The ECPGR European Evaluation Network (EVA) for Maize involves genebanks, research institutions, and private breeding companies from nine countries focusing on the valorization of maize genetic resources across Europe. This study describes a diverse collection of 626 local landraces and traditional varieties of maize (Zea mays L.) from nine European genebanks, including criteria for selection of the collection and its genetic and phenotypic diversity. High-throughput pool genotyping grouped the landraces into nine genetic groups with a threshold of 0.6 admixture, while 277 accessions were designated admixed and likely to have resulted from previous breeding activities. The grouping correlated well with the geographic origins of the collection, also reflecting the various pathways of introduction of maize to Europe. Phenotypic evaluations of 588 accessions for flowering time and plant architecture in multilocation trials over three years confirmed the great diversity within the collection, although phenotypic clusters only partially correlated with the genetic grouping. The EVA approach promotes conservation of genetic resources and opens an opportunity to increase genetic variability for developing improved varieties and populations for farmers, with better adaptation to specific environments and greater tolerance to various stresses. As such, the EVA maize collection provides valuable sources of diversity for facing climate change due to the varieties’ local adaptation.
Balconi C., Galaretto A., Ana Malvar R., Nicolas S. D., Redaelli R., Andjelkovic V., Revilla P., Bauland C., Gouesnard B., Butron A., Torri A., Barata A. M., Kravic N., Combes V., Mendes-Moreira P., Murariu D., Šarčević H., Schierscher-Viret B., Vincent M., Zanetto A., Kessel B., Madur D., Mary-Huard T., Pereira A., Placinta D. D., Strigens A., Charcosset A., Goritschnig S.
Genetic and phenotypic evaluation of European maize landraces as a tool for conservation and valorization of agrobiodiversity.
Biology, 13, (6), 2024, 1-25.
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ISSN Online: 2079-7737
Digital Object Identifier (DOI): https://doi.org/10.3390/biology13060454
Publikations-ID (Webcode): 56888 Per E-Mail versenden
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