摘要
选取来源于中国11个省份和其他9个国家的347份粳稻选育品种作为试验材料,分析了自然低温和冷水胁迫下,不同来源粳稻选育品种孕穗期的耐冷性及主要农艺性状的表型差异和聚类特点。研究表明,在自然低温和冷水胁迫下各省份或国家粳稻选育品种主要农艺性状及其冷水反应指数有明显的差异。在自然低温和冷水胁迫下,云南和日本品种的孕穗期结实率及其冷水反应指数均较高,表现出较强的孕穗期耐冷性。从总体趋势上看,在自然低温下,除个别省份外,我国纬度相对较高的北方省份品种的孕穗期耐冷性强于纬度相对较低的南方省份品种;而在冷水胁迫下,品种的耐冷性与其来源地的关系并不密切,没有呈现出一定的规律性。此外,聚类结果表明,不同省份或国家粳稻选育品种的聚类结果与其品种的地理来源均有一定的相关性,而与自然条件相比,冷水胁迫下粳稻选育品种的聚类结果与其品种的地理来源的相关性更为密切。
The cold tolerance at the booting stage and main agronomic traits of 347 improved japonica rice varieties,which were from nine countries and eleven provinces of China,were evaluated under natural low temperature and cold water irrigation and the cluster analysis of the varieties was conducted.The results showed that the main agronomic traits associated with cold tolerance and cold water response index（CRI）among the varieties were significant different under natural low temperature and cold water irrigation.Under both conditions seed setting rate at the booting stage and CRI of the improved rice varieties from Yunnan Province and Japan were higher than those of other countries or provinces.From the overall trend,The cold tolerance at booting stage of the varieties from relatively higher latitude of north provinces were stronger than those from relatively low latitude of southern provinces except few provinces under natural low temperature.However,under cold water irrigation,the relationship between the cold tolerance and origin of varieties was not close and did not show a regularity.In addition,the cluster analysis of the improved japonica rice varieties were associated with geographical locations.Moreover,the results was associared more closely with origins of varieties under cold water irrigation than natural condition.
出处
《植物遗传资源学报》
CAS
CSCD
北大核心
2012年第5期739-747,共9页
Journal of Plant Genetic Resources
基金
国家科技支撑项目(2006BAD13B01)
"973"项目(2004CB117201)
作物种质资源保护项目[NB10-2130135(25-30)-01]
国家科技基础条件平台项目(2005DKA21001-01)
关键词
粳稻选育品种
孕穗期
耐冷性
自然低温
冷水胁迫
聚类分析
Improved japonica rice variety
Booting stage
Cold tolerance
Natural low temperature
Cold water irrigation
Cluster analysis
