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Coupling computational vibrational models and experimental biotremology to develop a green pest control strategy against the greenhouse whitefly Trialeurodes vaporariorum

Berardo, Alice; Fattoruso, Valeria; Mazzoni, Valerio and Pugno, Nicola (2022) Coupling computational vibrational models and experimental biotremology to develop a green pest control strategy against the greenhouse whitefly Trialeurodes vaporariorum. Journal of the Royal Society Interface, 19, p. 2022311.

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Document available online at: https://royalsocietypublishing.org/doi/10.1098/rsif.2022.0311


Summary in the original language of the document

In applied biotremology, vibrational signals or cues are exploited to manipulate the target species behaviour. To develop an efficient pest control strategy, other than a detailed investigation into the pest biology and behaviour, the role of the substrate used to transmit the signal is an important feature to be considered, since it may affect vibrations spreading and effective signal transmission and perception. Therefore, we used a multi-disciplinary approach to develop a control technique against the greenhouse whitefly, Trialeurodes vaporariorum. First, an ad hoc vibrational disruptive noise has been developed, based on the acquired knowledge about the mating behaviour and vibrational communication of the mated species. Subsequently, we employed finite-element models to investigate a growing tomato plant response to the aforesaid noise. Modelling how vibrations spread along the plant allowed us to set up a greenhouse experiment to assess the efficacy in terms of insect population of the vibrational treatment, which was administrated through vibrational plates. The green methodology applied in this study represents an innovative, environmentally sound alternative to the usage of synthetic pesticides.


EPrint Type:Journal paper
Agrovoc keywords:
Language
Value
URI
English
Biotremology
UNSPECIFIED
UNSPECIFIED
Finite elements models
UNSPECIFIED
Subjects: Crop husbandry > Crop health, quality, protection
Research affiliation: European Union > Horizon 2020 > RELACS
Horizon Europe or H2020 Grant Agreement Number:773431
ISSN:1742-5662
DOI:10.1098/rsif.2022.0311
Deposited By: Mazzoni, Dr Valerio
ID Code:44542
Deposited On:04 Nov 2022 12:38
Last Modified:04 Nov 2022 12:38
Document Language:English
Status:Published
Refereed:Peer-reviewed and accepted

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