Search

Your search keyword '"Karla Jorge Da Silva"' showing total 2 results
Start Over Author "Karla Jorge Da Silva" Topic adaptability
2 results on '"Karla Jorge Da Silva"'

1. Multi-environmental evaluation of sorghum hybrids during off-season in Brazil

Author

Karla Jorge da Silva, Cicero Beserra de Menezes, Paulo Eduardo Teodoro, Larissa Pereira Ribeiro Teodoro, Crislene Vieira dos Santos, Alexon Fernandes Campos, Abner José de Carvalho, and Edmilson da Silva Barbosa

Subjects
Sorghum bicolor, adaptability, genotypic means, mixed models, REML/BLUP, stability, Agriculture (General), S1-972
Abstract

Abstract The objective of this work was to simultaneously select pre-commercial grain sorghum hybrids with high adaptability and yield stability, through mixed modeling, in 20 environments, during six years. The evaluated plant material consisted of 57 commercial grain sorghum hybrids. In all experiments, hybrids were arranged in a triple lattice design; some experiments used a 6x6 lattice, and others, a 5x5 lattice. Adaptability and stability parameters were obtained based on the prediction by harmonic mean of the relative performance of genotypic values (HMRPGV). The mixed models proved to be adequate to analyze the genotype x environment (GxE) interaction and the genotypic adaptability and stability studies on grain sorghum. The hybrids that stand out, considering all environments are 1G282, A9904, 50A50, A9902, and XB6022. The A9904 hybrid stands out in favorable environments, with a grain yield above average. Only 1G282 is among the five best hybrids for each group of environments, and it is the best grain sorghum hybrid for yield performance, adaptability, and stability. The predicted genotypic values based on genotypic means can be used in the environments with the same GxE interaction pattern because they are free of the GxE interaction.

Published
2022
Full Text
View/download PDF

2. Identification of mega-environments for grain sorghum in Brazil using GGE biplot methodology

Author

Vicente de Paulo Campos Godinho, Flávio Dessaune Tardin, Milton José Cardoso, Larissa Pereira Ribeiro Teodoro, Michele Jorge da Silva, F. L. Guedes, José Hortêncio Mota, Adelmo Resende da Silva, Paulo Eduardo Teodoro, Karla Jorge da Silva, Cícero Beserra de Menezes, Gustavo André Simon, KARLA JORGE DA SILVA, PAULO EDUARDO TEODORO, Universidade Federal de Mato Grosso do Sul, MICHELE JORGE DA SILVA, Universidade Federal de Viçosa, LARISSA PEREIRA RIBEIRO TEODORO, Universidade Federal de Mato Grosso do Sul, MILTON JOSE CARDOSO, CPAMN, VICENTE DE PAULO CAMPOS GODINHO, CPAF-RO, JOSÉ HORTÊNCIO MOTA, Universidade Federal de Jataí, GUSTAVO ANDRÉ SIMON, Universidade de Rio Verde, FLAVIO DESSAUNE TARDIN, CNPMS, ADELMO RESENDE DA SILVA, CNPMS, FERNANDO LISBOA GUEDES, CNPC, and CICERO BESERRA DE MENEZES, CNPMS.

Subjects
0106 biological sciences, biology, Biplot, media_common.quotation_subject, Genótipo, Sorgo, Sorghum bicolor, 04 agricultural and veterinary sciences, Sorghum, biology.organism_classification, Mega, 01 natural sciences, Adaptability, Crop, Método biplot, Agronomy, Homogeneous, Rendimento, Grão, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Grain yield, Agronomy and Crop Science, 010606 plant biology & botany, media_common
Abstract

The performance of genotypes in a wide range of environments can be affected by extensive genotype × environment (G × E) interactions, making the subdivision of the testing environments into relatively more homogeneous groups of locations (mega-environments) a necessary strategy. The genotype main effects + genotype × environment interaction biplot method (GGE) allows identification of megaenvironments and selection of stable genotypes adapted to specific environments and mega-environments. The objectives of this study were to identify mega-environments regarding sorghum [Sorghum bicolor (L.) Moench] grain yield and demonstrate that the GGE biplot method can identify essential locations for conducting tests in different mega-environments. A total of 22 competition trials of grain sorghum genotypes were conducted over three crop seasons across several production locations in Brazil. A total of 25, 22, and 30 genotypes were evaluated during the first, second, and third crop seasons, respectively. After identifying the presence of G × E interactions, the data were subjected to adaptability and stability analyses using the GGE biplot method. A phenotypic correlation network was used to express functional relationships between environments. The GGE biplot was found to be an efficient approach for identifying three mega-environments in grain sorghum in Brazil, selecting representative and discriminative environments, and recommending more adaptive and stable grain sorghum genotypes Made available in DSpace on 2021-12-15T12:06:58Z (GMT). No. of bitstreams: 1 Identification-of-megau2010environments-for-grain-sorghum-in-Brazil-using-GGE-biplot.pdf: 2189041 bytes, checksum: 72d181e5628b2eaa3a76f2ed7c73a106 (MD5) Previous issue date: 2021

Published
2021

Catalog

Books, media, physical & digital resources
See catalog results