Electronic Detection of Garlic Density in Various Kinds of Yogurts Using Statistical Features

Accurate detection of food components plays a critical role in developing modern culinary technologies and food safety practices. This study uses electronic nose technology to determine garlic concentration in garlic yogurts. An electronic nose system consisting of 11 different MQ brand gas sensors was used in the study. Five different yogurt types were prepared with three different garlic concentrations: plain, low, and high. A total of 225 odor records were taken from 15 yogurt samples, and various features were extracted from these data, which were analyzed using four different classification algorithms. The Extra Trees algorithm was the most successful method, with 89.14% classification accuracy, 89.80% sensitivity, and 94.57% specificity rates. The results of the study show that electronic nose technology can be used in many application areas, especially in smart kitchen devices analyzing food ingredients to provide information about freshness and composition, in the food industry to ensure standardization of product quality in production processes and to ensure that intense aromatic ingredients such as garlic are used in the right amount, and in the development of food products suitable for consumers’ special diets or personal tastes.