摘要
以晋大52、晋大57及其杂交衍生的55个稳定后代品系为材料,研究了株高、分枝数、生育期等15个农艺性状与产量的遗传关系。通过主成分分析,将15个指标综合成为累计贡献率达85.81%的6个新指标;经多元线性逐步回归分析得出产量与主成分值之间的回归方程;用回归方程预测品种产量,方程估产的误差百分率绝对值除2、10、21、22、30、39、53号品系外,其余品系误差绝对值均低于10%;以主成分值为指标的聚类分析将57个材料聚为高产、中产、低产3类。结果证明主成分回归法可以应用于大豆产量相关性状的研究;总荚数、总粒数、主茎荚数、分枝数、叶绿素含量等指标对产量的影响较大;大豆的产量能力可通过研究不同性状间的差异水平来评估。
Two soybean cultivars,＇Jinda 52＇,＇Jinda 57＇,and their filial generations were selected as tested materials to study genetic relationship of 15 agronomic characters including plant height,branch number,growth stage,yield,etc.Fifteen indicators could be integrated into six new indicators with the cumulative contribution rate of 85.81% by principal component analysis.The regression equation between yield and values of the principal components was acquired by multiple linear regression.The absolute values of error of varieties were below 10% except 6 lines by forecast of yield from regression equation.Fifty-seven lines were classified into three yield groups by cluster analysis.Results suggest that principal component regression could be used for study on the biological characters associated with yield.Indicators including total pod number,total seed number,pods of main stem,branch number and chlorophyll content had great influence on seed yield,and soybean yield potential could be predicted via research on distinct levels between different characters.
出处
《大豆科学》
CAS
CSCD
北大核心
2012年第1期38-41,共4页
Soybean Science
基金
国家科技支撑计划项目(2006BAD01A04)
山西省科技攻关项目(20080311007-1)
关键词
大豆
杂交后代
产量
主成分分析
多元回归分析
聚类分析
Soybean
Filial generations
Yield
Principal component analysis
Multiple regression analysis
Clustering analysis
