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在生物分类中许多指标往往是不确定的,即界限是模糊的。同时这样模糊的指标又有许多个,列此类没有明确界限带有模糊性问题,用摸糊聚类法分析是一种简便可靠,避免主观随意性和片面性的极好方法。本文根据模糊集合和模糊集合之间的隶属系数的定义,给出玉米自交系在产量构成因素上进行模糊聚类的各隶属函数,并就延边农学院1982年玉米育种试验中9个玉米自交系进行模糊聚类分析,结果,将9个自交系在产量构成的五个因素上分成5类。根据分类结果和多年的育种实践,讨论了此种分类方法对玉米自交系的改良,玉米杂交种的选配,改良群体的组成等方面的意义。模糊聚类在近两年内有极迅速的发展,在许多领域已有成功的先例。但把此理论用于玉米自交系的分类在国内外尚未见报道,此次在玉米育种上的应用乃是第一次,所以可以称为是一种有意义的尝试。
Many of the indicators in taxonomy are often uncertain, ie the boundaries are ambiguous. At the same time, there are many such ambiguous indicators. There is no definite boundary with ambiguity in this category. Fuzzy clustering analysis is an easy and reliable way to avoid subjective arbitrariness and one-sidedness. Based on the definition of membership coefficients between fuzzy sets and fuzzy sets, this paper presents the membership functions of fuzzy inference of maize inbred lines in terms of yield components. In this paper, The results of fuzzy cluster analysis of nine inbred lines divided the five inbred lines into five categories. Based on the classification results and years of breeding practice, this paper discusses the significance of this classification method in improvement of maize inbred lines, selection of maize hybrids and composition of improved populations. Fuzzy clustering has developed very rapidly in the past two years and has been a successful precedent in many fields. However, the application of this theory to the classification of maize inbred line has not been reported at home and abroad. The application of this theory in maize breeding is the first time, so it can be called a meaningful attempt.