Adaptability and stability of corn hybrids for the south of the Amazon biome via GGE biplot Article Swipe
Joameson Antunes Lima
,
Ana Aparecida Bandini Rossi
,
Talles de Oliveira Santos
,
Guilherme Ferreira Penna
,
F. D. Tardin
,
R. dos S. Trindade
,
P. E. de O. Guimarães
,
V. de P. C. Godinho
,
Antônio Teixeira do Amaral Júnior
,
Angelo Gabriel Mendes Cordeiro
,
Renan Colavite dos Santos
,
Marry Suelly Ferreira de Jesus
,
Letícia de Souza Pogalsky
,
Auana Vicente Tiago
,
Eliane Cristina Moreno de Pedri
,
Edimilson Leonardo Ferreira
,
Géssica Tais Zanetti
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.6084/m9.figshare.22268681
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.6084/m9.figshare.22268681
The objective of this work was to select maize hybrids using the GGE biplot analysis, as well as to evaluate their stability and adaptability in different environments of the North and Midwest regions of Brazil. Thirty-six maize hybrids were evaluated in 2018, in the following five environments in the Northern and Midwestern regions, respectively: in the municipality of Vilhena, in the state of Rondônia; and in the municipalities of Sorriso, Sinop, Alta Floresta, and Carlinda, in the Northern region of the state of Mato Grosso. The experimental design was a randomized complete block design. The analysis of variance was performed, and adaptability and stability were estimated by the GGE biplot method based on grain yield performance. A significant interaction between genotypes and environments was detected, and the biplot analysis was efficient in explaining 62.74% of the total variation in the first two principal components, with the formation of three macroenvironments. The 1P2227, 'BRS 3042', and 1P2265 hybrids showed high yield, responsiveness, and stability in the evaluated environments. The DKB310VTPRO2 hybrid was the most unstable genotype. The recommended hybrids are: DKB310 for the Sorriso and Vilhena macroenvironment; 1M1810 and 1O2106 for the Carlinda environment; and 1M1807 for the Sinop environment.
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Metadata
- Type
- dataset
- Language
- en
- Landing Page
- https://doi.org/10.6084/m9.figshare.22268681
- OA Status
- gold
- Related Works
- 10
- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4394510405Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.6084/m9.figshare.22268681Digital Object Identifier
- Title
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Adaptability and stability of corn hybrids for the south of the Amazon biome via GGE biplotWork title
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datasetOpenAlex work type
- Language
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enPrimary language
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2023Year of publication
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2023-01-01Full publication date if available
- Authors
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Joameson Antunes Lima, Ana Aparecida Bandini Rossi, Talles de Oliveira Santos, Guilherme Ferreira Penna, F. D. Tardin, R. dos S. Trindade, P. E. de O. Guimarães, V. de P. C. Godinho, Antônio Teixeira do Amaral Júnior, Angelo Gabriel Mendes Cordeiro, Renan Colavite dos Santos, Marry Suelly Ferreira de Jesus, Letícia de Souza Pogalsky, Auana Vicente Tiago, Eliane Cristina Moreno de Pedri, Edimilson Leonardo Ferreira, Géssica Tais ZanettiList of authors in order
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https://doi.org/10.6084/m9.figshare.22268681Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.6084/m9.figshare.22268681Direct OA link when available
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Biplot, Adaptability, Biome, Amazon rainforest, Hybrid, Stability (learning theory), Agroforestry, Biology, Agronomy, Computer science, Ecology, Ecosystem, Genotype, Genetics, Machine learning, GeneTop concepts (fields/topics) attached by OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.state | 62, 82 |
| abstract_inverted_index.their | 21 |
| abstract_inverted_index.three | 149 |
| abstract_inverted_index.total | 137 |
| abstract_inverted_index.using | 11 |
| abstract_inverted_index.yield | 115 |
| abstract_inverted_index.1M1807 | 195 |
| abstract_inverted_index.1M1810 | 187 |
| abstract_inverted_index.1O2106 | 189 |
| abstract_inverted_index.1P2265 | 156 |
| abstract_inverted_index.3042', | 154 |
| abstract_inverted_index.62.74% | 134 |
| abstract_inverted_index.DKB310 | 180 |
| abstract_inverted_index.Sinop, | 71 |
| abstract_inverted_index.biplot | 14, 110, 128 |
| abstract_inverted_index.design | 88 |
| abstract_inverted_index.hybrid | 170 |
| abstract_inverted_index.method | 111 |
| abstract_inverted_index.region | 79 |
| abstract_inverted_index.select | 8 |
| abstract_inverted_index.showed | 158 |
| abstract_inverted_index.yield, | 160 |
| abstract_inverted_index.1P2227, | 152 |
| abstract_inverted_index.Brazil. | 35 |
| abstract_inverted_index.Grosso. | 85 |
| abstract_inverted_index.Midwest | 32 |
| abstract_inverted_index.Sorriso | 183 |
| abstract_inverted_index.Vilhena | 185 |
| abstract_inverted_index.between | 120 |
| abstract_inverted_index.design. | 94 |
| abstract_inverted_index.hybrids | 10, 38, 157, 178 |
| abstract_inverted_index.regions | 33 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Carlinda | 192 |
| abstract_inverted_index.Northern | 50, 78 |
| abstract_inverted_index.Sorriso, | 70 |
| abstract_inverted_index.Vilhena, | 59 |
| abstract_inverted_index.analysis | 96, 129 |
| abstract_inverted_index.complete | 92 |
| abstract_inverted_index.evaluate | 20 |
| abstract_inverted_index.regions, | 53 |
| abstract_inverted_index.unstable | 174 |
| abstract_inverted_index.variance | 98 |
| abstract_inverted_index.Carlinda, | 75 |
| abstract_inverted_index.Floresta, | 73 |
| abstract_inverted_index.analysis, | 15 |
| abstract_inverted_index.detected, | 125 |
| abstract_inverted_index.different | 26 |
| abstract_inverted_index.efficient | 131 |
| abstract_inverted_index.estimated | 106 |
| abstract_inverted_index.evaluated | 40, 166 |
| abstract_inverted_index.following | 45 |
| abstract_inverted_index.formation | 147 |
| abstract_inverted_index.genotype. | 175 |
| abstract_inverted_index.genotypes | 121 |
| abstract_inverted_index.objective | 2 |
| abstract_inverted_index.principal | 143 |
| abstract_inverted_index.stability | 22, 104, 163 |
| abstract_inverted_index.variation | 138 |
| abstract_inverted_index.Midwestern | 52 |
| abstract_inverted_index.Rondônia; | 64 |
| abstract_inverted_index.Thirty-six | 36 |
| abstract_inverted_index.explaining | 133 |
| abstract_inverted_index.performed, | 100 |
| abstract_inverted_index.randomized | 91 |
| abstract_inverted_index.components, | 144 |
| abstract_inverted_index.interaction | 119 |
| abstract_inverted_index.recommended | 177 |
| abstract_inverted_index.significant | 118 |
| abstract_inverted_index.DKB310VTPRO2 | 169 |
| abstract_inverted_index.adaptability | 24, 102 |
| abstract_inverted_index.environment. | 199 |
| abstract_inverted_index.environment; | 193 |
| abstract_inverted_index.environments | 27, 47, 123 |
| abstract_inverted_index.experimental | 87 |
| abstract_inverted_index.municipality | 57 |
| abstract_inverted_index.performance. | 116 |
| abstract_inverted_index.environments. | 167 |
| abstract_inverted_index.respectively: | 54 |
| abstract_inverted_index.municipalities | 68 |
| abstract_inverted_index.responsiveness, | 161 |
| abstract_inverted_index.macroenvironment; | 186 |
| abstract_inverted_index.macroenvironments. | 150 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 17 |
| citation_normalized_percentile |