云南省夏大豆种质资源表型鉴定和综合评价模型构建
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云南省农业科学院粮食作物研究所,昆明 650205,云南省农业科学院粮食作物研究所,昆明 650205,云南省农业科学院粮食作物研究所,昆明 650205,云南省农业科学院粮食作物研究所,昆明 650205,云南省农业科学院粮食作物研究所,昆明 650205,云南省农业科学院粮食作物研究所,昆明 650205

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云南省“十一五”科技攻关项目(2006NG13);国家大豆现代产业技术体系(CARS-04-CES29)


Phenotypic Screening of Summer Sowing Soybean Germplasm Resources in Yunnan Province and Constructing A Comprehensive Evaluation Model
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Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205,Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205,Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205,Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205,Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205,Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205

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    【目的】为全面准确评价西南高原夏大豆种质资源,构建大豆种质资源综合评价体系,满足育种家快速、定向选择育种亲本的需求。【方法】本研究采用路径分析、主成分分析、隶属函数、聚类分析、回归分析等多元分析方法相结合,对451份夏大豆种质资源的11个重要表型性状进行研究。【结果】结果表明:各性状间存在丰富的变异和错综复杂的相关性,且性状间相互影响清晰的分为两条路径,一条最终影响因子为大豆品质,另一条最终影响因子为单株粒重。通过主成分分析,将11项相关指标转化为5项独立的综合指标,能代表全部数据81.2%的信息量。通过隶属函数计算综合评价值(D),并对其进行聚类分析,将451个种质划分成3类,筛选出综合表现较好种质97份。通过逐步回归建立大豆种质综合评价数学模型: ,估计精度在95.25%以上。【结论】在451个种质中筛选出97份综合表现较好的种质,并运用11个性状构建种质资源评价数学模型。

    Abstract:

    【objective】 The main purpose of the present study was to accurately evaluate soybean germplasm resources, build the comprehensive evaluation system, and satisfy the needs of fast and direct selection of breeding parent for breeder. 【method】 11 important agronomic traits in 451 soybean germplasm resources of Yunnan province, were studied by path analysis, principal component analysis, membership function method, clustering analysis, and stepwise regression analysis. 【result】 The results showed that there were plentiful phenotypic variations and the complex correlation among the 11 important agronomic traits. And the mutual influence between the 11 traits was clearly divided into two paths, one final impact factor was the quality of soybean, another final impact factor was seed weight per plant. The 11 single indexes were transformed into 5 independent comprehensive components through principal component analysis, which represent 87.685% variation of the raw data. The membership function method was employed to calculate comprehensive value (D) and carried on cluster analysis, and 451 soybean germplasm resources were divided into three types. 97 soybean germplasm resources of the best comprehensive performance wereSfiltered. At last, a mathematical evaluation model for soybean germplasm resources was established by stepwise regression analysis, and its accuracy was higher than 95.25%. 【conclusion】 97 soybean germplasm resources of the best comprehensive performance wereSfiltered to form 451 soybean germplasm resources, and we construct a comprehensive evaluation system by using 11 traits.

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代希茜,赵银月,詹和明,等.云南省夏大豆种质资源表型鉴定和综合评价模型构建[J].植物遗传资源学报,2018,19(5):830-845.

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  • 收稿日期:2018-01-22
  • 最后修改日期:2018-05-23
  • 录用日期:2018-04-24
  • 在线发布日期: 2018-09-14
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