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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。
The genetic relationships among 15 agronomic traits and yield, including plant height, branch number and growth period, were studied with 55 stable offspring derived from Jin 52, Jinda 57 and their hybrids. Through the principal component analysis, the 15 indicators were integrated into 6 new indicators with a cumulative contribution rate of 85.81%. The regression equation between yield and principal component value was obtained by multivariate linear stepwise regression analysis. The regression equation was used to predict the yield, The absolute value of the error of the estimated yield except for 2, 10, 21, 22, 30, 39, 53 strains, the rest of the absolute error of the strains were less than 10%; the main component value as an indicator of clustering analysis 57 materials poly For high yield, middle class, low yield 3 categories. The results showed that the principal component regression method can be applied to soybean yield-related traits; the total pods, total grains, main stem pods, branches, chlorophyll content and other indicators have a greater impact on yield; soybean yield capacity can be To study the differences between different traits to evaluate.