中文摘要：本研究旨在评估电子鼻结合侧向横流免疫分析在快速检测玉米样品黄曲霉毒素和伏马菌出现/共现的潜力。研究表明，即使全面评估需要更大的数据集来进行验证，但电子鼻(e-nose)仍是一种很有前途的快速/筛选方法，用来检测储存玉米粒黄曲霉毒素和伏马菌素的单独或共同污染。
外文摘要：The aim of this study was to evaluate the potential use of an e-nose in combination with lateral flow immunoassays for rapid aflatoxin and fumonisin occurrence/co-occurrence detection in maize samples. For this purpose, 161 samples of corn have been used. Below the regulatory limits, single-contaminated, and co-contaminated samples were classified according to the detection ranges established for commercial lateral flow immunoassays (LFIAs) for mycotoxin determination. Correspondence between methods was evaluated by discriminant function analysis (DFA) procedures using IBM SPSS Statistics 22. Stepwise variable selection was done to select the e-nose sensors for classifying samples by DFA. The overall leave-out-one cross-validated percentage of samples correctly classified by the eight-variate DFA model for aflatoxin was 81%. The overall leave-out-one cross-validated percentage of samples correctly classified by the seven-variate DFA model for fumonisin was 85%. The overall leave-out-one cross-validated percentage of samples correctly classified by the nine-variate DFA model for the three classes of contamination (below the regulatory limits, single-contaminated, co-contaminated) was 65%. Therefore, even though an exhaustive evaluation will require a larger dataset to perform a validation procedure, an electronic nose (e-nose) seems to be a promising rapid/screening method to detect contamination by aflatoxin, fumonisin, or both in maize kernel stocks.
外文关键词：Zea mays；aflatoxin；fumonisin；volatile organic compounds (VOCs)；electronic nose；co-contamination；discriminant analysis
作者：Ottoboni, M；Pinotti, L；Tretola, M；Giromini, C；Fusi, E；Rebucci, R；Grillo, M；Tassoni, L；Foresta, S；Gastaldello, S；Furlan, V；Maran, C；Dell'Orto, V；Cheli, F
作者单位：Univ Milan
期刊名称：TOXINS
期刊影响因子：3.571
出版年份：2018
出版刊次：10
点击下载：电子鼻结合侧向横流免疫分析(LFIAs)快速检测玉米中的黄曲霉毒素及伏马菌素的出现/共现