摘要
利用电子鼻技术,建立了花生受不同霉菌感染后的霉变程度及毒素含量的同步快速检测方法。花生经辐照灭菌后接种5种常见霉菌(3种产毒菌株、2种非产毒菌株),于培养箱(26℃、相对湿度80%)中培养6 d。每天取出不同霉菌污染的样品采集电子鼻信号,同时测定其菌落总数和黄曲霉毒素B_(1)(aflatoxin B_(1),AFB_(1))含量,建立不同霉菌感染下霉变程度及毒素含量定性判别模型。主成分分析结果显示不同霉菌污染下有一定的聚类趋势,且污染样品位于可接受样品的上方;利用线性判别分析和偏最小二乘判别分析整体准确率达到80%以上,其中根据产毒菌株和非产毒菌株分类正确率高于95.7%,根据AFB_(1)含量分类正确率90%以上,根据菌落总数分类正确率较低。所有模型中假阴性均低于17%。因此,电子鼻技术对不同霉菌感染下的霉变程度及毒素含量的测定具有可行性。未来研究应继续扩大样品数量,补充受其他更多霉菌侵染及不同品种的花生样品,同时考虑实际情况,以提高模型的准确性和稳定性。
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 B_(1)(AFB_(1))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 AFB_(1) 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.
作者
王蓓
沈飞
何学明
蒋雪松
袁建
方勇
胡秋辉
邱伟芬
MAMO Firew Tafesse
WANG Bei;SHEN Fei;HE Xueming;JIANG Xuesong;YUAN Jian;FANG Yong;HU Qiuhui;QIU Weifen;MAMO Firew Tafesse(Collaborative Innovation Center for Modern Grain Circulation and Safety,College of Food Science and Engineering,Nanjing University of Finance and Economics,Nanjing 210023,China;College of Mechanical and Electronic Engineering,Nanjing Forestry University,Nanjing 210037,China;Ethiopian Biotechnology Institute(EBTi),Bahir Dar University,Addis Ababa Ethiopia 5954,Ethiopian)
出处
《食品科学》
EI
CAS
CSCD
北大核心
2022年第12期310-316,共7页
Food Science
基金
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)。
作者简介
第一作者:王蓓(1997-)(ORCID:0000-0003-1837-6324),女,硕士研究生,研究方向为农产品无损检测技术。E-mail:1498969445@qq.com;通信作者:沈飞(1984-)(ORCID:0000-0002-8749-7472),男,副教授,博士,研究方向为农产品无损检测技术与装备。E-mail:shenfei@nufe.edu.cn。
