Amomi fructus (AF) has been used for both medicinal and food purposes for centuries.However, issues such as source mixing, substandard quality, and product adulteration often affect its efficacy.This study used E-nose (EN) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) to determine and analyze the volatile organic compounds (VOCs) in AF and its copyright products.
A total of 111 VOCs were detected by HS-GC-IMS, with 101 tentatively identified.Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) identified 47 VOCs as differential markers for distinguishing authentic AF from counterfeits (VIP value >1 and P < 0.05).
Based on the E-nose sensor response value and the peak volumes of the 111 VOCs, the unguided T Shirt Principal Component Analysis (PCA), guided Principal Component Analysis-Discriminant Analysis (PCA-DA), and Partial Least Squares-Discriminant Analysis (PLS-DA) models were established to differentiate AF by authenticity, origin, and provenance.The authenticity identification model achieved 100.00% accuracy after PCA analysis, while the origin identification model and the provenance identification model were 95.
65% (HS-GC-IMS: PLS-DA) and 98.18% (HS-GC-IMS: PCA-DA/PLS-DA), respectively.Further data-level fusion of E-nose and HS-GC-IMS significantly improved the accuracy of the origin identification model to 97.
96% (PLS-DA), outperforming single-source data modeling.In conclusion, the intelligent data fusion algorithm based on E-nose and HS-GC-IMS data RAW TURMERIC GOLD HONEY effectively identifies the authenticity, origin, and provenance of AF, providing a rapid and accurate method for quality evaluation.