不同杂种优势群玉米茎秆纤维品质及配合力分析
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河北农业大学农学院/国家玉米改良中心河北分中心/河北省作物种质资源实验室,保定 071001,河北农业大学农学院/国家玉米改良中心河北分中心/河北省作物种质资源实验室,保定 071001,河北农业大学农学院/国家玉米改良中心河北分中心/河北省作物种质资源实验室,保定 071001,河北农业大学农学院/国家玉米改良中心河北分中心/河北省作物种质资源实验室,保定 071001,河北农业大学农学院/国家玉米改良中心河北分中心/河北省作物种质资源实验室,保定 071001,河北农业大学农学院/国家玉米改良中心河北分中心/河北省作物种质资源实验室,保定 071001,河北农业大学农学院/国家玉米改良中心河北分中心/河北省作物种质资源实验室,保定 071001

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河北省高等学校科学技术研究重点项目(ZD201737)、国家重点研发计划(2016YFD0101204-3)


Analysis of Stalk Fiber Quality and Combining Ability in Different Maize Heterotic Groups
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College of Agronomy, Hebei Agricultural University / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of Hebei, Baoding 071001,College of Agronomy, Hebei Agricultural University / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of Hebei, Baoding 071001,College of Agronomy, Hebei Agricultural University / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of Hebei, Baoding 071001,College of Agronomy, Hebei Agricultural University / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of Hebei, Baoding 071001,College of Agronomy, Hebei Agricultural University / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of Hebei, Baoding 071001,College of Agronomy, Hebei Agricultural University / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of Hebei, Baoding 071001,College of Agronomy, Hebei Agricultural University / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of Hebei, Baoding 071001

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    摘要:

    研究建立快速测定玉米茎秆纤维品质的近红外模型,用于评价不同杂种优势群的玉米材料的茎秆纤维品质。分析纤维品质性状的一般配合力,筛选纤维品质和配合力好的材料,为培育抗倒耐密玉米品种提供借鉴。本试验以玉米茎秆基部第3节间和第4节间为材料,利用近红外光谱漫反射光谱(NIRS)技术建立测定秸秆中纤维素、半纤维素和木质素的数学模型。基于建立的纤维品质模型对一年两点的94份自交系和376份杂交种的茎秆纤维品质进行预测和分析。对不同杂种优势群间整体差异进行方差分析,并评价其一般配合力效应。结果表明,各组分数学模型的校正决定系数、交叉验证和外部验证决定系数在0.801-0.998之间,各项误差在0.131-1.454之间,该模型准确性高,能较为准确预测玉米茎秆的纤维品质,为抗倒伏种质资源材料的鉴定提供参考。在各杂种优势群中,旅大红骨群的纤维品质最低,P群和唐四平头群纤维品质及其一般配合力正向效应较好。共筛选出了9个纤维品质好且一般配合力正向效应高的自交系。其中P群有2个,唐四平头群有1个,兰卡斯特群有2个,瑞德群2个,混合群2个。

    Abstract:

    The objective of this experiment was to establish the model of near infrared for determining corn stalk fiber quality rapidly, Which is used for strawing fiber quality evaluation of different heterotic groups of maize. The general combining ability(GCA) of fiber quality traits are analyzed, and the lines with good fiber quality and high positive GCA effect are screened to provid reference for the cultivation of lodging resistant maize hybrids. With crushed the third internode and fourth internode of corn stalk as the material, the mathematical models of cellulose and hemicellulose and lignin were established in taking near infrared diffuse reflectance spectroscopy (NIRS) technology. The fiber quality models were used to calculate the stem fiber quality of 94 inbred lines and 376 hybrids, which were planted at two environments a year. Variance analysis of the overall difference in different heterotic groups. The results show that the mathematical models the correction coefficient of determination, cross validation and external are between 0.801-0.998, the error (RMSEC, RMSECV, RMSEP) are between 0.131-1.454. This correction model has high accuracy, which could predict the fiber quality of maize stalk accurately. Therefore,it could provide a reference for the identification of lodging resistant germplasm resources. The fiber quality of LRC is the lowest in these heterosis groups. The fiber quality of P group and TangSPT group are better than other heterosis groups, and it also have a high forward effect in GCA. There are 9 inbred lines in this study, which are not only good quality fiber but also GCA with high positive effect,and there are 2 lines in the P group,1 line in the TangSPT group,2 lines in the Lancaster group,2 lines in the Reid group,2 lines in the Mix group.

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关红辉,刘文斯,郭晋杰,等.不同杂种优势群玉米茎秆纤维品质及配合力分析[J].植物遗传资源学报,2018,19(5):925-936.

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  • 收稿日期:2018-01-09
  • 最后修改日期:2018-06-12
  • 录用日期:2018-05-03
  • 在线发布日期: 2018-09-14
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