Zobrazeno 1 - 10
of 209
pro vyhledávání: '"Osval A. Montesinos‐López"'
Autor:
Osval A. Montesinos-López, Andrew W. Herr, José Crossa, Abelardo Montesinos-López, Arron H. Carter
Publikováno v:
BMC Genomics, Vol 25, Iss 1, Pp 1-20 (2024)
Abstract In the realm of multi-environment prediction, when the goal is to predict a complete environment using the others as a training set, the efficiency of genomic selection (GS) falls short of expectations. Genotype by environment interaction po
Externí odkaz:
https://doaj.org/article/4b2aae55b0d241e186835e1b8a1959e9
Autor:
Osval A. Montesinos-López, Paolo Vitale, Guillermo Gerard, Leonardo Crespo-Herrera, Carolina Saint Pierre, Abelardo Montesinos-López, José Crossa
Publikováno v:
Plants, Vol 13, Iss 21, p 3059 (2024)
In plant breeding, Multi-Environment Trials (METs) evaluate candidate genotypes across various conditions, which is financially costly due to extensive field testing. Sparse testing addresses this challenge by evaluating some genotypes in selected en
Externí odkaz:
https://doaj.org/article/d92f47320ce94e98bc3684db0df4ea9d
Autor:
Osval A. Montesinos-López, Leonardo Crespo-Herrera, Carolina Saint Pierre, Bernabe Cano-Paez, Gloria Isabel Huerta-Prado, Brandon Alejandro Mosqueda-González, Sofia Ramos-Pulido, Guillermo Gerard, Khalid Alnowibet, Roberto Fritsche-Neto, Abelardo Montesinos-López, José Crossa
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
IntroductionBecause Genomic selection (GS) is a predictive methodology, it needs to guarantee high-prediction accuracies for practical implementations. However, since many factors affect the prediction performance of this methodology, its practical i
Externí odkaz:
https://doaj.org/article/bc352c418ea44b3aa88d1cf294b125fa
Partial least squares enhance multi-trait genomic prediction of potato cultivars in new environments
Autor:
Rodomiro Ortiz, Fredrik Reslow, Abelardo Montesinos-López, José Huicho, Paulino Pérez-Rodríguez, Osval A. Montesinos-López, José Crossa
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract It is of paramount importance in plant breeding to have methods dealing with large numbers of predictor variables and few sample observations, as well as efficient methods for dealing with high correlation in predictors and measured traits.
Externí odkaz:
https://doaj.org/article/3e7f5e53763447b695e0cb19d3fddc07
Publikováno v:
BMC Genomics, Vol 24, Iss 1, Pp 1-15 (2023)
Abstract Background Genomic selection (GS) is revolutionizing plant and animal breeding. However, still its practical implementation is challenging since it is affected by many factors that when they are not under control make this methodology not ef
Externí odkaz:
https://doaj.org/article/0decd32f1844498580dc88f02c8aeb65
Autor:
Osval A. Montesinos-López, Arvinth Sivakumar, Gloria Isabel Huerta Prado, Josafhat Salinas-Ruiz, Afolabi Agbona, Axel Efraín Ortiz Reyes, Khalid Alnowibet, Rodomiro Ortiz, Abelardo Montesinos-López, José Crossa
Publikováno v:
Algorithms, Vol 17, Iss 6, p 260 (2024)
Genomic selection (GS) is a groundbreaking statistical machine learning method for advancing plant and animal breeding. Nonetheless, its practical implementation remains challenging due to numerous factors affecting its predictive performance. This r
Externí odkaz:
https://doaj.org/article/18b0aed56a8948e89e137d7e12f1c1e9
Autor:
Raysa Gevartosky, Humberto Fanelli Carvalho, Germano Costa-Neto, Osval A. Montesinos-López, José Crossa, Roberto Fritsche-Neto
Publikováno v:
BMC Plant Biology, Vol 23, Iss 1, Pp 1-20 (2023)
Abstract Background Success in any genomic prediction platform is directly dependent on establishing a representative training set. This is a complex task, even in single-trait single-environment conditions and tends to be even more intricated wherei
Externí odkaz:
https://doaj.org/article/6dfd15457dc04f7aa0f1ee3df303f92a
Autor:
Osval A. Montesinos-López, Sofia Ramos-Pulido, Carlos Moisés Hernández-Suárez, Brandon Alejandro Mosqueda González, Felícitas Alejandra Valladares-Anguiano, Paolo Vitale, Abelardo Montesinos-López, José Crossa
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
IntroductionGenomic selection (GS) has gained global importance due to its potential to accelerate genetic progress and improve the efficiency of breeding programs.Objectives of the researchIn this research we proposed a method to improve the predict
Externí odkaz:
https://doaj.org/article/73541120d2894d3b9cbd8a631542b77a
Autor:
Osval A. Montesinos-López, Leonardo Crespo-Herrera, Carolina Saint Pierre, Alison R. Bentley, Roberto de la Rosa-Santamaria, José Alejandro Ascencio-Laguna, Afolabi Agbona, Guillermo S. Gerard, Abelardo Montesinos-López, José Crossa
Publikováno v:
Frontiers in Genetics, Vol 14 (2023)
Genomic selection (GS) is transforming plant and animal breeding, but its practical implementation for complex traits and multi-environmental trials remains challenging. To address this issue, this study investigates the integration of environmental
Externí odkaz:
https://doaj.org/article/d34300f6c3c24d7e80f4fa2602813761
Autor:
Osval A. Montesinos‐López, Brandon A. Mosqueda‐González, Josafat Salinas‐Ruiz, Abelardo Montesinos‐López, José Crossa
Publikováno v:
The Plant Genome, Vol 16, Iss 2, Pp n/a-n/a (2023)
Abstract Sparse testing is essential to increase the efficiency of the genomic selection methodology, as the same efficiency (in this case prediction power) can be obtained while using less genotypes evaluated in the fields. For this reason, it is im
Externí odkaz:
https://doaj.org/article/574eb570e79f4c46a8859a9a759854fb