A Nonparametric Test on Differences in Growth Direction of Rice Primary Roots

Japanese Journal of Crop Science

Keisuke NEMOTO¹  Jun ABE¹  Shigenori MORlTA¹  Dong Xu HU¹ 

关键词: Kolmogorov-Smirnov two sample test;    イネ;    Nonparametric method;    コルモゴロフーシミルノフ法;    Oryza sativa L.;    根の分布;    Rice plant;    ノンパラメトリック法;    Root distribution;   

DOI  :  10.1626/jcs.59.572

学科分类：农业科学（综合）

来源: Nihon Sakumotsu Gakkai / Crop Science Society of Japan

【 摘 要 】

Sometimes there is a need to examine the spatial distribution of roots in studies of rice plants. For analysis of growth direction of primary roots (GDPR), a statistical method requiring an assumption of a given distribution is not available, because the distribution pattern of GDPR is not always known. A nonparametric method will be useful for analysis of such an unknown distribution. We tested the difference in distribution of GDPR with Kolmogorov-Smirnov two sample test method among three samples of rice cultivars, Nankin 11 (A), Dobashi 1 (B) and Mubo-aikoku (C). The relative cumulative frequency distribution of GDPR (Sn(x)) was calculated for each sample. When the maximum absolute difference of Sn(x) was larger than the critical value (Dα) between two samples, we concluded that the two samples have significantly different distributions of GDPR at the level of α. The result of the test indicated a difference in distribution of only A from that of B or C, though it seemed in histogram that B had a distribution pattern of GDPR intermediate beetween those of A and C. That suggests the effectiveness of nonparametric methods for precise analysis of GDPR.

【 授权许可】

Unknown