Zobrazeno 1 - 8
of 8
pro vyhledávání: '"George Graef"'
Autor:
Nicholas Dietz, Yen On Chan, Andrew Scaboo, George Graef, David Hyten, Mary Happ, Brian Diers, Aaron Lorenz, Dechun Wang, Trupti Joshi, Kristin Bilyeu
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
Adaptation of soybean cultivars to the photoperiod in which they are grown is critical for optimizing plant yield. However, despite its importance, only the major loci conferring variation in flowering time and maturity of US soybean have been isolat
Externí odkaz:
https://doaj.org/article/b28296accbc14d81a16952b27a64b4b2
Publikováno v:
Frontiers in Genetics, Vol 12 (2021)
The effects of climate change create formidable challenges for breeders striving to produce sufficient food quantities in rapidly changing environments. It is therefore critical to investigate the ability of multi-environment genomic prediction (GP)
Externí odkaz:
https://doaj.org/article/dc74828fe81a48009950bb49d2d89057
Autor:
Brian W. Diers, Jim Specht, Katy Martin Rainey, Perry Cregan, Qijian Song, Vishnu Ramasubramanian, George Graef, Randall Nelson, William Schapaugh, Dechun Wang, Grover Shannon, Leah McHale, Stella K. Kantartzi, Alencar Xavier, Rouf Mian, Robert M. Stupar, Jean-Michel Michno, Yong-Qiang Charles An, Wolfgang Goettel, Russell Ward, Carolyn Fox, Alexander E. Lipka, David Hyten, Troy Cary, William D. Beavis
Publikováno v:
G3: Genes, Genomes, Genetics, Vol 8, Iss 10, Pp 3367-3375 (2018)
Soybean is the world’s leading source of vegetable protein and demand for its seed continues to grow. Breeders have successfully increased soybean yield, but the genetic architecture of yield and key agronomic traits is poorly understood. We develo
Externí odkaz:
https://doaj.org/article/854c68e899e44be5be6a2f64684e1e21
Publikováno v:
Evolutionary Bioinformatics, Vol 15 (2019)
An important and broadly used tool for selection purposes and to increase yield and genetic gain in plant breeding programs is genomic prediction (GP). Genomic prediction is a technique where molecular marker information and phenotypic data are used
Externí odkaz:
https://doaj.org/article/35c9877e8fd846edb1e453e91cde6336
Publikováno v:
Frontiers in Plant Science, Vol 9 (2018)
Alkaline soils comprise 30% of the earth and have low plant-available iron (Fe) concentration, and can cause iron deficiency chlorosis (IDC). IDC causes soybean yield losses of $260 million annually. However, it is not known whether molecular respons
Externí odkaz:
https://doaj.org/article/a1cf0bc44f2045ea95dbee7cf1c9a411
Autor:
Nicolás Cafaro La Menza, Timothy J Arkebauer, John L Lindquist, Juan Pablo Monzon, Johannes M H Knops, George Graef, David Scoby, Réka Howard, Jennifer Rees, James E Specht, Patricio Grassini
Publikováno v:
Journal of Experimental Botany.
Ontogenic changes in soybean radiation-use efficiency (RUE) have been attributed to variation in specific leaf nitrogen (SLN) based only on data collected during seed filling. We evaluated this hypothesis using data on leaf area, absorbed radiation (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d9e4132ad77ec8fa7ff32b67fedc368
https://doi.org/10.1093/jxb/erac408
https://doi.org/10.1093/jxb/erac408
Autor:
Nicolás Cafaro La Menza, Timothy J. Arkebauer, John L. Lindquist, Juan Pablo Monzon, Johannes M.H. Knops, George Graef, David Scoby, Réka Howard, Jennifer Rees, James E. Specht, Patricio Grassini
Ontogenic changes in soybean radiation-use efficiency (RUE) have been attributed to variation in specific leaf nitrogen (SLN) based only on data collected during seed filling. We evaluated this hypothesis using data on leaf area, absorbed photosynthe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0171ecfb4cd906bd12436cffbd35cdcc
https://doi.org/10.1101/2022.03.24.485711
https://doi.org/10.1101/2022.03.24.485711
Autor:
Shirley Sato, Aiqiu Xing, Xingguo Ye, Bruce Schweiger, Anthony Kinney, George Graef, Tom Clemente
Publikováno v:
Crop Science. 44:646
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::01db6ce9608422c3426b2c311dedd0bd
https://doi.org/10.2135/cropsci2004.0646
https://doi.org/10.2135/cropsci2004.0646