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<p>The search for superior sweet potato genotypes that combine high productivity with pest resistance and tuber quality is essential for advancing the genetic breeding of this crop. This study aimed to estimate genetic parameters and evaluate selection indices to identify promising sweet potato genotypes, focusing on agronomic and physical traits of the roots. In the first experiment, 1223 individuals from crosses between ten previously selected genotypes were evaluated, considering traits such as productivity, resistance to soil pests, and pulp color. The Multi-Trait Genotype-Ideotype Distance Index (MGIDI) demonstrated greater efficacy in genotype selection, surpassing the traditional indices of Mulamba and Mock (Egypt J Genet Cytol Alex 7:40–51, 1978) and Smith (Ann Eugen 7:240–250) and Hazel (Genetics 28:476–490), resulting in the selection of 90 individuals with improved agronomic traits. In the second experiment, these genotypes were subjected to a randomized block design, including 100 treatments, of which 90 were selected clones and 10 were controls. Once again, the MGIDI index stood out, allowing the identification of 15 genotypes with superior agronomic and physical traits, demonstrating great potential for the development of commercial sweet potato cultivars. These results reinforce the importance of using efficient selection indices, such as MGIDI, in achieving genetic gains, leading to advances in the productivity and quality of sweet potato cultivars.</p>

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Estimation of genetic parameters and use of selection indices in the identification of superior sweet potato genotypes

  • 期刊论文

  • 发表日期：

    2025年4月15日

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  • André Dutra Silva Junior,
  • Carlos Nick Gomes,
  • Dalcirlei Pinheiro Albuquerque,
  • Francisca Adaíla da Silva Oliveira,
  • Jéssica Lino Gomes,
  • Luan del Rey Silva de Melo,
  • Pablo Forlan Vargas,
  • Tiago Olivoto,
  • André Ricardo Zeist

摘要

The search for superior sweet potato genotypes that combine high productivity with pest resistance and tuber quality is essential for advancing the genetic breeding of this crop. This study aimed to estimate genetic parameters and evaluate selection indices to identify promising sweet potato genotypes, focusing on agronomic and physical traits of the roots. In the first experiment, 1223 individuals from crosses between ten previously selected genotypes were evaluated, considering traits such as productivity, resistance to soil pests, and pulp color. The Multi-Trait Genotype-Ideotype Distance Index (MGIDI) demonstrated greater efficacy in genotype selection, surpassing the traditional indices of Mulamba and Mock (Egypt J Genet Cytol Alex 7:40–51, 1978) and Smith (Ann Eugen 7:240–250) and Hazel (Genetics 28:476–490), resulting in the selection of 90 individuals with improved agronomic traits. In the second experiment, these genotypes were subjected to a randomized block design, including 100 treatments, of which 90 were selected clones and 10 were controls. Once again, the MGIDI index stood out, allowing the identification of 15 genotypes with superior agronomic and physical traits, demonstrating great potential for the development of commercial sweet potato cultivars. These results reinforce the importance of using efficient selection indices, such as MGIDI, in achieving genetic gains, leading to advances in the productivity and quality of sweet potato cultivars.