您好，欢迎访问河北省农林科学院 机构知识库！
河北省农林科学院机构知识库

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

Genomic Prediction for 25 Agronomic and Quality Traits in Alfalfa (Medicago sativa)

文献类型： 外文期刊

作者： Jia, Congjun 1 ; Zhao, Fuping 1 ; Wang, Xuemin 1 ; Han, Jianlin 2 ; Zhao, Haiming 4 ; Liu, Guibo 4 ; Wang, Zan 1 ;

作者机构： 1.Chinese Acad Agr Sci, Inst Anim Sci, Beijing, Peoples R China

2.Chinese Acad Agr Sci, Inst Anim Sci, CAAS ILRI Joint Lab Livestock & Forage Genet Reso, Beijing, Peoples R China

3.ILRI, Nairobi, Kenya

4.Hebei Acad Agr & Forestry Sci, Inst Dryland Farming, Hengshui, Peoples R China

关键词： alfalfa; genomic prediction; agronomic trait; quality trait; estimated breeding value

期刊名称：FRONTIERS IN PLANT SCIENCE （ 影响因子：5.753； 五年影响因子：6.612 ）

ISSN： 1664-462X

年卷期： 2018 年 9 卷

页码：

收录情况： SCI

摘要： Agronomic and quality traits in alfalfa are very important to forage industry. Genomic prediction (GP) based on genotyping-by-sequencing (GBS) data could shorten the breeding cycles and accelerate the genetic gains of these complex traits, if they display moderate to high prediction accuracies. The aim of this study was to investigate the predictive potentials of these traits in alfalfa. A total of 322 genotypes from 75 alfalfa accessions were used for GP of the agronomic and quality traits, which were related to yield and nutrition value, respectively, using BayesA, BayesB, and BayesC p methods. Ten-fold cross validation was used to evaluate the accuracy of GP represented by the correlation between genomic estimated breeding value (GEBV) and estimated breeding value (EBV). The accuracies ranged from 0.0021 to 0.6485 for different traits. For each trait, three GP methods displayed similar prediction accuracies. Among 15 quality traits, mineral element Ca had a moderate and the highest prediction accuracy (0.34). NDF digestibility after 48 h (NDFD 48 h) and 30 h (NDFD 30 h) and mineral element Mg had prediction accuracies varying from 0.20 to 0.25. Other traits, for example, fat and crude protein, showed low prediction accuracies (0.05 to 0.19). Among 10 agronomic traits, however, some displayed relatively high prediction accuracies. Plant height (PH) in fall (FH) had the highest prediction accuracy (0.65), followed by flowering date (FD) and plant regrowth (PR) with accuracies at 0.52 and 0.51, respectively. Leaf to stem ratio (LS), plant branch (PB), and biomass yield (BY) reached to moderate prediction accuracies ranging from 0.25 to 0.32. Our results revealed that a few agronomic traits, such as FH, FD, and PR, had relatively high prediction accuracies, therefore it is feasible to apply genomic selection (GS) for these traits in alfalfa breeding programs. Because of the limitations of population size and density of SNP markers, several traits displayed low accuracies which could be improved by a bigger reference population, higher density of SNP markers, and more powerful statistic tools.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：河北省农林科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台