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http://repositorio.ufla.br/jspui/handle/1/40118
Title: | Genotype by environment interaction and adaptability of photoperiod-sensitive biomass sorghum hybrids |
Keywords: | Sorghum bicolor Single-cross Toler nonlinear regression Recommendation index Genotypes plus genotype by environment Sorgo Interação genótipo-ambiente Híbridos Regressão não linear |
Issue Date: | 2019 |
Publisher: | Instituto Agronômico de Campinas |
Citation: | DELGADO, I. D. et al. Genotype by environment interaction and adaptability of photoperiod-sensitive biomass sorghum hybrids. Bragantia, Campinas, v. 78, n. 4, p. 509-521, 2019. |
Abstract: | Biomass sorghum is an alternative feedstock to cogenerate energy and produce second-generation ethanol. The aim of this study was to evaluate the Genotype by Environment Interaction (GEI) in biomass sorghum and to identify the hybrids that associate high adaptability and stability using the Toler nonlinear regression, the Genotypes plus Genotype by Environment (GGE) biplot, and the Annicchiarico recommendation index. Thirty-three experimental photoperiod-sensitive single-cross hybrids and three checks were evaluated in relation to the traits: flowering time, plant height, moisture content, green mass yield, and dry mass yield. It was observed that the effects of hybrids, environment, and GEI were expressive. The GEI was predominantly complex for the traits related to the biomass yield. The Toler, GGE biplot and Annicchiarico methods show complementarity. The experimental hybrids 1, 8, 22, 31 and 33 are promising because of associating stability and lower recommendation risk. The hybrids 1 and 8 present broad adaptability, while the hybrids 22, 31 and 33 exhibit specific adaptability to high quality environments. |
URI: | http://repositorio.ufla.br/jspui/handle/1/40118 |
Appears in Collections: | DBI - Artigos publicados em periódicos |
Files in This Item:
File | Description | Size | Format | |
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ARTIGO_Genotype by environment interaction and adaptability of photoperiod-sensitive biomass sorghum hybrids.pdf | 776,65 kB | Adobe PDF | View/Open |
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