Analysis of roasted peanuts based on GC–MS combined with GC–IMS

Abstract The present study used gas chromatography–mass spectrometry (GC–MS) and gas chromatography–ion mobility spectrometry (GC–IMS) to separate and identify the characteristic volatile flavor substances in 30 roasted peanut samples. GC–MS identified 59 volatile compounds, and GC–IMS detected 61 volatile flavor substances. The 30 peanut varieties were then divided into four groups on the basis of their volatile flavor substances using principal component analysis (PCA), and a fingerprint profile of the varieties' volatile characteristics was established from information peaks identified in the spectra. Descriptive sensory analysis (DSA) was performed to distinguish differences in flavor attributes between roasted peanut varieties. Partial least squares regression (PLSR) was performed with the volatile flavor content of roasted peanuts as the independent variable and the flavor attribute score as the dependent variable. These findings provide a basis for predicting the appeal of roasted peanuts based on their composition and demonstrate a potential avenue for improving food flavor quality.