Agronomy (Aug 2021)

Multi-Trait Selection Indices for Identifying New Cassava Varieties Adapted to the Caribbean Region of Colombia

  • Rommel León,
  • Amparo Rosero,
  • Jorge-Luis García,
  • Julio Morelo,
  • Alfonso Orozco,
  • Gabriel Silva,
  • Víctor De la Ossa,
  • Ender Correa,
  • Carina Cordero,
  • Leonardo Villalba,
  • John Belalcazar,
  • Hernán Ceballos

DOI
https://doi.org/10.3390/agronomy11091694
Journal volume & issue
Vol. 11, no. 9
p. 1694

Abstract

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In Colombia, the highest cassava production comes from the semi-arid region of the Atlantic Coast with relatively low yield for fresh consumption (≤11 t/ha). Development of improved varieties is based on a plant ideotype which integrates a group of desirable traits independently measured in the field. However, selecting high performance genotypes for several traits simultaneously is a complex process. Sixteen genotypes were evaluated under four environmental conditions (localities) of the Colombian Caribbean region (Cereté, Carmen de Bolivar, Agustín Codazzi, and Sevilla), and two production cycles (2016/2017–2017/2018) in order to assess phenotypic expression of selected traits, their stability, and utility in genotype selection. Selection of promising genotypes should consider both their superiority and stability. Genotypes SM3106-14, GM1692-56, CM9456-12, and GM214-62 were selected based on their agronomic performance. In addition, frequency analysis of sensorial data showed that genotypes CM9456-12, SM1127-8, SM3553-27, and SM3562-32 were preferred by panelists who assessed, color, flavor, texture, and root shape. Determination of superiority through across-environments, multi-trait selection index allows identifying genotypes with superior performance. However, selection was improved when local multi-trait selection indices were included—phenotypic stability determination (through Lin and Binns index and AMMI model) supported an adequate selection of superior and stable cassava genotypes. The inclusion of palatability response and quality features determination in cassava genotypes can be recommended to identify genotypes with higher adoption rates by farmers and consumers.

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