Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits

PLoS One. 2021 Dec 29;16(12):e0260997. doi: 10.1371/journal.pone.0260997. eCollection 2021.

Abstract

Breeding programs of the species Coffea canephora rely heavily on the significant genetic variability between and within its two varietal groups (conilon and robusta). The use of hybrid families and individuals has been less common. The objectives of this study were to evaluate parents and families from the populations of conilon, robusta, and its hybrids and to define the best breeding and selection strategies for productivity and disease resistance traits. As such, 71 conilon clones, 56 robusta clones, and 20 hybrid families were evaluated over several years for the following traits: vegetative vigor, incidence of rust and cercosporiosis, fruit ripening time, fruit size, plant height, canopy diameter, and yield per plant. Components of variance and genetic parameters were estimated via residual maximum likelihood (REML) and genotypic values were predicted via best linear unbiased prediction (BLUP). Genetic variability among parents (clones) and hybrid families was detected for most of the evaluated traits. The Mulamba-Rank index suggests potential gains up to 17% for the genotypic aggregate of traits in the hybrid population. An intrapopulation recurrent selection within the hybrid population would be the best breeding strategy because the genetic variability, narrow and broad senses heritabilities and selective accuracies for important traits were maximized in the crossed population. Besides, such strategy is simple, low cost and quicker than the concurrent reciprocal recurrent selection in the two parental populations, and this maximizes the genetic gain for unit of time.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Coffea / genetics*
  • Disease Resistance / genetics*
  • Environment
  • Genotype
  • Hybridization, Genetic*
  • Likelihood Functions
  • Plant Breeding*
  • Plant Diseases / genetics*
  • Quantitative Trait, Heritable*

Grants and funding

This work was financially supported by the Brazilian Coffee Research and Development Consortium (CBP&D/Café), the National Institute of Science and Technology of Coffee (INCT-Café), the Foundation for Research Support of the State of Minas Gerais (FAPEMIG), the National Council of Scientific and Technological Development (CNPq), and the Coordination for the Improvement of Higher Education Personnel (CAPES) - Finance code 001. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.