Genomic Prediction of Complex Traits in Forage Plants Species:Perennial Grasses Case

Autor: Philippe Barre, Torben Asp, Stephen Byrne, Michael Casler, Marty Faville, Odd Arne Rognli, Isabel Roldan-Ruiz, Leif Skøt, Marc Ghesquière

Publikováno v: Barre, P, Asp, T, Byrne, S, Casler, M, Faville, M, Rognli, O A, Roldan-Ruiz, I, Skøt, L & Ghesquière, M 2022, Genomic Prediction of Complex Traits in Forage Plants Species : Perennial Grasses Case . in Methods in Molecular Biology . Humana Press Inc, Methods in Molecular Biology, vol. 2467, pp. 521-541 . https://doi.org/10.1007/978-1-0716-2205-6_19
Methods in Molecular Biology ISBN: 9781071622049

The majority of forage grass species are obligate outbreeders. Their breeding classically consists of an initial selection on spaced plants for highly heritable traits such as disease resistances and heading date, followed by familial selection on sw

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e21a6aeddf7909156917f4168876185a
https://pure.au.dk/portal/da/publications/genomic-prediction-of-complex-traits-in-forage-plants-species(ca89c077-4996-4903-96e2-39dc958d9ec6).html

Flemish soils contain rhizobia partners for Northwestern Europe-adapted soybean cultivars

Autor: Judith Van Dingenen, Sonia Garcia Mendez, Stien Beirinckx, Lena Vlaminck, Annick De Keyser, Naomi Stuer, Severine Verschaete, Alexander Clarysse, Joke Pannecoucque, Stephane Rombauts, Isabel Roldan‐Ruiz, Anne Willems, Sofie Goormachtig

Publikováno v: ENVIRONMENTAL MICROBIOLOGY

In Europe, soybean (Glycine max) used for food and feed has to be imported, causing negative socioeconomic and environmental impacts. To increase the local production, breeding generated varieties that grow in colder climates, but the yield using the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10af1240832311cc7e7a80192e9bea9c
https://pubmed.ncbi.nlm.nih.gov/35212122

Quantification of species composition in grass-clover swards using RGB and multispectral UAV imagery and machine learning

Autor: Joanna Pranga, Irene Borra-Serrano, Paul Quataert, Tom De Swaef, Thijs Vanden Nest, Koen Willekens, Greet Ruysschaert, Ivan A. Janssens, Isabel Roldán-Ruiz, Peter Lootens

Publikováno v: Frontiers in Plant Science, Vol 15 (2024)

IntroductionGrowing grass-legume mixtures for forage production improves both yield productivity and nutritional quality, while also benefiting the environment by promoting species biodiversity and enhancing soil fertility (through nitrogen fixation)

Externí odkaz: https://doaj.org/article/0396b56a49714fec921b0d46068d28de

Phenotypic characterization of drought responses in red clover (Trifolium pratense L.)

Autor: Tim Vleugels, Aamir Saleem, Reena Dubey, Hilde Muylle, Irene Borra-Serrano, Peter Lootens, Tom De Swaef, Isabel Roldán-Ruiz

Publikováno v: Frontiers in Plant Science, Vol 14 (2024)

IntroductionRed clover (Trifolium pratense) is a protein-rich, short-lived perennial forage crop that can achieve high yields, but suffers increasingly from drought in different cultivation areas. Breeding for increased adaptation to drought is becom

Externí odkaz: https://doaj.org/article/cbbbbe328e984b9cba81a535753286c3

Quaternary climate changes explain the current genetic variation in a major European grassland species, Lolium perenne

Autor: José Luis Blanco-Pastor, Stéphanie Manel, Philippe Barre, Roschanski, Anna M., Evelin Willner, Dehmer, Klaus J., Matthew Hegarty, Hilde Muylle, Tom Ruttink, Isabel Roldan-Ruiz, Thomas Ledauphin, Jean-Paul Sampoux

Publikováno v: 26. International Plant and Animal Genome Conference (PAG)
26. International Plant and Animal Genome Conference (PAG), Jan 2018, San Diego, United States
HAL

International audience; Grasslands have been pivotal in the development of domestic herbivore breeding since the Neolithic and are nowadays the most widespread agricultural land-use over Europe. We have demonstrated that the genealogy of natural Loli

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::4bce12a46cdeae8a12bcc79c3b4154ed
https://hal.inrae.fr/hal-02789621