Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Julio Isidro y Sánchez"'
Publikováno v:
Plant Methods, Vol 20, Iss 1, Pp 1-16 (2024)
Abstract The selection of highly productive genotypes with stable performance across environments is a major challenge of plant breeding programs due to genotype-by-environment (GE) interactions. Over the years, different metrics have been proposed t
Externí odkaz:
https://doaj.org/article/75c45ba03ff64d78b98ef5e0d63a0b49
Autor:
Javier Fernández-González, Bertrand Haquin, Eliette Combes, Karine Bernard, Alix Allard, Julio Isidro y Sánchez
Publikováno v:
Plant Methods, Vol 20, Iss 1, Pp 1-23 (2024)
Abstract Genomic selection (GS) has become an increasingly popular tool in plant breeding programs, propelled by declining genotyping costs, an increase in computational power, and rediscovery of the best linear unbiased prediction methodology over t
Externí odkaz:
https://doaj.org/article/7ed496ec5d104047879a86b8489d333b
Publikováno v:
Plant Methods, Vol 20, Iss 1, Pp 1-1 (2024)
Externí odkaz:
https://doaj.org/article/88c52791292843ad9bc3b3ec2202a8f9
Autor:
Javier Fernández-González, Bertrand Haquin, Eliette Combes, Karine Bernard, Alix Allard, Julio Isidro y Sánchez
Publikováno v:
Plant Methods, Vol 20, Iss 1, Pp 1-1 (2024)
Externí odkaz:
https://doaj.org/article/49a32e806b444b199485e3b3b3fe00dd
Autor:
Ajmalud Din, Rozina Gul, Hamayoon Khan, Julian Garcia-Abadillo Velasco, Reyna Persa, Julio Isidro y Sánchez, Diego Jarquin
Publikováno v:
Agriculture, Vol 14, Iss 2, p 215 (2024)
Chickpea is the second most important legume crop in pulses, and its performance is greatly influenced by environmental factors inducing a change in the response patterns, complicating the selection of the best cultivar(s). The genotype-by-environmen
Externí odkaz:
https://doaj.org/article/3d26944fb7c14899a4f712c3b85fe777
Autor:
Julio Isidro y Sánchez, Deniz Akdemir
Publikováno v:
Frontiers in Plant Science, Vol 12 (2021)
Genomic selection (GS) is becoming an essential tool in breeding programs due to its role in increasing genetic gain per unit time. The design of the training set (TRS) in GS is one of the key steps in the implementation of GS in plant and animal bre
Externí odkaz:
https://doaj.org/article/a792192bab6b4c45822407175d40d02e
Publikováno v:
Frontiers in Genetics, Vol 12 (2021)
A major barrier to the wider use of supervised learning in emerging applications, such as genomic selection, is the lack of sufficient and representative labeled data to train prediction models. The amount and quality of labeled training data in many
Externí odkaz:
https://doaj.org/article/4ad341d91ea64542ae88634d4fcd3cd5
Publikováno v:
Frontiers in Plant Science, Vol 11 (2020)
Private and public breeding programs, as well as companies and universities, have developed different genomics technologies that have resulted in the generation of unprecedented amounts of sequence data, which bring new challenges in terms of data ma
Externí odkaz:
https://doaj.org/article/43b87d6c53eb48aabecc120f0b70261b
Publikováno v:
Agronomy, Vol 11, Iss 3, p 499 (2021)
Spring barley (Hordeum vulgare L.) is the most important cereal in Iceland and its national breeding program aims to select barley genotypes adapted to its environment. A critical step to understand the adaptation of Nordic barley material to a cool
Externí odkaz:
https://doaj.org/article/6a0244fbf4644d8884c43b2a88831b17
20 Pág..
Maximizing CDmean and Avg_GRM_self were the best criteria for training set optimization. A training set size of 50-55% (targeted) or 65-85% (untargeted) is needed to obtain 95% of the accuracy. With the advent of genomic selection (GS)
Maximizing CDmean and Avg_GRM_self were the best criteria for training set optimization. A training set size of 50-55% (targeted) or 65-85% (untargeted) is needed to obtain 95% of the accuracy. With the advent of genomic selection (GS)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41575bbd5a34dc8ea13dbed3af0b7b82
http://hdl.handle.net/10261/310782
http://hdl.handle.net/10261/310782
