Early detection of toxigenic fungi on maize by hyperspectral imaging analysis

被引:207
作者
Del Fiore, A. [1 ]
Reverberi, M. [2 ]
Ricelli, A. [3 ]
Pinzari, F. [4 ]
Serranti, S. [5 ]
Fabbri, A. A. [2 ]
Bonifazi, G. [5 ]
Fanelli, C. [2 ]
机构
[1] ENEA, Lab Innovaz Agroind, CR Casaccia, I-00123 Rome, Italy
[2] Univ Roma La Sapienza, Dipartimento Biol Vegetale, I-00165 Rome, Italy
[3] CNR, Ist Sci Prod Alimentari, I-70126 Bari, Italy
[4] Ist Cent Restauro & Conservaz Patrimonio Archivis, Biol Lab, I-00184 Rome, Italy
[5] Univ Roma La Sapienza, Dipartimento Ingn Chim Mat Ambiente, I-00184 Rome, Italy
关键词
Food commodities; Toxigenic fungi; Maize; Early detection; Non destructive analysis; Hyperspectral imaging; WHEAT KERNELS; FOOD QUALITY; REFLECTANCE; SPECTROSCOPY; APPLES; SCAB;
D O I
10.1016/j.ijfoodmicro.2010.08.001
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Fungi can grow on many food commodities. Some fungal species, such as Aspergillus flavus, Aspergillus parasiticus, Aspergillus niger and Fusarium spp., can produce, under suitable conditions. mycotoxins, secondary metabolites which are toxic for humans and animals. Toxigenic fungi are a real issue, especially for the cereal industry. The aim of this work is to carry out a non destructive, hyperspectral imaging-based method to detect toxigenic fungi on maize kernels, and to discriminate between healthy and diseased kernels. A desktop spectral scanner equipped with an imaging based spectrometer ImSpector-Specim V10, working in the visible-near infrared spectral range (400-1000 nm) was used. The results show that the hyperspectral imaging is able to rapidly discriminate commercial maize kernels infected with toxigenic fungi from uninfected controls when traditional methods are not yet effective: i.e. from 48 h after inoculation with A. niger or A. flavus. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:64 / 71
页数:8
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