Models for optimizing selection based on adaptability and stability of cotton genotypes
| Autor: | Luiz Paulo de Carvalho, Jeniffer Santana Pinto Coelho Evangelista, Marco Antônio Peixoto, Larissa Pereira Ribeiro Teodoro, Rodrigo Silva Alves, Leonardo Lopes Bhering, Paulo Eduardo Teodoro, F.C. Farias |
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| Přispěvatelé: | MARCO ANTÔNIO PEIXITO, UNIVERSIDADE FEDERAL DE VIÇOSA, JENIFFER SANTANA PINTO COELHO EVANGELISTA, UNIVERSIDADE FEDERAL DE VIÇOSA, RODRIGO SILVA ALVES, UNIVERSIDADE FEDERAL DE VIÇOSA, FRANCISCO JOSÉ CORREA FARIAS, CNPA, LUIZ PAULO DE CARVALHO, CNPA, LARISSA PEREIRA RIBEIRO TEODORO, UNIVERSIDADE FEDERAL DE MATO GROSSO, PAULO EDUARDO TEODORO, UNIVERSIDADE FEDERAL DE MATO GROSSO, LEONARDO LOPES BHERING, UNIVERSIDADE FEDERAL DE VIÇOSA. |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0106 biological sciences
Multi environment trials Restricted maximum likelihood media_common.quotation_subject Agriculture (General) Fibra Vegetal Gossypium hirsutum Best linear unbiased prediction Produtividade Residual 01 natural sciences Adaptability S1-972 Bayesian information criterion Statistics BIC Selection (genetic algorithm) Mathematics media_common General Veterinary Model selection Algodão Agriculture 04 agricultural and veterinary sciences Cotton HMRPGV Estabilidade REML/BLUP Média Harmônica do Desempenho Relativo dos Valores Genéticos multi-environment trials Ensaios multi ambientes 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Bayesian Information Criterion Animal Science and Zoology Akaike information criterion Agronomy and Crop Science 010606 plant biology & botany |
| Zdroj: | Ciência Rural v.51 n.5 2021 Ciência Rural Universidade Federal de Santa Maria (UFSM) instacron:UFSM Ciência Rural, Vol 51, Iss 5 (2021) Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA-Alice) Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
| Popis: | In multi-environment trials (MET), large networks are assessed for results improvement. However, genotype by environment interaction plays an important role in the selection of the most adaptable and stable genotypes in MET framework. In this study, we tested different residual variances and measure the selection gain of cotton genotypes accounting for adaptability and stability, simultaneously. Twelve genotypes of cotton were bred in 10 environments, and fiber length (FL), fiber strength (FS), micronaire (MIC), and fiber yield (FY) were determined. Model selection for different residual variance structures (homogeneous and heterogeneous) was tested using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The variance components were estimated through restricted maximum likelihood and genotypic values were predicted through best linear unbiased prediction. The harmonic mean of relative performance of genetic values (HMRPGV) were applied for simultaneous selection for adaptability, stability, and yield. According to BIC heterogeneous residual variance was the best model fit for FY, whereas homogeneous residual variance was the best model fit for FL, FS, and MIC traits. The selective accuracy was high, indicating reliability of the prediction. The HMRPGV was capable to select for stability, adaptability and yield simultaneously, with remarkable selection gain for each trait. Made available in DSpace on 2022-02-13T01:57:44Z (GMT). No. of bitstreams: 1 MODELS-FOR-OPTIMIZING-SELECTION-BASED-ON-ADAPTABILITY.pdf: 950073 bytes, checksum: 5909b05e3bda8c464287e292d89d14ce (MD5) Previous issue date: 2021 |
| Databáze: | OpenAIRE |
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