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

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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Autores principales:	C. Martinez-Martinez, C. Somoza-Vargas
Formato:	article
Lenguaje:	EN
Publicado:	Universidad Nacional Agraria La Molina 2019
Materias:	pest management applied software population prediction entomology Agriculture (General) S1-972
Acceso en línea:	https://doaj.org/article/a3fbf3bf614445fb927719b3626f7be1
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spelling	oai:doaj.org-article:a3fbf3bf614445fb927719b3626f7be12021-12-04T17:36:08ZA Simple and Rapid Algorithm for Predicting Froghopper (Aeneolamia spp.) Population Increase in Sugarcane Fields based on Temperature and Relative Humidity2616-447710.21704/pja.v3i2.1314https://doaj.org/article/a3fbf3bf614445fb927719b3626f7be12019-08-01T00:00:00Zhttps://revistas.lamolina.edu.pe/index.php/jpagronomy/article/view/1314https://doaj.org/toc/2616-4477In 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/viewC. Martinez-MartinezC. Somoza-VargasUniversidad Nacional Agraria La Molinaarticlepest managementapplied softwarepopulation predictionentomologyAgriculture (General)S1-972ENPeruvian Journal of Agronomy, Vol 3, Iss 2, Pp 47-56 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	pest management applied software population prediction entomology Agriculture (General) S1-972
spellingShingle	pest management applied software population prediction entomology Agriculture (General) S1-972 C. Martinez-Martinez C. Somoza-Vargas A Simple and Rapid Algorithm for Predicting Froghopper (Aeneolamia spp.) Population Increase in Sugarcane Fields based on Temperature and Relative Humidity
description	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
format	article
author	C. Martinez-Martinez C. Somoza-Vargas
author_facet	C. Martinez-Martinez C. Somoza-Vargas
author_sort	C. Martinez-Martinez
title	A Simple and Rapid Algorithm for Predicting Froghopper (Aeneolamia spp.) Population Increase in Sugarcane Fields based on Temperature and Relative Humidity
title_short	A Simple and Rapid Algorithm for Predicting Froghopper (Aeneolamia spp.) Population Increase in Sugarcane Fields based on Temperature and Relative Humidity
title_full	A Simple and Rapid Algorithm for Predicting Froghopper (Aeneolamia spp.) Population Increase in Sugarcane Fields based on Temperature and Relative Humidity
title_fullStr	A Simple and Rapid Algorithm for Predicting Froghopper (Aeneolamia spp.) Population Increase in Sugarcane Fields based on Temperature and Relative Humidity
title_full_unstemmed	A Simple and Rapid Algorithm for Predicting Froghopper (Aeneolamia spp.) Population Increase in Sugarcane Fields based on Temperature and Relative Humidity
title_sort	simple and rapid algorithm for predicting froghopper (aeneolamia spp.) population increase in sugarcane fields based on temperature and relative humidity
publisher	Universidad Nacional Agraria La Molina
publishDate	2019
url	https://doaj.org/article/a3fbf3bf614445fb927719b3626f7be1
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A Simple and Rapid Algorithm for Predicting Froghopper (Aeneolamia spp.) Population Increase in Sugarcane Fields based on Temperature and Relative Humidity

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