Simultaneous Detection of Harmful Fungi and Mycotoxin Contamination in Peanuts by Electronic Nose

In this study, electronic nose technology was used to establish a method for the simultaneous detection of fungal and mycotoxin contamination in peanuts infected with different strains. Peanuts were irradiated, inoculated with five common mold strains (three toxigenic strains and two non-toxic strains), and cultured in an incubator (26 ℃ and 80% RH) for six days. Samples were taken every day to collect electronic nose signals, and to measure the number of colonies and aflatoxin B₁ (AFB₁) content. Qualitative discriminant models for fungal and mycotoxin contamination levels were established. The results of principal component analysis (PCA) showed that the samples contaminated with different molds tended to be clustered, and they were located above the acceptable samples. The overall accuracy of linear discriminant analysis and partial least squares-discriminant analysis was more than 80%; the classification accuracy based on toxigenic and non-toxic strains was higher than 95.7%, the classification accuracy based on AFB₁ content was more than 90%, while the classification accuracy based on the number of colonies was lower. False negative percentages were lower than 17% for all models. Electronic nose technology is feasible to determine fungal and mycotoxin contamination levels in peanuts infected with different strains. In order to improve the accuracy and stability of the models, peanut samples infected with more strains and different peanut varieties should be considered in further research.