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作 者:李森林 刘挺 唐勇 彭忠华[1] LI Senlin;LIU Ting;TANG Yong;PENG Zhonghua(College of Agronomy,Guizhou University, Guiyang, Guizhou 550025,China)
出 处:《山地农业生物学报》2020年第1期20-25,共6页Journal of Mountain Agriculture and Biology
基 金:贵州省特色资源植物抗逆种质选育([2016]5624)。
摘 要:为有效地筛选出适宜贵州种植的玉米品种,本文采用随机区组设计及主成分分析法,对61(含CK贵农玉889,下同)个玉米品种(组合)F1代的10个不同农艺性状及产量性状进行了研究。主成分分析法表明选择玉米株高、穗位高、百粒重和产量等10个指标进行分析,可以避免单一指标的片面性,能够较全面地进行先锋玉米新配杂交组合筛选,综合评价表现较好的组合依次是PA-26、PA-9、PA-36、PA-20、PA-55、PA-19、PA-35、PA-54、PA-11、PA-51;相关性分析表明百粒重、株高和穗位高与产量呈现出极显著相关关系,穗长和行粒数与产量表现出显著相关关系。这一分析方法将多个农艺性状组合转化为少数几个综合指标,可为下一年参加区域试验及杂交组合选配提供理论和实践依据。In order to effectively screen out maize varieties suitable for planting in Guizhou,this experiment uses randomized block design and principal component analysis method to match the F1 generation of 61(including CK Gui Nongyu 889,the same below)corn varieties(combination).A variety of agronomic traits and yield traits were studied.The results showed that the selection of 10 indicators including plant height,ear height,100-grain weight and yield based on principal component analysis could avoid the one-sidedness of single index,and could comprehensively screen the new hybrid combination of pioneer corn.Thecombination with better overall performance were PA-26,PA-9,PA-36,PA-20,PA-55,PA-19,PA-35,PA-54,PA-11,and PA-51;correlation analysis showed that:100-grain weight,plant height and ear height showed a significant correlation with yield;there was a significant correlation between ear length and grain number and yield.This analysis method combines multiple agronomic traits with the idea of dimensionality reduction,and transforms into a few comprehensive indicators to provide theoretical and practical basis for participating in regional trials and hybrid combination selection in the next year.
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