Phenotypic stability and GGE biplot analysis in Pigeonpea [Cajanus cajan (L.) Mill sp.] genotypes across the environments

ABSTRACT The objective of this study was to investigate the association between the GGE Biplot and REML/BLUP methods and select cowpea genotypes that meet simultaneously high grain yield, adaptability and stability in the Mato Grosso do Sul environments. The experiments were carried out from February to July 2010, 2011 and 2012 in the municipalities of Dourados, Aquidauana and Chapadão do Sul. The experiments in Chapadão do Sul were conducted only in the years of 2010 and 2011, totaling eight environments. After detecting significant genotypes × environments (GE) interaction, the adaptability and the phenotypic stability of cowpea genotypes were analyzed by GGE Biplot and REML/BLUP methods. These methods were concordant in the identification of the best cowpea genotypes for the State of Mato Grosso do Sul. The BRS- Tumucumaque and BRS-Guariba cultivars are the closest to the ideal in terms of high grain yield and phenotypic stability, being suitable for cultivation in the State.

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Evaluation of sugarcane genotypes with respect to sucrose yield across three crop cycles using GGE biplot analysis

Experimental Agriculture ◽

10.1017/s0014479721000144 ◽

2021 ◽

pp. 1-13

Author(s):

Aliya Momotaz ◽

Per H. McCord ◽

R. Wayne Davidson ◽

Duli Zhao ◽

Miguel Baltazar ◽

...

Keyword(s):

Block Design ◽

Genotype By Environment Interaction ◽

Environment Interaction ◽

Gge Biplot ◽

Genotype By Environment ◽

Biplot Analysis ◽

Genotype Environment Interaction ◽

Area 5 ◽

Randomized Complete Block Design ◽

Main Effects

Summary The experiment was carried out in three crop cycles as plant cane, first ratoon, and second ratoon at five locations on Florida muck soils (histosols) to evaluate the genotypes, test locations, and identify the superior and stable sugarcane genotypes. There were 13 sugarcane genotypes along with three commercial cultivars as checks included in this study. Five locations were considered as environments to analyze genotype-by-environment interaction (GEI) in 13 genotypes in three crop cycles. The sugarcane genotypes were planted in a randomized complete block design with six replications at each location. Performance was measured by the traits of sucrose yield tons per hectare (SY) and commercial recoverable sugar (CRS) in kilograms of sugar per ton of cane. The data were subjected to genotype main effects and genotype × environment interaction (GGE) analyses. The results showed significant effects for genotype (G), locations (E), and G × E (genotype × environment interaction) with respect to both traits. The GGE biplot analysis showed that the sugarcane genotype CP 12-1417 was high yielding and stable in terms of sucrose yield. The most discriminating and non-representative locations were Knight Farm (KN) for both SY and CRS. For sucrose yield only, the most discriminating and non-representative locations were Knight Farm (KN), Duda and Sons, Inc. USSC, Area 5 (A5), and Okeelanta (OK).

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GGE Biplot Analysis of Yield Associations with Root Traits in a Mesoamerican Bean Diversity Panel

Crop Science ◽

10.2135/cropsci2015.10.0609 ◽

2016 ◽

Vol 56 (3) ◽

pp. 1081-1094 ◽

Cited By ~ 4

Author(s):

V. Hoyos-Villegas ◽

E.M. Wright ◽

J.D. Kelly

Keyword(s):

Root Traits ◽

Gge Biplot ◽

Biplot Analysis ◽

Diversity Panel

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GGE biplot analysis of multi-location yield trial of ginger (Zingiber Officinale Rosc.) Genotypes in South-Eastern, Nigeria

Asian Journal of Agriculture and Rural Development ◽

10.18488/journal.1005/2020.10.1/1005.1.485.503 ◽

2020 ◽

Vol 10 (1) ◽

pp. 485-503

Author(s):

Abua Mary Njei ◽

Iwo Godfery Akpan ◽

Ittah Macauley Asim ◽

Obok Ekemini Edet ◽

Edugbo Richmond Emu

Keyword(s):

Zingiber Officinale ◽

Gge Biplot ◽

Biplot Analysis ◽

South Eastern ◽

Yield Trial

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GENOTYPE BY ENVIRONMENT INTERACTION IN COWPEA LINES USING GGE BIPLOT METHOD

Revista Caatinga ◽

10.1590/1983-21252018v31n108rc ◽

2018 ◽

Vol 31 (1) ◽

pp. 64-71 ◽

Cited By ~ 6

Author(s):

MASSAINE BANDEIRA E SOUSA ◽

KAESEL JACKSON DAMASCENO-SILVA ◽

MAURISRAEL DE MOURA ROCHA ◽

JOSÉ ÂNGELO NOGUEIRA DE MENEZES JÚNIOR ◽

LAÍZE RAPHAELLE LEMOS LIMA

Keyword(s):

Maximum Yield ◽

Genotype By Environment Interaction ◽

Superior Performance ◽

Environment Interaction ◽

Gge Biplot ◽

Brazilian Cerrado ◽

Genotype By Environment ◽

Biplot Analysis ◽

Adjusted Means ◽

Selection Of

ABSTRACT The GGE Biplot method is efficien to identify favorable genotypes and ideal environments for evaluation. Therefore, the objective of this work was to evaluate the genotype by environment interaction (G×E) and select elite lines of cowpea from genotypes, which are part of the cultivation and use value tests of the Embrapa Meio-Norte Breeding Program, for regions of the Brazilian Cerrado, by the GGE-Biplot method. The grain yield of 40 cowpea genotypes, 30 lines and 10 cultivars, was evaluated during three years (2010, 2011 and 2012) in three locations: Balsas (BAL), São Raimundo das Mangabeiras (SRM) and Primavera do Leste (PRL). The data were subjected to analysis of variance, and adjusted means were obtained to perform the GGE-Biplot analysis. The graphic results showed variation in the performance of the genotypes in the locations evaluated over the years. The performance of the lines MNC02-675F-4-9 and MNC02-675F-4-10 were considered ideal, with maximum yield and good stability in the locations evaluated. There mega-environments were formed, encompassing environments correlated positively. The lines MNC02-675F-4-9, MNC02-675F-9-3 and MNC02-701F-2 had the best performance within each mega-environment. The environment PRL10 and lines near this environment, such as MNC02-677F-2, MNC02-677F-5 and the control cultivar (BRS-Marataoã) could be classified as those of greater reliability, determined basically by the genotypic effects, with reduced G×E. Most of the environments evaluated were ideal for evaluation of G×E, since the genotypes were well discriminated on them. Therefore, the selection of genotypes with adaptability and superior performance for specific environments through the GGE-Biplot analysis was possible.

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