D. Dubberstein, F.L. Partelli, J.H.S. Guilhen, W.P. Rodrigues, J.C. Ramalho, A.I. Ribeiro-Barros
Published: May 30, 2020
Genet. Mol. Res. 19(2): GMR18541
DOI: https://doi.org/10.4238/gmr18541
Cite this Article:
D. Dubberstein, F.L. Partelli, J.H.S. Guilhen, W.P. Rodrigues, J.C. Ramalho, A.I. Ribeiro-Barros (2020). Biometric traits as a tool for the identification and breeding of Coffea canephora genotypes. Genet. Mol. Res. 19(2): GMR18541. https://doi.org/10.4238/gmr18541
About the Authors
D. Dubberstein, F.L. Partelli, J.H.S. Guilhen, W.P. Rodrigues, J.C. Ramalho, A.I. Ribeiro-Barros
Corresponding Author
F.L. Partelli
Email: partelli@yahoo.com.br
ABSTRACT
Cross-pollination and gametophytic self-incompatibility reduce the stability of Coffea canephora genotypes. This is an important crop for Brazil, the largest producer of this type of coffee and also a major exporter. The study of biometric characteristics is essential to assist in the selection of promising plant materials. We examined the diversity of morpho-agronomic traits of genotypes of C. canephora cv. Conilon through the evaluation of branch and leaf parameters. Assessments included plagiotropic branch length, number of nodes in plagiotropic branches, distance between nodes in plagiotropic branches, orthotropic branch length, number of nodes in orthotropic branch, distance between nodes in orthotropic branch, plant height, canopy diameter, leaf length, leaf width, and leaf area in two periods. The data from the 43 coffee genotypes were tested by multivariate and cluster analyses. Six groups were formed by the Tocher optimization method, and five groups by the unweighted pair group method with arithmetic mean (UPGMA) hierarchical method, suggesting an important genetic variability among plant materials. Both Tocher optimization and UPGMA hierarchical methods were consistent for clustering the genotypes, ordering them in six and five dissimilar groups, respectively, with genotypes 25 and 37 standing out with the greatest dissimilarity, constituting isolated groups by both methods. Pearson’s correlation ranged from very weak to very strong, positive and negative, among the characteristics, as also shown by principal component analyses. These analyses indicated the morpho-agronomic traits with a greater degree of correlation, assisting in the choice of promising plant materials. The genetic parameters estimates demonstrate genetic variability and thus breeding potential within the Conilon coffee genotypes studied. These results emphasize the usefulness of biometric evaluations as a tool for the identification and breeding of genotypes to compose new Conilon coffee cultivars.
Keywords: Biometrics, Breeding, Clustering, Conilon coffee, Multivariate analysis.