Controlling the quality and health of foodstuffs is of great importance. The quality of foods like garlic is strongly influenced by the conditions of processing. Fungal infection is one of the most common hazards of garlic produc- tivity that can affect its processing as well. This research aimed to use the E-Nose to investigate the aroma of garlic as a quality control factor influenced by different treatments such as type of processing, type of fungal infection, and time elapsed since the date of inoculation. The data was investigated and categorized through different meth- ods such as principal component analysis (PCA), linear discriminant analysis (LDA), Support vector machine (SVM), and backpropagation neural network (BPNN). The Index of deterioration toughness increased during the monitor- ing period. In the analysis of the data related to the unprocessed whole (UW), dried slices (DS), garlic powder (PO), and garlic tablet (TA), the PCA included 55%, 75%, 47%, and 53% of the data, respectively. The LDA was able to clas- sify the aroma of UW, DS, PO, and TA samples based on the TFI treatment with an accuracy of 90%, 93.33%, 88.89%, and 60%, respectively. Also, the BPNN classified the aromas of UW, DS, PO, and TA samples based on the TEI treatment with an accuracy of 90%, 95.6%, 72.2%, and 82.2%, respectively. The results revealed that the aroma alteration can be used as a comprehensive factor in the quality control of processed products. As well, the type of processing had significant effects on the severity of decay caused by fungal infection.
