constituents of iron rod yam(TG)and non-iron rod yam(FTG)from different origins under ambient temperature and pressure,With 200 sets of data collected from each type of TG and FTG,and a total of 3 600 mass spectrometry data points were obtained.Subsequently,the initial level of the mass spectrometry data obtained was analyzed using Principal Component Analysis(PCA)and the random forest(RF)algorithm.Pattern recognition analysis established a model to differentiate between TG and FTG based on their chemical compositions.[Results]The difference between the first-level mass spectra obtained by HS-APCI-MS was obvious between TG samples and FTG samples.The cumulative variance contribution plot of the principal components showed that the first seven principal components accounted for 85.63%(≥85%)of the variance.The accuracy of the training set and detection set reached 100%when the number of decision trees was 25.HS-APCI-MS combined with RF algorithm had a significant identification effect on TG,and the classification effect of RF was superior to that of PCA.[Conclusion]Atmospheric pressure chemical ionization mass spectrometry,combined with the RF algorithm,can rapidly and non-destructively identify TG and FTG,providing a new technical method for authenticating TG.
iron rod yamatmospheric chemical ionization sourceprincipal component analysisrandom forest algorithmidentification
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