Genetic Diversity Assessment through Cluster and Principal Component Analysis in Potato (Solanum tuberosum L.) Genotypes for Processing Traits

Abstract

Potato (Solanum tuberosum L.) is the third most important food crop in the world in terms of consumption after rice and wheat. It can be used as fresh products and commercially processed foods such as French fries and chips. In Ethiopia, the released varieties have not met the consumers' demand for processing purpose. Therefore, the objective of this study was to estimate the magnitude of genetic distance and to identify the major traits contributing for processing quality traits among the studied genotypes by using cluster and principal component analysis. The experiment was conducted during the main rainy season of 2017 at Holetta, Ethiopia. A total of 24 potato genotypes were evaluated for 23 quantitative traits in randomized complete block design with three replications. The genetic distances among the 24 potato genotypes ranged from 2.73 to 10.94 and the genotypes were grouped into six clusters based on quantitative traits. Cluster II consisted of 33.33%, Cluster I contained 29.17%, cluster III had 16.67% and cluster IV had 12.50% potato genotypes, while cluster V and VI contained each one (4.17%) genotype. The first six principal components accounted for 88.20% for the observed variations among 24 potato genotypes. Of these, the first, the second and the third principal components constituted 34.30%, 20.70% and 12.00% of the variation, respectively. In conclusion, according to cluster mean and principal component analysis cluster II and cluster VI contained the best genotypes for highest total tuber yield, marketable tuber yield, specific gravity of tuber, dry matter content and total starch content traits and could be used as parents in crossing program targeted at developing processing type varieties.