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Preliminary genetic characterization of fall armyworm Spodoptera frugiperda from maize fields in Cabo Verde
* 1 , 2 , 3 , 4 , * 5
1  LEAF, Linking Landscape, Environment, Agriculture and Food Research Center, Associated Laboratory TERRA, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal; DGASP-MAA - General Direction of Agriculture, Forestry and Li
2  LEAF, Linking Landscape, Environment, Agriculture and Food Research Center, Associated Laboratory TERRA, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal; CE3C, Centre for Ecology, Evolution and and Environmental Cha
3  LEAF, Linking Landscape, Environment, Agriculture and Food Research Center, Associated Laboratory TERRA, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal.
4  CEF, Forest Research Centre, Associated Laboratory TERRA, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal
5  LEAF, Linking Landscape, Environment, Agriculture and Food Research Center, Associated Laboratory TERRA, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal; CE3C, Centre for Ecology, Evolution and Environmental Changes
Academic Editor: David Haymer

Abstract:

The fall armyworm Spodoptera frugiperda (Lepidoptera: Noctuidae), an invasive pest in West Africa, threatens agricultural production in the region. Accurate identification and genetic diversity assessment are crucial for developing effective management strategies. This study aimed to characterize the S. frugiperda population, identify its strain diversity in maize fields across Cabo Verde, and investigate potential introduction routes within the archipelago.

Specimens were collected from maize fields in two agroecological zones on Santiago Island, as well as from other islands in Cabo Verde and multiple West and Central African countries. DNA barcoding of the cytochrome oxidase I (COI) gene was performed by means of PCR amplification using universal primers. Sequences were obtained using sanger sequencing, edited, and supplemented with reference sequence data from the NCBI and BOLD databases. Then, a phylogenetic analysis using the Maximum Likelihood method was carried out in MEGA with 1000 bootstrap analyses.

The preliminary genetic analysis revealed the strain variability in S. frugiperda populations across Cabo Verde, with evidence of Rice- and Corn-strain overlap on maize fields. The phylogenetic analysis suggested a complex species diversity and possible hybridization, warranting further investigation.

These findings emphasize the need for extending sample collection to assess the progeny of each strain and its implications for S. frugiperda's population dynamics. Understanding the genetic composition of predominant strains will contribute to the development of targeted pest management strategies.

Keywords: DNA barcoding, strain differentiation, genotypic variability, agroecology
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