中文摘要：

燕麦种质资源是燕麦育种的重要基础，对燕麦遗传多样性的研究不仅有助于种质资源的搜集、管理和利用，也有利于进行核心种质的研究。为了解不同地区燕麦种质资源在农艺性状上的遗传多样性，对74份皮、裸燕麦种质资源13个性状的遗传多样性进行了聚类分析与主成分分析。结果表明：各性状的遗传多样性指数较大，多样性指数最高的是主穗粒重，其次是千粒重和穗长；性状变异系数最大的是单株分蘖数，其后依次为单株粒重和主穗粒重，最小的为株高；根据品种间各性状的遗传差异，通过聚类分析将74份资源材料划分为5类，其中36份皮燕麦资源被分为2类，26份裸燕麦资源被分为2类，7份皮燕麦和5份裸燕麦被分为一类，其中，类群Ⅰ可作为高产育种目标的亲本，类群Ⅲ可作为粒型育种目标的亲本，类群Ⅳ、Ⅴ可作为株高和小穗等育种目标的亲本；8个数量性状主成分分析的结果表明，前4个主成分对变异的累计贡献率达86．27％，第一主成分反应产量，第二主成分反应粒型，第三、第四主成分分别反应分蘖数和株高。

英文摘要：

Oats germplasm are the important basis of oat breeding. The research of oats genetic diversity not only contributed to the collection, management and utilization of germplasm, but also benefited to the conducting of the research of core collection. Genetic diversity of 74 accessions of hulled and naked oat, which were from different sources,were planted in Hohhot in Inner Mongolia Science and Technology Park, and analyzed by cluster analysis and principal component analysis for the purpose of investigating genetic diversity of agronomic characters. The resuits showed that the genetic diversity index of all traits were relatively large, grain weight per plant had the highest genetic diversity index,followed by TGW and panicle length. The variation coefficient of the tillering number per plant was the maximal, while grain weight per plant and the main spike grain weight was the next. The minimum genetic diversity index was presented by plant height. According to genetic difference of each characteristic among varieties, the 74 accessions could be classified into 5 categories by cluster analysis,36 accessions of hulled oat were be classified into 2 categories. And 26 accessions of naked oat were classified into 2 categories. 7 accessions of hulled oat and 5 naked oat were classified into 1 category. The first group could be used as parents of high-yield breeding objectives, the third group could be used as parents of grain shape breeding objectives, the fourth and fifth could be used as parents of plant height and spikelet breeding objectives. The principal component analysis on quantitative characters showed that the accumulative contribution rate of the first four principal components accounted for 86.27% of the total variation accounted ,the first principal component mainly reflected the yield, while the second principal component reflected the grain shape. The third and fifth principal component reflected tiller number and plant height, respectively.