scholarly journals GGE biplot analysis of vegetable type soybean genotypes under multi-environmental conditions in India

2021 ◽  
Vol 42 (2) ◽  
pp. 247-253
Author(s):  
V. Nataraj ◽  
◽  
N. Pandey ◽  
R. Ramteke ◽  
P. Verghese ◽  
...  
Keyword(s):  
Block Design ◽  
Test Weight ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Design Data ◽  
Green Seed ◽  
Pod Yield ◽  
Biplot Analysis ◽  
Randomized Block Design ◽  
Soybean Genotypes

Aim: To understand the magnitude and pattern of genotype-environment interaction in vegetable type soybeans and to identify mega environment(s) and best performing genotype(s) across environments. Methodology: Five vegetable type soybean genotypes were evaluated across five geographical locations viz., Indore, Parbhani, Adilabad, Bengaluru and Pune, during rainy season of 2018. Genotypes were grown in a plot size of 1.35 x 3 m2 in three replications in randomized block design. Data on green pod yield, green seed test weight, days to 50% flowering, days to maturity and plant height were recorded using standard methods. GGE biplot analysis was performed using software “GGE Biplot version 7.0”. Results: In the present investigation, except in case of green seed test weight, in remaining four traits, major portion of variation was contributed by location (52.95-79.4%) followed by genotype (17.7-42.7%) and genotype x location interaction (2.21-4.29%). Through GGE biplot analysis, Bengaluru was found to be near ideal environment and genotypes Karune and Harasoya were found to be the best performers across the locations with respect to green pod yield. Interpretation: Bengaluru was found to be near ideal environment for vegetable type soybean evaluation. Selection for genotypes having wider adaptability can be conducted at this location. Genotypes Karune and Harasoya were found to be the best performers with respect to green pod yield. These two genotypes can be included as parents for breeding as vegetable type soybean. Key words: GEE biplot, Multienvironmental analyses, Soybean genotypes

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

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).

scholarly journals GGE Biplot Analysis of Multi-Environment Yield Trials in Soybean Promising Lines

2019 ◽  
Vol 3 (2) ◽  
pp. 72
Author(s):  
Ayda Krisnawati ◽  
M. Muchlish Adie
Keyword(s):  
Block Design ◽  
Genotype By Environment Interaction ◽  
Yield Stability ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Tropical Regions ◽  
Biplot Analysis ◽  
Genotype Environment Interaction ◽  
Promising Line ◽  
The Tropics

Soybean in Indonesia is grown in diverse agro-ecological environments. The performance of soybean yield often varies due to significant genotype × environment interaction (GEI), therefore the yield stability of performance is an important consideration in the breeding program. The aim of the research was to exploring the GEI pattern and yield stability of soybean promising lines in the tropics using GGE (Genotype and Genotype by Environment Interaction) biplot method. A total of 16 soybean promising lines were evaluated in ten environments during 2016 growing season. The experiment was arranged in a randomized completely block design with four replicates. The analysis of variance revealed that environments (E) explained the highest percentage of variation (51.45%), meanwhile the genotypes (G) and genotype × environment interactions (GEI) contributed for 3.24%, and 14.59% of the total variation, respectively. Seed yield of 16 soybean promising lines ranged from 2.41 to 2.83 t.ha-1 with an average of 2.74 t.ha-1. Joint effects of genotype and interaction (G+GE) which was partitioned using GGE biplot analysis showed that the first two components were significant, explaining 60.88% (37.89% PC1 and 22.98% PC2) of the GGE sum of squares. Indonesia can be divided into at least four putative mega environments for soybean production. The GGE biplot identified G10 as high yielding and stable promising line, thus recommended to be developed in multi-environment in tropical regions of Indonesia.

scholarly journals GGE-Biplot analysis of multienvironments yield trials of Egyptian cotton (Gossypium barbadense L.,)

2021 ◽  
Vol 2 (1) ◽  
pp. 61
Author(s):  
Ahmed Mohamed Abdelmoghny ◽  
Reham Helmy Gibely ◽  
Mariz Sobhy Max ◽  
Emad Abdelazeim Amer ◽  
Salah Saber Hassan
Keyword(s):  
Block Design ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Cotton Yield ◽  
Comparative Performance ◽  
Genotype X Environment ◽  
Biplot Analysis ◽  
Cotton Genotypes ◽  
Egyptian Cotton ◽  
The Ideal

GGE biplot technique is one of the most appropriate methods for investigating the genotype x environment interaction. A total of twenty one Egyptian cotton genotypes were tested to evaluate stability and adaptability during two agricultural years at four environments using randomized complete block design with six replications. The analysis of variance showed that the effect of environments, years, environment x years, genotypes, and genotype x environment was highly significant for lint cotton yield / plot. Also, the interaction effect due to G x Y x E was also significant. The variation of sum of squares was divided for genotypes, years, environments, and GEI to 25.261 %, 0.574 %, 36.660 % and 3.396 % respectively of total variance for lint cotton yield / plot. The analysis of environments revealed that the cotton genotypes showed maximum mean values for lint cotton yield in El-Gharbiya then Kafr El-Sheikh. Comparative performance of genotypes through genotype by environment interaction (GEI) revealed that genotypes produced maximum lint cotton yield during 2019 at El-Gharbiya followed by Kafr El-Sheikh. The results of biplot analysis showed that the first and second principle components accounted 87.96 % and 5.86 %, respectively, and in total of 93.82 % lint cotton yield variance. The polygon view led to the identification of top six genotypes. G6, G7 and G15 were the ideal genotypes which has the highest mean performance coupled with maximum stability. The ideal genotype could be used as a benchmark for selection. While, the desirable genotypes was (G2, G4 and G5) characterized by high mean yield but less ideal genotypes. E2 was the ideal environment across four environments which have the highest ability to discriminate the genotypes. Four environments had long vectors with small angles (acute) are highly correlated and clustered as one mega-environment. The cotton breeder should evaluate the genotypes under new environments to reduce the costs.     

scholarly journals Estimation of adaptability and stability of early strains of ‘Carioca’ and black beans (Phaseolus vulgaris) in Pernambuco State, Brazil

2020 ◽  
pp. 263-270 ◽  
Author(s):  
Richardson Sales Rocha ◽  
Paulo Ricardo dos Santos ◽  
Tâmara Rebecca Albuquerque de Oliveira ◽  
Rogério Figueiredo Daher ◽  
Maxwel Rodrigues Nascimento ◽  
...  
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Yield Data ◽  
Black Beans ◽  
Black Bean ◽  
Randomized Block Design ◽  
Yield Trait ◽  
Selection For

Low yields of early ‘Carioca’ and black bean varieties are a consequence of instability and low yield adaptability to specific growing environments. The goal of this work was to evaluate the genotype x environment interaction of early ‘Carioca’ and black bean new lines aiming at obtaining genotypes with high grain yield and good adaptability and stability. In (2012), 15 genotypes of the black group were evaluated in Ibimirim, Belém do São Francisco, and Petrolina municipalities, in Pernambuco State, Brazil; and, in (2016), 11 genotypes of early ‘Carioca’ bean were evaluated in Caruaru, Arcoverde, and Araripina municipalities, also in Pernambuco State. The experiment was conducted in a randomized block design with three replicates, and grain yield data were submitted to analysis of variance, in which means were compared by the Tukey’s test and analysis via GGE Biplot. In Arcoverde, the grain yield was greater for all early ‘Carioca’ bean genotypes, whereas, in the environment of Petrolina, there was the worst grain yield in kg ha-1 for all black bean genotypes, individually. The GGE Biplot methodology was found to be efficient in identifying genotypes with good adaptability, stability, and yield. Differences presented by the genotypes for the grain yield trait give the basis to recommend the genotypes and express the possibility of selection for genetic improvement of the species.

Biplot analysis of genotype-environment interaction in durum wheat using the AMMI model

2006 ◽  
Vol 54 (4) ◽  
pp. 459-467 ◽  
Author(s):  
E. Farshadfar ◽  
J. Sutka
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Field Experiments ◽  
Block Design ◽  
Environment Interaction ◽  
Ge Interaction ◽  
Biplot Analysis ◽  
Randomized Block Design ◽  
Total Variability ◽  
Ammi Model

The genotype by environment (GE) interaction is a major problem in the study of quantitative traits because it complicates the interpretation of genetic experiments and makes predictions difficult. In order to quantify GE interaction effects on the grain yield of durum wheat and to determine stable genotypes, field experiments were conducted with ten genotypes for four consecutive years in two different conditions (irrigated and rainfed) in a completely randomized block design with three replications in each environment. Combined analysis of variance exhibited significant differences for the GE interaction, indicating the possibility of stable entries. The results of additive main effect and multiplicative interaction (AMMI) analysis revealed that 12% of total variability was justified by the GE interaction, which was six times more than that of genotype. Ordination techniques displayed high differences for the interaction principal components (IPC1, IPC2 and IPC3), indicating that 92.5% of the GE sum of squares was justified by AMMI1, AMMI2 and AMMI3, i.e. 4.5 times more than that explained by the linear regression model. The results of the AMMI model and biplot analysis showed two stable genotypes with high grain yield, due to general adaptability to both rainfed and irrigated conditions, and one with specific adaptation.

scholarly journals Simultaneous Selection Index as a Tool for Identification of Stable High Yielding Maydis Leaf Blight Resistant Maize Prebreeding Lines

2021 ◽  
Author(s):  
Anjali Joshi ◽  
Sneha Adhikari ◽  
Narendra Kumar Singh ◽  
Amarjeet Kumar ◽  
Jai Prakash Jaiswal ◽  
...  
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Selection Index ◽  
Leaf Blight ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype X Environment ◽  
Biplot Analysis ◽  
Breeding Programmes ◽  
Simultaneous Selection

Abstract Maize is a crop possessing high adaptability however, large differential genotypic responses have been reported when evaluated under multiple environments. Using randomized complete block design with two replications a total of 169 teosinte derived maize backcross inbred lines (BILs) were evaluated in three different environments namely, E2, E4 and E6 for maydis leaf blight (MLB) resistance and grain yield. Out of these, 73 BILs were identified displaying resistance to MLB in at least one of the environments and were subjected to additive main effect and multiplicative interaction (AMMI) analysis and genotype and genotype X environment (GGE) biplot analysis for identification of lines showing stable and high MLB resistance and grain yield. Highly significant effects of genotype, environment and genotype X environment interaction (GEI) were observed for both the traits studied. AMMI ANOVA for percent disease index (PDI) revealed that highest percentage of total sum of squares (SS) was attributed to GEI (40.55%) while 32.86% and 26.59% was contributed by genotype and environment, respectively. For grain yield largest contribution of 68.02% towards SS was done by genotype component followed by GEI (17.50%) and E (14.48%). GGE biplot analysis identified two mega environments for both PDI (E2, E4/E6) and grain yield (E2/E4, E6). Based on AMMI stability value (ASV), genotype MT-90 (32) was observed to be most stable for PDI. While for grain yield highest stability was displayed by genotype MT-83 (28). Simultaneous selection index (SSI) helped in identification of ten stable high yielding MLB resistant genotypes namely, MT-120 (45), MT-14 (2), MT-166 (62), MT-148 (55), MT-190 (72), MT-37 (9), MT-19 (3), MT-114 (42), MT-77 (27) and MT-94 (35) which could be used in future breeding programmes either as donor of MLB resistance and grain yield or after combining ability analysis these genotypes could be used as parents for development of superior yielding MLB resistant hybrids.

scholarly journals GGE Biplot projection in discriminating the efficiency of popcorn lines to use nitrogen

2017 ◽  
Vol 41 (1) ◽  
pp. 22-31 ◽  
Author(s):  
Adriano dos Santos ◽  
Antônio Teixeira do Amaral Júnior ◽  
Railan do Nascimento Ferreira Kurosawa ◽  
Ismael Fernando Schegoscheski Gerhardt ◽  
Roberto Fritsche Neto
Keyword(s):  
Nitrogen Availability ◽  
Block Design ◽  
Germplasm Collection ◽  
Inbred Lines ◽  
Gge Biplot ◽  
State University ◽  
Information Ratio ◽  
The North ◽  
Randomized Block Design ◽  
Main Components

ABSTRACT Nitrogen is essential for sustaining life on the planet, and it is the most important nutrient for obtaining high agricultural production. However, their use leads to the release of nitrous oxide with a global warming potential 296 times higher than the CO2 molecule, making it a challenge to reduce their use in agriculture. The objective of this research was to identify efficient popcorn inbred lines and responsive nitrogen use and exhibit a good expansion volume. For this, 29 inbred lines from the Germplasm Collection of Darcy Ribeiro North Fluminense State University (UENF) were evaluated at two contrasting levels of nitrogen availability (low and ideal) at two representative locations in the north and northwest of the state of Rio de Janeiro, Brazil, arranged in a randomized block design with three replicates. These inbred lines were discriminated against efficient use of nitrogen by multivariate GGE Biplot. Selective accuracy was close to 1, showing that the genotypes were enough to provide contrasting success in selection procedures. The first two main components (PC) retained 93.82% of the total variation, and PC1 furnished an information ratio (IR) that was unaffected by noise. L77 was the most unstable line, while P7, P2, P6, P3, P5, P4, P9, P10, P8, P9, L70, L74, and L55 were efficient and responsive. The GGE biplot method is recommended for the reliable identification of popcorn lines that are efficient and responsive to the use of nitrogen.

scholarly journals AN INVESTIGATION ON HETEROSIS, GENERAL AND SPECIFIC COMBINING ABILITY FOR POD YIELD AND ITS CONTRIBUTING PARAMETERS IN OKRA [ABELMOSCHUS ESCULENTUS (L.) MOENCH]

2021 ◽  
Vol 9 (08) ◽  
pp. 334-341
Author(s):  
Shailesh Kapadia ◽  
◽  
Kirti Patel ◽  
P.K. Patel ◽  
Mempal D. ◽  
...  
Keyword(s):  
Combining Ability ◽  
Quantitative Traits ◽  
Block Design ◽  
Abelmoschus Esculentus ◽  
F1 Hybrids ◽  
Research Centre ◽  
Pod Yield ◽  
Randomized Block Design ◽  
Per Se ◽  
Almost All

The heterosis and combining ability studies were conducted by utilizing modified Line X Tester mating design involving 6 Lines and 9 testers of Okra [Abelmoschus esculentus (L.) Moench]. The breeding material involving fifty four F1 hybrids along with 15 parents with one commercial check were evaluated during Kharif 2020 in a Randomized Block Design (R.B.D.) with three replications at Research Centre of Goldking Biogene Private Limited with an aim to estimate the magnitude of heterosis and to identify the good parents and good hybrid combinations for pod yield and other quantitative traits. Among the parents GKOF-1, GKOF-5 and GOM-7 were found to be good general combiners for pod yield per plot. Among the lines GKOF-3, GKOF-4 and GKOF-6 and testers GKOM-4, GKOM-5, GKOM-7 and GKOM-9 were found to be involved in exhibiting significant sca effects for almost all characters. Among the crosses GKOF-2 X GKOM-5, GKOF-1 X GKOM-8 and GKOF-6 X GKOM-7 exhibited high per se performance for pod yield per plot. Further the cross GKOF-1 X GKOM-7, GKOF-4 X GKOM-9 and GKOF-6 X GKOM-4 revealed highest positively significant sca effects for pod yield per plot.

scholarly journals Genotype × Environment Interaction and Stability Analysis in Basmati Rice (Oryza sativa L.) Genotypes

2021 ◽  
Author(s):  
Hari Kesh ◽  
Khushi Ram Battan ◽  
Rakesh Kumar
Keyword(s):  
Stability Analysis ◽  
Oryza Sativa L ◽  
Block Design ◽  
Quality Parameters ◽  
Basmati Rice ◽  
Eating Quality ◽  
Environment Interaction ◽  
Indian Agriculture ◽  
Randomized Block Design ◽  
Cooking And Eating Quality

Background: Basmati rice is an important cereal crop occupying a unique position in Indian agriculture. More than 90% of global rice is produced and consumed in Asia and plays a crucial role in the entry of mineral nutrients into the food chain. Identification of stable genotypes is of great significance because the environmental conditions vary from season to season and year to year. Methods: Thirty six Basmati rice genotypes were evaluated in four production environments during kharif 2016 and kharif 2017 at two locations Kaul and Uchani to study the G × E interaction for milling, appearance, cooking and eating quality parameters. The genotypes were grown in randomized block design with three replications. Result: Based on the stability analysis of Eberhart and Russell model, genotypes viz., Haryana Mahak 1, Pusa 1826-12-271-4 and HKR 06-434 were found stable across the environments for milling%, grain length before cooking and length breadth ratio before cooking, respectively.

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