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 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.

scholarly journals Performance evaluation of commercial maize hybrids across diverse Terai environments during the winter season in Nepal

2016 ◽  
Vol 2 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Mahendra Prasad Tripathi ◽  
Jiban Shrestha ◽  
Dil Bahadur Gurung
Keyword(s):  
Grain Yield ◽  
Winter Season ◽  
First Year ◽  
Environment Interaction ◽  
Maize Hybrids ◽  
Site Analysis ◽  
Maize Cultivars ◽  
Genotype Environment Interaction ◽  
Winter Time ◽  
Hybrid Maize

The hybrid maize cultivars of multinational seed companies are gradually being popular among the farmers in Nepal. This paper reports on research finding of 117 maize hybrids of 20 seed companies assessed for grain yield and other traits at three sites in winter season of 2011 and 2012. The objective of the study was to identify superior maize hybrids suitable for winter time planting in eastern, central and inner Terai of Nepal. Across site analysis of variance revealed that highly significant effect of genotype and genotype × environment interaction (GEI) on grain yield of commercial hybrids. Overall, 47 genotypes of 16 seed companies identified as high yielding and stable based on superiority measures. The statistical analysis ranked topmost three genotypes among tested hybrids as P3856 (10515 kg ha-1), Bisco prince (8763 kg ha-1) as well as Shaktiman (8654 kg ha-1) in the first year; and 3022 (8378 kg ha-1), Kirtiman manik (8323 kg ha-1) as well as Top class (7996 kg ha-1) in the second year. It can be concluded that stable and good performing hybrids identified as potential commercial hybrids for general cultivation on similar environments in Nepal.

Adaptation of field pea varieties to organic farming across different environments of Italy

2019 ◽  
Vol 70 (4) ◽  
pp. 327 ◽  
Author(s):  
Luciano Pecetti ◽  
Angelo R. Marcotrigiano ◽  
Luigi Russi ◽  
Massimo Romani ◽  
Paolo Annicchiarico
Keyword(s):  
Grain Yield ◽  
Southern Italy ◽  
Ascochyta Blight ◽  
Genetic Correlations ◽  
Field Pea ◽  
Environment Interaction ◽  
Adaptive Responses ◽  
Climatic Regions ◽  
Organic Systems ◽  
Genotype Environment Interaction

This study aimed to support field pea (Pisum sativum L.) breeding strategies for organic systems of southern European environments, by assessing the size of genotype × environment interaction (GEI) due to spatial and temporal factors across climatically contrasting regions and identifying plant characters associated with genotype adaptive responses. Twelve recent varieties were evaluated for grain yield and other traits in six organically managed environments (three sites × two cropping years) of northern, central and southern Italy. GEI for grain yield was large, with the variety × site × year interaction greatly exceeding the variety × site interaction. This finding, and the similar magnitude of the mean genetic correlations for variety yields across pairs of sites (rg = 0.56) and pairs of years (rg = 0.51), indicated the difficulty of exploiting variety × site interaction effects by breeding for specific climatic regions. Pattern analysis highlighted the large inconsistency across years for GEI pattern of the sites from central and southern Italy. GEI also complicated the targeting of varieties, owing to inconsistent top-performing material across years according to additive main effects and multiplicative interaction (AMMI)-modelled yields. Higher genotype mean yield was strictly associated (P &lt; 0.01) with lower weed proportion (hence, greater competitiveness against weeds: r = –0.96), taller plants (r = 0.89) and larger seeds (r = 0.78), with looser associations with lower susceptibility to lodging and ascochyta blight. These traits, which also contributed to preferential adaptation to the moisture-favourable environments of northern Italy, could be selected in breeding widely adapted varieties.

Genotype × environment interaction patterns for grain yield of spring barley in different regions of Kazakhstan

2013 ◽  
Vol 49 (2) ◽  
pp. 196-205 ◽  
Author(s):  
Y. Turuspekov ◽  
B. Sariev ◽  
V. Chudinov ◽  
G. Sereda ◽  
L. Tokhetova ◽  
...  
Keyword(s):  
Grain Yield ◽  
Spring Barley ◽  
Environment Interaction ◽  
Interaction Patterns ◽  
Genotype Environment Interaction
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