Sensing of Airborne Infochemicals for Green Pest Management: What Is the Challenge? - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
Article Dans Une Revue ACS Sensors Année : 2022

Sensing of Airborne Infochemicals for Green Pest Management: What Is the Challenge?

Résumé

One of the biggest global challenges for our societies is to provide natural resources to the rapidly expanding population while maintaining sustainable and ecologically friendly products. The increasing public concern about toxic insecticides has resulted in the rapid development of alternative techniques based on natural infochemicals (ICs). ICs (e.g., pheromones, allelochemicals, volatile organic compounds) are secondary metabolites produced by plants and animals and used as information vectors governing their interactions. Such chemical language is the primary focus of chemical ecology, where behavior-modifying chemicals are used as tools for green pest management. The success of ecological programs highly depends on several factors, including the amount of ICs that enclose the crop, the range of their diffusion, and the uniformity of their application, which makes precise detection and quantification of ICs essential for efficient and profitable pest control. However, the sensing of such molecules remains challenging, and the number of devices able to detect ICs in air is so far limited. In this review, we will present the advances in sensing of ICs including biochemical sensors mimicking the olfactory system, chemical sensors, and sensor arrays (e-noses). We will also present several mathematical models used in integrated pest management to describe how ICs diffuse in the ambient air and how the structure of the odor plume affects the pest dynamics.
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Dates et versions

hal-03611845 , version 1 (17-03-2022)

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Petra Ivaskovic, Bedr’eddine Ainseba, Yohann Nicolas, Thierry Toupance, Pascal Tardy, et al.. Sensing of Airborne Infochemicals for Green Pest Management: What Is the Challenge?. ACS Sensors, 2022, 6 (11), pp.3824-3840. ⟨10.1021/acssensors.1c00917⟩. ⟨hal-03611845⟩
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