Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement
| cg.identifier.doi | https://doi.org/10.1016/j.fcr.2016.02.004 | en |
| cg.issn | 0378-4290 | en |
| cg.journal | Field Crops Research | en |
| cg.volume | 189 | en |
| dc.contributor.author | Meng, Lijun | en |
| dc.contributor.author | Zhao, Xiangqian | en |
| dc.contributor.author | Ponce, Kimberly | en |
| dc.contributor.author | Ye, Guoyou | en |
| dc.contributor.author | Leung, Hei | en |
| dc.date.accessioned | 2024-12-19T12:54:55Z | en |
| dc.date.available | 2024-12-19T12:54:55Z | en |
| dc.identifier.uri | https://hdl.handle.net/10568/165289 | |
| dc.title | Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement | en |
| dcterms.bibliographicCitation | Meng, Lijun; Zhao, Xiangqian; Ponce, Kimberly; Ye, Guoyou and Leung, Hei. 2016. Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement. Field Crops Research, Volume 189 p. 19-42 | en |
| dcterms.extent | pp. 19-42 | en |
| dcterms.issued | 2016-03 | |
| dcterms.language | en | |
| dcterms.license | Copyrighted; all rights reserved | |
| dcterms.publisher | Elsevier | en |
| dcterms.type | Journal Article |