转基因甘蓝型油菜亲和性等级识别方法构建

为预测转基因甘蓝型油菜商业释放的基因流环境生态风险,基于模糊数学中模糊聚类分析与模糊模型识别,并结合生物统计学相关知识,构建了转基因甘蓝型油菜亲和性等级识别方法.该方法包含转基因甘蓝型油菜种间组合亲和性的模糊聚类分析、模糊聚类结果F检验、种间组合风险等级划分和风险等级模式识别4个基本步骤.并在等级模式识别步骤中针对样本数据收集情况的不同,构建了不同的等级识别方法,与传统聚类的硬性划分相比更具灵活性.以收集的常规油菜杂交实验数据聚类形成6个风险等级模式,将一甘蓝型油菜种间杂交实验进行亲和性等级识别为例对该方法进行了演示,论证了该方法具可操作性.

Predicting transgene flow by modeling compatibility with Brassia napus

To predict the environmental risk of the gene flow of transgenic B.napus after commercialization, a protocol for assessing its compatibility risks was proposed by the fuzzy clustering analysis and fuzzy model identification along with the biometric theory. The protocol included four steps: the fuzzy clustering analysis of interspecific crossing compatibility of transgenic B.napus, the F test of the outcome of the fuzzy clustering analysis, ranking of the risk of the interspecific crossing compatibility, and identifying the risk ranks. At the final stage of the protocol, various methods for identifying risk ranks were proposed to accommodate different data collection situations, therefore this approach was more flexible than the rigid ranking by the traditional clustering analysis. Subsequently, the protocol was demonstrated in a case study of the experimental data of common B.napus, and six ranks of risks were established, and the risk rank of the interspecific compatibility was identified successfully in a crossing experiment of B.napus. These results proved that the protocol proposed was operational.