Parcourir par Mots clés libres

Regression methods for prediction. Part I Mixed model and regularization methods. Part II Bayesian approaches. Garin Vincent. 2024. Montpellier : CIRAD, 2 diaporamas (102 vues, 83 vues)

Revisiting superiority and stability metrics of cultivar performances using genomic data: Derivations of new estimators. Carvalho Fanelli Humberto, Rio Simon, García-Abadillo Julian, Isidro y Sánchez Julio. 2024. Plant Methods, 20:85, 16 p.

Performance of phenomic selection in sorghum: Exploring population structure and GXE effects on prediction accuracy. Salas Nicolas, Garin Vincent, Thera Korothimi, Diallo Chiaka, Tekete Mohamed Lamine, Guitton Baptiste, Dagno Karim, Diallo Abdoulaye, Kouressy Mamoutou, Leiser Willmar L., Rattunde Fred, Sissoko Ibrahima, Touré Aboubacar, Baloua Nébié, Samaké Moussa, Kholova Jana, Frouin Julien, Vaksmann Michel, Weltzien Eva, Témé Niaba, Rami Jean-François, Segura Vincent, Pot David. 2023. In : Sorghum in the 21st century: Resiliency and sustainability in the face of climate change. Book of abstracts. CIRAD, Kansas State University, Collaborative Research on Sorghum and Millet, SorghumID, IRD, CERAAS. Montpellier : CIRAD-Kansas State University, Résumé, p. 115. Sorghum in the 21st Century, Global Sorghum Conference, Montpellier, France, 5 Juin 2023/9 Juin 2023.

A comparative analysis of genomic and phenomic predictions of growth-related traits in three-way coffee hybrids. Mbebi Alain J., Breitler Jean-Christophe, Bordeaux Mélanie, Sulpice Ronan, McHale Marcus, Hao Tong, Toniutti Lucile, Alonso Castillo Jonny, Bertrand Benoît, Nikoloski Zoran. 2022. G3 - Genes Genomes Genetics, 12 (9):jkac170, 14 p.

A divide-and-conquer approach for genomic prediction in rubber tree using machine learning. Hild Aono Alexandre, Francisco Felipe Roberto, Moura Souza Livia, De Souza Gonçalves Paulo, Scaloppi Junior Erivaldo José, Le Guen Vincent, Fritsche-Neto Roberto, Gorjanc Gregor, Gonçalves Quiles Marcos, Pereira de Souza Anete. 2022. Scientific Reports, 12:18023, 14 p.

Breeding for nitrogen use efficiency: Lessons from genomic prediction experiments based on a broad-based population of upland rice. Rakotomalala Joël, Vom Brocke Kirsten, Frouin Julien, Pot David, Rabekijana Ravonantenaina Rhodia, Ramanantsoanirina Alain, Ratsimiala Ramonta Isabelle, Cao Tuong-Vi. 2021. Rice Research: Open Access, 9 (9):1000264, 26 p.

Genomic selection and genome-wide association study for feed-efficiency traits in a farmed Nile tilapia (Oreochromis niloticus) population. Barria Augustin, Benzie John A.H., Houston Ross D., De Koning Dirk-Jan, De Verdal Hugues. 2021. Frontiers in Genetics, 12:737906, 13 p.

Impact of early genomic prediction for recurrent selection in an upland rice synthetic population. Baertschi Cédric, Cao Tuong-Vi, Bartholome Jérôme, Ospina Yolima, Quintero Constanza, Frouin Julien, Bouvet Jean-Marc, Grenier Cécile. 2021. G3 - Genes Genomes Genetics, 11 (12):jkab320, 16 p.

Integration of genomics with crop modeling for predicting rice days to flowering: A multi-model analysis. Yang Yubin, Wilson Lloyd Ted, Li Tao, Paleari Livia, Confalonieri Roberto, Zhu Yan, Tang Liang, Qiu Xiaolei, Tao Fulu, Chen Yi, Hoogenboom Gerrit, Boote Ken, Gao Yujing, Onogi Akio, Nakagawa Hiroshi, Yoshida Hiroe, Yabe Shiori, Dingkuhn Michael, Lafarge Tanguy, Wang Jing, Hasegawa Toshihiro. 2021. Field Crops Research, 276:108394, 15 p.

Optimizing imputation of marker data from genotyping-by-sequencing (GBS) for genomic selection in non-model species: Rubber tree (Hevea brasiliensis) as a case study. Munyengwa Norman, Le Guen Vincent, Ngalle Bille Hermine, Souza Livia Moura, Clément-Demange André, Mournet Pierre, Masson Aurélien, Soumahoro Mouman, Kouassi Daouda, Cros David. 2021. Genomics, 113 (2) : 655-668.