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An E-Nose Using Metal Oxide Semiconductor Sensors Array to Recognize the Odors of Fall Armyworm Pest for Its Early Detection in the Farm

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Innovations and Interdisciplinary Solutions for Underserved Areas (InterSol 2022)

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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.

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Acknowledgement

The authors would like to thank International Institute of Tropical Agriculture (IITA) of Benin Republic for its helpful assistance during the experimental work. Especially for the stock farming of the fall armyworm pest. Without it, this work could not be achieved.

Author information

Authors and Affiliations

  1. Ecole Polytechnique d’Abomey-Calavi, Université d’Abomey-Calavi, Cotonou, Bénin

    Manhougbé Probus A. F. Kiki & Kokou M. Assogba

  2. Institut de Formation et de Recherche en Informatique, Université d’Abomey-Calavi, Cotonou, Bénin

    Sèmèvo Arnaud R. M. Ahouandjinou

  3. Institut Lafayette, 2 Rue Marconi, 57070, Metz, France

    Yves N. Sama

Authors
  1. Manhougbé Probus A. F. Kiki
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  2. Sèmèvo Arnaud R. M. Ahouandjinou
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  3. Kokou M. Assogba
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  4. Yves N. Sama
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Corresponding author

Correspondence to Manhougbé Probus A. F. Kiki .

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Editors and Affiliations

  1. Nile University of Nigeria, Abuja, Nigeria

    Abdulhameed Danjuma Mambo

  2. Carnegie Mellon University Africa, Kigali, Rwanda

    Assane Gueye

  3. Ain Shams University, Cairo, Egypt

    Ghada Bassioni

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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Kiki, M.P.A.F., Ahouandjinou, S.A.R.M., Assogba, K.M., Sama, Y.N. (2022). An E-Nose Using Metal Oxide Semiconductor Sensors Array to Recognize the Odors of Fall Armyworm Pest for Its Early Detection in the Farm. In: Mambo, A.D., Gueye, A., Bassioni, G. (eds) Innovations and Interdisciplinary Solutions for Underserved Areas. InterSol 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 449. Springer, Cham. https://doi.org/10.1007/978-3-031-23116-2_5

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  • DOI: https://doi.org/10.1007/978-3-031-23116-2_5

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-23116-2

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