Drying of garlic is one of the essential post-harvest processing techniques to increase the efficiency of its usage. The present study aimed to assess the influence of different drying methods (DMs) and various pre-storage periods (PSPs) on the aroma of dried garlic using an electronic nose (E-nose). Garlic was dried by near-infrared fluidized bed drying (NIFBD), atmospheric freeze-drying (AFD), and near-infrared vacuum drying (NIVD) methods after 1-, 8-, and 16-day PSPs. The results revealed that the highest and lowest drying rates occurred in the NIVD and AFD, respectively. As the PSP prolonged, the drying time of the product also increased. To analyze and classify the data obtained from the E-nose, the principal component analysis (PCA), linear discriminant analysis (LDA), and backpropagation neural network (BPNN) methods were employed. The PCA results showed that the samples dehydrated by different DMs could be easily distinguished by assessing the garlic’s aroma. However, various PSPs had a lower impact on the aroma of the samples than the DMs. Compared to the aroma classification of samples based on different PSPs, the LDA and BPNN methods were more accurate in classifying the aroma of samples based on different DMs.
