Phenotypic correlation network analysis of garlic variables

Abstract

In this paper we applied weighted correlation networks in order to discover correlation structures and link patterns of sixteen garlic variables related to leaf, bulb and other vegetative and growth variables. By using the Fruchterman-Reingold algorithm, correlation clusters and other structures could be easily identified. Overall, we detected a link between clusters of leaf and bulb variables. The harvest index was negatively associated with vegetative variables, as expected. In addition, bulb growth rate was positively associated with leaf area rate, root growth rate and plant liquid assimilation rate.