Self-organizing maps in the study of genetic diversity among irrigated rice genotypes

ABSTRACT. This study presents self-organizing maps (SOM) as an alternative method to evaluate genetic diversity in plant breeding programs. Twenty-five genotypes were evaluated in two environments for 11 phenotypic traits. The genotypes were clustered according to the SOM technique, with variable topology and numbers of neurons. In addition to the SOM analysis, unweighted pair group method with arithmetic mean clustering (UPGMA) was performed to observe the behavior of the clustering when submitted to these techniques and to evaluate their complementarities. Genotype ordering according to SOM was consistent with UPGMA results, evidenced by the basic structure of UPGMA groups being preserved in each group of the maps. Regarding genotype arrangement and the group neighbors, maps involving five neurons presented inferior organization efficiency compared to the six-map arrangements in both environments. It was observed that the organization pattern among the rice genotypes evaluated by the maps was complementary to the UPGMA approach, as observed in all scenarios. It can be concluded that self-organizing maps have the potential to be useful for genetic diversity studies in breeding programs.

摘要。本研究提出采用自组织映射（self-organizing maps, SOM）作为评估植物育种项目中遗传多样性的替代方法。本研究选取25份水稻基因型材料，在2种环境下对11个表型性状开展鉴定与评估。基于SOM方法对基因型材料进行聚类分析，聚类过程采用可变拓扑结构与神经元数量。除SOM分析外，本研究还开展了非加权组平均法（unweighted pair group method with arithmetic mean, UPGMA）聚类分析，以对比不同聚类方法的聚类表现，并评估二者的互补性。基于SOM得到的基因型排序结果与UPGMA结果具有一致性，具体表现为UPGMA聚类组的基本结构在SOM映射的各分组中均得到保留。针对基因型排列与组邻域划分，相较于6神经元映射结构，包含5个神经元的映射结构的组织效率更低，该结果在两种环境下均成立。本研究观察到，通过SOM映射得到的水稻基因型组织模式与UPGMA方法具有互补性，该结论在所有分析场景中均成立。综上可知，自组织映射在植物育种项目的遗传多样性研究中具备应用潜力。