稻谷中真菌污染早期在线监测压电微阵列传感新方法研究

A sensitive, rapid and stable piezoelectric microarray sensing system will be constructed by integrating microelectrode arrays, molecular wires and a piezoelectric sensor for early, online monitoring trace indicator of fungal contamination (the frequent Aspergillus flavus) in rice and a piezoelectric microarray sensing method will be proposed as follows:1) an early indicator group will be identified based on both metabolic pathway and modern analysis techniques; 2) The microarray chips, reacting with indicator sensitively, specifically and rapidly, will be designed by integrating microelectrode arrays with molecular wires; 3) The piezoelectric microarray sensing system was construced by connecting microarray chips and a piezoelectric sensor in series; 4) The proposed system will be used to detect stimulated indicator, standard fungi and isolates, and then microarray chips and the oscillating circuit will be optimized. The piezoelectric microarray sensing method will be proposed based on analyzing the frequency responsive data using pattern recognition. The detection time for monitoring fungal contamination will decrease from 8-10 days to several hours, which will provide remedial measures to be more effectively implemented, and also provide new thought for early, online monitoring fungal contamination in food.

融合微电极阵列、分子导线和压电传感器构建对稻谷中真菌污染（以常见黄曲霉为模式菌）痕量指示物组有灵敏特异稳定响应的压电微阵列传感系统，并建立真菌污染早期在线监测的新方法，具体如下：1）基于真菌代谢途径，结合现代分析技术筛选可实现稻谷中真菌污染早期在线监测的指示物组； 2）融合微电极阵列和分子导线构建对痕量指示物组有灵敏特异快速响应的微阵列芯片；3）将微阵列芯片与压电传感器串联构建压电微阵列传感系统；4）将系统应用于指示物模拟体系、标准菌、分离菌的检测，优化微阵列芯片和传感电路，获得频率响应数据库，结合模式识别建立稻谷中真菌污染早期在线监测压电微阵列传感新方法。该传感方法的研究可望使黄曲霉菌污染的鉴别时间由8-10天降至几小时，为制定及时有效的防控措施提供理论依据，为粮食中真菌污染的早期在线监测提供全新思路。

本项目通过剖析真菌（以黄曲霉菌为模式菌株）在稻谷基质中的代谢特征，研究了稻谷中真菌污染早期在线监测压电微阵列传感新方法，具体为：1）在前期项目的基础上提升了压电微阵列传感装置的响应稳定性。基于压电传感器的响应机理，完善振荡电路、优化自动读数系统与显示系统，提升了压电微阵列传感器的响应稳定性；2）筛选出特征性的挥发性代谢产物组。以稻谷为对象，通过HS/SPME/GC/MS对稻谷中黄曲霉菌污染的挥发性代谢产物成分进行分析，筛选出特征性的挥发性代谢产物组；3）进一步构建了稻谷中黄曲霉菌污染早期在线监测压电微阵列传感器。根据挥发性代谢产物组的特点，筛选出合适的探针微阵列，将系统应用于指示物模拟体系、标准真菌及稻谷中黄曲霉菌污染的检测，优化微阵列芯片和传感电路，获得频率响应数据库；4）结合神经网络分析法对检测获得的频移数据集进行分析，从而提出稻谷中黄曲霉菌污染早期在线监测压电微阵列传感的方法。该方法同时用经典的微生物学方法进行佐证。该传感技术及其方法的研究与应用，可望使稻谷中黄曲霉菌污染的检测时间由原来的5天以上缩短至48小时以内，并实现黄曲霉菌污染的实时、在线、原位监测。