基于向日葵DUS测试的遗传多样性分析及代码分级
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摘要
通过对来源于全国各地的253份向日葵种质资源进行相关、回归、遗传多样性分析,为向日葵种质资源开发、利用、评价提供参考;利用2倍标准差法对数量性状进行代码分级,并采用频次分析对代码分级的科学性进行探讨,为向日葵DUS测试[对申请保护的植物新品种进行特异性(distinctness)、一致性(uniformity)和稳定性(stability)的栽培鉴定试验或室内分析测试]指南的修订提供依据。通过相关分析和回归分析发现叶片大小与叶长、叶宽,瘦果大小与瘦果长度、瘦果宽度存在极显著相关关系且存在着一定的线性函数关系。通过性状代码分级和频次分析发现苞叶密度、舌状花密度、叶长、瘦果厚度分级比较少,且数据较为集中,不利于区分不同品种。瘦果长度、瘦果宽度、瘦果大小虽然分级较多,但不符合正态分布,表明代码分级不够科学合理。而主茎叶数、叶宽、叶片大小、花盘直径、株高这些性状数据分布符合正态分布,代码分级较为科学,便于区分不同品种。造成代码分级不合理的主要原因是人工选择的结果,同时也受品种保护意识淡薄、法律法规不完善的影响。
This experiment with 253 sunflower germplasm resources from all parts of the country carried correlation, regression, genetic diversity analysis which provided reference for the development, utilization and evaluation of sunflower germplasm resources. The quantitative traits were classified by the method of double standard deviation, and the scientific nature of code classification was discussed by frequency analysis, which laid the basis for the revision of sunflower DUS testing guideline. Through correlation and regression analysis, it was found that the leaf size had a very significant correlation with the leaf length and leaf width, and the seed size had very significant correlation with the seed length and seed width, and there had a certain linear functional relationship between them. According to character code classification and frequency analysis, it was found that the classification of bract density, ligulate flower density, leaf length and seed thickness was relatively small, and the data were relatively concentrated, which was not conducive to distinguishing different varieties. Although seed length, seed width and seed size were classified much, they did not conform to the normal distribution, it showed that the code classification was not scientific and reasonable. However, the data distribution of leaves of main stem, leaf width, leaf size, disc diameter and plant height conformed to the normal distribution, code classification is more scientific and useful to distinguish different varieties. The main reason for the unreasonable code classification is the result of manual selection, which is also affected by poor awareness of variety protection and imperfect laws and regulations.
This experiment with 253 sunflower germplasm resources from all parts of the country carried correlation, regression, genetic diversity analysis which provided reference for the development, utilization and evaluation of sunflower germplasm resources. The quantitative traits were classified by the method of double standard deviation, and the scientific nature of code classification was discussed by frequency analysis, which laid the basis for the revision of sunflower DUS testing guideline. Through correlation and regression analysis, it was found that the leaf size had a very significant correlation with the leaf length and leaf width, and the seed size had very significant correlation with the seed length and seed width, and there had a certain linear functional relationship between them. According to character code classification and frequency analysis, it was found that the classification of bract density, ligulate flower density, leaf length and seed thickness was relatively small, and the data were relatively concentrated, which was not conducive to distinguishing different varieties. Although seed length, seed width and seed size were classified much, they did not conform to the normal distribution, it showed that the code classification was not scientific and reasonable. However, the data distribution of leaves of main stem, leaf width, leaf size, disc diameter and plant height conformed to the normal distribution, code classification is more scientific and useful to distinguish different varieties. The main reason for the unreasonable code classification is the result of manual selection, which is also affected by poor awareness of variety protection and imperfect laws and regulations.
引文
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[4]谭美莲,严明芳,汪磊,等.世界特种油料种质资源保存概况.植物遗传资源学报,2011,12(3):339-345.
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[11]万述伟,宋凤景,郝俊杰,等. 271份豌豆种质资源农艺性状遗传多样性分析.植物遗传资源学报,2017,18(1):10-18.
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[13]聂石辉,彭琳,王仙,等.鹰嘴豆种质资源农艺性状遗传多样性分析.植物遗传资源学报,2015,16(1):64-70.
[14]李鸿雁.扁蓿豆种质资源遗传多样性的研究.呼和浩特:内蒙古农业大学,2008.
[15]贺晨帮,宗绪晓.豌豆种质资源形态标记遗传多样性分析.植物遗传资源学报,2011,12(1):42-48.
[16]赖俊生,江锡兵,龚榜初,等.板栗地方品种质量性状多样性分析.浙江农业科学,2016,57(8):1196-1200.
[17]李玉发,梁军,窦忠玉,等.食用向日葵杂交种主要性状与产量间的灰色关联分析.山东农业科学,2011(12):19-21.
[2]Singh J. Standardization of growing substrates and NPK doses for growth and flowering of alstroemeria(Alstroemeria hybrida L.). Nauni:Dr Yashwant Singh Parmar University of Horticulture and Forestry,2013.
[3]Healy W E,Wilkins H F. Alstroemeria culture.Herbertia,1986,42:16-20.
[4]谭美莲,严明芳,汪磊,等.世界特种油料种质资源保存概况.植物遗传资源学报,2011,12(3):339-345.
[5]中华人民共和国农业农村部.中华人民共和国农业植物品种保护名录(第10批),2016.
[6]中华人民共和国农业农村部.植物新品种特异性、一致性和稳定性测试指南:向日葵.北京:中国农业出版社,2013:4-6.
[7]刘孟军.枣树数量性状的概率分级研究.园艺学报,1996(2):105-109.
[8]UPOV. Document TGP/9/1(draft:7):Examining Distinctness,2006:26-32.
[9]唐浩.植物品种特异性、一致性、稳定性测试总论.北京:中国农业出版社,2017:83-87.
[10]冯章丽,于文泉,顾广军,等.东北部分地区山荆子种质资源表型多样性及聚类分析.植物遗传资源学报,2016,17(6):984-992.
[11]万述伟,宋凤景,郝俊杰,等. 271份豌豆种质资源农艺性状遗传多样性分析.植物遗传资源学报,2017,18(1):10-18.
[12]刘玉皎,宗绪晓.青海蚕豆种质资源形态多样性分析.植物遗传资源学报,2008,9(1):79-83.
[13]聂石辉,彭琳,王仙,等.鹰嘴豆种质资源农艺性状遗传多样性分析.植物遗传资源学报,2015,16(1):64-70.
[14]李鸿雁.扁蓿豆种质资源遗传多样性的研究.呼和浩特:内蒙古农业大学,2008.
[15]贺晨帮,宗绪晓.豌豆种质资源形态标记遗传多样性分析.植物遗传资源学报,2011,12(1):42-48.
[16]赖俊生,江锡兵,龚榜初,等.板栗地方品种质量性状多样性分析.浙江农业科学,2016,57(8):1196-1200.
[17]李玉发,梁军,窦忠玉,等.食用向日葵杂交种主要性状与产量间的灰色关联分析.山东农业科学,2011(12):19-21.
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