Half a century of studying adaptability and stability in maize and soybean in Brazil

Rezende, Wender Santos; Cruz, Cosme Damião; Borém, Aluízio; Rosado, Renato Domiciano Silva

doi:10.1590/1678-992x-2019-0197

Cited by 8 publications

(6 citation statements)

References 25 publications

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“…For Rezende et al (2020), the Eberhart and Russell, and AMMI methods are complementary: while the first evaluates the responsivity of each genotype to improvements in the environment, the AMMI estimates include the contribution of the genotype to the noise-free GE interaction (Silva and Duarte, 2006) since the initial eigenvalues of the PCA component of the AMMI model selectively recover the interaction pattern (Gauch and Zobel, 1988).…”

Section: Comparison Of Parameters and Line Selection By The Three Met...mentioning

confidence: 99%

Research Article Adaptability and stability parameters for grain production in pigeonpea lines in the Brazilian semiarid region

Costa¹,

Santos²

2022

Genet. Mol. Res.

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Pigeonpea is a multipurpose species and can be used for grain, forage production, and as a soil improver. In Brazil, the scarcity of productive cultivars adapted to various growing conditions contribute to the underutilization of this legume crop. The genotype × environment (G×E) interaction is one of the main challenges to the development and recommendation of cultivars. Estimates of adaptability and stability parameters make it possible to predict the behavior and effects of the G×E interaction to reduce possible inconsistencies in cultivar recommendation. From this perspective, we assessed the adaptability and stability parameters for grain yield of 21 pigeonpea lines developed in the breeding program of this pulse at Embrapa Semiárido, Petrolina, PE, Brazil, and the variety "guandu Petrolina" (control), in order to recommend new cultivars for general use. The genotypes were evaluated in eight environments, with experiments conducted in five irrigated and three rainfed environments using a randomized complete block design with three replications. Grain yield was corrected by covariance based on the average plant stand. The Eberhart and Russel, AMMI, and GGE Biplot methods were used in this study. The coefficient of variation for the experiments was 12.41%, with data transformed to square root. The effects of genotypes, the environments, and the genotype-byenvironment interaction were highly significant (p < 0.01). The mean ©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 21 (4): gmr19066A.E. da S. Costa et al. 2 grain yield of the genotypes was 1,516 kg ha -1 . Lines 87, 100, and 158 simultaneously showed wide adaptability and good predictability according to the three methods, with mean yields of 1,530, 1,701, and 1,812 kg ha -1 , respectively, and reaching yields of up to 2,725, 2,928, and 2,955 kg ha -1 in some environments. These lines are indicated for recommendation as new pigeonpea cultivars for the semi-arid region of Brazil.

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Section: Comparison Of Parameters and Line Selection By The Three Met...mentioning

confidence: 99%

Research Article Adaptability and stability parameters for grain production in pigeonpea lines in the Brazilian semiarid region

Costa¹,

Santos²

2022

Genet. Mol. Res.

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“…(2021) reported that Eberhart and Russell (1966), which is based on linear regression, is the most widely used method for assessing the GEI and adaptability and stability of maize genotypes across tropical areas, mainly in Brazilian environments. In addition, the use of genotype main effect plus genotype × environment interaction (GGE) biplot (Yan et al., 2000) and harmonic mean of the relative performance of the predicted genetic values (HMRPGV) (Resende, 2007) methods, which are based on fixed models (sum of squares based) and mixed models (variance based), respectively, for studying GEI in maize breeding programs has increased considerably in the last two decades (Akinwale et al., 2014; Alwala et al., 2010; Elias et al., 2016; Faria et al., 2017; Oliveira et al., 2017; Rezende et al., 2021; van Eeuwijk et al., 2016). The employment of more than one method to handle the GEI and to identify high‐yielding and stable genotypes may increase the reliability of cultivar recommendations and has been endorsed by many maize breeders since the results provided may complement each other and help in the interpretation of data from breeding and agronomic field evaluation trials (Badu‐Apraku et al., 2012; Faria et al., 2017; Rezende et al., 2020, 2021; Yamamoto et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

“…In this scenario, several statistical approaches have been proposed to handle GEI across diverse environments and facilitate the allocation of high-yielding and stable cultivars to target environments. In a recent review, Rezende et al (2021) reported that Eberhart and Russell (1966), which is based on linear regression, is the most widely used method for assessing the GEI and adaptability and stability of maize genotypes across tropical areas, mainly in Brazilian environments. In addition, the use of genotype main effect plus genotype × environment interaction (GGE) biplot (Yan et al, 2000) and harmonic mean of the relative performance of the predicted genetic values (HMRPGV) (Resende, 2007) methods, which are based on fixed models (sum of squares based) and mixed models (variance based), respectively, for studying GEI in maize breeding programs has increased considerably in the last two decades (Akinwale et al, 2014;Alwala et al, 2010;Elias et al, 2016;Faria et al, 2017;Oliveira et al, 2017;Rezende et al, 2021;van Eeuwijk et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Assessment of yield performance and stability of hybrids and populations of tropical maize across multiple environments in Southeastern Brazil

et al. 2023

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The identification of stable genotypes with high yield in diverse multiple‐stress environments is important to increase maize (Zea mays L.) grain yield under tropical environments. Our objective was to assess the yield performance and stability of experimental hybrids and broad‐based populations of tropical maize across diverse environments in Southeastern Brazil. We evaluated two sets of maize genotypes for grain yield: 190 experimental hybrids along with 6 commercial hybrids and 45 population hybrids along with their 10 parental populations across 8 environments in Southeastern Brazil. Multiple statistical methods were used and compared in the analyses. Combined analysis of variance indicated that genotypic main effect (G), environmental main effect (E), and genotype by environment interaction were highly significant (p < 0.0001) for grain yield. The E accounted for 42% of the total variation for both hybrids and populations, and they were more similar within the growing season than between seasons, mainly for populations. Low nitrogen (N) stress was a key factor in hybrid evaluation and recommendation, particularly under drought stress conditions. Among the environment classification methods, genotype main effect plus genotype × environment interaction (GGE) biplot provided more accurate information about environments grouping and selection of the genotypes than the Eberhart and Russell method. Harmonic mean of the relative performance of the predicted genetic values (HMRPGV) based on mixed models ranked the hybrids and populations according to mean grain yield and stability, penalizing hybrids, and populations with lower stability. Therefore, we recommend the GGE biplot and HMRPGV for genotype evaluation based on multi‐environment trials data. These methods identified 92V2144 and 92V2033 as the most promising hybrids for favorable and 92V2141, 92V2153, and 92V2137 as the most promising for unfavorable environments. 92VX033 and 92VX043 were identified as broadly adapted and stable populations across multiple environments in Southeastern Brazil.

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“…Eberhart and Russel was the traditional predominant method in the study of adaptability and stability in maize and soybean. Other methods as AMMI, GGE Biplot and MHPRVG had their used increased (Rezende et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Adaptability and stability of maize genotypes in growing regions of central Brazil

et al. 2021

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This study aimed to estimate and compare parameters of adaptability and stability for maize grain yield in a variety of environments by different projection methods. Data from experiments on 36 maize genotypes, in simple lattice 6x6, in 2012/13 season performed at nine growing locations in central Brazil were used. Adaptability and stability analyses were performed using the methods of Lin & Binns (1988) with decomposition, MHPRVG through REML/BLUP, AMMI-Biplot, and GGE-Biplot analysis. These methods have similarities in terms of genotype ordering but differ in precision and amount of information provided on genotype-environment (GxE) interactions. When compared to GGE-Biplot, AMMI method retained a good percentage of the total square sum, based on pattern of GxE interaction. The method of Lin & Binns with decomposition is similar to MHPRVG, but these one is more accurate, practice and informative. MHPRVG and GGE-Biplot methods should be used together to select the most promising genotypes. The genotypes G5 and G8 can be recommended for cultivation in central Brazil due to their adaptability, stability, and yield.

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Half a century of studying adaptability and stability in maize and soybean in Brazil

Cited by 8 publications

References 25 publications

Research Article Adaptability and stability parameters for grain production in pigeonpea lines in the Brazilian semiarid region

Research Article Adaptability and stability parameters for grain production in pigeonpea lines in the Brazilian semiarid region

Assessment of yield performance and stability of hybrids and populations of tropical maize across multiple environments in Southeastern Brazil

Adaptability and stability of maize genotypes in growing regions of central Brazil

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