• 安全检测 •

### 电子鼻同步检测花生霉菌及霉菌毒素

1. （1.南京财经大学食品科学与工程学院，江苏省现代粮食流通与安全协同创新中心，江苏 南京 210023；2.南京林业大学机械电子工程学院，江苏 南京 210037；3.巴赫达尔大学生物技术研究所，埃塞俄比亚 亚的斯亚贝巴 5954）
• 发布日期:2022-07-01
• 基金资助:
国家战略性国际合作专项（2020YFE0200200）；国家自然科学基金面上项目（32172306；31772061）； 江苏省农业科技自主创新资金项目（CX(19)2005）；江苏省自然科学基金面上项目（BK20211291）

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

WANG Bei, SHEN Fei, HE Xueming, JIANG Xuesong, YUAN Jian, FANG Yong, HU Qiuhui, QIU Weifen, MAMO Firew Tafesse

1. (1. Collaborative Innovation Center for Modern Grain Circulation and Safety, College of Food Science and Engineering, Nanjing University of Finance and Economics, Nanjing 210023, China; 2. College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China; 3. Ethiopian Biotechnology Institute (EBTi), Bahir Dar University, Addis Ababa Ethiopia 5954, Ethiopian)
• Published:2022-07-01

Abstract: 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.