基于离子迁移谱的花生霉变早期预警标示分子研究

花生作为我国主要的油料经济作物之一，在加工贮藏等环节极易受到黄曲霉菌的侵染而失去使用价值。挖掘黄曲霉菌污染发生早期预警标识分子对于花生霉变的早期监测预警具有重要意义。本研究采用气相色谱-离子迁移谱法对花生中黄曲霉侵染过程中的挥发性有机化合物进行分析，共检测到53种挥发性有机化合物，其中包含34种化合物单体及部分物质的二聚体，另外19种物质目前尚未定性分析。结果表明黄曲霉不同生长阶段产生的挥发性有机化合物具有较大差异。通过挥发性物质的指纹谱图观察侵染过程中各阶段挥发性物质的变化规律和相对含量的变化，根据特征峰图片库结果结合化学计量学方法可以对花生的早期霉变程度进行有效的区分。热图聚类分析和主成分分析比较不同化合物之间的差异性和相似性，结果表明不同侵染阶段挥发性有机化合物差异明显，具有明显区分度，其中己酸、2，3-丁二酮、2-己烯-1-醇-M、戊-1-醇-M和己醛可作为花生早期霉变的潜在生物标志物。本研究为仓储条件下花生霉变程度的早期预警监测体系的开发提供了有效的标识分子。

Molecular Markers for Early Warning of Peanut mildew by Gas Chromatography-Ion Mobility Spectrometry

As one of the main oil-bearing crops in China, peanuts are susceptible to the contamination of Aspergillus flavus during processing and storage, which results in the loss of commercial values. Hence, it is crucial to investigate the signaling molecules during the early stage of contamination in order to monitor and control the spread of A. flavus in peanuts. In this study, Gas chromatography–ion mobility spectrometry (GC-IMS) was used to analyze the volatile organic compounds (VOCs) during the invasion of A. flavus in peanuts. A total of 53 compounds were detected, including 34 confirmed monomers and dimers. The other 19 compounds were yet to be qualitatively determined. The results showed that the organic compounds produced by A. flavus varied significantly in the different growth stages. The fingerprint spectrum demonstrated the changing patterns and relative concentrations of the volatile organic compounds as the contamination progressed, and the characteristic peaks could be used to quantify the level of contamination at the early stages. The volatile organic compounds were also analyzed with heat map clustering and principal component analysis. Significant differences were observed among the volatile organic compounds at different stages of contamination. The study determined that caproic acid, 2, 3-butanedione, 2-hexen-1-ol-M, pentan-1-ol-M and hexanal could be used as the signaling molecules during the early stages of A. flavus contamination. The results of this study provide an effective marker for the development of early warning monitoring system for peanut mildew degree under storage conditions.