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DNA sequencing to help identify crop pests and their natural enemies in agro-ecosystems: The case of the millet head miner Heliocheilus albipunctella (Lepidoptera: Noctuidae) in sub-Saharan Africa

Sow A., Brévault T., Delvare G., Haran J., Benoit L., Coeur d'Acier A., Galan M., Thiaw C., Soti V., Sembène M.. 2018. Biological Control, 121 : p. 199-207.

DOI: 10.1016/j.biocontrol.2018.03.007

Better knowledge of natural enemy communities and their relative contribution to biological control is needed to design ecology-based pest management in agro-ecosystems. Here, we investigated the arthropod communities of pearl millet-based agro-ecosystems in sub-Saharan Africa (Senegal), with a focus on natural enemies of the millet head miner (MHM), Heliocheilus albipunctella (de Joannis). A set of 105 millet fields was monitored over the 2014¿2016 growing seasons. Arthropods were sampled at three successive phenological stages, from panicle emergence to grain maturity. Eggs and larvae from Lepidoptera pests were collected to assess their identity and relative contribution to the biological control of parasitoids. Morphological identification combined with Sanger and Illumina DNA sequencing, using the COI full barcode (658¿bp) and the COI mini-barcode (133¿bp) respectively, was carried out to characterize arthropod samples. MHM was by far the main herbivore on millet, with a relative abundance of 97%. Predators were mostly ants (28%), earwigs (Forficula senegalensis, 26%), mirids (20%), spiders (12%), carabid larvae (7%), flower bugs (Orius maxidentex, 6%), and ladybirds (Declivitata hamata, 1%). In all, 13 primary parasitoid species were collected, including five new species. Parasitism was dominated by three key species, including Trichogrammatoidea armigera (12.4% of egg parasitism), Copidosoma primulum and Schoelandella spp. (46 and 32% of larval parasitism, respectively). A primary reference database including standard and mini-barcode sequences of specimens attributed to species (15) was designed as a reliable tool for assisting arthropod identification. The results will be helpful when selecting candidates for augmentative biological control in millet-based agro-ecosystems in sub-Saharan Africa.

Mots-clés : sénégal

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