Analysis of the phenotypic adaptability and stability of strains of cowpea through the GGE Biplot approach

Cruz, Derivaldo Pureza da; Gravina, Geraldo de Amaral; Vivas, Marcelo; Entringer, Geovana Cremonini; Rocha, Richardson Sales; Jaeggi, Mário Euclides Pechara da Costa; Gravina, Lília Marques; Pereira, Israel Martins; Amaral, Antônio Teixeira do; Moraes, Ramon de; Oliveira, Tâmara Rebecca Albuquerque de; Daher, Rogério Figueiredo

doi:10.1007/s10681-020-02693-9

Cited by 11 publications

(16 citation statements)

References 25 publications

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“…Under genotype evaluation, much work has been devoted in developing stability indices to quantify and select against GE interactions. Some procedures can be performed to attenuate the inconsistency of the superiority of the genotypes (Cruz et al 2020). Although many stability indices have been proposed by various researchers, graphical interpretation of genetic main effect (G) and genotype-byenvironment interaction effect (GE) is the most preferable method (GGE).…”

Section: Genotype-by-environment Interaction Effectmentioning

confidence: 99%

“…In addition, the GGE biplot method is considered as an attractive method to identify superior genotypes with wide adaptability and stability because it provides effective overview of the genotype main effect plus genotype x environment interaction (GGE) effect (Yan2015). This method has been used for the evaluation of stability and adaptability of various annual crop species such as rice (Samonte et al 2005), sugarcane (Glaz and Kang 2008), soybean (Dalló et al 2019) and cowpea (Cruz et al 2020) in multi-environment trials. Recently, Reddy et al (2022) also used GGE biplot analysis to identify the ideal cultivars and testing locations of pearl millet (Pennisetum glaucum L.R.…”

Section: Introductionmentioning

confidence: 99%

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Utilization of within location non-replicated multi-locational yield trials and GGE biplot methods for testing adaptability of tea [(Camellia sinensis (L.) O. Kuntze)] over diverse environments

Kottawa-Arachchi

Ranatunga

Abeysiriwardena

2022

IJGPB

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Selection of tea [Camellia sinensis (L.) O. Kuntze] cultivars with wide adaptability over diverse environments is an important criteria to get prior information to recommend the cultivar for a particular region. A study was carried out to identify the most adaptable and stable tea genotypes for recommendation in the Up-country tea growing region in Sri Lanka by evaluating several potential tea genotypes for their wide adaptability and stability over diverse environments based on the analysis of GE interaction using within location non-replicated multi-environmental yield trials and GGE biplot methods. Six promising tea genotypes with desirable agronomic traits selected based on preliminary yield trials were evaluated along with a standard check in large scale within location non-replicated multi-locational yield trials at six locations (tea estates) in the Up-country tea growing region in Sri Lanka. The crop yields were recorded by harvesting green leaves in every seven days for three years covering six seasons (1st pruning cycle). Yield data were analyzed by within location non-replicated multi-locational yield trials and GGE biplot analysis. The genotype 272 was identified as the most adaptable and stable genotype followed by 582 and rest of the genotypes showed poor adaptability in the test region.

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Section: Genotype-by-environment Interaction Effectmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Utilization of within location non-replicated multi-locational yield trials and GGE biplot methods for testing adaptability of tea [(Camellia sinensis (L.) O. Kuntze)] over diverse environments

Kottawa-Arachchi

Ranatunga

Abeysiriwardena

2022

IJGPB

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“…(de Farias Neto et al., 2018; Yokomizo et al., 2020), cowpea [ Vigna unguiculata (L.) Walp.] (D. P. D. Cruz et al., 2020; Santos, Ceccon, et al., 2017), soybean [ Glycine max (L.) Merr.] (Albuquerque et al., 2022), and sorghum [ Sorghum bicolor (L.) Moench] (Gomes et al., 2019; K. J. Silva et al., 2021), but there are few reports in the literature about its use in corn for silage production.…”

Section: Introductionmentioning

confidence: 99%

Adaptability and stability of corn hybrids for silage via genotype and genotype × environment interaction biplot

et al. 2023

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The occurrence of the genotype × environment (G × E) interaction is one of the main factors that hinder the selection of adapted and stable genotypes. The genotype and G × E interaction (GGE) biplot methodology is an efficient process to detect corn (Zea mays L.) hybrids for silage and, consequently, will help in the recommendation of new and more stable hybrids in different environments in breeding programs. In this sense, this study aimed to evaluate and select corn hybrids for silage that simultaneously combine high yield and stability in different environments in the state of Rio de Janeiro, Brazil, via GGE biplot. Eleven corn hybrids, eight precommercial topcrosses and three commercial controls, were evaluated at three sites (Campos dos Goytacazes, Cambuci, and Itaocara, Rio de Janeiro) during two seasons: the 2017-2018 season and 2018-2018 off-season. The experiments were designed in completely randomized blocks with three replications. Individual and joint analyses of variance were performed and, after detecting significant interaction between genotype and environment, the adaptability and phenotypic stability of corn genotypes for silage were analyzed using the GGE biplot methodology. The GGE biplot analysis was efficient in interpreting the data and represented 83.68% of the total variation in the first two principal components. The use of the GGE biplot method allowed the recommendation of more productive, stable, and responsive hybrids for the state of Rio de Janeiro. The hybrid UENF MS2208 is indicated for cultivation in the state of Rio de Janeiro for combining high green biomass yield and stability. INTRODUCTIONCorn (Zea mays L.) is a crop that has importance in the socioeconomic, environmental, and cultural spheres worldwide and also in Brazil. It mainly is due to its potential use in human and animal food and biofuel production among others AEC, average environment coordinate; G × E, genotype × environment interaction; GGE, genotype and genotype × environment interaction; GMY, green biomass yield.

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“…The genotype by environment interaction is very important for plant breeders to identify the general and specific adaptability of the genotypes in crop plant improvement [5][6][7]. AMMI and GGE-biplot are an important and widely used by different scholars to identify the most stable genotype and environment [8][9][10][11][12] Yield enhancement in crop genetic resources are currently of great interest to ensure food security.…”

Section: Introductionmentioning

confidence: 99%

Genotype by Environment Interaction and Stability Analysis in Sunflower Genotypes

Abu

2023

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The study was conducted during the main cropping season of 2019/2020 to evaluate advanced sunflower genotypes for its stability over multiple environments. The study was carried out at six locations namely; Holeta, Debrezeit, Fenoteselam, Arsi Negele, Kulumsa and Ambo. Randomized complete block design with four replication was used in layout of the experiment. Data were collected for seed yield and yield related components and subjected to analysis using R-software. AMMI and GGE-biplot were used to estimate the stability of genotypes across test environments. The results from AMMI analysis of variance showed that there is significant difference for environment, genotype and genotype by environment interaction for seed yield. AMMI analysis of variance for oil content revealed the significant differences for genotypes, genotype by environment interaction and non-significant for environment. The Gollob's test showed that total variation greater than 70% was explained together by PC1 and PC2 for both seed yield and oil content. AMMI 1 bi-plot analysis for seed yield revealed that E1 and E5 was high seed yielder than others and genotypes, G4, G5 and G2 were stable genotypes relative to others. AMMI2 Bi-plot showed genotypes G3, G1, G6 and G8 were stable for seed yield whereas, G7, G8 and G1 were stable for oil content.

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Analysis of the phenotypic adaptability and stability of strains of cowpea through the GGE Biplot approach

Cited by 11 publications

References 25 publications

Utilization of within location non-replicated multi-locational yield trials and GGE biplot methods for testing adaptability of tea [(Camellia sinensis (L.) O. Kuntze)] over diverse environments

Utilization of within location non-replicated multi-locational yield trials and GGE biplot methods for testing adaptability of tea [(Camellia sinensis (L.) O. Kuntze)] over diverse environments

Adaptability and stability of corn hybrids for silage via genotype and genotype × environment interaction biplot

Genotype by Environment Interaction and Stability Analysis in Sunflower Genotypes

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