1.吉林省农业科学院(中国农业科技东北创新中心);2.山东农业大学植物保护学院;3.延边大学
国家作物种质资源库(吉林)分库运行服务(NCGRC2025-052)
1.Jilin Academy of Agricultural Sciences(Northeast Agricultural Research Center of China);2.Institute of Plant Protection, Shandong Agricultural University;3.Yanbian University
Operation service of the National Crop Germplasm Bank (Jilin) Branch(NCGRC2025-052)
玉米地方种质蕴藏的基因丰富多样,对拓宽当前玉米种质资源遗传基础、丰富材料类型具有重要的潜在价值。本研究以90份玉米地方品种为研究对象,基于两年的表型鉴定,计算了其40个表型性状(5个质量性状、15个数量性状及20个品质性状)的变异系数(CV)与表型多样性指数(H′),同时对这些材料进行了聚类分析。结果显示:表型性状的CV变化范围为2.89%(总淀粉含量)~44.20%(赖氨酸含量),其中,30个表型性状的变异系数CV >10.00%,表明这些性状的表型变异较丰富。H′变化范围为0.892(穗形)~2.088(穗位高),5个质量性状的H′相对较低(<1.2),9个数量性状及5个品质性状的H′相对较高(>2.0),表明后14个性状的表型多样性更为丰富。相关分析结果显示,株高及穗位高与其余13个数量性状均呈极显著正相关,相关程度较高;粗蛋白质含量、粗脂肪含量及总淀粉含量共3个品质性状与脂肪酸含量及16种氨基酸含量之间相关程度较高。主成分分析发现,15个数量性状中贡献率最大的为单株穗干重、单株粒干重、穗粗及穗长;20个品质性状中贡献率最大的为酪氨酸含量、异亮氨酸含量、丝氨酸含量、苏氨酸含量、脯氨酸含量、总氨基酸含量,说明果穗、籽粒及6种氨基酸含量是形成这些种质遗传变异比较丰富的主要因素。聚类分析发现,基于15个数量性状可将90份玉米地方品种聚成3类,类群Ⅰ囊括的主要是高秆大穗型资源,可作为稀植品种选育的基础材料;类群Ⅱ资源的主要特征是植株较矮,果穗较短,该类群种质可作为高密品种选育的潜在基础材料;类群Ⅲ资源的主要特征是穗行数较多,可为玉米产量及相关性状的改良提供优异资源。基于20个品质性状同样将90份玉米地方品种聚成3类,类群Ⅰ包含1份高淀粉种质、类群Ⅱ包含8份高蛋白种质、类群Ⅲ包含13份高油种质,这些种质可分别为高淀粉、高蛋白及高油等特/专用玉米品种选育提供潜在的材料支撑。
The abundant and diverse genes are contained in the maize Landraces, which have important potential value for broadening the genetic basis of current maize germplasm resources and enriching the types of germplasms. In this study, 90 maize landraces were used as the research object. Based on the phenotypic identification over two years, the coefficient of variation ( CV ) and phenotypic diversity index ( H′) of 40 phenotypic traits ( 5 qualitative traits,15 quantitative traits and 20 quality traits ) were calculated, and cluster analysis was performed on these materials. The results showed that the CV of phenotypic traits ranged from 2.89 % ( total starch content ) to 44.20 % ( lysine content ). Among them, the CV of 30 phenotypic traits was greater than 10.00 %, indicating that the phenotypic variation of these traits was abundant. The H ' ranged from 0.892 ( ear shape ) to 2.088 ( ear height ), and the H ' of the five qualitative traits was relatively low ( all < 1.2 ), whereas that for nine quantitative traits and five quality traits was notably higher (all > 2.0), suggesting more abundant diversity in these 14 traits. Correlation analysis revealed that plant height and ear height were significantly and positively correlated with the other 13 quantitative traits, and the correlation degree was high. The three quality traits of protein content, crude fat content and starch content were highly correlated with fatty acid content and 16 amino acid contents. Principal component analysis indicated that among the 15 quantitative traits, the largest contribution rate was ear weight per plant, grain weight per plant, ear diameter, and ear length. Among the 20 quality traits, the the largest contribution rate was tyrosine content, isoleucine content, serine content, threonine content, proline content and total amino acid content , indicating that the ear, grain and six amino acid content were the main factors for the formation of these genetic variation. Cluster analysis showed that 90 maize landraces could be clustered into three categories based on 15 quantitative traits. Group I mainly included high-stalk and large- panicle resources, which could be used as the basic materials for the breeding of sparsely planted varieties. The main characteristics of group II are short plants and short ears, which can be used as potential basic materials for breeding high-density varieties. Group III was characterized by the large number of ear rows, which can provide excellent resources for the improvement of maize yield and related traits. Based on 20 quality traits, 90 maize landraces were also clustered into 3 groups. Group I contained one high-starch germplasm, group II included etight high-protein germplasms, and group III comprised 13 high-oil germplasms. These germplasms can provide potential material support for the breeding of special / special maize varieties with high starch, high protein and high oil, respectively.
