Univariate stability analysis methods for determining genotype × environment interaction of durum wheat grain yield

2012 ◽  
Vol 11 (10) ◽  
Author(s):  
Rahmatollah Karimizadeh
Keyword(s):  
Stability Analysis ◽  
Grain Yield ◽  
Durum Wheat ◽  
Environment Interaction ◽  
Wheat Grain ◽  
Genotype Environment Interaction ◽  
Analysis Methods

Agro-morphological diversity and stability of durum wheat lines (Triticum durum Desf.) in Algeria

2013 ◽  
Vol 61 (2) ◽  
pp. 149-159 ◽  
Author(s):  
A. Mekliche ◽  
F. Dahlia ◽  
L. Hanifi-Mekliche
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Morphological Diversity ◽  
Environment Interaction ◽  
The North ◽  
Genotype Environment Interaction ◽  
Genotypic Stability ◽  
Triticum Durum Desf ◽  
Heterogeneity Variance ◽  
Wheat Lines

This study focuses on the genetic potential and genotypic stability of 17 durum wheat genotypes during three crop years under wet conditions in the north of Algeria (Algiers). The results showed highly significant (P<0.001) agro-morphological diversity between the genotypes and a genotype × environment interaction for all the traits except for fertile spikelet number. Wricke’s ecovalance (wi), Shukla's stability variance (σi2), heterogeneity variance (%HV) and the incomplete correlation (%IC) method were used to analyse the genotype × environment interaction on grain yield. The genotypes Ardente/Waha L2, Ardente and Saadi/Simeto L3 exhibited great instability with the highest values of wi, σi2, %HV and %IC. Ardente/Waha L1, Simeto/Vitron L5, Simeto and Ardente/Vitron L1 had the highest grain yield and average stability (wi, %HV and %IC were weak). Significant correlations were found between %HV, Rij2, bi, wi, σi2 and %IC, implying that they were similarly efficient in detecting stable genotypes and in measuring stability.

scholarly journals Genotype × Environment Interaction and Stability Analysis for Grain Yield of Mid-hill Rice Genotypes

2014 ◽  
Vol 8 ◽  
pp. 14-17 ◽  
Author(s):  
Hari K. Upreti ◽  
Sudarshan Bista ◽  
Surya N. Sah ◽  
Ramesh Dhakal
Keyword(s):  
Stability Analysis ◽  
Grain Yield ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Stability Parameters ◽  
Genotype X Environment ◽  
Genotype Environment Interaction ◽  
Significant Difference ◽  
Rice Genotypes

Genotype x Environment interaction limits the effectiveness of selection when selection is based only on mean yield. This G × E interaction was studied for grain yield in 7 genotypes  of mid-hill rice in five different environments across the Nepal. Significant difference was observed among genotype (G), environment (E) and interaction (G × E) but could not identify the stable high yielding genotypes for diverse environments. Therefore, stability parameters were calculated and analyzed. On the basis of stability parameters, two genotypes, NR 10414, NR 10492 and NR 10515 were found to be most stable over different environments. NR 10353 was identified as suitable genotypes with high grain yield for favorable environment.Nepal Agric. Res. J. Vol. 8, 2007, pp. 14-17DOI: http://dx.doi.org/10.3126/narj.v8i0.11565

scholarly journals Yield Stability and Genotype Environment Interaction of Water Deficit Stress Tolerant Mung Bean (Vigna radiata L. Wilczak) Genotypes of Bangladesh

Agronomy ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2136
Author(s):  
Mohammad Rafiqul Islam ◽  
Bikas Chandra Sarker ◽  
Mohammad Ashraful Alam ◽  
Talha Javed ◽  
Mohammad Jahangir Alam ◽  
...  
Keyword(s):  
Stability Analysis ◽  
Grain Yield ◽  
Water Deficit ◽  
Analysis Of Variance ◽  
Mung Bean ◽  
Water Deficit Stress ◽  
Environment Interaction ◽  
Stability Parameters ◽  
Genotype Environment Interaction ◽  
Ammi Analysis

Water deficit stress is a critical abiotic constraint to mung bean production that affects plant growth and development and finally reduces crop yield. Therefore, a field experiment was conducted at five diverse environments using four water stress-tolerant genotypes, namely BARI Mung-8, BMX-08010-2, BMX-010015, and BMX-08009-7, along with two popular cultivated varieties (check) of BARI Mung-6 and BARI Mung-7 to evaluate more stable tolerant genotypes across the country. Stability analysis was performed based on the grain yield. The combined analysis of variance showed significant variations among genotypes, environments, and their interactions. The AMMI analysis of variance indicated that genotype accounted for 91% of the total sum of squares for grain yield, followed by genotype × environment interaction (5%), and environment (4%). Partitioning of interaction indicated that the first three interaction principal components (IPCA1–IPCA3) were highly significant (p ≤ 0.01). Using these significant IPCAs, AMMI stability parameters and non-parameter indices BMX-010015 was found stable across the environment based on yield traits and grain yield. The BMX-08010-2 genotype also showed significant regression coefficient (bi) more than unity, and non-significant deviation from regression (S2di) values, indicating suitable for a favorable environment considering grain yield. So, based on the stability analysis (Eberhart and Russell), additive main effects, and multiplicative interactions (AMMI) analysis, the BMX-010015 and BMX-08010-2 could be suitable for having tolerance to water deficit stress.

scholarly journals Stability Analysis of Maize (Zea mays L.) Hybrids for Grain Yield and Its Attributing Traits Using Eberhart and Russel Model

2020 ◽  
pp. 52-63
Author(s):  
B. Arunkumar ◽  
E. Gangapp ◽  
S. Ramesh ◽  
D. L. Savithramma ◽  
N. Nagaraju ◽  
...  
Keyword(s):  
Stability Analysis ◽  
Grain Yield ◽  
Block Design ◽  
Joint Analysis ◽  
Environment Interaction ◽  
Production Environment ◽  
Stability Parameters ◽  
Environmental Indices ◽  
Genotype Environment Interaction ◽  
Single Cross

A genotype is considered to be most adaptive / stable, when it registers high mean yield but show a minimum interaction with the environment. Knowledge of genotype × environment interaction and yield stability are important parameters in breeding new cultivars with improved adaptation to environmental constraints prevailing in the target environments. Therefore, an effort was made to know the genotype - environment interaction and to identify stable single cross hybrids across the environments. Eight newly synthesized single cross maize hybrids and 7 checks were evaluated in a Randomized Block Design with three replications during Rabi-2016 across three locations spread over different agro-climatic zones of Karnataka state, India. Different stability parameters as suggested by Eberhart and Russell [1] were estimated. Joint analysis of variance revealed significant differences among environments, hybrids and environments × hybrids interactions advocating the adequacy of stability analysis. Hybrids, viz., MAI 349×MAI 283, KDMI 16×BGUDI 118 were stable for days to anthesis and silking, respectively. Whereas, hybrids viz., KDMI 16×BGUDI 118, BGUDI 120×VL 109252 and MAI 283× KDMI 16 registered mean values lower than the overall mean with bi value nearer to unity and non significant S2di for anthesis silking interval. Hybrid, MAI 349×MAI 283 for plant height and cob length, KDMI 16×MAI 283 for cob length, number of kernel rows-1 and 100 grain weight, BGUDI 88×MAI 349 for cob diameter, MAI 394×BGUDI 88  for shelling % and KDMI 16×BGUDI 118 for grain yield plant-1 registered stable performance across the environments. Based on the positive and negative environmental indices, production environment at location 1 (K Block UAS, GKVK, Bengaluru), was most favorable for expression of majority of characters studied. Hybrid KDMI 16×MAI 283 was found stable across the environments for most of the characters studied.

scholarly journals Analysis of genotype × environment interaction in rain-fed durum wheat of Iran using GGE-biplot and non-parametric methods

2012 ◽  
Vol 92 (4) ◽  
pp. 757-770 ◽  
Author(s):  
Reza Mohammadi ◽  
Ahmed Amri
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Environment Interaction ◽  
Parametric Methods ◽  
Gge Biplot ◽  
Ge Interaction ◽  
Yield Data ◽  
Stability Performance ◽  
Genotype Environment Interaction ◽  
Non Parametric

Mohammadi, R. and Amri, A. 2012. Analysis of genotype × environment interaction in rain-fed durum wheat of Iran using GGE-biplot and non-parametric methods. Can. J. Plant Sci. 92: 757–770. Multi-environment trials (MET) are conducted annually throughout the world in order to use the information contained in MET data for genotype evaluation and mega-environment identification. In this study, grain yield data of 13 durum and one bread wheat genotypes grown in 16 diversified environments (differing in winter temperatures and water regimes) were used to analyze genotype by environment (GE) interactions in rain-fed durum MET data in Iran. The main objectives were (i) to investigate the possibility of dividing the test locations representative for rain-fed durum production in Iran into mega-environments using the genotype main effect plus GE interaction (GGE) biplot model and (ii) to compare the effectiveness of the GGE-biplot and several non-parametric stability measures (NPSM), which are not well-documented, for evaluating the stability performance of genotypes tested and the possibility of recommending the best genotype(s) for commercial release in the rain-fed areas of Iran. The results indicate that the grain yield of different genotypes was significantly influenced by environmental effect. The greater GE interaction relative to genotype effect suggested significant environmental groups with different top-yielding genotypes. Warm environments differed from cold environments in the ranking of genotypes, while moderate environments were highly divergent and correlated with both cold and warm environments. Cold and warm environments were better than moderate environments in both discriminating and representativeness, suggesting the efficiency and accuracy of genotype selection would be greatly enhanced in such environments. According to the NPSM, genotypes tend to be classified into groups related to the static and dynamic concepts of stability. Both the GGE-biplot and NPSM methods were found to be useful, and generally gave similar results in identifying high-yielding and stable genotypes. In contrast to NPSM, the GGE-biplot analysis would serve as a better platform to analyze MET data, because it always explicitly indicates the average yield and stability of the genotypes and the discriminating ability and representativeness of the test environments.

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.

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