| Title: | Asymptomatic Diagnosis of Huanglongbing Disease Using Metalloporphyrin Functionalized Single-Walled Carbon Nanotubes Sensor Arrays |
| Author(s): | Wang H; Ramnani P; Pham T; Villarreal CC; Yu X; Liu G; Mulchandani A; |
| Address: | "Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education and Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture China Agricultural University, Beijing, China. State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China. Department of Chemical and Environmental Engineering and Materials Science and Engineering Program, University of California, Riverside, Riverside, CA, United States. Research Institute of Wood Industry, Chinese Academy of Forestry, Beijing, China. Escuela de Ciencia e Ingenieria de Materiales, Centro de Investigacion y Extension de Materiales, Instituto Tecnologico de Costa Rica, Cartago, Costa Rica" |
| ISSN/ISBN: | 2296-2646 (Print) 2296-2646 (Electronic) 2296-2646 (Linking) |
| Abstract: | "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" |
| Keywords: | artificial neural networks (ANN) carbon nanotube chemiresistor citrus greening disease gas sensor metalloporphyrin volatile organic compounds; |
| Notes: | "PubMed-not-MEDLINEWang, Hui Ramnani, Pankaj Pham, Tung Villarreal, Claudia Chaves Yu, Xuejun Liu, Gang Mulchandani, Ashok eng Switzerland 2020/06/02 Front Chem. 2020 May 12; 8:362. doi: 10.3389/fchem.2020.00362. eCollection 2020" |
