A Simple and Rapid Algorithm for Predicting Froghopper (Aeneolamia spp.) Population Increase in Sugarcane Fields based on Temperature and Relative Humidity

Descripción del Articulo

In Integrated Pest Management practices, knowledge from multiple disciplines is incorporated to facilitate the understanding of a problem and the development a practical, feasible, and ecologically sustainable solution. A froghopper (Aeneolamia spp.) plague can trigger major economic losses in sugar...

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Detalles Bibliográficos
Autores: Martinez-Martinez, C., Somoza-Vargas, C.
Formato: artículo
Fecha de Publicación:2019
Institución:Universidad Nacional Agraria La Molina
Repositorio:Revistas - Universidad Nacional Agraria La Molina
Lenguaje:inglés
OAI Identifier:oai:revistas.lamolina.edu.pe:article/1314
Enlace del recurso:https://revistas.lamolina.edu.pe/index.php/jpagronomy/article/view/1314
Nivel de acceso:acceso abierto
Materia:Pest management
applied software
population prediction
entomology
Descripción
Sumario:In Integrated Pest Management practices, knowledge from multiple disciplines is incorporated to facilitate the understanding of a problem and the development a practical, feasible, and ecologically sustainable solution. A froghopper (Aeneolamia spp.) plague can trigger major economic losses in sugarcane plantations in countries such as El Salvador and others in Latin America. Losses are often due to a lack of understanding of the life cycle of a pest and the underestimation of its annual reproductive potential. An algorithm was developed to model the most relevant aspects of froghopper reproduction and its interactions with the environment, to facilitate the prediction of potential increases in adult populations and its propagation in fields. Data on several biological variables were collected as numerical measures and used to perform calculations based on a mathematical model designed particularly to simulate the reproduction of the pest, its economic threshold, and potential losses due to major natural events, with the aim of developing a tool that could support decision-making. The predictions of the tool were consistent with the findings of other studies in the field. The software and its installation instructions can be downloaded for free from https://drive.google.com/file/d/1oUWTTbi lWMhoFuTH4wCKtuzjFwDd89/view
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