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为了筛选到优异的种质资源用于水稻育种研究,对来自于不同国家和地区的95份爪哇稻分8期播种,考察了株高、穗长、单株穗数、每穗总粒数、每穗实粒数、千粒重、结实率和播始历期共8个农艺性状。以超级稻Y两优1号为模型构建的理想品种的农艺性状值为参考序列,利用灰色关联模型,求得理想品种与各爪哇稻的关联度系数,根据关联度系数大小对爪哇稻品种排序。结果表明,爪哇稻各农艺性状既受自身遗传背景的影响,也受外部环境因素的影响,但每个性状受环境因素影响的程度不同。爪哇稻各农艺性状间的密切程度不同,要想提高爪哇稻的结实率,应注重筛选每穗实粒数和单株穗数较高的品种。应用灰色关联度分析法筛选出LABELLE-2、IR71217-24-1-2、IAPAR9、MUAT MENIA 16238、C711098、IRAT 109、MD762、MD756、KIYALEH和PANTIA等综合性状较好的爪哇稻品种。
In order to screen excellent germplasm resources for rice breeding research, 95 Javanese rice varieties from different countries and regions were sown in 8 stages. Plant height, spike length, panicles per plant, total grains per panicle, There were 8 agronomic traits per panicle, 1000-grain weight, seed setting rate and initial duration. The agronomic traits of ideal cultivars constructed with the model “Y Liangyou 1” as reference were used as reference sequences, and the correlation coefficients between ideal varieties and Javanese rice were calculated by using the gray relational model. According to the correlation coefficient, the Java rice varieties were sequenced . The results showed that agronomic traits of Javanese paddy were affected not only by their own genetic background but also by external environmental factors, but the extent of each trait was affected by environmental factors. Java agro-agronomic traits between the different levels of closeness, in order to improve the seed rate of Java rice, should focus on screening per panicle and panicle per plant higher number of varieties. Gray relational analysis was used to screen out the best varieties of Java, such as LABELLE-2, IR71217-24-1-2, IAPAR9, MUAT MENIA 16238, C711098, IRAT 109, MD762, MD756, KIYALEH and PANTIA.