[关键词]
[摘要]
以质量性状和数量性状为依据对观赏向日葵株系进行评价,为观赏向日葵新品种选育提供参考。以23个具有较高观赏价值的观赏向日葵株系为研究材料,对苗期及花期表型性状进行分析,采用赋值法对质量性状指标进行分级;在表型性状相关性分析基础上,进行主成分分析和系统聚类分析。结果表明,观赏向日葵株系的多样性指数、变异程度均较高,质量性状多样性指数为0.614~1.818,数量性状为1.240~1.794;舌状花宽、舌状花瓣数在各材料中的变异系数较大,分别为60.32%、42.99%。主成分分析发现前5个主成分的特征值分别为4.431、2.447、1.807、1.322、1.054,方差贡献率分别为27.696%、15.293%、11.297%、8.261%、6.585%,累计贡献率为69.132%。系统聚类分析法将该观赏向日葵株系聚为3个类群,幼苗茎色、花瓣类型、舌状花颜色、花药颜色等是进行不同类群区分的主要表型性状。筛选出开花天数最长的株系gsk3014,开花期较早的株系gsk3013、gsk3014、gsk3019、gsk3020。
[Key word]
[Abstract]
To evaluate ornamental sunflower lines based on quality and quantity characters, so as to provide reference for breeding new varieties of ornamental sunflowers, high ornamental value sunflower lines were used as materials, the seedling and flowering phenotypic traits were analyzed, and the quality traits were graded by assigning values. On the basis of correlation analysis of all phenotypic traits, principal component analysis and systematic cluster analysis were performed on the data. Results showed that the diversity index and variation degree of ornamental sunflower lines were high, the diversity index of quality traits was 0.614 to 1.818, and the quantitative traits were 1.240 to 1.794. The variation coefficients of lingual flower width and lingual petal were 60.32% and 42.99%, respectively. Principal component analysis revealed that the eigenvalues of the first 5 principal components were 4.431, 2.447, 1.807, 1.322, and 1.054, respectively, with corresponding variance contribution rates of 27.696%, 15.293%, 11.297%, 8.261% and 6.585%, respectively. The cumulative contribution rate reached a significant value of 69.132%. The ornamental sunflower lines were grouped into 3 groups by systematic clustering analysis. Stem color, petal type, tongue flower color and anther color were the main phenotypic traits to distinguish different groups. Line gsk3014 were with the longest flowering days and line gsk3013, gsk3014, gsk3019 and gsk3020 were with earlier flowering stage.
[中图分类号]
S681.9
[基金项目]
国家特色油料产业技术体系(CARS-14-2-22);甘肃省农业科学院青年基金(2022GAAS52); 2024年甘肃省重点人才项目(甘组通字〔2024〕4号)。