Detecting the adulteration in apple vinegar using olfactory machine coupled PCA and ANN methods

Abstract

Nowadays, the number of food adulteration cases is increasing sharply for reasons such as population growth, increasing demand and profitability of suppliers. Mixing apple vinegar with white vinegar and acetic acid are the most common methods of cheating on the market in Iran. In this study, an electrical olfactory system was used to detect pure apple vinegar from acetic acid and white vinegar. The data obtained from the sensors were analyzed by PCA and ANN methods after preprocessing. Based on the results, TGS822 and MQ136 sensors showed the highest response to odor of samples of vinegar mixed with acetic acid and white vinegar, respectively. Also, the confusion matrix obtained from ANN analysis for different levels of adulteration with acetic acid and white vinegar showed correct classification rate of 93.3% and 94.7%, respectively.