Identification of stable lentil (Lens culinaris Medik) genotypes through GGE biplotand AMMI analysis for North Hill Zone of India

2018 ◽  
Author(s):  
Muniyandi Samuel Jeberson ◽  
Kadanamari Sankarappa Shashidhar ◽  
Shabir Hussain Wani ◽  
Amit Kumar Singh ◽  
Sher Ahmad Dar
Keyword(s):  
Principal Components ◽  
Lens Culinaris ◽  
Graphical Representation ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype X Environment ◽  
Ammi Analysis ◽  
Total Variability ◽  
Wide Adaptation ◽  
Superior Genotypes

In the present investigation with 24 lentil genotypes, first two Principal components revealed more than 90 per cent of the variability for the yield which indicates that G and GE together accounted for more than 10 per cent of total variability. Based on the present analysis of using GGE biplot models, considering simultaneous mean yield and stability, the genotypes G4, G12, G6, G13 and G2 were relatively stable in all the environments.The environment E1(Berthin) was discriminative (informative). This environment contributed most to the variability in grain yield. Hence, GGE biplot method is suitable to discriminate the genotypes based on their stable and instability nature across the environments.The AMMI analysis revealed that G13, G14, G12, G2, G23, G16 and G9 had wide adaptation and not be affected by the Genotype x environment interaction (GxE); hence mayyieldedgood across the environments. E2 and E3 could be considered as good selection sites for identifying broad based and most adaptable lentil genotypes. This study has clearly and by far aided in identification of stable and superior genotypes in graphical representation.

scholarly journals Genotype environment interaction and stability for yield and its components in advanced breeding lines of red rice (Oryza sativa L.)

2020 ◽  
Vol 49 (3) ◽  
pp. 425-435
Author(s):  
BM Dushyantha Kumar ◽  
AP Purushottam ◽  
P Raghavendra ◽  
T Vittal ◽  
KN Shubha ◽  
...  
Keyword(s):  
Grain Yield ◽  
Oryza Sativa L ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Red Rice ◽  
Yield Performance ◽  
Breeding Lines ◽  
Genotype Environment Interaction ◽  
Ammi Analysis ◽  
Total Variability

Effects of genotype, environment and their interaction for grain yield and yield attributing characters in 20 advanced breeding lines of rice across six environments was investigated. Yield stability and adaptability of yield performance were analyzed by Eberhart and Russel model and (GGE) bi-plot. The AMMI analysis of variance indicated that mean squares due to genotypes, location and genotype location contributed per cent 59.08, 5.79 and 21.63, respectively for total variability in grain yield per hectare. Estimates of GGE bi-plot revealed that the lines G1, G3, G11, G13, G15, G12, G16, G7 and G10 were positioned near GGL bi-plot origin indicating wider adaptation for the trait grain yield per hectare. Eberhart and Russel Model and GGE biplot model showed the advanced breeding lines viz., JB 1-11-7 (G1) and JA 6-2 (G15) exhibited wider adaptability across the tested environments for number of productive tillers per plant and yield per hectare.

scholarly journals Evaluation of maize grain yield and yield stability by AMMI analysis

Genetika ◽  
2018 ◽  
Vol 50 (3) ◽  
pp. 1067-1080 ◽  
Author(s):  
Dragana Brankovic-Radojcic ◽  
Vojka Babic ◽  
Zdenka Girek ◽  
Tomislav Zivanovic ◽  
Aleksandar Radojĉic ◽  
...  
Keyword(s):  
Grain Yield ◽  
Yield Stability ◽  
Environment Interaction ◽  
Maize Hybrids ◽  
Genotype X Environment ◽  
Maize Grain Yield ◽  
Ammi Analysis ◽  
Ammi Model ◽  
Superior Genotypes ◽  
Maize Grain

Significant genotype x environment interaction for quantitative traits, such is grain yield, reduces the usefulness of genotype means, over all environments, for selecting superior genotypes. AMMI model is a valuable statistical tool in identifying systemic variation contained in the interaction effect. Obtained data could be applied in maximizing yield potential in every environment based on both narrow and wide genotype adaptability, without the necessity of developing breeding programs for smaller targeted environments. Precise assortment of superior genotypes, with the assistance of AMMI model, leads to the better recommendation of newly bred hybrids, and thus increasing maize grain yield in a targeted environment. In this research genotype x environment interaction and yield stability of 36 maize hybrids of FAO 300-700 maturity group was investigating. The trial was set according to Randomized Complete Block Design (RCBD). Data were processed in order to obtain average estimates of grain yield, and yield stability was assessed by the method of AMMI analysis. The highest average grain yield was achieved in 2011 (11.62 t/ha), and the lowest in the most stressful and dry 2012 (6.90 t/ha). In the region Loznica L2 the highest average yield was noticed (13.81 t/ha), while at L7 (Sremska Mitrovica) average grain yield was the lowest (6.97 t/ha). Results of AMMI analysis gave precise recommendation for production of maize hybrids in certain environments, by determining winning areas of hybrids H20, H11 and H36. Medium early maturing and high yielding hybrids (H11 and H20) are therefore considered more favorable for production in environments with lower precipitation, while high yielding and more stable hybrids H21 and H35 are suitable for a wider range of environments. Hybrid H36 (FAO 700) showed its full potential at L2, and L3 which did not suffer from a lack of moisture. This hybrid also expressed its best potential in environments with favorable conditions.

scholarly journals Delineation of Genotype × Environment Interaction for Identification of Stable Genotypes to Grain Yield in Mungbean

2020 ◽  
Vol 2 ◽  
Author(s):  
Santhi Madhavan Samyuktha ◽  
Devarajan Malarvizhi ◽  
Adhimoolam Karthikeyan ◽  
Manickam Dhasarathan ◽  
Arumugam Thanga Hemavathy ◽  
...  
Keyword(s):  
Grain Yield ◽  
Tamil Nadu ◽  
Stability Index ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype Environment Interaction ◽  
South Indian ◽  
Indian State ◽  
Wide Adaptation ◽  
High Yields

In the present study, fifty-two mungbean (Vigna radiata) genotypes were evaluated for seven morphological traits at three different environments in South Indian state Tamil Nadu, namely Virinjipuram (E1), Eachangkottai (E2), and Bhavanisagar (E3) during Kharif 2017, 2018, and 2019, respectively. The data collected were subjected to variability and correlation analyses, followed by stability analysis using additive main effects and multiplicative interaction (AMMI) model, genotype and genotype × environment interaction effects (GGE) biplot. Variablility was observed among the genotypes for the following traits viz., plant height, days to fifty per cent flowering, number of pods per plant, pod length, number of seeds per pod, hundred seed weight and grain yield. Correlation analysis showed that the trait number of pods per plant was significantly associated with grain yield. The G × E was smaller than the genetic variation of grain yield as it portrayed the maximum contribution of genotypic effects (61.07%). GGE biplot showed E3 as a highly discriminating and representative environment. It also identified environment-specific genotypes viz., EC 396111 for E1, EC 396125 for E2 and EC 396101 for E3 environments. The genotypes with minimum genotype stability index (GSI) viz., V2802BG (7), HG 22 (13), and EC 396098 (13) were observed with wide adaptation and high yields across all the three environments. In summary, we identified stable genotypes adapted across environments for grain yield. These genotypes can be used as parent/pre-breeding materials in future mungbean breeding programs.

scholarly journals AMMI and GGE Biplot Analysis for Stability of Yield in Mid-early Pigeonpea [Cajanus cajan (L.) Millspaugh] Genotypes

2022 ◽  
Author(s):  
P. Jagan Mohan Rao ◽  
N. Sandhyakishore ◽  
S. Sandeep ◽  
G. Neelima ◽  
A. Saritha ◽  
...  
Keyword(s):  
Block Design ◽  
High Yield ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype By Environment ◽  
Genotype Environment Interaction ◽  
Single Location ◽  
Randomized Complete Block Design ◽  
Advanced Stages ◽  
Superior Genotypes

Background: The genotype × environment interaction greatly influences the success of breeding and in multi-location trials complicates the identification of superior genotypes for a single location, due to magnitude of genotype by location interaction are often greater than genotype by year interaction. This necessitates genotype evaluation in multi environments trials in the advanced stages of selection. Methods: Nine elite pigeonpea genotypes of mid-early duration were evaluated in six diverse locations in randomized complete block design with three replications during kharif, 2019 to ascertain the stable genotypes, environments discrimination and genotype by environment crossovers using AMMI and GGE biplot stability models. Result: The results in the present investigation revealed that first two principal components explained 73.4% of variation interaction, while, 80.50% in GGE biplot. Both the models identified WRGE-126 (G6) as stable performer with high yield (1733 kg ha-1) and among the locations Tandur (E1) measured as the ideal environment. Whereas, the environments, Adilabad (E3) and Warangal (E4) were observed representative with better discriminating ability.

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.

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