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通过对国内外 8个不同粒形的粳稻品种及 2 8个正交组合的粒长 (x1 )、粒宽 (x2 )、粒厚 (x3)、粒重 (y)间相关、回归、主成分分析 ,结果显示 :粒长与粒厚、粒重间偏相关关系均达极显著水平 ,偏相关系数分别为 -0 .6682 和 0 .840 9 ;粒厚与粒重间偏相关关系也达极显著水平 ,偏相关系数为 0 .670 7 ,长、宽、厚对粒重的贡献力大小分别为粒长 >粒厚 >粒宽。直线回归分析显示谷粒性状间回归方程为y =4.175x1 + 0 .83 8x2 + 19.63 0x3-5 2 .0 3 8,复相关系数R2 =0 .73 0 ,方差分析F =2 1.60 3 ,达 1‰以上水平 ,说明y与x间的拟合度较好 ,另外 ,从方程中还可以看出 ,当x1 、x2 、x3变化量相同时 ,粒厚 (x3)对粒重 (y)的影响最大 ,其次为粒长 (x1 )。主成分分析显示第 1主成分的特征根λ1 =1.80 4,贡献率为 45 .0 92 % ,为粒重因子 ;第 2主成分特征根λ2 =1.3 69,贡献率为 3 4.2 2 5 % ,为粒厚因子 ;第 3主成分特征根λ3=0 .70 0 ,贡献率为 17.5 0 % ,为粒宽因子。并提出在选育优质、高产品种时 ,主成分值要选择适宜 ,才能获得优质、高产组合
Through the correlation analysis of grain length (x1), grain width (x2), grain thickness (x3) and grain weight (y) of eight japonica rice varieties with different grain sizes and 28 orthogonal varieties at home and abroad, The results showed that there was a significant correlation between grain length and grain thickness and grain weight, the partial correlation coefficients were -0.6682 and 0.8409, respectively. The correlation between grain thickness and grain weight was also extremely significant Significant level, partial correlation coefficient of 0.6707, length, width, thickness of the contribution to the size of grain size were grain length> grain thickness> grain width. Linear regression analysis showed that the regression equation of grain traits was y = 4.175x1 +0.883 8x2 + 19.63 0x3-5 2 .0 3 8, the correlation coefficient R2 = 0.73 0, the analysis of variance F = 2 1.603, 1 ‰ or above, indicating good fitting between y and x, in addition, it can also be seen from the equation that when the variation of x1, x2, and x3 is the same, the grain thickness (x3) The greatest impact, followed by grain length (x1). The principal component analysis showed that the eigenvalue λ1 of the first principal component is 1.80 4, the contribution rate is 45.92%, which is the grain weight factor; the second principal component eigenvalue λ2 = 1.3 69, the contribution rate is 4.225.5% For the grain thickness factor; the third principal component eigenvalue λ3 = 0.70 0, the contribution rate of 17.5 0%, as the grain-wide factor. And put forward that in breeding high-quality and high-yielding varieties, the principal component values should be selected appropriately to obtain high quality and high yield combination