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Phenotypic correlation network analysis of garlic variables

Authors :
Mário Puiatti
Anderson Rodrigo da Silva
Paulo Roberto Cecon
Source :
Multi-Science Journal, Vol 1, Iss 3, Pp 9-12 (2018), Multi-Science Journal; Vol. 1 No. 3 (2015); 9-12, Multi-Science Journal; v. 1 n. 3 (2015); 9-12, Multi-Science Journal, Instituto Federal de Educação, Ciência e Tecnologia Goiano (IF Goiano), instacron:IFGO
Publication Year :
2018
Publisher :
Instituto Federal Goiano, 2018.

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.

Details

Language :
Portuguese
ISSN :
23596902
Volume :
1
Issue :
3
Database :
OpenAIRE
Journal :
Multi-Science Journal
Accession number :
edsair.doi.dedup.....8165bce5689a1c7c6f2c3bc975dce808