Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Osval A. Montesinos-Lopez"'
Autor:
Alexander Loladze, Francelino Rodrigues, Jr, Cesar D. Petroli, Carlos Muñoz-Zavala, Sergio Naranjo, Felix San Vicente, Bruno Gerard, Osval A. Montesinos-Lopez, Jose Crossa, Johannes W.R. Martini
Publikováno v:
Data in Brief, Vol 54, Iss , Pp 110300- (2024)
Three F2-derived biparental doubled haploid (DH) maize populations were generated for genetic mapping of resistance to common rust. Each of the three populations has the same susceptible parent, but a different resistance donor parent. Population 1 a
Externí odkaz:
https://doaj.org/article/330242be14de4676bab6c5de052ced42
Publikováno v:
Remote Sensing, Vol 15, Iss 7, p 1771 (2023)
Many processes concerning below-ground plant performance are not fully understood, such as spatial and temporal dynamics and their relation to environmental factors. Accounting for these spatial patterns is very important as they may be used to adjus
Externí odkaz:
https://doaj.org/article/4d1dc5add02e45a5bff2cc5ada4eb8fd
Autor:
Osval A. Montesinos‐Lopez, Jose C. Montesinos‐Lopez, Eduardo Salazar, Jose Alberto Barron, Abelardo Montesinos‐Lopez, Raymundo Buenrostro‐Mariscal, Jose Crossa
Publikováno v:
The Plant Genome, Vol 14, Iss 3, Pp n/a-n/a (2021)
Abstract Genomic selection (GS) is revolutionizing conventional ways of developing new plants and animals. However, because it is a predictive methodology, GS strongly depends on statistical and machine learning to perform these predictions. For cont
Externí odkaz:
https://doaj.org/article/b692d1010fdd4c00a5ac6ed88572f440
Autor:
Jose Crossa, Roberto Fritsche-Neto, Osval A. Montesinos-Lopez, Germano Costa-Neto, Susanne Dreisigacker, Abelardo Montesinos-Lopez, Alison R. Bentley
Publikováno v:
Frontiers in Plant Science, Vol 12 (2021)
Externí odkaz:
https://doaj.org/article/615d60c058244e8b9fad0eaf321e3465
Autor:
Afolabi Agbona, Brody Teare, Henry Ruiz-Guzman, Iliyana D. Dobreva, Mark E. Everett, Tyler Adams, Osval A. Montesinos-Lopez, Peter A. Kulakow, Dirk B. Hays
Publikováno v:
Remote Sensing, Vol 13, Iss 23, p 4908 (2021)
Cassava as a world food security crop still suffers from an inadequate means to measure early storage root bulking (ESRB), a trait that describes early maturity and a key characteristic of improved cassava varieties. The objective of this study is to
Externí odkaz:
https://doaj.org/article/f4dbec436fb94f5b9e3857b5329fc3fd
Autor:
Osval Antonio Montesinos‐Lopez, Abelardo Montesinos‐Lopez, Ricardo Acosta, Rajeev K. Varshney, Alison Bentley, Jose Crossa
Publikováno v:
The plant genomeREFERENCES. 15(1)
Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the sp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f682b8345fd60240257c7e553f32ece
https://pubmed.ncbi.nlm.nih.gov/35170851
https://pubmed.ncbi.nlm.nih.gov/35170851
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
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