Uni- and multivariate methods applied to the study of the adaptability and stability of white oat

Rother, Vianei; Verdi, Cezar Augusto; Thurow, Liamara Bahr; Carvalho, Ivan Ricardo; Oliveira, Victoria Freitas de; Maia, Luciano Carlos da; Venske, Eduardo; Pegoraro, Camila; Oliveira, Antônio Costa de

doi:10.1590/s1678-3921.pab2019.v54.00656

Cited by 5 publications

(1 citation statement)

References 10 publications

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“…Some recent research has focused on the study of the interaction between genotype x environment in white oat (Rother et al, 2019;Corazza et al, 2021;Moura et al, 2021), promoting proper positioning in the evaluated environments and evidencing the significant effects of the interaction, mainly, on grain yield. Therefore, it is necessary constant research advancement in the area, in order to maximize the performance of genotypes by targeting them to specific micro regions.…”

Section: Introductionmentioning

confidence: 99%

Positioning of White Oat Cultivars in Different Environments for High Grain Productivity in Organic System

Savicki

Carvalho

Loro

et al. 2023

Trop Subtrop Agroecosyst

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Background. White oat is a multifunctional species with significant benefits to human health, so the positioning of genotypes in the organic system is substantial to promote the expression of maximum productive potential. Objective. To select and identify the genotypes with greater stability and productive adaptability. Methodology. The study was carried out in 11 environments located in the countries of Brazil (states of Rio Grande do Sul and Paraná) and Paraguay (Itapúa) in 2019 and 2020, evaluating in each of them four genotypes of white oats (Avena sativa) (URS Corona, URS Brava, IPR Artemis and IPR Afrodite) each considered as treatments. The experimental design was randomized blocks with four replications per treatment. The variables analyzed were grain yield (GY, kg ha-1) and the cycle in days from emergence to physiological maturity (PM). With the presence of G x E interaction, AMMI and GGE biometric methods were used to study adaptability and stability. Results. With the data obtained, it was possible to form three mega-environments with the identification of specifically adapted genotypes. The URS Brava genotype was characterized as the ideal genotype, with high stability and wide adaptability for grain yield, which can be positioned in all environments. High altitudes promoted a longer crop cycle and lower grain yield, while low altitudes induced a shorter cycle and grain yield maximization of white oat genotypes. Implications. The current results indicate that it is possible to position a single genotype within a region formed by similar environments, as well as it was identified that the crops should preferably be carried out in regions of lower altitudes. Conclusion. The URS Brava genotype is considered the ideal genotype with high potential for productivity at low altitudes.

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Section: Introductionmentioning

confidence: 99%

Positioning of White Oat Cultivars in Different Environments for High Grain Productivity in Organic System

Savicki

Carvalho

Loro

et al. 2023

Trop Subtrop Agroecosyst

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Soybean adaptability and stability analyzes to the organic system through AMMI, GGE Biplot and mixed models methodologies

et al. 2023

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This research determined the adaptability and stability of soybean yield for organic systems in different environments. Grain yield data (GY, kg ha-1) from experiments with six soybean genotypes evaluated in six environments in Brazil and one environment in Paraguay were used. The experimental design used was randomized blocks, organized in an incomplete factorial scheme, with six environments in Brazil (Toledo- PR, Palotina- PR, Mangueirinha- PR, Três Passos- RS, Passo Fundo- RS, Major Vieira- SC) and one in Paraguay (Bela Vista do Norte- PY) with six soybean genotypes (BRS 284, BRS 391, BRS 511, BRS 523, BRS 525, BRS 535) arranged in four replications per environment. BRS 511 genotype was characterized by high average grain yield and stability by the AMMI method. BRS 284 genotype was identified as the ideal genotype in the GGE biplot method. WAASBY and BLUP index selected BRS511 and BRS284 genotypes.

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Selection of white oat genotypes for contrasting fungicide management conditions

Berlezi

Carvalho

Silva

et al. 2023

Pesq. agropec. bras.

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The objective of this work was to select white oat (Avena sativa) genotypes for environments with and without fungicide application, as well as to identify relationships between meteorological variables and agronomic traits. Two experiments were carried out: one without and the other with the use of the tebuconazole fungicide. In each experiment, 26 genotypes were evaluated, conducted during ten years in the same experimental area; cultivation years were considered as one environment. The methodologies of genotype and of the genotypes x environments interaction were used to define the ideal genotype. 'URS Corona' is considered an ideal genotype due to its excellent responses in the environment with tebuconazole. The 'Brisasul', 'IPR Aphrodite', and 'URS Taura' genotypes respond better in the environment without the fungicide. However, based on multitraits, the 'URS Taura' and 'IPR Afrodite' genotypes can be positioned in environments with or without the use of tebuconazole. Genotypes with a rust incidence lower than 15% and a height higher than 93 cm in an environment with a relative humidity lower than 70.75% have a higher grain yield regardless of fungicide use. Greater magnitudes of air temperature and solar radiation result in a higher grain yield of white oat, regardless of fungicide use.

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Uni- and multivariate methods applied to the study of the adaptability and stability of white oat

Cited by 5 publications

References 10 publications

Positioning of White Oat Cultivars in Different Environments for High Grain Productivity in Organic System

Positioning of White Oat Cultivars in Different Environments for High Grain Productivity in Organic System

Soybean adaptability and stability analyzes to the organic system through AMMI, GGE Biplot and mixed models methodologies

Selection of white oat genotypes for contrasting fungicide management conditions

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