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of 5
pro vyhledávání: '"Jeffrey Endelman"'
Autor:
Sapinder Bali, Girijesh Patel, Rich Novy, Kelly Vining, Chuck Brown, David Holm, Gregory Porter, Jeffrey Endelman, Asunta Thompson, Vidyasagar Sathuvalli
Publikováno v:
PLoS ONE, Vol 13, Iss 8, p e0201415 (2018)
DNA fingerprinting is a powerful tool for plant diversity studies, cultivar identification, and germplasm conservation and management. In breeding programs, fingerprinting and diversity analysis provide an insight into the extent of genetic variabili
Externí odkaz:
https://doaj.org/article/d7f844d1c3b94072b768139b2184681b
Autor:
Jesse Poland, Jeffrey Endelman, Julie Dawson, Jessica Rutkoski, Shuangye Wu, Yann Manes, Susanne Dreisigacker, José Crossa, Héctor Sánchez-Villeda, Mark Sorrells, Jean-Luc Jannink
Publikováno v:
The Plant Genome, Vol 5, Iss 3, Pp 103-113 (2012)
Genomic selection (GS) uses genomewide molecular markers to predict breeding values and make selections of individuals or breeding lines prior to phenotyping. Here we show that genotyping-by-sequencing (GBS) can be used for de novo genotyping of bree
Externí odkaz:
https://doaj.org/article/fa4255ec69a3445baa2c4a79b9db271a
Autor:
Maria Caraza-Harter, Jeffrey Endelman
Publikováno v:
Theoretical and Applied Genetics. 135:2943-2951
Potato vine and skin maturity, which refer to foliar senescence and adherence of the tuber periderm, respectively, are both important to production and therefore breeding. Our objective was to investigate the genetic architectures of these traits in
Autor:
Lin Song, Jeffrey Endelman
At present, the potato of international commerce is autotetraploid, and the complexity of this genetic system creates limitations for breeding. Diploid potato breeding has long been used for population improvement, and thanks to improved understandin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bd4a75de89035328be29540ccae6fa44
https://doi.org/10.1101/2022.11.09.515871
https://doi.org/10.1101/2022.11.09.515871
Autor:
Jeffrey Endelman
Plant breeders interested in genomic selection often face challenges to fully utilizing the multi-trait, multi-environment datasets they rely on for selection. R package StageWise was developed to go beyond the capabilities of most specialized softwa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::12c2a0a08d84c2e7029ef69d60759dcf
https://doi.org/10.1101/2022.09.28.509884
https://doi.org/10.1101/2022.09.28.509884