4.7 Article

Rapid Identification of Aphid Species by Headspace GC-MS and Discriminant Analysis

Journal

INSECTS
Volume 14, Issue 7, Pages -

Publisher

MDPI
DOI: 10.3390/insects14070589

Keywords

pest; chemotaxonomy; aphid; Taif Governate; CAP analysis; GC-MS headspace; closed-loop stripping

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A new method using chemical profiles to identify aphid species has been developed. This method is faster and less laborious compared to traditional DNA analysis.
Simple Summary Aphids are small insects that damage plants by sucking plant phloem sap. Aphids cause severe losses to agriculture. In order to control aphids by environmentally friendly methods, it is necessary to identify them. Identification of aphids is difficult because there are ca. 5000 species which undergo different life stages and vary much in appearance (e.g., coloration). Here, we presented a novel method to determine aphid species using their chemical profiles. There are compounds (biomarkers) that are characteristic for a particular aphid species like a fingerprint. After grinding aphids, the released compounds were collected and the compound mixtures were separated by gas chromatography connected to a mass spectrometer to identify the individual compounds. The obtained compound profiles were subjected to the software CAP12.exe to reveal the biomarkers from the headspace profiles for each aphid species. It was possible to reliably differentiate aphid species using our approach. Compared to the established identification of aphids that uses characteristic DNA sequences from their genome, using the chemical biomarkers is much less laborious and faster. Moreover, it is possible with the chemical profile analysis to reveal other aspects of an aphid's life history such as the food plant it fed on. Aphids are a ubiquitous group of pests in agriculture that cause serious losses. For sustainable aphid identification, it is necessary to develop a precise and fast aphid identification tool. A new simple chemotaxonomy approach to rapidly identify aphids was implemented. The method was calibrated in comparison to the established phylogenetic analysis. For chemotaxonomic analysis, aphids were crushed, their headspace compounds were collected through closed-loop stripping (CLS) and analysed using gas chromatography-mass spectrometry (GC-MS). GC-MS data were then subjected to a discriminant analysis using CAP12.exe software, which identified key biomarkers that distinguish aphid species. A dichotomous key taking into account the presence and absence of a set of species-specific biomarkers was derived from the discriminant analysis which enabled rapid and reliable identification of aphid species. As the method overcomes the limits of morphological identification, it works with aphids at all life stages and in both genders. Thus, our method enables entomologists to assign aphids to growth stages and identify the life history of the investigated aphids, i.e., the food plant(s) they fed on. Our experiments clearly showed that the method could be used as a software to automatically identify aphids.

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