陕西省农家小麦品种主要加工品质特性及其聚类分析

来源 :西北农业学报 | 被引量 : 0次 | 上传用户:tian1_sheng2_wo3_cai
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研究测定了陕西省131个主要农家小麦品种的粗蛋白含量、籽粒硬度和全麦粉SDS-沉淀值,并根据这3个品质性状,利用离差平方和法对供试品种进行了总聚类和分区聚类分析。总聚类分析中,供试品种被聚为4类。第Ⅰ类品种粗蛋白含量和沉淀值均较高,但其籽粒硬度最小;第Ⅱ类品种粗蛋白含量和沉淀值最小,籽粒硬度却很高;第Ⅲ类品种籽粒硬度、粗蛋白含量和沉淀值均较高,3个品质指标综合平衡较好;第Ⅳ类品种籽粒硬度、粗蛋白含量均较高,沉淀值居中。在分区聚类分析中,陕北和陕南品种分别被聚为两类。陕北的两类品种间沉淀值相似,籽粒硬度差异较大。陕南的两类品种间籽粒硬度和淀淀值均差异较大。关中品种品质性状变异较大,被聚为3类,第Ⅰ类各品质指标与陕南品种第Ⅰ类相似,第Ⅲ类各品质指标与陕北第Ⅱ类及陕南第Ⅱ类相似,且这3类中绝大部分品种在总聚类分析中都被聚在第Ⅲ类中。 The crude protein content, grain hardness and SDS-sedimentation value of 131 wheat cultivars in Shaanxi Province were determined. According to the three quality traits, the total variance Partition clustering analysis. In the total cluster analysis, the tested varieties were grouped into four categories. The crude protein content and sedimentation value of the first type of cultivars were higher, but the hardness of the seeds was the lowest. The crude protein content and sedimentation value of the second cultivars were the lowest, but the grain hardness was very high. The hardness, crude protein content and precipitation The values ​​were higher, and the three quality indexes were well balanced. The grain hardness and crude protein content of the fourth type were higher, and the sedimentation value was middle. In the cluster analysis, the varieties in northern Shaanxi and southern Shaanxi were grouped into two categories respectively. The sedimentation values ​​of two types of cultivars in northern Shaanxi are similar, and the hardness of the grains is quite different. There were significant differences in grain hardness and grain size between the two varieties in southern Shaanxi. The quality traits of Guanzhong varieties varied greatly and were grouped into three categories. The quality indexes of the first category were similar to the first category of Southern Shaanxi varieties. The quality indexes of the third category were similar to the second category of Northern Shaanxi and the second category of Southern Shaanxi Most of these three categories were clustered in Category III in the total cluster analysis.
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