Correlation of resistance to Nilaparvata lugens Stal with secondary metabolites of rice plants

文献类型： 外文期刊

第一作者： Liang, Guang-Wen

作者： Liang, Guang-Wen;Zeng, Ling;Lin, Bing;Yang, Lang;Huang, Feng-Kuan

作者机构：

关键词： Brown planthopper;Nilaparvata lugens Stal;field population;high performance liquid chromatography;model

期刊名称：AFRICAN JOURNAL OF AGRICULTURAL RESEARCH （ 影响因子：0.263； 五年影响因子：0.203 ）

ISSN： 1991-637X

年卷期： 2011 年 6 卷 8 期

页码：

收录情况： SCI

摘要： It is very difficult and complex to distinguish and estimate rice varieties' resistance. Thus, it is necessary to built up a simple, nicety, steady and speedy method of resistant appraisement. Secondary metabolite is the important basic substance of rice resistance. The correlation of rice plant resistance to brown planthopper (BPH), Nilaparvata lugens Stal, with 20 distinct secondary metabolite high performance liquid chromatography (HPLC) peaks were investigated. Two resistance prediction models were established through multiple regression analysis. Model A was established for the resistance of brown planthopper (BPH) field population II, and model B was established for the resistance of field population Bangladesh. The correlations between the BPH resistance levels (Y) of rice varieties and the peak areas (X) were significant (R' = 0.961 and 0.942 for model A and model B respectively, p<0.01). The results showed that in model A, peak 2, 5, 6, 7, 11, 12, 13, 15, 16, 17 and 18 were the secondary metabolites that affected the resistance to BPH. In model B, peak 1, 2, 5, 6, 7, 8, 10, 12, 13, 14, 15, 16, and 17 were the metabolite peaks that affected resistance. It was demonstrated that the resistant activity of rice varieties to BPH was closely associated with quantitative combinations of many secondary metabolites, which suggested that the BPH resistance of rice plants was the results of actions of several secondary metabolites that varied in contributions. The validation results showed that field bioassay scores agreed with the simulated scores well, indicating that these models were useful and accurate. And these models can be used as fast assistant-method to evaluate the resistance of rice plant to BPH and assist the selection of resistant rice plants for breeding.

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