Research Article
An E-Nose Using Metal Oxide Semiconductor Sensors Array to Recognize the Odors of Fall Armyworm Pest for Its Early Detection in the Farm
@INPROCEEDINGS{10.1007/978-3-031-23116-2_5, author={Manhougb\^{e} Probus A. F. Kiki and S\'{e}m\'{e}vo Arnaud R. M. Ahouandjinou and Kokou M. Assogba and Yves N. Sama}, title={An E-Nose Using Metal Oxide Semiconductor Sensors Array to Recognize the Odors of Fall Armyworm Pest for Its Early Detection in the Farm}, proceedings={Innovations and Interdisciplinary Solutions for Underserved Areas. 5th EAI International Conference, InterSol 2022, Abuja, Nigeria, March 23-24, 2022, Proceedings}, proceedings_a={INTERSOL}, year={2023}, month={2}, keywords={E-nose Odors recognition Pest monitoring Fall armyworm detection}, doi={10.1007/978-3-031-23116-2_5} }- Manhougbé Probus A. F. Kiki
Sèmèvo Arnaud R. M. Ahouandjinou
Kokou M. Assogba
Yves N. Sama
Year: 2023
An E-Nose Using Metal Oxide Semiconductor Sensors Array to Recognize the Odors of Fall Armyworm Pest for Its Early Detection in the Farm
INTERSOL
Springer
DOI: 10.1007/978-3-031-23116-2_5
Abstract
Considerably decrease hunger and food insecurity in the world is one of sustainable development goals of the horizon 2030. Agriculture, which is one of most countries main sector and the only factor in the diet of the world’s population, is challenged by pest attack. Technology tools offer real opportunities to better protect farms from many damages caused to crops. In this work, an e-nose system using Metal Oxide Semiconductor sensors for early detection of fall armyworm (FAW) pest is proposed. This is based on a special architecture designed to have an affordable and efficient e-nose. Detailed investigations were carried out to identify sensors with potential sensitivity to FAW odors. Then, the sensors were used in a sensor matrix as electronic nose. An electronic acquisition card was achieved to interface the electrical output of the array of seven metal oxide semiconductor gas sensors exposed to an odor diffusion system with the computer. A LabVIEW program was developed for data analysis. The system was successfully exploited to study the response of the sensor array to volatile organic compounds (VOC) released by FAW and for optimizing the data acquisition, as well as signal preprocessing, storage, and wave forms presentation. Experiments were carried out using real FAW. The results and analysis presented in this paper show evidence of discrimination of Fall armyworm’s VOC signature, thus the first detection of FAW presence by e-nose system.
