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| 不同基因型水稻种质对黑条矮缩病抗性的初步分析 | |
| 引用本文： | 李爱宏,戴正元,季红娟,张小祥,李育红,潘存红,张洪熙,潘学彪.不同基因型水稻种质对黑条矮缩病抗性的初步分析[J].扬州大学学报(农业与生命科学版),2008,29(3). |
| 作者姓名： | 李爱宏 戴正元 季红娟 张小祥 李育红 潘存红 张洪熙 潘学彪 |
| 作者单位： | 1. 江苏里下河地区农业科学研究所/国家水稻改良中心南京分中心,江苏,扬州,225007;扬州大学,江苏省作物遗传生理重点实验室,江苏,扬州,225009 2. 江苏里下河地区农业科学研究所/国家水稻改良中心南京分中心,江苏,扬州,225007 3. 扬州大学,江苏省作物遗传生理重点实验室,江苏,扬州,225009 |
| 基金项目： | 江苏省自然科学基金资助项目 |
| 摘 要： | 对包含不育系、中籼稻恢复系、粳稻恢复系和常规粳稻等不同类型在内的175份水稻种质进行水稻黑条矮缩病的自然诱发鉴定,同时调查粳稻条纹叶枯病的发病率,通过聚类分析等方法进行抗感分类和评价.结果表明: 水稻黑条矮缩病与条纹叶枯病呈相互独立的遗传关系;不同基因型水稻种质对黑条矮缩病的抗性存在极显著差异,可分为抗/高抗、中抗、中感、感和高感等5种类型,三系早籼稻不育系基本为感或高感型,绝大多数的中籼稻恢复系为抗病型,通过籼粳杂交培育的粳稻恢复系基本为感或中感型,而常规粳稻中分布有抗、中抗、中感、感和高感的不同基因型.筛选抗性种质,加以创新和改良,可有效开展水稻黑条矮缩病抗性育种应用研究. |
| 关 键 词： | 水稻 黑条矮缩病 种质 抗性 聚类分析 |
Preliminary analysis on resistance of rice black-streaked dwarf viral visease for germplasms with different gene-types |
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| LI Ai-hong,DAI Zheng-yuan,JI Hong-juan,ZHANG Xiao-xiang,LI Yu-hong,PAN Cun-hong,ZHANG Hong-xi,PAN Xue-biao.Preliminary analysis on resistance of rice black-streaked dwarf viral visease for germplasms with different gene-types[J].Journal of Yangzhou University:Agricultural and Life Science Edition,2008,29(3). | |
| Authors: | LI Ai-hong DAI Zheng-yuan JI Hong-juan ZHANG Xiao-xiang LI Yu-hong PAN Cun-hong ZHANG Hong-xi PAN Xue-biao |
| Institution: | 1.Lixiahe Reg Agri Res Inst of Jiangsu Prov;Nanjing Subcen of Nat Rice Improvement Cen;Yangzhou 225007;China;2.Key Lab of Crop Gen and Phys of Jiangsu Prov;Yangzhou Univ;Yangzhou 225009;China |
| Abstract: | One hundred and seventy five germplasms including cytoplasmic male sterile lines(CMS),medium-maturity indica restorer lines(IRL),japonica restorer lines(JRL) and regular japonica varieties(RJV) were employed to evaluate the resistance to rice black-streaked dwarf viral disease(RBSDV) under condition of natural induced infection.Meanwhile,the incidence of rice strip viral disease(RSV) also was investigated.The results showed that the genetic relationship between resistance of RSBDV and RSV was independent.Th... |
| Keywords: | rice RSBDV germplasms resistance cluster analysis |
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