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http://www.alice.cnptia.embrapa.br/alice/handle/doc/1178362
Title: | Multi-information analysis to recommend alfalfa cultivars for adaptability and phenotypic stability. |
Authors: | SILVA JÚNIOR, A. C. da![]() ![]() PONTES, D. ![]() ![]() ROSADO, R. D. S. ![]() ![]() VILELA, D. ![]() ![]() FERREIRA, R. de P. ![]() ![]() NASCIMENTO, M. ![]() ![]() BHERING, L. ![]() ![]() CRUZ, C. D. ![]() ![]() |
Affiliation: | ANTÔNIO CARLOS DA SILVA JÚNIOR, UNIVERSIDADE FEDERAL DE VIÇOSA; DAIANA PONTES, UNIVERSIDADE FEDERAL DE VIÇOSA; RENATO DOMICIANO SILVA ROSADO, UNIVERSIDADE FEDERAL DE VIÇOSA; DUARTE VILELA, CNPGL; REINALDO DE PAULA FERREIRA, CPPSE; MOYSES NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA; LEONARDO BHERING, UNIVERSIDADE FEDERAL DE VIÇOSA; COSME DAMIÃO CRUZ, UNIVERSIDADE FEDERAL DE VIÇOSA. |
Date Issued: | 2025 |
Citation: | Crop Breeding and Applied Biotechnology, v. 25, n. 2, e45012525, 2025. |
Description: | This study provided a comprehensive overview of the behavior of alfalfa genotypes in response to environmental variations. We utilized established methods from literature and examined the unique aspects of each approach to collectively create a criterion for recommending cultivars. To this end, seventy-seven genotypes were cultivated with 24 consecutive cuts (months), during two years. Adaptability and stability analyses were conducted using multiple information estimates. The results indicated no significant effect of the genotypes, but there were significant effects from the environment and the genotype-by-environment (GxE) interaction. Through multi-information analysis, genotype 21 was identified as the most promising due to its superior dry matter yield, predictable performance, and responsiveness to environmental changes across various cuts. Combining data and thoroughly describing the behavior of alfalfa genotypes has proven to be an effective method for studying their adaptability and stability. |
Thesagro: | Medicago Sativa Melhoramento Vegetal Genótipo |
Keywords: | Interação genótipo-ambiente |
DOI: | http://dx.doi.org/10.1590/1984-70332025v25n2a05 |
Type of Material: | Artigo de periódico |
Access: | openAccess |
Appears in Collections: | Artigo em periódico indexado (CNPGL)![]() ![]() |
Files in This Item:
File | Size | Format | |
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Multi-information-analysis-to-recommend-alfalfa.pdf | 373.41 kB | Adobe PDF | View/Open |