花生种质资源表型性状的综合评价及指标筛选
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1江苏徐淮地区徐州农业科学研究所,徐州 221131;,1江苏徐淮地区徐州农业科学研究所,徐州 221131;,2江苏省农业科学院经济作物研究所,南京 210014;,1江苏徐淮地区徐州农业科学研究所,徐州 221131;,1江苏徐淮地区徐州农业科学研究所,徐州 221131;,1江苏徐淮地区徐州农业科学研究所,徐州 221131;,1江苏徐淮地区徐州农业科学研究所,徐州 221131;,1江苏徐淮地区徐州农业科学研究所,徐州 221131;,3徐州沐阳生物科技发展有限公司,徐州 221131

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徐州市农业高技术攻关项目(KC16NG068);国家花生产业技术体系徐州综合试验站(CARS-13);徐州市重点研发计划(KC17069)


Comprehensive Evaluation and Index Screening of Phenotypic Traits in Peanut Germplasm Resources
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1Xuzhou Institute of Agricultural Sciences of the Xuhuai District, Xuzhou 221131;,1Xuzhou Institute of Agricultural Sciences of the Xuhuai District, Xuzhou 221131;,2Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014;,1Xuzhou Institute of Agricultural Sciences of the Xuhuai District, Xuzhou 221131;,1Xuzhou Institute of Agricultural Sciences of the Xuhuai District, Xuzhou 221131;,1Xuzhou Institute of Agricultural Sciences of the Xuhuai District, Xuzhou 221131;,1Xuzhou Institute of Agricultural Sciences of the Xuhuai District, Xuzhou 221131;,1Xuzhou Institute of Agricultural Sciences of the Xuhuai District, Xuzhou 221131;,3Xuzhou Mu Yang Biotechnology Development Co., Ltd.,Xuzhou 221131

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    摘要:

    分析花生种质资源表型性状的遗传变异规律,构建花生种质资源的综合评价体系,筛选最优的评价指标。本研究以40份花生种质资源的17个表型性状为研究对象,利用变异系数与Shannon-Weaver多样性指数对表型性状的遗传多样性进行分析,采用聚类分析、主成分分析以及逐步回归分析对花生种质资源进行了综合评价和鉴定指标的筛选。结果表明:17个表型性状的变异系数变化范围为4.15%-31.82%,油酸、亚油酸以及蔗糖含量的性状变异丰富,出仁率、粗脂肪及蛋白质的性状较稳定。多样性指数变化范围为1.39-2.06,主茎高、百仁重及蛋白质的性状分布比较均匀,油酸、亚油酸及棕榈酸的性状分级及分布较不均匀。聚类分析把40份花生种质资源分为了4个类群。主成分分析把17个表型性状归为5个主成分(累计贡献率80.41%,反映出17个表型性状的大部分信息),依次为花生籽粒含油量因子、籽粒含糖量因子及丰产性因子,以上因子可以较准确的评价花生种质。花生种质表型性状的综合评价由F值大小判定,F值均值为0.73,开农176的F值最高,阜花12号的F值最低。由逐步回归分析筛选出8个表型性状:单株鲜果重、百果重、出仁率、粗脂肪、蛋白质、棕榈酸、油酸和蔗糖含量。花生种质资源遗传多样性较丰富,综合评价F值可以为花生种质资源评价提供参考,筛选的8个表型性状可以作为花生种质资源性状评价指标。

    Abstract:

    The objective of this study is to analyze the law of genetic variation of phenotypic traits in peanut germplasm resources, constructing comprehensive evaluation system of peanut germplasm resources, selecting the optimal evaluation indexes. Seventeen phenotypic traits of 40 peanut germplasm resources were studied by using variation coefficient and diversity index of Shannon-Weaver to analyze genetic diversity of phenotypic traits. Cluster analysis, principal component analysis and stepwise regression analysis were used to comprehensively evaluate peanut germplasm resources and select identification indexes. The result shows that variation coefficients range from 4.15% to 31.82%, and traits vary significantly in oleic acid, linoleic acid and sucrose content, while the traits of shelling percentage, oil content and protein content are stable. Diversity indexes range from 1.39 to 2.06. In terms of traits, height of main stem, 100-seed weight, and protein content distribute equally, while the characters of oleic acid, linoleic acid and palmitic acid distribute unevenly. 40 peanut germplasm resources were divided into 4 groups by cluster analysis. Seventeen phenotypic traits were classified into five principal components with principal component analysis (cumulative contribution rate 80.41%, reflecting most information of 17 phenotypic traits). The five principal components are grain oil content factor, grain sugar content factor and high yield factor which could accurately evaluate peanut germplasm. The comprehensive evaluation of phenotypic traits of peanut germplasm is determined by the value of F value. The average value is 0.73, KN 176 is the highest, and FH 12 is the lowest. Eight phenotypic traits are screened by stepwise regression analysis: fresh yield/plant, 100-pod weight, shelling percentage, oil content, protein content, palmitic acid, oleic acid and sucrose content. Peanut germplasm resources are abundant in genetic diversity. Comprehensive evaluation of peanut germplasm resources can provide references for peanut germplasm evaluation. 8 phenotypic traits selected can be used as evaluation indexes for peanut germplasm resources traits.

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孙东雷,卞能飞,陈志德,等.花生种质资源表型性状的综合评价及指标筛选[J].植物遗传资源学报,2018,19(5):865-874.

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  • 收稿日期:2018-01-05
  • 最后修改日期:2018-05-11
  • 录用日期:2018-03-02
  • 在线发布日期: 2018-07-12
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