Section: Mathematical & Computational Biology
Topic: Biophysics and computational biology, Applied mathematics

Biology-Informed inverse problems for insect pests detection using pheromone sensors

Malou, Thibault1 ; Parisey, Nicolas2 ; Adamczyk-Chauvat, Katarzyna1 ; Vergu, Elisabeta1 †; Laroche, Béatrice1, 3 ; Calatayud, Paul-André4, 5 ; Lucas, Philippe6 ; Labarthe, Simon1, 7, 8  
1 Université Paris-Saclay, INRAE, MaIAGE, 78350, Jouy-en-Josas, France
2 INRAE, Institute of Genetics, Environment and Plant Protection (IGEPP—Joint Research Unit 1349), Le Rheu, France
3 Université Paris-Saclay, Inria, 91120, Palaiseau, France
4 Institut de Diversité, Ecologie et Evolution du Vivant (IDEEV), Université Paris-Saclay, CNRS, IRD, UMR Evolution, Génome, Comportement et Ecologie (EGCE), Gif-sur-Yvette, France
5 International Center of Insect Physiology and Ecology (icipe), Nairobi, Kenya
6 Institute of Ecology and Environmental Sciences of Paris (iEES-Paris - Joint Research Unit 1392 - INRAE, CNRS, IRD, Sorbonne Univ., UPEC, Univ. Paris Cité), INRAE, 78000, Versailles, France
7 Univ. Bordeaux, INRAE, BIOGECO, 33610, Cestas, France
8 Univ. Bordeaux, Inria, INRAE, 33400, Talence, France

Corresponding author(s): Labarthe, Simon (simon.labarthe@inrae.fr)

10.24072/pcjournal.520 - Peer Community Journal, Volume 5 (2025), article no. e19.

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Most insects have the ability to modify the odor landscape in order to communicate with their conspecies during key phases of their life cycle such as reproduction. They release pheromones in their nearby environment, volatile compounds that are detected by insects of the same species with exceptional specificity and sensitivity. Efficient pheromone detection is then an interesting lever for insect pest management in a precision agroecological culture context. A precise and early detection of pests using pheromone sensors offers a strategy for pest management before infestation. In this paper, we develop a biology-informed inverse problem framework that leverages temporal signals from a pheromone sensor network to build insect presence maps. Prior biological knowledge is introduced in the inverse problem by the mean of a specific penalty, using population dynamics PDE residuals. We benchmark the biological-informed penalty with other regularization terms such as Tikhonov, LASSO or composite penalties in a simplified toy model. We use classical comparison criteria, such as target reconstruction error, or Jaccard distance on pest presence-absence. But we also use more task-specific criteria such as the number of informative sensors during inference. Finally, the inverse problem is solved in a realistic context of pest infestation in an agricultural landscape by the fall armyworm (Spodoptera frugiperda).

Published online:
DOI: 10.24072/pcjournal.520
Type: Research article
Mots-clés : Inverse problem, Data assimilation, Biology-informed estimation, PDE, Pest detection, Pheromone

Malou, Thibault 1; Parisey, Nicolas 2; Adamczyk-Chauvat, Katarzyna 1; Vergu, Elisabeta 1; Laroche, Béatrice 1, 3; Calatayud, Paul-André 4, 5; Lucas, Philippe 6; Labarthe, Simon 1, 7, 8

1 Université Paris-Saclay, INRAE, MaIAGE, 78350, Jouy-en-Josas, France
2 INRAE, Institute of Genetics, Environment and Plant Protection (IGEPP—Joint Research Unit 1349), Le Rheu, France
3 Université Paris-Saclay, Inria, 91120, Palaiseau, France
4 Institut de Diversité, Ecologie et Evolution du Vivant (IDEEV), Université Paris-Saclay, CNRS, IRD, UMR Evolution, Génome, Comportement et Ecologie (EGCE), Gif-sur-Yvette, France
5 International Center of Insect Physiology and Ecology (icipe), Nairobi, Kenya
6 Institute of Ecology and Environmental Sciences of Paris (iEES-Paris - Joint Research Unit 1392 - INRAE, CNRS, IRD, Sorbonne Univ., UPEC, Univ. Paris Cité), INRAE, 78000, Versailles, France
7 Univ. Bordeaux, INRAE, BIOGECO, 33610, Cestas, France
8 Univ. Bordeaux, Inria, INRAE, 33400, Talence, France
License: CC-BY 4.0
Copyrights: The authors retain unrestricted copyrights and publishing rights 
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     title = {Biology-Informed inverse problems for insect pests detection using pheromone sensors},
     journal = {Peer Community Journal},
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Malou, Thibault; Parisey, Nicolas; Adamczyk-Chauvat, Katarzyna; Vergu, Elisabeta; Laroche, Béatrice; Calatayud, Paul-André; Lucas, Philippe; Labarthe, Simon. Biology-Informed inverse problems for insect pests detection using pheromone sensors. Peer Community Journal, Volume 5 (2025), article  no. e19. doi : 10.24072/pcjournal.520. https://peercommunityjournal.org/articles/10.24072/pcjournal.520/

PCI peer reviews and recommendation, and links to data, scripts, code and supplementary information: 10.24072/pci.mcb.100313

Conflict of interest of the recommender and peer reviewers:
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article.

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