scholarly journals Stability and G × E Analysis of Oil Yield of Sunflower Single Cross Hybrids In Diverse Environments

2021 ◽  
Author(s):  
Mehdi Ghaffari ◽  
Amir Gholizadeh ◽  
Seyyed Abbasali Andarkhor ◽  
َAsadolah Zareei Siahbidi ◽  
Seyed Ahmad Kalantar Ahmadi ◽  
...  
Keyword(s):  
Graphical Method ◽  
Block Design ◽  
Oil Yield ◽  
Gge Biplot ◽  
Biplot Analysis ◽  
Growing Seasons ◽  
Superior Genotypes ◽  
Ideal Genotype ◽  
Selection Of ◽  
The Ideal

Abstract Multi-environment trials have a fundamental role in selection of the best genotypes across different environments before its commercial release. This study was carried out to identify high-yielding stable sunflower genotypes using the graphical method of the GGE biplot. For this purpose, 11 new hybrids along with four cultivars were evaluated in a randomized complete block design with four replications across 8 environments (combination of years and locations) during 2018–2020 growing seasons. The results indicated that genotype (G), environment (E) and genotype × environment (G×E) effects were significant for oil yield. The G, E and G×E interaction effects accounted for 51.94, 9.50 and 18.67% of the total variation, respectively. Results of biplot analysis showed that the first and second principle components accounted 45.9% and 20.4%, respectively, and in total 66.3% of oil yield variance. GGE biplot analysis indicated two major mega-environments of sunflower testing locations in Iran. Based on the hypothetical ideal genotype biplot, the genotypes G3 and G5 were better than the other genotypes for oil yield and stability, and had the high general adaptation to all environments. Ranking of genotypes based on the ideal genotype from the most appropriate to most inappropriate genotypes is as follows: G5 ˃ G3 ˃ G8 ˃ G14 ˃ G6 ˃ G2 ˃ G13 ˃ G12 ˃ G10 ˃ G11 ˃ G1 ˃ G7 ˃ G4 ˃ G15 ˃ G9. Furthermore, ranking the environments based on the ideal environment introduced Sari location as the best environment. Therefore, the Sari location can be used as suitable test location for selecting superior genotypes of sunflower in Iran. Generally, our results showed the efficiency of the graphical method of the GGE biplot for selection of the genotypes that are stable, high yielding, and responsive.

scholarly journals Evaluation of sugarcane genotypes and production environments in Paraná by GGE biplot and AMMI analysis

2013 ◽  
Vol 13 (1) ◽  
pp. 83-90 ◽  
Author(s):  
Pedro Henrique Costa de Mattos ◽  
Ricardo Augusto de Oliveira ◽  
João Carlos Bespalhok Filho ◽  
Edelclaiton Daros ◽  
Mario Alvaro Aloiso Veríssimo
Keyword(s):  
Gge Biplot ◽  
Ge Interaction ◽  
Growing Seasons ◽  
Production Environments ◽  
Ammi Analysis ◽  
Superior Genotypes ◽  
Definition Of ◽  
Ideal Genotype ◽  
Selection Of ◽  
Slight Advantage

The purpose of this study was to evaluate sugarcane genotypes for the trait tons of sugar per hectare (TSH), stratifying five production environments in the state of Paraná. The performance of 20 genotypes and 2 standard cultivars was analyzed in three consecutive growing seasons by the statistical methods AMMI and GGE Biplot. The GGE Biplot grouped the locations into two mega-environments and indicated the best-performing genotypes for each one, facilitating the selection of superior genotypes. Another advantage of GGEBiplot is the definition of an ideal genotype (G) and environment (E), serving as reference for the evaluation of genotypes and choice of environments with greater GE interaction. Both models indicated RB006970, RB855156 and RB855453 as the genotypes with highest TSH and São Pedro do Ivai as the environment with the greatest GE interaction. Both approaches explained a high percentage of the sum of squares, with a slight advantage of AMMI over GGE Biplot analysis.

scholarly journals Identification of the Optimum Environments for the High Yield and Quality Traits of Lentil Genotypes Evaluated in Multi-Location Trials

2021 ◽  
Vol 13 (15) ◽  
pp. 8247
Author(s):  
Dimitrios N. Vlachostergios ◽  
Christos Noulas ◽  
Anastasia Kargiotidou ◽  
Dimitrios Baxevanos ◽  
Evangelia Tigka ◽  
...  
Keyword(s):  
Crude Protein ◽  
Agronomic Traits ◽  
High Yield ◽  
Breeding Programs ◽  
Growing Seasons ◽  
Yield And Quality ◽  
Food And Feed ◽  
Superior Genotypes ◽  
Selection Of ◽  
The Ideal

Lentil is a versatile and profitable pulse crop with high nutritional food and feed values. The objectives of the study were to determine suitable locations for high yield and quality in terms of production and/or breeding, and to identify promising genotypes. For this reason, five lentil genotypes were evaluated in a multi-location network consisting of ten diverse sites for two consecutive growing seasons, for seed yield (SY), other agronomic traits, crude protein (CP), cooking time (CT) and crude protein yield (CPY). A significant diversification and specialization of the locations was identified with regards to SY, CP, CT and CPY. Different locations showed optimal values for each trait. Locations E4 and E3, followed by E10, were “ideal” for SY; locations E1, E3 and E7 were ideal for high CP; and the “ideal” locations for CT were E3 and E5, followed by E2. Therefore, the scope of the cultivation determined the optimum locations for lentil cultivation. The GGE-biplot analysis revealed different discriminating abilities and representativeness among the locations for the identification of the most productive and stable genotypes. Location E3 (Orestiada, Region of Thrace) was recognized as being optimal for lentil breeding, as it was the “ideal” or close to “ideal” for the selection of superior genotypes for SY, CP, CT and CPY. Adaptable genotypes (cv. Dimitra, Samos) showed a high SY along with excellent values for CP, CT and CPY, and are suggested either for cultivation in many regions or to be exploited in breeding programs.

scholarly journals Adaptability and phenotypic stability of sugarcane clones

2018 ◽  
Vol 53 (1) ◽  
pp. 42-52 ◽  
Author(s):  
Jiuli Ani Vilas Boas Regis ◽  
João Antonio da Costa Andrade ◽  
Adriano dos Santos ◽  
Aparecido Moraes ◽  
Rafael William Romo Trindade ◽  
...  
Keyword(s):  
Block Design ◽  
Saccharum Officinarum ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Phenotypic Stability ◽  
Genotype X Environment ◽  
Randomized Complete Block Design ◽  
Ideal Genotype ◽  
The Ideal

Abstract: The objective of this work was to select superior sugarcane (Saccharum officinarum) clones with good stability and adaptability, considering the genotype x environment interaction in two productive cycles. Twenty-five early clones plus five control clones were evaluated during two cuts (ratoon cane and plant cane) in 24 environments. A randomized complete block design was used, with three replicates. Tons of stems per hectare and tons of pol per hectare were evaluated. To verify adaptability and stability, the bisegmented regression and the multivariate (AMMI and GGE biplot) methods were used. According to the three methods, which are complementary regarding the desired information, the most promising clones in terms of stability and general adaptability are G5, G12, and G13; the last two are closest to the ideal genotype. The G13 clone is highly productive in favorable and unfavorable environments, presenting the highest averages for ton of stems and pol per hectare. The G3, G4, G10, G15, G17, G18, G22, G23, G25, G26, and G30 clones are not recommended for the 24 evaluated environments.

ADAPTIVE PROPERTIES OF NEW OAT VARIETIES IN THE MIDDLE VOLGA REGION

2020 ◽  
pp. 100-107
Author(s):  
V.G. Zakharov ◽  
◽  
О.G. Mishenkina ◽  
Keyword(s):  
Stability Index ◽  
Volga Region ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Average Yield ◽  
Middle Volga Region ◽  
Biplot Analysis ◽  
Middle Volga ◽  
Ideal Genotype ◽  
The Ideal

The research was conducted in 2016-2020 in the Ulyanovsk region. The aim was to assess the yield and genotype-environment interaction of varieties and promising lines of spring oats in the Middle Volga region. The source material was 9 varieties and 4 promising lines of oats created in the Ulyanovsk RAS. Contrasting moisture and temperature conditions provided differentiation of the studied material by yield and level of adaptability. Two-factor dispersion analysis revealed significant differences between genotypes in yield, media, and their interaction. The highest average yield among filmy varieties was formed by the Dragun variety (42.7 c/ha), the lowest by Vsadnik (37.0 c/ha). Naked varieties Azil and Griva showed the same yield (24.3 c / ha). The share of influence of environmental conditions (years) was 51.6%, varieties-33.8%. According to GGE biplot analysis, 2016, 2017, and 2020 were characterized by a high differentiating ability, while 2018 was the most representative. A rank assessment based on six adaptive criteria (regression coefficient (bi), stability index (S2 j), coefficient of variation (Vc), Martynov ultrastability (Hi), ultrastability (Hom) and selection value of the variety (Sc) V.V. Khangildin revealed the advantage of Grum (17), Dragun (22), Konkur (18), and Kenter (24) varieties, while Troika (64) had the lowest rank. Evaluation and ranking of genotypes by average yield and stability in different environments using GGE biplot analysis relative to the “ideal” genotype showed that the highest average yield was in the Dragun variety, which also has high stability, and practically corresponds to the «ideal» genotype. Next are the lines 479/11, 549/15, and the varieties Grum and Konkur, which are close to the « ideal» genotype. Less stable is the 537/15 line, which produced yields less than expected in 2016, 2018 and 2019 environments and more in 2017 and 2020. Biplot analysis of the yield of film varieties confirmed the results of the rank assessment for adaptability parameters, adjusting the location in the group of the best varieties.

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 GGE Biplot Analysis of Yield Stability in Multi-environment Trials of Lentil Genotypes under Rainfed Condition

2013 ◽  
Vol 5 (2) ◽  
pp. 256-262 ◽  
Author(s):  
Rahmatollah KARIMIZADEH ◽  
Mohtasham MOHAMMADI ◽  
Naser SABAGHNI ◽  
Ali Akbar MAHMOODI ◽  
Barzo ROUSTAMI ◽  
...  
Keyword(s):  
Block Design ◽  
Gge Biplot ◽  
Average Yield ◽  
Ge Interaction ◽  
Rainfed Condition ◽  
Yield Variation ◽  
Randomized Complete Block Design ◽  
Ideal Genotype ◽  
Genotype G1 ◽  
The Ideal

This investigation was done to study GE interaction over twelve environments for seed yield in 18 genetically diverse genotypes. Grain yield performances were evaluated for three years at four locations in Iran using a randomized complete block design. The first two principal components (IPC1 and IPC2) were used to create a two-dimensional GGE biplot that accounted percentages of 49% and 20% respectively of sums of squares of the GE interaction. The combined analysis of variance indicated that year and location were the most important sources affecting yield variation and these factors accounted for percentages of 50.0% and 33.3% respectively of total G+E+GE variation. The GGE biplot suggested the existence of three lentil mega-environments with wining genotypes G1, G11 and G14. According to the ideal-genotype biplot, genotype G1 was the better genotype demonstrating high mean yield and high stability of performance across test locations. The average tester coordinate view indicated that genotype G1 had the highest average yield, and genotypes G1 and G12 recorded the best stability. The study revealed that a GGE biplot graphically displays interrelationships between test locations as well as genotypes and facilitates visual comparisons.

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 Tolerance to preharvest sprouting and yield of wheat genotypes from different breeding programs

2015 ◽  
Vol 50 (8) ◽  
pp. 698-706
Author(s):  
Rafael Nörnberg ◽  
José Antonio Gonzalez da Silva ◽  
Henrique de Souza Luche ◽  
Elisane Weber Tessmann ◽  
Sydney Antonio Frehner Kavalco ◽  
...  
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Preharvest Sprouting ◽  
Rio Grande Do Sul ◽  
Falling Number ◽  
Breeding Programs ◽  
Wheat Genotypes ◽  
Randomized Complete Block Design ◽  
Superior Genotypes ◽  
Selection Of

Abstract:The objective of this work was to characterize the performance of elite wheat genotypes from different Brazilian breeding programs for traits associated with grain yield and preharvest sprouting. The study was conducted in 2010 and 2011 in the municipality of Capão do Leão, in the state of Rio Grande do Sul, Brazil, in a randomized complete block design with three replicates. Thirty-three wheat genotypes were evaluated for traits related to preharvest sprouting and grain yield. The estimate of genetic distance was used to predict potential combinations for selection of plants with high grain yield and tolerance to preharvest sprouting. The combined analysis of sprouted grains and falling number shows that the TBIO Alvorada, TBIO Mestre, Frontana, Fundacep Raízes, Fundacep Cristalino, and BRS Guamirim genotypes are tolerant to preharvest sprouting. Combinations of TBIO Alvorada and TBIO Mestre with Fundacep Cristalino show high potential for recovering superior genotypes for high grain yield and tolerance to preharvest sprouting.

scholarly journals GENOTYPE BY ENVIRONMENT INTERACTION IN COWPEA LINES USING GGE BIPLOT METHOD

2018 ◽  
Vol 31 (1) ◽  
pp. 64-71 ◽  
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.

Evaluation of genetic variability, heritability and genetic advance in blackgram [Vigna mungo (L.) Hepper]

2018 ◽  
Author(s):  
Shilpa Chauhan ◽  
Raj Kumar Mittal ◽  
A. Lohar ◽  
Vinod Kumar Sood ◽  
Ranjana Patial
Keyword(s):  
Experimental Study ◽  
Seed Yield ◽  
Harvest Index ◽  
Block Design ◽  
Genetic Advance ◽  
Biological Yield ◽  
High Heritability ◽  
Superior Genotypes ◽  
Transgressive Segregants ◽  
Selection Of

An attempt was made to study blackgram germplasm with an objective to develop genetically diverse genotypes accompanied with high heritable components of yield contributing traits. The experimental material comprised of 21 blackgram genotypes, was examined during kharif 2015 and 2016. Experimental study conducted during kharif 2015, was mainly relied on selection of transgressive segregants, which were further analyzed in Compact Family Block Design during kharif 2016. The results depicted that families and progenies within families were significantly different for majority of the traits and found to be highly variable for biological yield, harvest index and seed yield. High heritability coupled with high genetic advance were recorded for plant height (74.15%, 33.12%), branches per plant (84.34%, 40.55%), biological yield (83.51%, 69.11%) and seed yield (84.50%, 66.11%). Thus, the present findings could be beneficial to develop superior genotypes through selection in blackgram breeding program.

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