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 催化作用 工程类
作者
Linjiang Pang,Lu Zhang,Zhenhe Wang,Guoquan Lu,Xiaodong 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]
卷期号:386: 133761-133761 被引量:1
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
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
搜集达人应助风中冷珍采纳,获得10
1秒前
太阳风暴剑完成签到,获得积分10
2秒前
黑胡椒完成签到 ,获得积分10
3秒前
威武的匕完成签到 ,获得积分10
6秒前
墨羽翔天完成签到,获得积分10
6秒前
穆一手完成签到 ,获得积分10
7秒前
Summer完成签到,获得积分10
7秒前
Drvictor完成签到,获得积分10
9秒前
有终完成签到 ,获得积分10
11秒前
13秒前
焚心结完成签到 ,获得积分0
14秒前
梅溪湖的提词器完成签到,获得积分10
16秒前
852应助风中冷珍采纳,获得10
16秒前
chillin完成签到 ,获得积分10
17秒前
是真的宇航员啊完成签到,获得积分10
17秒前
罗胖胖完成签到 ,获得积分10
18秒前
丫丫完成签到,获得积分20
19秒前
lixiang完成签到,获得积分10
21秒前
阿潇完成签到 ,获得积分10
22秒前
kobiy完成签到 ,获得积分10
23秒前
脑洞疼应助科研通管家采纳,获得10
23秒前
科研通AI2S应助科研通管家采纳,获得10
24秒前
24秒前
无花果应助科研通管家采纳,获得10
24秒前
敬老院N号应助科研通管家采纳,获得50
24秒前
英姑应助科研通管家采纳,获得10
24秒前
深情安青应助科研通管家采纳,获得10
24秒前
天天快乐应助科研通管家采纳,获得10
24秒前
orixero应助科研通管家采纳,获得10
24秒前
安宁完成签到,获得积分10
27秒前
爆米花应助sycamore采纳,获得10
28秒前
30秒前
明理从露完成签到 ,获得积分10
30秒前
星辰完成签到,获得积分10
31秒前
drjj完成签到 ,获得积分10
34秒前
35秒前
36秒前
37秒前
车车完成签到,获得积分10
38秒前
Kevin Huang发布了新的文献求助10
39秒前
高分求助中
Rock-Forming Minerals, Volume 3C, Sheet Silicates: Clay Minerals 2000
The late Devonian Standard Conodont Zonation 2000
Nickel superalloy market size, share, growth, trends, and forecast 2023-2030 2000
The Lali Section: An Excellent Reference Section for Upper - Devonian in South China 1500
The Healthy Socialist Life in Maoist China 600
The Vladimirov Diaries [by Peter Vladimirov] 600
encyclopedia of computational mechanics,2 edition 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3268873
求助须知:如何正确求助?哪些是违规求助? 2908265
关于积分的说明 8345348
捐赠科研通 2578665
什么是DOI,文献DOI怎么找? 1402283
科研通“疑难数据库(出版商)”最低求助积分说明 655381
邀请新用户注册赠送积分活动 634500