Applying Biogeochemistry to Identify the Geographic Origins of Insects-A Model Using Prostephanus truncatus

Barbara Tigar, Andrew Hursthouse

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The application of geochemical screening for tracking insects and other organisms is poorly understood. We explored multi-elemental profiles of an insect pest and its food from different locations in order to identify intrinsic markers of geographic origin.

ICP-AES screening was completed for soil, maize grains and Prostephanus truncatus of different geographic origin, with insects collected in the field or reared on maize under controlled conditions. Background level geochemical data are presented with concentrations of Cu, S and Sr in maize, and Al, Ba, Ca, Fe, S, Si, Sr, Ti and Zn in insects differing according to their origin, or that of their food. Cu, Fe and Zn determinations of insects were 20, 6.5 and 11.5 times the concentrations of the maize they were reared on.

A Linear Discriminant Analysis (LDA) based on Al, Fe, Sr and Zn successfully assigned 78% of laboratory-reared P. truncatus and 94% of field-caught insects to their origin (68% and 75% respectively after jacknifing). There was excellent discrimination between insects reared on maize from Guanajuato and Nuevo Léon, and Guanajuato and Michoacán, good separation between Sonora and Nuevo Léon but overlap for Sonora, Guanajuato and Michoacán, and Michoacán and Nuevo Léon. The same LDA for field-caught insects gave complete separation between Michoacán and Sonora, but some overlap between Michoacán and Nuevo Léon.

This robust ICP-AES technique successfully identified a combination of elements able to classify insects according to their origin. The model was restricted to elements showing a normal distribution but nonparametric tests suggest other elements may act as intrinsic markers. This shows the potential of atomic spectroscopy for remotely tracing insects and other biological materials, with applications including providing provenance data for species routinely captured for surveillance and to track natural enemies and wildlife.
Original languageEnglish
JournalJournal of Environmental Studies
Issue number1
Publication statusPublished - 27 Jan 2016


  • Chemical geolocators
  • PCA: Principal Components Analysis
  • LDA: Linear Discriminate Analysis;
  • ICP-AES: Inductively Coupled Plasma Atomic Emission Spectrometry
  • LGB: Larger Grain Borer
  • RBPH: Rice Brown Plant Hopper


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