Multivariate data analysis for semen quality in two frog species

Marcelo Maia Pereira
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Abstract

Despite the growing body of research on frog reproduction and semen quality, studies employing statistical methods and analyses are scarce. The present study aimed to examine the use of exploratory multivariate data analysis for evaluating the seminal quality of frogs, determining a possible hierarchy among frog species based on semen characteristics, and identifying the most effective clustering strategy. Data on the seminal quality of the butter frog (Leptodactylus ocellatus, native specie) were collected from seven samples, and for the bullfrog (Lithobates catesbeianus, exotic specie), five samples were used, all derived from a literature review. Four distinct clustering strategies were tested: Single Linkage, Unweighted Pair Group Method with Arithmetic Mean (UPGMA), Complete Linkage, and Ward’s method. Exploratory multivariate data analysis could effectively evaluate frog seminal quality, allowing the classification of frog species (both native and exotic) based on semen. Among the tested strategies, UPGMA emerged as the most suitable grouping method.
两种青蛙精液质量的多变量数据分析
尽管有关青蛙繁殖和精液质量的研究越来越多,但采用统计方法和分析的研究却很少。本研究旨在检验探索性多元数据分析在评估蛙类精液质量中的应用,根据精液特征确定蛙类物种之间可能存在的等级,并确定最有效的聚类策略。黄油蛙(Leptodactylus ocellatus,本地品种)的精液质量数据来自七个样本,牛蛙(Lithobates catesbeianus,外来品种)的精液质量数据来自五个样本,所有样本均来自文献综述。测试了四种不同的聚类策略:单链法、算术平均非加权配对组法(UPGMA)、完全链法和沃德法。探索性多元数据分析能有效评估青蛙精液的质量,并能根据精液对青蛙物种(包括本地青蛙和外来青蛙)进行分类。在测试的策略中,UPGMA 是最合适的分组方法。
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