4.6 Article

Asymptomatic Diagnosis of Huanglongbing Disease Using Metalloporphyrin Functionalized Single-Walled Carbon Nanotubes Sensor Arrays

期刊

FRONTIERS IN CHEMISTRY
卷 8, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fchem.2020.00362

关键词

citrus greening disease; carbon nanotube; metalloporphyrin; chemiresistor; volatile organic compounds; artificial neural networks (ANN); gas sensor

资金

  1. United States Department of Agriculture [2014-67021-21589]
  2. Chinese National Natural Science Foundation [31671578]
  3. Key Realm R&D Program of Guangdong Province [2019B020215002, 2019B020215004]
  4. W. Ruel Johnson Chair
  5. NIFA [2014-67021-21589, 687862] Funding Source: Federal RePORTER

向作者/读者索取更多资源

Porphyrins, with or without metal ions (MPs), have been explored and applied in optical and electrochemical sensor fields owing to their special physicochemical properties. The presence of four nitrogen atoms at the centers of porphyrins means that porphyrins chelate most metal ions, which changes the binding ability of MPs with gas molecules via non-specific binding. In this article, we report hybrid chemiresistor sensor arrays based on single-walled carbon nanotubes (SWNTs) non-covalently functionalized with six different MPs using the solvent casting technique. The characteristics of MP-SWNTs were investigated through various optical and electrochemical methods, including UV spectroscopy, Raman, atomic force microscopy, current-voltage (I-V), and field-effect transistor (FET) measurement. The proposed sensor arrays were employed to monitor the four VOCs (tetradecene, linalool, phenylacetaldehyde, and ethylhexanol) emitted by citrus trees infected with Huanglongbing (HLB), of which the contents changed dramatically at the asymptomatic stage. The sensitivity to VOCs could change significantly, exceeding the lower limits of the SWNT-based sensors. For qualitative and quantitative analysis of the four VOCs, the data collected by the sensor arrays were processed using different regression models including partial least squares (PLS) and an artificial neural network (ANN), which further offered a diagnostic basis for Huanglongbing disease at the asymptomatic stage.

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