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Mechanistic modelling for thrips incidence in organic banana

  • This contribution introduces a data acquisition and modelling framework for the prediction of banana pests’ incidence. An IoT sensors-based system collects weather and micro-climate variables, such as temperature, relative humidity, and wind speed, which are uploaded in real time to a cloud storage space. The incidence of the red rust thrips (Chaetanaphothrips signipennis) is collected “manually” by periodic inspection. The mathematical model is adapted from population growth functions and a model of insect species development and allows predictions to be made at various time intervals with an accuracy greater than 80%, improving decision-making capacity for agro-producers and enabling the improvement of pest management actions.

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Author: Jean C. Campos, José Manrique-Silupú, William Ipanaqué, Bogdan DorneanuORCiD, Harvey Arellano-GarciaORCiD
URL:https://www.sciencedirect.com/science/article/abs/pii/B9780323958790500461?via%3Dihub
DOI:https://doi.org/10.1016/B978-0-323-95879-0.50046-1
ISSN:1570-7946
Title of the source (English):Computer Aided Chemical Engineering
Document Type:Scientific journal article peer-reviewed
Language:English
Year of publication:2022
Volume/Year:51
First Page:271
Last Page:276
Faculty/Chair:Fakultät 3 Maschinenbau, Elektro- und Energiesysteme / FG Prozess- und Anlagentechnik
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