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Information flow diagram for the STABILITYSOFT software tool.

Information flow diagram for the STABILITYSOFT software tool.

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Premise of the study: Access to improved crop cultivars is the foundation for successful agriculture. New cultivars must have improved yields that are determined by quantitative and qualitative traits. Genotype-by-environment interactions (GEI) occur for quantitative traits such as reproductive fitness, longevity, height, weight, yield, and diseas...

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... Figure 1 shows the information flow in the STABILITYSOFT program. The software can be used online and is available in R programming language for advanced users, which offers more flexibility. ...

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... Genotype x Environment interactions of cross over type would introduce inconsistency in the behaviour of genotypes evaluated in the various environmental conditions. 1 Adaptability and stability of various crops under multi-environment field trials studied by number of analytic measures as observed in the literature. 2 Moreover non parametric measures to assess GxE interaction and stability analysis had been also reflected. 6 The components of analysis of variance, the regression models, non-parametric methods, AMMI methods, BLUP based mixed models would be most suitable analytic methods. 3 AMMI stability value (ASV), ASV1, Modified AMMI stability value (MASV) & MASV1) have been registered visibility. ...
... 5 Besides that nonparametric measures S i 1 , S i 2 , S i 3 , S i 4 , S i 5 ,S i 6 , S i 7 , NP i (1) , NP i (2) , NP i (3) , NP i (4) have been also utilized for genotypes x environmental conditions. 6 All recent analytic measures have been compared to decipher the Gx E interactions effects for fodder barley genotypes evaluated in northern hills zone of the country. ...
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... Additionally, eleven parametric and nine non-parametric common stability statistics were calculated (see Table 3), and furthermore, the investigated genotypes were ranked based on each statistic. All these stability statistics were estimated using a web-based STABILITYSOFT program (Pour-Aboughadareh et al., 2019) and the "metan" package in R. An overview of their equations and how they were used in the analysis of GEI effects is given in a recent review by Pour-Aboughadareh et al. (2022a). ...
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... N = total environment. Rank stability of KR was computed by Kang [31], wherein yield and stability variance of the genotype with a high yield and stability is weighed 1. Software STABILITYSOFT [32] was used to compute yield stability based on parametric and nonparametric methods. ...
... The GGE biplot was composed of the general mean and interaction principal component axes score. STABI-LITYSOFT was also used to estimate combined ANOVA, GGE, and to form their biplots [32]. ...
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... The phenotype is also influenced by non-linear interactions between genes and the environment (see Liu et al., 2008;Sa et al., 2016;Pour-Aboughadareh et al., 2019), transgenerational effects, i.e., epigenetics (Bird, 2007;Horvath and Raj, 2008), and by the errors we make in observing, recording, analyzing, and interpreting the data. Beyond the patterns of heredity, how could all the changes an organism experience through its life, or development, be explained? ...
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... Low values of these statistics reflect high stability. The data were analyzed by the using of the online software (STABILITYSOFT) developed by Pour-Aboughadareh et al. (2019). ...
... . As illustrated in theTable 1, significant correlation registered between the different parametric and non-parametric indices. Many studies revealed that S (1) and S (6) were positively and significantly correlated with each other and with NP (2) and NP (4)(Pour-Aboughadareh et al., 2019). During this study significant and positive parameters, many studies have been reported like these results in durum wheat ...
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T he Field experiment was conducted during 03 cropping season from 2017 to 2020 and sowing at the same period in December at the experimental field of ITGC, Setif, Algeria. The aims of this study were the selection of adapted and stable genotypes based on the use of parametric and non-parametric index. To calculate the parametric and non-parametric index we used the program STABILITYSOFT. The graphic distribution of the genotypes tested based on the relationship between the mean grain yield and regression coefficient (bi), proved that the suitable genotypes for the tested conditions were the advanced line G2, Fouarra and G12. The values of deviation from regression (S² di) classified the genotype the advanced line G6 as the most desirable genotypes. The association between Wricke's ecovalence (Wi²) indice and the grain yield proved that the best genotypes for growing under these conditions are G13, G10, G6 and Fouarra. In addition, the non-parametric index confirmed the results which registered by the selection based on the parametric index. Thus, the genotypes Fouarra and the advanced line G6 are the most stable genotypes. The combination selection based on highest grain yield and the parametric indices proved that the genotypes G6, Fouarra and G2 were the more stable and adapted genotypes under semi-arid conditions. The Principal component (PC) analysis classified the genotype Fouarra and G2 in dynamic stability group with highest grain yield. Overall, the results of this study confirmed that the parametric and Non-parametric methods were the suitable tools to identify the most stable barley genotypes at various environmental conditions. In addition, the best adapted and stable genotypes during this study were Fouarra and G6. ABSTRACT Algeria, barley, non-parametric, parametric, stability KEY WORDS: Open Access