Breedbase: a digital ecosystem for modern plant breeding

Modern breeding methods integrate next-generation sequencing (NGS) and phenomics to identify plants with the best characteristics and greatest genetic merit for use as parents in subsequent breeding cycles to ultimately create improved cultivars able to sustain high adoption rates by farmers. This d...

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Autores principales:	Morales, Nicolas, Ogbonna, Alex C., Ellerbrock, Bryan J., Bauchet, Guillaume J., Tantikanjana, Titima, Tecle, Isaak Y., Powell, Adrian F., Lyon, David, Menda, Naama, Simoes, Christiano C., Saha, Surya, Hosmani, Prashant, Flores, Mirella, Panitz, Naftali, Preble, Ryan S., Agbona, Afolabi, Rabbi, Ismail, Kulakow, Peter A., Peteti, Prasad, Kawuki, Robert, Esuma, Williams, Kanaabi, Micheal, Chelangat, Doreen M., Uba, Ezenwanyi, Olojede, Adeyemi, Onyeka, Joseph, Shah, Trushar, Karanja, Margaret, Egesi, Chiedozie N., Tufan, Hale Ann, Paterne, Agre, Asfaw, Asrat, Jannink, Jean-Luc, Wolfe, Marnin, Birkett, Clay L., Waring, David J., Hershberger, Jenna M., Gore, Michael A., Robbins, Kelly R., Rife, Trevor, Courtney, Chaney, Poland, Jesse A., Arnaud, Elizabeth, Laporte, Marie-Angélique, Kulembeka, Heneriko, Salum, Kasele, Mrema, Emmanuel, Brown, Allan, Bayo, Stanley, Uwimana, Brigitte, Akech, Violet, Yencho, Craig, Boeck, Bert de, Campos, Hugo, Swennen, Rony L., Edwards, Jeremy D., Mueller, Lukas A.
Formato:	Journal Article
Lenguaje:	Inglés
Publicado:	Oxford University Press 2022
Materias:	data databases breeding phenotypes genotyping marker-assisted selection digital technology mejora fenotipos
Acceso en línea:	https://hdl.handle.net/10568/119327