Multi-Trait selection indices for identifying new cassava varieties adapted to the Caribbean Region of Colombia

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 per-formance. However, selection was improved when local multi-trait selection indices were includ-ed—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 re-sponse 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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Bibliographic Details
Main Authors: León, Rommel, Rosero, Elvia Amparo, García, Jorge Luis, Morelo, Julio, Orozco, Alfonso, Silva, Gabriel, Ossa, Víctor de la, Correa, Ender, Cordero, Carina, Villalba, Leonardo, Belalcázar, John Eiver, Ceballos, Hernán
Format: Journal Article biblioteca
Language:English
Published: MDPI 2021-08-25
Subjects:variety choice, genotype environment interaction, plant breeding, genotypes, food security, elección de variedades, interacción genotipo ambiente, fitomejoramiento,
Online Access:https://hdl.handle.net/10568/114959
https://doi.org/10.3390/agronomy11091694
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Summary: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 per-formance. However, selection was improved when local multi-trait selection indices were includ-ed—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 re-sponse and quality features determination in cassava genotypes can be recommended to identify genotypes with higher adoption rates by farmers and consumers.