Skip navigation

Analytical methods for detecting pesticide switches with evolution of pesticide resistance

Analytical methods for detecting pesticide switches with evolution of pesticide resistance

Liang, Juhua, Tang, Sanyi, Nieto, Juan J. and Cheke, Robert A. (2013) Analytical methods for detecting pesticide switches with evolution of pesticide resistance. Mathematical Biosciences, 245 (2). pp. 249-257. ISSN 0025-5564 (Print), 1879-3134 (Online) (doi:10.1016/j.mbs.2013.07.008)

[img]
Preview
PDF
LiangEtAl2013PesticideSwitchesMathBioSci.pdf

Download (1MB)

Abstract

After a pest develops resistance to a pesticide, switching between different unrelated pesticides is a common management option, but this raises the following questions: (1) What is the optimal frequency of pesticide use? (2) How do the frequencies of pesticide applications affect the evolution of pesticide resistance? (3) How can the time when the pest population reaches the economic injury level (EIL) be estimated and (4) how can the most efficient frequency of pesticide applications be determined? To address these questions, we have developed a novel pest population growth model incorporating the evolution of pesticide resistance and pulse spraying of pesticides. Moreover, three pesticide switching methods, threshold condition-guided, density-guided and EIL-guided, are modelled, to determine the best choice under different conditions with the overall aim of eradicating the pest or maintaining its population density below the EIL. Furthermore, the pest control outcomes based on those three pesticide switching methods are discussed. Our results suggest that either the density-guided or EIL-guided method is the optimal pesticide switching strategy, depending on the frequency (or period) of pesticide applications.

Item Type: Article
Uncontrolled Keywords: Pesticide switches, Dynamic threshold, Pesticide application frequency, Evolution, Pulse spraying
Subjects: S Agriculture > S Agriculture (General)
S Agriculture > SB Plant culture
Faculty / Department / Research Group: Faculty of Engineering & Science > Natural Resources Institute > Agriculture, Health & Environment Department
Faculty of Engineering & Science > Natural Resources Institute
Last Modified: 27 Apr 2016 17:56
URI: http://gala.gre.ac.uk/id/eprint/10292

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics