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:21
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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科研通AI6.4应助qiu采纳,获得30
刚刚
a半城繁华半城殇完成签到,获得积分10
1秒前
tplink发布了新的文献求助10
1秒前
shaovbnm93完成签到,获得积分10
1秒前
李爱国应助予青采纳,获得10
2秒前
yx发布了新的文献求助10
2秒前
大模型应助大力金毛采纳,获得10
3秒前
3秒前
研友_LX62KZ完成签到,获得积分10
3秒前
4秒前
4秒前
4秒前
SAGE完成签到,获得积分20
5秒前
科研通AI6.3应助签到采纳,获得10
5秒前
5秒前
5秒前
Ykook发布了新的文献求助10
5秒前
MIN完成签到 ,获得积分10
6秒前
研友_LX62KZ发布了新的文献求助30
6秒前
思源应助芋袁采纳,获得10
7秒前
8秒前
minnn应助热心市民小杨采纳,获得10
8秒前
lin发布了新的文献求助10
8秒前
8秒前
Ava应助cindy采纳,获得10
8秒前
英姑应助哭泣觅儿采纳,获得30
8秒前
9秒前
cool完成签到,获得积分10
9秒前
10秒前
yyyy发布了新的文献求助10
11秒前
忘乎所以完成签到,获得积分10
11秒前
zkx发布了新的文献求助30
11秒前
11秒前
11秒前
夕木木应助程绪洋采纳,获得10
13秒前
鹅鹅Namae应助程绪洋采纳,获得10
13秒前
李健应助程绪洋采纳,获得10
13秒前
14秒前
FashionBoy应助yx采纳,获得10
14秒前
14秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场规模及竞争格局分析报告 1000
模型平均及其应用 900
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
作者名:Kristopher P. Plain,悉尼大学的,目前只能查到其四篇论文,想找到其博士论文 550
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7335830
求助须知:如何正确求助?哪些是违规求助? 8949699
关于积分的说明 18991397
捐赠科研通 6989481
什么是DOI,文献DOI怎么找? 3217759
关于科研通互助平台的介绍 2383830
邀请新用户注册赠送积分活动 2197849