Identification of sweetpotato black spot disease caused by Ceratocystis fimbriata by quartz crystal microbalance array

石英晶体微天平 三氯氢硅 傅里叶变换红外光谱 分子印迹聚合物 沸石咪唑盐骨架 质谱法 分析化学(期刊) 材料科学 化学工程 化学 色谱法 金属有机骨架 光电子学 选择性 吸附 有机化学 工程类 催化作用
作者
Linjiang Pang,Lu Zhang,Zhenhe Wang,Guoquan Lu,Xia Sun,Jiyu Cheng,Shihao Chen,Guangyu Qi,Xiaoyi Duan,Rui Xu,Wei Chen,Xinghua Lu
出处
期刊:Sensors and Actuators B-chemical [Elsevier BV]
卷期号:386: 133761-133761 被引量:17
标识
DOI:10.1016/j.snb.2023.133761
摘要

Sweetpotato black spot disease caused by Ceratocystis fimbriata is a major sweetpotato disease that not only affects yield and storage but also damages human or animal health. Herein, a four-element quartz crystal microbalance (QCM) gas sensor array based on molecularly imprinted polymers (MIPs) and zeolitic imidazolate frameworks (ZIFs) materials were reported to differentiate healthy sweetpotatoes and sick sweetpotatoes. Several volatile organic compounds, namely citronellol, heptanal, benzaldehyde, and 2-pentylfuran, were selected for detection based on the results of gas chromatography-mass spectrometry (GC-MS). The MIPs and ZIFs were characterized by X-ray diffraction, scanning electron microscopy, Fourier transform infrared spectroscopy, and nitrogen adsorption-desorption, and the results show that materials were successfully obtained. The four sensors based on the as-prepared materials exhibited excellent sensitivity and selectivity toward target gases. Finally, the sensor array was applied to identify sick sweetpotatoes. Frequency shift was selected as the eigenvalue and quadratic support vector machine (QSVM) and weighted k-nearest neighbor (WKNN) models were employed for discrimination. QSVM and WKNN exhibited 100% accuracy in classification, proving that the sensor array can be used for the identification of Ceratocystis-fimbriata-infested sweetpotatoes. This study may contribute to the development of gas sensor arrays for use in agri-food quality control and protection.
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