Abstract

Common bean provides diet rich in vitamins, fiber, minerals, and protein, which could contribute into food security of needy populations in many countries. Developing genotypes that associate favorable agronomic and grain quality traits in the common bean crop could increase the chances of adopting new cultivars black bean. In this context, the present study aimed at selection of superior black bean lines using multi-variate indexes, Smith-Hazel-index, and genotype by yield*trait biplot analysis. These trials were conducted in Campos dos Goytacazes - RJ, in 2020 and 2021. The experimental design used was randomized blocks, with 28 treatments and three replications. The experimental unit consisted of four rows 4.0 m long, spaced at 0.50 m apart, with a sowing density of 15 seeds per meter. The two central rows were used for the evaluations. The selection of superior genotypes was conducted using the multiple trait stability index (MTSI), multi-trait genotype-ideotype distance index (MGIDI), multi-trait index based on factor analysis and genotype-ideotype distance (FAI-BLUP), Smith-Hazel index, and Genotype by Yield*Trait Biplot (GYT). The multivariate indexes efficiently selected the best black bean genotypes, presenting desirable selection gains for most traits. The use of multivariate indexes and GYT enable the selection of early genotypes with higher grain yields. These lines G9, G13, G17, G23, and G27 were selected based on their performance for multiple traits closest to the ideotype and could be recommended as new varieties.

Details

Title
Multi-trait index: selection and recommendation of superior black bean genotypes as new improved varieties
Author
Ambrósio, Moisés; Rogério Figueiredo Daher; Raiane Mariani Santos; Josefa Grasiela Silva Santana; Ana Kesia Faria Vidal; Maxwel Rodrigues Nascimento; Cleudiane Lopes Leite; Gomes de Souza, Alexandre; Rafael Souza Freitas; Wanessa Francesconi Stida; João Esdras Calaça Farias; Benedito Fernandes de Souza Filho; Leonardo Cunha Melo; dos Santos, Paulo Ricardo
Pages
1-12
Section
Research
Publication year
2024
Publication date
2024
Publisher
BioMed Central
e-ISSN
14712229
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3066881481
Copyright
© 2024. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.