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利用傅里叶变换红外光谱技术对食品腐败真菌进行特征分析。

Characterization of food spoilage fungi by FTIR spectroscopy.

机构信息

Nofima AS, Ås, Norway.

出版信息

J Appl Microbiol. 2013 Mar;114(3):788-96. doi: 10.1111/jam.12092. Epub 2013 Jan 7.

Abstract

AIMS

The objective of the study was to evaluate a high-throughput liquid microcultivation protocol and FTIR spectroscopy for the differentiation of food spoilage filamentous fungi.

METHODS AND RESULTS

For this study, fifty-nine food-related fungal strains were analysed. The cultivation of fungi was performed in liquid medium in the Bioscreen C microtitre plate system with a throughput of 200 samples per cultivation run. Mycelium was prepared for FTIR analysis by a simple procedure, including a washing and a homogenization step. Hierarchical cluster analysis was used to study affinity among the different species. Based on the hierarchical cluster analysis, a classification and validation scheme was developed by artificial neural network analysis. The classification network was tested by an independent test set. The results show that 93.9 and 94.0% of the spectra were correctly identified at the species and genus level, respectively.

CONCLUSIONS

The use of high-throughput liquid microcultivation protocol combined with FTIR spectroscopy and artificial neural network analysis allows differentiation of food spoilage fungi on the phylum, genus and species level.

SIGNIFICANCE AND IMPACT OF THE STUDY

The high-throughput liquid microcultivation protocol combined with FTIR spectroscopy can be used for the detection, classification and even identification of food-related filamentous fungi. Advantages of the method are high-throughput characteristics, high sensitivity, low costs and relatively short time of analysis.

摘要

目的

本研究旨在评估高通量液体微培养方案和傅里叶变换红外(FTIR)光谱技术,以区分食品腐败丝状真菌。

方法和结果

在这项研究中,分析了 59 株与食品相关的真菌菌株。采用 Bioscreen C 微量滴定板系统中的液体培养基进行真菌培养,每个培养运行的通量为 200 个样本。通过简单的步骤,包括洗涤和均化步骤,为 FTIR 分析制备菌丝体。采用层次聚类分析研究不同物种之间的亲和性。基于层次聚类分析,通过人工神经网络分析开发了分类和验证方案。分类网络通过独立测试集进行测试。结果表明,在种和属水平上,分别有 93.9%和 94.0%的光谱正确识别。

结论

高通量液体微培养方案与 FTIR 光谱和人工神经网络分析的结合可用于区分食源性腐败真菌的门、属和种水平。

研究的意义和影响

高通量液体微培养方案结合 FTIR 光谱可用于检测、分类甚至鉴定与食品相关的丝状真菌。该方法的优点是高通量特性、高灵敏度、低成本和相对较短的分析时间。

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